GW150914—The papers

In 2015 I made a resolution to write a blog post for each paper I had published. In 2016 I’ll have to break this because there are too many to keep up with. A suite of papers were prepared to accompany the announcement of the detection of GW150914 [bonus note], and in this post I’ll give an overview of these.

The papers

As well as the Discovery Paper published in Physical Review Letters [bonus note], there are 12 companion papers. All the papers are listed below in order of arXiv posting. My favourite is the Parameter Estimation Paper.

Subsequently, we have produced additional papers on GW150914, describing work that wasn’t finished in time for the announcement. The most up-to-date results are currently given in the O2 Catalogue Paper.

0. The Discovery Paper

Title: Observation of gravitational waves from a binary black hole merger
arXiv:
 1602.03837 [gr-qc]
Journal:
 Physical Review Letters; 116(6):061102(16); 2016
LIGO science summary:
 Observation of gravitational waves from a binary black hole merger

This is the central paper that announces the observation of gravitational waves. There are three discoveries which are describe here: (i) the direct detection of gravitational waves, (ii) the existence of stellar-mass binary black holes, and (iii) that the black holes and gravitational waves are consistent with Einstein’s theory of general relativity. That’s not too shabby in under 11 pages (if you exclude the author list). Coming 100 years after Einstein first published his prediction of gravitational waves and Schwarzschild published his black hole solution, this is the perfect birthday present.

More details: The Discovery Paper summary

1. The Detector Paper

Title: GW150914: The Advanced LIGO detectors in the era of first discoveries
arXiv:
 1602.03838 [gr-qc]
Journal: Physical Review Letters; 116(13):131103(12); 2016
LIGO science summary: GW150914: The Advanced LIGO detectors in the era of the first discoveries

This paper gives a short summary of how the LIGO detectors work and their configuration in O1 (see the Advanced LIGO paper for the full design). Giant lasers and tiny measurements, the experimentalists do some cool things (even if their paper titles are a little cheesy and they seem to be allergic to error bars).

More details: The Detector Paper summary

2. The Compact Binary Coalescence Paper

Title: GW150914: First results from the search for binary black hole coalescence with Advanced LIGO
arXiv:
 1602.03839 [gr-qc]
Journal: Physical Review D; 93(12):122003(21); 2016
LIGO science summary: How we searched for merging black holes and found GW150914

Here we explain how we search for binary black holes and calculate the significance of potential candidates. This is the evidence to back up (i) in the Discovery Paper. We can potentially detect binary black holes in two ways: with searches that use templates, or with searches that look for coherent signals in both detectors without assuming a particular shape. The first type is also used for neutron star–black hole or binary neutron star coalescences, collectively known as compact binary coalescences. This type of search is described here, while the other type is described in the Burst Paper.

This paper describes the compact binary coalescence search pipelines and their results. As well as GW150914 there is also another interesting event, LVT151012. This isn’t significant enough to be claimed as a detection, but it is worth considering in more detail.

More details: The Compact Binary Coalescence Paper summary

3. The Parameter Estimation Paper

Title: Properties of the binary black hole merger GW150914
arXiv:
 1602.03840 [gr-qc]
Journal: Physical Review Letters; 116(24):241102(19); 2016
LIGO science summary: The first measurement of a black hole merger and what it means

If you’re interested in the properties of the binary black hole system, then this is the paper for you! Here we explain how we do parameter estimation and how it is possible to extract masses, spins, location, etc. from the signal. These are the results I’ve been most heavily involved with, so I hope lots of people will find them useful! This is the paper to cite if you’re using our best masses, spins, distance or sky maps. The masses we infer are so large we conclude that the system must contain black holes, which is discovery (ii) reported in the Discovery Paper.

More details: The Parameter Estimation Paper summary

4. The Testing General Relativity Paper

Title: Tests of general relativity with GW150914
arXiv:
 1602.03841 [gr-qc]
Journal: Physical Review Letters; 116(22):221101(19); 2016
LIGO science summary:
 Was Einstein right about strong gravity?

The observation of GW150914 provides a new insight into the behaviour of gravity. We have never before probed such strong gravitational fields or such highly dynamical spacetime. These are the sorts of places you might imagine that we could start to see deviations from the predictions of general relativity. Aside from checking that we understand gravity, we also need to check to see if there is any evidence that our estimated parameters for the system could be off. We find that everything is consistent with general relativity, which is good for Einstein and is also discovery (iii) in the Discovery Paper.

More details: The Testing General Relativity Paper summary

5. The Rates Paper

Title: The rate of binary black hole mergers inferred from Advanced LIGO observations surrounding GW150914
arXiv:
 1602.03842 [astro-ph.HE]1606.03939 [astro-ph.HE]
Journal: Astrophysical Journal Letters; 833(1):L1(8); 2016; Astrophysical Journal Supplement Series; 227(2):14(11); 2016
LIGO science summary: The first measurement of a black hole merger and what it means

Given that we’ve spotted one binary black hole (plus maybe another with LVT151012), how many more are out there and how many more should we expect to find? We answer this here, although there’s a large uncertainty on the estimates since we don’t know (yet) the distribution of masses for binary black holes.

More details: The Rates Paper summary

6. The Burst Paper

Title: Observing gravitational-wave transient GW150914 with minimal assumptions
arXiv: 1602.03843 [gr-qc]
Journal: Physical Review D; 93(12):122004(20); 2016

What can you learn about GW150914 without having to make the assumptions that it corresponds to gravitational waves from a binary black hole merger (as predicted by general relativity)? This paper describes and presents the results of the burst searches. Since the pipeline which first found GW150914 was a burst pipeline, it seems a little unfair that this paper comes after the Compact Binary Coalescence Paper, but I guess the idea is to first present results assuming it is a binary (since these are tightest) and then see how things change if you relax the assumptions. The waveforms reconstructed by the burst models do match the templates for a binary black hole coalescence.

More details: The Burst Paper summary

7. The Detector Characterisation Paper

Title: Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914
arXiv: 1602.03844 [gr-qc]
Journal: Classical & Quantum Gravity; 33(13):134001(34); 2016
LIGO science summary:
How do we know GW150914 was real? Vetting a Gravitational Wave Signal of Astrophysical Origin
CQG+ post: How do we know LIGO detected gravitational waves? [featuring awesome cartoons]

Could GW150914 be caused by something other than a gravitational wave: are there sources of noise that could mimic a signal, or ways that the detector could be disturbed to produce something that would be mistaken for a detection? This paper looks at these problems and details all the ways we monitor the detectors and the external environment. We can find nothing that can explain GW150914 (and LVT151012) other than either a gravitational wave or a really lucky random noise fluctuation. I think this paper is extremely important to our ability to claim a detection and I’m surprised it’s not number 2 in the list of companion papers. If you want to know how thorough the Collaboration is in monitoring the detectors, this is the paper for you.

More details: The Detector Characterisation Paper summary

8. The Calibration Paper

Title: Calibration of the Advanced LIGO detectors for the discovery of the binary black-hole merger GW150914
arXiv:
 1602.03845 [gr-qc]
Journal: Physical Review D; 95(6):062003(16); 2017
LIGO science summary:
 Calibration of the Advanced LIGO detectors for the discovery of the binary black-hole merger GW150914

Completing the triumvirate of instrumental papers with the Detector Paper and the Detector Characterisation Paper, this paper describes how the LIGO detectors are calibrated. There are some cunning control mechanisms involved in operating the interferometers, and we need to understand these to quantify how they effect what we measure. Building a better model for calibration uncertainties is high on the to-do list for improving parameter estimation, so this is an interesting area to watch for me.

More details: The Calibration Paper summary

9. The Astrophysics Paper

Title: Astrophysical implications of the binary black-hole merger GW150914
arXiv:
 1602.03846 [astro-ph.HE]
Journal: Astrophysical Journal Letters; 818(2):L22(15); 2016
LIGO science summary:
 The first measurement of a black hole merger and what it means

Having estimated source parameters and rate of mergers, what can we say about astrophysics? This paper reviews results related to binary black holes to put our findings in context and also makes statements about what we could hope to learn in the future.

More details: The Astrophysics Paper summary

10. The Stochastic Paper

Title: GW150914: Implications for the stochastic gravitational wave background from binary black holes
arXiv:
 1602.03847 [gr-qc]
Journal: Physical Review Letters; 116(13):131102(12); 2016
LIGO science summary: Background of gravitational waves expected from binary black hole events like GW150914

For every loud signal we detect, we expect that there will be many more quiet ones. This paper considers how many quiet binary black hole signals could add up to form a stochastic background. We may be able to see this background as the detectors are upgraded, so we should start thinking about what to do to identify it and learn from it.

More details: The Stochastic Paper summary

11. The Neutrino Paper

Title: High-energy neutrino follow-up search of gravitational wave event GW150914 with ANTARES and IceCube
arXiv:
 1602.05411 [astro-ph.HE]
Journal: Physical Review D; 93(12):122010(15); 2016
LIGO science summary: Search for neutrinos from merging black holes

We are interested so see if there’s any other signal that coincides with a gravitational wave signal. We wouldn’t expect something to accompany a black hole merger, but it’s good to check. This paper describes the search for high-energy neutrinos. We didn’t find anything, but perhaps we will in the future (perhaps for a binary neutron star merger).

More details: The Neutrino Paper summary

12. The Electromagnetic Follow-up Paper

Title: Localization and broadband follow-up of the gravitational-wave transient GW150914
arXiv: 1602.08492 [astro-ph.HE]; 1604.07864 [astro-ph.HE]
Journal: Astrophysical Journal Letters; 826(1):L13(8); 2016; Astrophysical Journal Supplement Series; 225(1):8(15); 2016

As well as looking for coincident neutrinos, we are also interested in electromagnetic observations (gamma-ray, X-ray, optical, infra-red or radio). We had a large group of observers interesting in following up on gravitational wave triggers, and 25 teams have reported observations. This companion describes the procedure for follow-up observations and discusses sky localisation.

This work split into a main article and a supplement which goes into more technical details.

More details: The Electromagnetic Follow-up Paper summary

The Discovery Paper

Synopsis: Discovery Paper
Read this if: You want an overview of The Event
Favourite part: The entire conclusion:

The LIGO detectors have observed gravitational waves from the merger of two stellar-mass black holes. The detected waveform matches the predictions of general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.

The Discovery Paper gives the key science results and is remarkably well written. It seems a shame to summarise it: you should read it for yourself! (It’s free).

The Detector Paper

Synopsis: Detector Paper
Read this if: You want a brief description of the detector configuration for O1
Favourite part: It’s short!

The LIGO detectors contain lots of cool pieces of physics. This paper briefly outlines them all: the mirror suspensions, the vacuum (the LIGO arms are the largest vacuum envelopes in the world and some of the cleanest), the mirror coatings, the laser optics and the control systems. A full description is given in the Advanced LIGO paper, but the specs there are for design sensitivity (it is also heavy reading). The main difference between the current configuration and that for design sensitivity is the laser power. Currently the circulating power in the arms is 100~\mathrm{kW}, the plan is to go up to 750~\mathrm{kW}. This will reduce shot noise, but raises all sorts of control issues, such as how to avoid parametric instabilities.

Noise curves

The noise amplitude spectral density. The curves for the current observations are shown in red (dark for Hanford, light for Livingston). This is around a factor 3 better than in the final run of initial LIGO (green), but still a factor of 3 off design sensitivity (dark blue). The light blue curve shows the impact of potential future upgrades. The improvement at low frequencies is especially useful for high-mass systems like GW150914. Part of Fig. 1 of the Detector Paper.

The Compact Binary Coalescence Paper

Synopsis: Compact Binary Coalescence Paper
Read this if: You are interested in detection significance or in LVT151012
Favourite part: We might have found a second binary black hole merger

There are two compact binary coalescence searches that look for binary black holes: PyCBC and GstLAL. Both match templates to the data from the detectors to look for anything binary like, they then calculate the probability that such a match would happen by chance due to a random noise fluctuation (the false alarm probability or p-value [unhappy bonus note]). The false alarm probability isn’t the probability that there is a gravitational wave, but gives a good indication of how surprised we should be to find this signal if there wasn’t one. Here we report the results of both pipelines on the first 38.6 days of data (about 17 days where both detectors were working at the same time).

Both searches use the same set of templates to look for binary black holes [bonus note]. They look for where the same template matches the data from both detectors within a time interval consistent with the travel time between the two. However, the two searches rank candidate events and calculate false alarm probabilities using different methods. Basically, both searches use a detection statistic (the quantity used to rank candidates: higher means less likely to be noise), that is based on the signal-to-noise ratio (how loud the signal is) and a goodness-of-fit statistic. They assess the significance of a particular value of this detection statistic by calculating how frequently this would be obtained if there was just random noise (this is done by comparing data from the two detectors when there is not a coincident trigger in both). Consistency between the two searches gives us greater confidence in the results.

PyCBC’s detection statistic is a reweighted signal-to-noise ratio \hat{\rho}_c which takes into account the consistency of the signal in different frequency bands. You can get a large signal-to-noise ratio from a loud glitch, but this doesn’t match the template across a range of frequencies, which is why this test is useful. The consistency is quantified by a reduced chi-squared statistic. This is used, depending on its value, to weight the signal-to-noise ratio. When it is large (indicating inconsistency across frequency bins), the reweighted signal-to-noise ratio becomes smaller.

To calculate the background, PyCBC uses time slides. Data from the two detectors are shifted in time so that any coincidences can’t be due to a real gravitational wave. Seeing how often you get something signal-like then tells you how often you’d expect this to happen due to random noise.

GstLAL calculates the signal-to-noise ratio and a residual after subtracting the template. As a detection statistic, it uses a likelihood ratio \mathcal{L}: the probability of finding the particular values of the signal-to-noise ratio and residual in both detectors for signals (assuming signal sources are uniformly distributed isotropically in space), divided by the probability of finding them for noise.

The background from GstLAL is worked out by looking at the likelihood ratio fro triggers that only appear in one detector. Since there’s no coincident signal in the other, these triggers can’t correspond to a real gravitational wave. Looking at their distribution tells you how frequently such things happen due to noise, and hence how probable it is for both detectors to see something signal-like at the same time.

The results of the searches are shown in the figure below.

Search results for GW150914

Search results for PyCBC (left) and GstLAL (right). The histograms show the number of candidate events (orange squares) compare to the background. The black line includes GW150914 in the background estimate, the purple removes it (assuming that it is a signal). The further an orange square is above the lines, the more significant it is. Particle physicists like to quote significance in terms of \sigma and for some reason we’ve copied them. The second most significant event (around 2\sigma) is LVT151012. Fig. 7 from the Compact Binary Coalescence Paper.

GW150914 is the most significant event in both searches (it is the most significant PyCBC event even considering just single-detector triggers). They both find GW150914 with the same template values. The significance is literally off the charts. PyCBC can only calculate an upper bound on the false alarm probability of < 2 \times 10^{-7}. GstLAL calculates a false alarm probability of 1.4 \times 10^{-11}, but this is reaching the level that we have to worry about the accuracy of assumptions that go into this (that the distribution of noise triggers in uniform across templates—if this is not the case, the false alarm probability could be about 10^3 times larger). Therefore, for our overall result, we stick to the upper bound, which is consistent with both searches. The false alarm probability is so tiny, I don’t think anyone doubts this signal is real.

There is a second event that pops up above the background. This is LVT151012. It is found by both searches. Its signal-to-noise ratio is 9.6, compared with GW150914’s 24, so it is quiet. The false alarm probability from PyCBC is 0.02, and from GstLAL is 0.05, consistent with what we would expect for such a signal. LVT151012 does not reach the standards we would like to claim a detection, but it is still interesting.

Running parameter estimation on LVT151012, as we did for GW150914, gives beautiful results. If it is astrophysical in origin, it is another binary black hole merger. The component masses are lower, m_1^\mathrm{source} = 23^{+18}_{-5} M_\odot and m_2^\mathrm{source} 13^{+4}_{-5} M_\odot (the asymmetric uncertainties come from imposing m_1^\mathrm{source} \geq m_2^\mathrm{source}); the chirp mass is \mathcal{M} = 15^{+1}_{-1} M_\odot. The effective spin, as for GW150914, is close to zero \chi_\mathrm{eff} = 0.0^{+0.3}_{-0.2}. The luminosity distance is D_\mathrm{L} = 1100^{+500}_{-500}~\mathrm{Mpc}, meaning it is about twice as far away as GW150914’s source. I hope we’ll write more about this event in the future; there are some more details in the Rates Paper.

Trust LIGO

Is it random noise or is it a gravitational wave? LVT151012 remains a mystery. This candidate event is discussed in the Compact Binary Coalescence Paper (where it is found), the Rates Paper (which calculates the probability that it is extraterrestrial in origin), and the Detector Characterisation Paper (where known environmental sources fail to explain it). SPOILERS

The Parameter Estimation Paper

Synopsis: Parameter Estimation Paper
Read this if: You want to know the properties of GW150914’s source
Favourite part: We inferred the properties of black holes using measurements of spacetime itself!

The gravitational wave signal encodes all sorts of information about its source. Here, we explain how we extract this information  to produce probability distributions for the source parameters. I wrote about the properties of GW150914 in my previous post, so here I’ll go into a few more technical details.

To measure parameters we match a template waveform to the data from the two instruments. The better the fit, the more likely it is that the source had the particular parameters which were used to generate that particular template. Changing different parameters has different effects on the waveform (for example, changing the distance changes the amplitude, while changing the relative arrival times changes the sky position), so we often talk about different pieces of the waveform containing different pieces of information, even though we fit the whole lot at once.

Waveform explained

The shape of the gravitational wave encodes the properties of the source. This information is what lets us infer parameters. The example signal is GW150914. I made this explainer with Ban Farr and Nutsinee Kijbunchoo for the LIGO Magazine.

The waveform for a binary black hole merger has three fuzzily defined parts: the inspiral (where the two black holes orbit each other), the merger (where the black holes plunge together and form a single black hole) and ringdown (where the final black hole relaxes to its final state). Having waveforms which include all of these stages is a fairly recent development, and we’re still working on efficient ways of including all the effects of the spin of the initial black holes.

We currently have two favourite binary black hole waveforms for parameter estimation:

  • The first we refer to as EOBNR, short for its proper name of SEOBNRv2_ROM_DoubleSpin. This is constructed by using some cunning analytic techniques to calculate the dynamics (known as effective-one-body or EOB) and tuning the results to match numerical relativity (NR) simulations. This waveform only includes the effects of spins aligned with the orbital angular momentum of the binary, so it doesn’t allow us to measure the effects of precession (wobbling around caused by the spins).
  • The second we refer to as IMRPhenom, short for IMRPhenomPv2. This is constructed by fitting to the frequency dependence of EOB and NR waveforms. The dominant effects of precession of included by twisting up the waveform.

We’re currently working on results using a waveform that includes the full effects of spin, but that is extremely slow (it’s about half done now), so those results won’t be out for a while.

The results from the two waveforms agree really well, even though they’ve been created by different teams using different pieces of physics. This was a huge relief when I was first making a comparison of results! (We had been worried about systematic errors from waveform modelling). The consistency of results is partly because our models have improved and partly because the properties of the source are such that the remaining differences aren’t important. We’re quite confident that we’ve most of the parameters are reliably measured!

The component masses are the most important factor for controlling the evolution of the waveform, but we don’t measure the two masses independently.  The evolution of the inspiral is dominated by a combination called the chirp mass, and the merger and ringdown are dominated by the total mass. For lighter mass systems, where we gets lots of inspiral, we measure the chirp mass really well, and for high mass systems, where the merger and ringdown are the loudest parts, we measure the total mass. GW150914 is somewhere in the middle. The probability distribution for the masses are shown below: we can compensate for one of the component masses being smaller if we make the other larger, as this keeps chirp mass and total mass about the same.

Binary black hole masses

Estimated masses for the two black holes in the binary. Results are shown for the EOBNR waveform and the IMRPhenom: both agree well. The Overall results come from averaging the two. The dotted lines mark the edge of our 90% probability intervals. The sharp diagonal line cut-off in the two-dimensional plot is a consequence of requiring m_1^\mathrm{source} \geq m_2^\mathrm{source}.  Fig. 1 from the Parameter Estimation Paper.

To work out these masses, we need to take into account the expansion of the Universe. As the Universe expands, it stretches the wavelength of the gravitational waves. The same happens to light: visible light becomes redder, so the phenomenon is known as redshifting (even for gravitational waves). If you don’t take this into account, the masses you measure are too large. To work out how much redshift there is you need to know the distance to the source. The probability distribution for the distance is shown below, we plot the distance together with the inclination, since both of these affect the amplitude of the waves (the source is quietest when we look at it edge-on from the side, and loudest when seen face-on/off from above/below).

Distance and inclination

Estimated luminosity distance and binary inclination angle. An inclination of \theta_{JN} = 90^\circ means we are looking at the binary (approximately) edge-on. Results are shown for the EOBNR waveform and the IMRPhenom: both agree well. The Overall results come from averaging the two. The dotted lines mark the edge of our 90% probability intervals.  Fig. 2 from the Parameter Estimation Paper.

After the masses, the most important properties for the evolution of the binary are the spins. We don’t measure these too well, but the probability distribution for their magnitudes and orientations from the precessing IMRPhenom model are shown below. Both waveform models agree that the effective spin \chi_\mathrm{eff}, which is a combination of both spins in the direction of the orbital angular momentum) is small. Therefore, either the spins are small or are larger but not aligned (or antialigned) with the orbital angular momentum. The spin of the more massive black hole is the better measured of the two.

Orientation and magnitudes of the two spins

Estimated orientation and magnitude of the two component spins from the precessing IMRPhenom model. The magnitude is between 0 and 1 and is perfectly aligned with the orbital angular momentum if the angle is 0. The distribution for the more massive black hole is on the left, and for the smaller black hole on the right. Part of Fig. 5 from the Parameter Estimation Paper.

The Testing General Relativity Paper

Synopsis: Testing General Relativity Paper
Read this if: You want to know more about the nature of gravity.
Favourite part: Einstein was right! (Or more correctly, we can’t prove he was wrong… yet)

The Testing General Relativity Paper is one of my favourites as it packs a lot of science in. Our first direct detection of gravitational waves and of the merger of two black holes provides a new laboratory to test gravity, and this paper runs through the results of the first few experiments.

Before we start making any claims about general relativity being wrong, we first have to check if there’s any weird noise present. You don’t want to have to rewrite the textbooks just because of an instrumental artifact. After taking out a good guess for the waveform (as predicted by general relativity), we find that the residuals do match what we expect for instrumental noise, so we’re good to continue.

I’ve written about a couple of tests of general relativity in my previous post: the consistency of the inspiral and merger–ringdown parts of the waveform, and the bounds on the mass of the graviton (from evolution of the signal). I’ll cover the others now.

The final part of the signal, where the black hole settles down to its final state (the ringdown), is the place to look to check that the object is a black hole and not some other type of mysterious dark and dense object. It is tricky to measure this part of the signal, but we don’t see anything odd. We can’t yet confirm that the object has all the properties you’d want to pin down that it is exactly a black hole as predicted by general relativity; we’re going to have to wait for a louder signal for this. This test is especially poignant, as Steven Detweiler, who pioneered a lot of the work calculating the ringdown of black holes, died a week before the announcement.

We can allow terms in our waveform (here based on the IMRPhenom model) to vary and see which values best fit the signal. If there is evidence for differences compared with the predictions from general relativity, we would have evidence for needing an alternative. Results for this analysis are shown below for a set of different waveform parameters \hat{p}_i: the \varphi_i parameters determine the inspiral, the \alpha_i parameters determine the merger–ringdown and the \beta_i parameters cover the intermediate regime. If the deviation \delta \hat{p}_i is zero, the value coincides with the value from general relativity. The plot shows what would happen if you allow all the variable to vary at once (the multiple results) and if you tried just that parameter on its own (the single results).

Testing general relativity bounds

Probability distributions for waveform parameters. The single analysis only varies one parameter, the multiple analysis varies all of them, and the J0737-3039 result is the existing bound from the double pulsar. A deviation of zero is consistent with general relativity. Fig. 7 from the Testing General Relativity Paper.

Overall the results look good. Some of the single results are centred away from zero, but we think that this is just a random fluctuate caused by noise (we’ve seen similar behaviour in tests, so don’t panic yet). It’s not surprising the \varphi_3, \varphi_4 and \varphi_{5l} all show this behaviour, as they are sensitive to similar noise features. These measurements are much tighter than from any test we’ve done before, except for the measurement of \varphi_0 which is better measured from the double pulsar (since we have lots and lots of orbits of that measured).

The final test is to look for additional polarizations of gravitational waves. These are predicted in several alternative theories of gravity. Unfortunately, because we only have two detectors which are pretty much aligned we can’t say much, at least without knowing for certain the location of the source. Extra detectors will be useful here!

In conclusion, we have found no evidence to suggest we need to throw away general relativity, but future events will help us to perform new and stronger tests.

The Rates Paper

Synopsis: Rates Paper
Read this if: You want to know how often binary black holes merge (and how many we’ll detect)
Favourite part: There’s a good chance we’ll have ten detections by the end of our second observing run (O2)

Before September 14, we had never seen a binary stellar-mass black hole system. We were therefore rather uncertain about how many we would see. We had predictions based on simulations of the evolution of stars and their dynamical interactions. These said we shouldn’t be too surprised if we saw something in O1, but that we shouldn’t be surprised if we didn’t see anything for many years either. We weren’t really expecting to see a black hole system so soon (the smart money was on a binary neutron star). However, we did find a binary black hole, and this happened right at the start of our observations! What do we now believe about the rate of mergers?

To work out the rate, you first need to count the number of events you have detected and then work out how sensitive you are to the population of signals (how many could you see out of the total).

Counting detections sounds simple: we have GW150914 without a doubt. However, what about all the quieter signals? If you have 100 events each with a 1% probability of being real, then even though you can’t say with certainty that anyone is an actual signal, you would expect one to be so. We want to work out how many events are real and how many are due to noise. Handily, trying to tell apart different populations of things when you’re not certain about individual members is a common problem is astrophysics (where it’s often difficult to go and check what something actually is), so there exists a probabilistic framework for doing this.

Using the expected number of real and noise events for a given detection statistic (as described in the Compact Binary Coalescence Paper), we count the number of detections and as a bonus, get a probability that each event is of astrophysical origin. There are two events with more than a 50% chance of being real: GW150914, where the probability is close to 100%, and LVT151012, where to probability is 84% based on GstLAL and 91% based on PyCBC.

By injecting lots of fake signals into some data and running our detection pipelines, we can work out how sensitive they are (in effect, how far away can they find particular types of sources). For a given number of detections, the more sensitive we are, the lower the actual rate of mergers should be (for lower sensitivity we would miss more, while there’s no hiding for higher sensitivity).

There is one final difficulty in working out the total number of binary black hole mergers: we need to know the distribution of masses, because our sensitivity depends on this. However, we don’t yet know this as we’ve only seen GW150914 and (maybe) LVT151012. Therefore, we try three possibilities to get an idea of what the merger rate could be.

  1. We assume that binary black holes are either like GW150914 or like LVT151012. Given that these are our only possible detections at the moment, this should give a reasonable estimate. A similar approach has been used for estimating the population of binary neutron stars from pulsar observations [bonus note].
  2. We assume that the distribution of masses is flat in the logarithm of the masses. This probably gives more heavy black holes than in reality (and so a lower merger rate)
  3. We assume that black holes follow a power law like the initial masses of stars. This probably gives too many low mass black holes (and so a higher merger rate)

The estimated merger rates (number of binary black hole mergers per volume per time) are then: 1. 83^{+168}_{-63}~\mathrm{Gpc^{-3}\,yr^{-1}}; 2. 61^{+124}_{-48}~\mathrm{Gpc^{-3}\,yr^{-1}}, and 3. 200^{+400}_{-160}~\mathrm{Gpc^{-3}\,yr^{-1}}. There is a huge scatter, but the flat and power-law rates hopefully bound the true value.

We’ll pin down the rate better after a few more detections. How many more should we expect to see? Using the projected sensitivity of the detectors over our coming observing runs, we can work out the probability of making N more detections. This is shown in the plot below. It looks like there’s about about a 10% chance of not seeing anything else in O1, but we’re confident that we’ll have 10 more by the end of O2, and 35 more by the end of O3! I may need to lie down…

Expected number of detections

The percentage chance of making 0, 10, 35 and 70 more detections of binary black holes as time goes on and detector sensitivity improves (based upon our data so far). This is a simplified version of part of Fig. 3 of the Rates Paper taken from the science summary.

The Burst Paper

Synopsis: Burst Paper
Read this if: You want to check what we can do without a waveform template
Favourite part: You don’t need a template to make a detection

When discussing what we can learn from gravitational wave astronomy, you can almost guarantee that someone will say something about discovering the unexpected. Whenever we’ve looked at the sky in a new band of the electromagnetic spectrum, we found something we weren’t looking for: pulsars for radio, gamma-ray burst for gamma-rays, etc. Can we do the same in gravitational wave astronomy? There may well be signals we weren’t anticipating out there, but will we be able to detect them? The burst pipelines have our back here, at least for short signals.

The burst search pipelines, like their compact binary coalescence partners, assign candidate events a detection statistic and then work out a probability associated with being a false alarm caused by noise. The difference is that the burst pipelines try to find a wider range of signals.

There are three burst pipelines described: coherent WaveBurst (cWB), which famously first found GW150914; omicron–LALInferenceBurst (oLIB), and BayesWave, which follows up on cWB triggers.

As you might guess from the name, cWB looks for a coherent signal in both detectors. It looks for excess power (indicating a signal) in a time–frequency plot, and then classifies candidates based upon their structure. There’s one class for blip glitches and resonance lines (see the Detector Characterisation Paper), these are all thrown away as noise; one class for chirp-like signals that increase in frequency with time, this is where GW150914 was found, and one class for everything else. cWB’s detection statistic \eta_c is something like a signal-to-noise ratio constructed based upon the correlated power in the detectors. The value for GW150914 was \eta_c = 20, which is higher than for any other candidate. The false alarm probability (or p-value), folding in all three search classes, is 2\times 10^{-6}, which is pretty tiny, even if not as significant as for the tailored compact binary searches.

The oLIB search has two stages. First it makes a time–frequency plot and looks for power coincident between the two detectors. Likely candidates are then followed up by matching a sine–Gaussian wavelet to the data, using a similar algorithm to the one used for parameter estimation. It’s detection statistic is something like a likelihood ratio for the signal verses noise. It calculates a false alarm probability of about 2\times 10^{-6} too.

BayesWave fits a variable number of sine–Gaussian wavelets to the data. This can model both a signal (when the wavelets are the same for both detectors) and glitches (when the wavelets are independent). This is really clever, but is too computationally expensive to be left running on all the data. Therefore, it follows up on things highlighted by cWB, potentially increasing their significance. It’s detection statistic is the Bayes factor comparing the signal and glitch models. It estimates the false alarm probability to be about 7 \times 10^{-7} (which agrees with the cWB estimate if you only consider chirp-like triggers).

None of the searches find LVT151012. However, as this is a quiet, lower mass binary black hole, I think that this is not necessarily surprising.

cWB and BayesWave also output a reconstruction of the waveform. Reassuringly, this does look like binary black hole coalescence!

Estimated waveforms from different models

Gravitational waveforms from our analyses of GW150914. The wiggly grey line are the data from Hanford (top) and Livinston (bottom); these are analysed coherently. The plots show waveforms whitened by the noise power spectral density. The dark band shows the waveform reconstructed by BayesWave without assuming that the signal is from a binary black hole (BBH). The light bands show the distribution of BBH template waveforms that were found to be most probable from our parameter-estimation analysis. The two techniques give consistent results: the match between the two models is 94^{+2}_{-3}\%. Fig. 6 of the Parameter Estimation Paper.

The paper concludes by performing some simple fits to the reconstructed waveforms. For this, you do have to assume that the signal cane from a binary black hole. They find parameters roughly consistent with those from the full parameter-estimation analysis, which is a nice sanity check of our results.

The Detector Characterisation Paper

Synopsis: Detector Characteristation Paper
Read this if: You’re curious if something other than a gravitational wave could be responsible for GW150914 or LVT151012
Favourite part: Mega lightning bolts can cause correlated noise

The output from the detectors that we analyses for signals is simple. It is a single channel that records the strain. To monitor instrumental behaviour and environmental conditions the detector characterisation team record over 200,000 other channels. These measure everything from the alignment of the optics through ground motion to incidence of cosmic rays. Most of the data taken by LIGO is to monitor things which are not gravitational waves.

This paper examines all the potential sources of noise in the LIGO detectors, how we monitor them to ensure they are not confused for a signal, and the impact they could have on estimating the significance of events in our searches. It is amazingly thorough work.

There are lots of potential noise sources for LIGO. Uncorrelated noise sources happen independently at both sites, therefore they can only be mistaken for a gravitational wave if by chance two occur at the right time. Correlated noise sources effect both detectors, and so could be more confusing for our searches, although there’s no guarantee that they would cause a disturbance that looks anything like a binary black hole merger.

Sources of uncorrelated noise include:

  • Ground motion caused by earthquakes or ocean waves. These create wibbling which can affect the instruments, even though they are well isolated. This is usually at low frequencies (below 0.1~\mathrm{Hz} for earthquakes, although it can be higher if the epicentre is near), unless there is motion in the optics around (which can couple to cause higher frequency noise). There is a network of seismometers to measure earthquakes at both sites. There where two magnitude 2.1 earthquakes within 20 minutes of GW150914 (one off the coast of Alaska, the other south-west of Seattle), but both produced ground motion that is ten times too small to impact the detectors. There was some low frequency noise in Livingston at the time of LVT151012 which is associated with a period of bad ocean waves. however, there is no evidence that these could be converted to the frequency range associated with the signal.
  • People moving around near the detectors can also cause vibrational or acoustic disturbances. People are kept away from the detectors while they are running and accelerometers, microphones and seismometers monitor the environment.
  • Modulation of the lasers at 9~\mathrm{MHz} and 45~\mathrm{MHz} is done to monitor and control several parts of the optics. There is a fault somewhere in the system which means that there is a coupling to the output channel and we get noise across 10~\mathrm{Hz} to 2~\mathrm{kHz}, which is where we look for compact binary coalescences. Rai Weiss suggested shutting down the instruments to fix the source of this and delaying the start of observations—it’s a good job we didn’t. Periods of data where this fault occurs are flagged and not included in the analysis.
  • Blip transients are a short glitch that occurs for unknown reasons. They’re quite mysterious. They are at the right frequency range (30~\mathrm{Hz} to 250~\mathrm{Hz}) to be confused with binary black holes, but don’t have the right frequency evolution. They contribute to the background of noise triggers in the compact binary coalescence searches, but are unlikely to be the cause of GW150914 or LVT151012 since they don’t have the characteristic chirp shape.

    Normalised spectrogram of a blip transient.

    A time–frequency plot of a blip glitch in LIGO-Livingston. Blip glitches are the right frequency range to be confused with binary coalescences, but don’t have the chirp-like structure. Blips are symmetric in time, whereas binary coalescences sweep up in frequency. Fig. 3 of the Detector Characterisation Paper.

Correlated noise can be caused by:

  • Electromagnetic signals which can come from lightning, solar weather or radio communications. This is measured by radio receivers and magnetometers, and its extremely difficult to produce a signal that is strong enough to have any impact of the detectors’ output. There was one strong  (peak current of about 500~\mathrm{kA}) lightning strike in the same second as GW150914 over Burkino Faso. However, the magnetic disturbances were at least a thousand times too small to explain the amplitude of GW150914.
  • Cosmic ray showers can cause electromagnetic radiation and particle showers. The particle flux become negligible after a few kilometres, so it’s unlikely that both Livingston and Hanford would be affected, but just in case there is a cosmic ray detector at Hanford. It has seen nothing suspicious.

All the monitoring channels give us a lot of insight into the behaviour of the instruments. Times which can be identified as having especially bad noise properties (where the noise could influence the measured output), or where the detectors are not working properly, are flagged and not included in the search analyses. Applying these vetoes mean that we can’t claim a detection when we know something else could mimic a gravitational wave signal, but it also helps us clean up our background of noise triggers. This has the impact of increasing the significance of the triggers which remain (since there are fewer false alarms they could be confused with). For example, if we leave the bad period in, the PyCBC false alarm probability for LVT151012 goes up from 0.02 to 0.14. The significance of GW150914 is so great that we don’t really need to worry about the effects of vetoes.

At the time of GW150914 the detectors were running well, the data around the event are clean, and there is nothing in any of the auxiliary channels that record anything which could have caused the event. The only source of a correlated signal which has not been rules out is a gravitational wave from a binary black hole merger. The time–frequency plots of the measured strains are shown below, and its easy to pick out the chirps.

Normalised spectrograms for GW150914

Time–frequency plots for GW150914 as measured by Hanford (left) and Livingston (right). These show the characteristic increase in frequency with time of the chirp of a binary merger. The signal is clearly visible above the noise. Fig. 10 of the Detector Characterisation Paper.

The data around LVT151012 are significantly less stationary than around GW150914. There was an elevated noise transient rate around this time. This is probably due to extra ground motion caused by ocean waves. This low frequency noise is clearly visible in the Livingston time–frequency plot below. There is no evidence that this gets converted to higher frequencies though. None of the detector characterisation results suggest that LVT151012 has was caused by a noise artifact.

Normalised spectrograms for LVT151012

Time–frequency plots for LVT151012 as measured by Hanford (left) and Livingston (right). You can see the characteristic increase in frequency with time of the chirp of a binary merger, but this is mixed in with noise. The scale is reduced compared with for GW150914, which is why noise features appear more prominent. The band at low frequency in Livingston is due to ground motion; this is not present in Hanford. Fig. 13 of the Detector Characterisation Paper.

If you’re curious about the state of the LIGO sites and their array of sensors, you can see more about the physical environment monitors at pem.ligo.org.

The Calibration Paper

Synopsis: Calibration Paper
Read this if: You like control engineering or precision measurement
Favourite part: Not only are the LIGO detectors sensitive enough to feel the push from a beam of light, they are so sensitive that you have to worry about where on the mirrors you push

We want to measure the gravitational wave strain—the change in length across our detectors caused by a passing gravitational wave. What we actually record is the intensity of laser light out the output of our interferometer. (The output should be dark when the strain is zero, and the intensity increases when the interferometer is stretched or squashed). We need a way to convert intensity to strain, and this requires careful calibration of the instruments.

The calibration is complicated by the control systems. The LIGO instruments are incredibly sensitive, and maintaining them in a stable condition requires lots of feedback systems. These can impact how the strain is transduced into the signal readout by the interferometer. A schematic of how what would be the change in the length of the arms without control systems \Delta L_\mathrm{free} is changed into the measured strain h is shown below. The calibration pipeline build models to correct for the effects of the control system to provide an accurate model of the true gravitational wave strain.

Calibration control system schematic

Model for how a differential arm length caused by a gravitational wave \Delta L_\mathrm{free} or a photon calibration signal x_\mathrm{T}^\mathrm{(PC)} is converted into the measured signal h. Fig. 2 from the Calibration Paper.

To measure the different responses of the system, the calibration team make several careful measurements. The primary means is using photon calibration: an auxiliary laser is used to push the mirrors and the response is measured. The spots where the lasers are pointed are carefully chosen to minimise distortion to the mirrors caused by pushing on them. A secondary means is to use actuators which are parts of the suspension system to excite the system.

As a cross-check, we can also use two auxiliary green lasers to measure changes in length using either a frequency modulation or their wavelength. These are similar approaches to those used in initial LIGO. These go give consistent results with the other methods, but they are not as accurate.

Overall, the uncertainty in the calibration of the amplitude of the strain is less than 10\% between 20~\mathrm{Hz} and 1~\mathrm{kHz}, and the uncertainty in phase calibration is less than 10^\circ. These are the values that we use in our parameter-estimation runs. However, the calibration uncertainty actually varies as a function of frequency, with some ranges having much less uncertainty. We’re currently working on implementing a better model for the uncertainty, which may improve our measurements. Fortunately the masses, aren’t too affected by the calibration uncertainty, but sky localization is, so we might get some gain here. We’ll hopefully produce results with updated calibration in the near future.

The Astrophysics Paper

Synopsis: Astrophysics Paper
Read this if: You are interested in how binary black holes form
Favourite part: We might be able to see similar mass binary black holes with eLISA before they merge in the LIGO band [bonus note]

This paper puts our observations of GW150914 in context with regards to existing observations of stellar-mass black holes and theoretical models for binary black hole mergers. Although it doesn’t explicitly mention LVT151012, most of the conclusions would be just as applicable to it’s source, if it is real. I expect there will be rapid development of the field now, but if you want to catch up on some background reading, this paper is the place to start.

The paper contains lots of references to good papers to delve into. It also highlights the main conclusion we can draw in italics, so its easy to skim through if you want a summary. I discussed the main astrophysical conclusions in my previous post. We will know more about binary black holes and their formation when we get more observations, so I think it is a good time to get interested in this area.

The Stochastic Paper

Synopsis: Stochastic Paper
Read this if: You like stochastic backgrounds
Favourite part: We might detect a background in the next decade

A stochastic gravitational wave background could be created by an incoherent superposition of many signals. In pulsar timing, they are looking for a background from many merging supermassive black holes. Could we have a similar thing from stellar-mass black holes? The loudest signals, like GW150914, are resolvable, they stand out from the background. However, for every loud signal, there will be many quiet signals, and the ones below our detection threshold could form a background. Since we’ve found that binary black hole mergers are probably plentiful, the background may be at the high end of previous predictions.

The background from stellar-mass black holes is different than the one from supermassive black holes because the signals are short. While the supermassive black holes produce an almost constant hum throughout your observations, stellar-mass black hole mergers produce short chirps. Instead of having lots of signals that overlap in time, we have a popcorn background, with one arriving on average every 15 minutes. This might allow us to do some different things when it comes to detection, but for now, we just use the standard approach.

This paper calculates the energy density of gravitational waves from binary black holes, excluding the contribution from signals loud enough to be detected. This is done for several different models. The standard (fiducial) model assumes parameters broadly consistent with those of GW150914’s source, plus a particular model for the formation of merging binaries. There are then variations on the the model for formation, considering different time delays between formation and merger, and adding in lower mass systems consistent with LVT151012. All these models are rather crude, but give an idea of potential variations in the background. Hopefully more realistic distributions will be considered in the future. There is some change between models, but this is within the (considerable) statistical uncertainty, so predictions seems robust.

Models for a binary black hole stochastic background

Different models for the stochastic background of binary black holes. This is plotted in terms of energy density. The red band indicates the uncertainty on the fiducial model. The dashed line indicates the sensitivity of the LIGO and Virgo detectors after several years at design sensitivity. Fig. 2 of the Stochastic Paper.

After a couple of years at design sensitivity we may be able to make a confident detection of the stochastic background. The background from binary black holes is more significant than we expected.

If you’re wondering about if we could see other types of backgrounds, such as one of cosmological origin, then the background due to binary black holes could make detection more difficult. In effect, it acts as another source of noise, masking the other background. However, we may be able to distinguish the different backgrounds by measuring their frequency dependencies (we expect them to have different slopes), if they are loud enough.

The Neutrino Paper

Synopsis: Neutrino Paper
Read this if: You really like high energy neutrinos
Favourite part: We’re doing astronomy with neutrinos and gravitational waves—this is multimessenger astronomy without any form of electromagnetic radiation

There are multiple detectors that can look for high energy neutrinos. Currently, LIGO–Virgo Observations are being followed up by searches from ANTARES and IceCube. Both of these are Cherenkov detectors: they look for flashes of light created by fast moving particles, not the neutrinos themselves, but things they’ve interacted with. ANTARES searches the waters of the Mediterranean while IceCube uses the ice of Antarctica.

Within 500 seconds either side of the time of GW150914, ANTARES found no neutrinos and IceCube found three. These results are consistent with background levels (you would expect on average less than one and 4.4 neutrinos over that time from the two respectively). Additionally, none of the IceCube neutrinos are consistent with the sky localization of GW150914 (even though the sky area is pretty big). There is no sign of a neutrino counterpart, which is what we were expecting.

Subsequent non-detections have been reported by KamLAND, the Pierre Auger ObservatorySuper-Kamiokande, Borexino and NOvA.

The Electromagnetic Follow-up Paper

Synopsis: Electromagnetic Follow-up Paper
Read this if: You are interested in the search for electromagnetic counterparts
Favourite part: So many people were involved in this work that not only do we have to abbreviate the list of authors (Abbott, B.P. et al.), but we should probably abbreviate the list of collaborations too (LIGO Scientific & Virgo Collaboration et al.)

This is the last of the set of companion papers to be released—it took a huge amount of coordinating because of all the teams involved. The paper describes how we released information about GW150914. This should not be typical of how we will do things going forward (i) because we didn’t have all the infrastructure in place on September 14 and (ii) because it was the first time we had something we thought was real.

The first announcement was sent out on September 16, and this contained sky maps from the Burst codes cWB and LIB. In the future, we should be able to send out automated alerts with a few minutes latency.

For the first alert, we didn’t have any results which assumed the the source was a binary, as the searches which issue triggers at low latency were only looking for lower mass systems which would contain a neutron star. I suspect we’ll be reprioritising things going forward. The first information we shared about the potential masses for the source was shared on October 3. Since this was the first detection, everyone was cautious about triple-checking results, which caused the delay. Revised false alarm rates including results from GstLAL and PyCBC were sent out October 20.

The final sky maps were shared January 13. This is when we’d about finished our own reviews and knew that we would be submitting the papers soon [bonus note]. Our best sky map is the one from the Parameter Estimation Paper. You might it expect to be more con straining than the results from the burst pipelines since it uses a proper model for the gravitational waves from a binary black hole. This is the case if we ignore calibration uncertainty (which is not yet included in the burst codes), then the 50% area is 48~\mathrm{deg}^2 and the 90% area is 150~\mathrm{deg^2}. However, including calibration uncertainty, the sky areas are 150~\mathrm{deg^2} and 590~\mathrm{deg^2} at 50% and 90% probability respectively. Calibration uncertainty has the largest effect on sky area. All the sky maps agree that the source is in in some region of the annulus set by the time delay between the two detectors.

Sky map

The different sky maps for GW150914 in an orthographic projection. The contours show the 90% region for each algorithm. The faint circles show lines of constant time delay \Delta t_\mathrm{HL} between the two detectors. BAYESTAR rapidly computes sky maps for binary coalescences, but it needs the output of one of the detection pipelines to run, and so was not available at low latency. The LALInference map is our best result. All the sky maps are available as part of the data release. Fig. 2 of the Electromagnetic Follow-up Paper.

A timeline of events is shown below. There were follow-up observations across the electromagnetic spectrum from gamma-rays and X-rays through the optical and near infra-red to radio.

EM follow-up timeline

Timeline for observations of GW15014. The top (grey) band shows information about gravitational waves. The second (blue) band shows high-energy (gamma- and X-ray) observations. The third and fourth (green) bands show optical and near infra-red observations respectively. The bottom (red) band shows radio observations. Fig. 1 from the Electromagnetic Follow-up Paper.

Observations have been reported (via GCN notices) by

Together they cover an impressive amount of the sky as shown below. Many targeted the Large Magellanic Cloud before the knew the source was a binary black hole.

Follow-up observations

Footprints of observations compared with the 50% and 90% areas of the initially distributed (cWB: thick lines; LIB: thin lines) sky maps, also in orthographic projection. The all-sky observations are not shown. The grey background is the Galactic plane. Fig. 3 of the Electromagnetic Follow-up Paper.

Additional observations have been done using archival data by XMM-Newton and AGILE.

We don’t expect any electromagnetic counterpart to a binary black hole. No-one found anything with the exception of Fermi GBM. This has found a weak signal which may be coincident. More work is required to figure out if this is genuine (the statistical analysis looks OK, but some times you do have a false alarm). It would be a surprise if it is, so most people are sceptical. However, I think this will make people more interested in following up on our next binary black hole signal!

Bonus notes

Naming The Event

GW150914 is the name we have given to the signal detected by the two LIGO instruments. The “GW” is short for gravitational wave (not galactic worm), and the numbers give the date the wave reached the detectors (2015 September 14). It was originally known as G184098, its ID in our database of candidate events (most circulars sent to and from our observer partners use this ID). That was universally agreed to be terrible to remember. We tried to think of a good nickname for the event, but failed to, so rather by default, it has informally become known as The Event within the Collaboration. I think this is fitting given its significance.

LVT151012 is the name of the most significant candidate after GW150914, it doesn’t reach our criteria to claim detection (a false alarm rate of less than once per century), which is why it’s not GW151012. The “LVT” is short for LIGO–Virgo trigger. It took a long time to settle on this and up until the final week before the announcement it was still going by G197392. Informally, it was known as The Second Monday Event, as it too was found on a Monday. You’ll have to wait for us to finish looking at the rest of the O1 data to see if the Monday trend continues. If it does, it could have serious repercussions for our understanding of Garfield.

Following the publication of the O2 Catalogue Paper, LVT151012 was upgraded to GW151012, AND we decided to get rid of the LVT class as it was rather confusing.

Publishing in Physical Review Letters

Several people have asked me if the Discovery Paper was submitted to Science or Nature. It was not. The decision that any detection would be submitted to Physical Review was made ahead of the run. As far as I am aware, there was never much debate about this. Physical Review had been good about publishing all our non-detections and upper limits, so it only seemed fair that they got the discovery too. You don’t abandon your friends when you strike it rich. I am glad that we submitted to them.

Gaby González, the LIGO Spokesperson, contacted the editors of Physical Review Letters ahead of submission to let them know of the anticipated results. They then started to line up some referees to give confidential and prompt reviews.

The initial plan was to submit on January 19, and we held a Collaboration-wide tele-conference to discuss the science. There were a few more things still to do, so the paper was submitted on January 21, following another presentation (and a long discussion of whether a number should be a six or a two) and a vote. The vote was overwhelmingly in favour of submission.

We got the referee reports back on January 27, although they were circulated to the Collaboration the following day. This was a rapid turnaround! From their comments, I suspect that Referee A may be a particle physicist who has dealt with similar claims of first detection—they were most concerned about statistical significance; Referee B seemed like a relativist—they made comments about the effect of spin on measurements, knew about waveforms and even historical papers on gravitational waves, and I would guess that Referee C was an astronomer involved with pulsars—they mentioned observations of binary pulsars potentially claiming the title of first detection and were also curious about sky localization. While I can’t be certain who the referees were, I am certain that I have never had such positive reviews before! Referee A wrote

The paper is extremely well written and clear. These results are obviously going to make history.

Referee B wrote

This paper is a major breakthrough and a milestone in gravitational science. The results are overall very well presented and its suitability for publication in Physical Review Letters is beyond question.

and Referee C wrote

It is an honor to have the opportunity to review this paper. It would not be an exaggeration to say that it is the most enjoyable paper I’ve ever read. […] I unreservedly recommend the paper for publication in Physical Review Letters. I expect that it will be among the most cited PRL papers ever.

I suspect I will never have such emphatic reviews again [happy bonus note][unhappy bonus note].

Publishing in Physical Review Letters seems to have been a huge success. So much so that their servers collapsed under the demand, despite them adding two more in anticipation. In the end they had to quintuple their number of servers to keep up with demand. There were 229,000 downloads from their website in the first 24 hours. Many people remarked that it was good that the paper was freely available. However, we always make our papers public on the arXiv or via LIGO’s Document Control Center [bonus bonus note], so there should never be a case where you miss out on reading a LIGO paper!

Publishing the Parameter Estimation Paper

The reviews for the Parameter Estimation Paper were also extremely positive. Referee A, who had some careful comments on clarifying notation, wrote

This is a beautiful paper on a spectacular result.

Referee B, who commendably did some back-of-the-envelope checks, wrote

The paper is also very well written, and includes enough background that I think a decent fraction of it will be accessible to non-experts. This, together with the profound nature of the results (first direct detection of gravitational waves, first direct evidence that Kerr black holes exist, first direct evidence that binary black holes can form and merge in a Hubble time, first data on the dynamical strong-field regime of general relativity, observation of stellar mass black holes more massive than any observed to date in our galaxy), makes me recommend this paper for publication in PRL without hesitation.

Referee C, who made some suggestions to help a non-specialist reader, wrote

This is a generally excellent paper describing the properties of LIGO’s first detection.

Physical Review Letters were also kind enough to publish this paper open access without charge!

Publishing the Rates Paper

It wasn’t all clear sailing getting the companion papers published. Referees did give papers the thorough checking that they deserved. The most difficult review was of the Rates Paper. There were two referees, one astrophysics, one statistics. The astrophysics referee was happy with the results and made a few suggestions to clarify or further justify the text. The statistics referee has more serious complaints…

There are five main things which I think made the statistics referee angry. First, the referee objected to our terminology

While overall I’ve been impressed with the statistics in LIGO papers, in one respect there is truly egregious malpractice, but fortunately easy to remedy. It concerns incorrectly using the term “false alarm probability” (FAP) to refer to what statisticians call a p-value, a deliberately vague term (“false alarm rate” is similarly misused). […] There is nothing subtle or controversial about the LIGO usage being erroneous, and the practice has to stop, not just within this paper, but throughout the LIGO collaboration (and as a matter of ApJ policy).

I agree with this. What we call the false alarm probability is not the probability that the detection is a false alarm. It is not the probability that the given signal is noise rather that astrophysical, but instead it is the probability that if we only had noise that we would get a detection statistic as significant or more so. It might take a minute to realise why those are different. The former (the one we should call p-value) is what the search pipelines give us, but is less useful than the latter for actually working out if the signal is real. The probabilities calculated in the Rates Paper that the signal is astrophysical are really what you want.

p-values are often misinterpreted, but most scientists are aware of this, and so are cautious when they come across them

As a consequence of this complaint, the Collaboration is purging “false alarm probability” from our papers. It is used in most of the companion papers, as they were published before we got this report (and managed to convince everyone that it is important).

Second, we were lacking in references to existing literature

Regarding scholarship, the paper is quite poor. I take it the authors have written this paper with the expectation, or at least the hope, that it would be read […] If I sound frustrated, it’s because I am.

This is fair enough. The referee made some good suggestions to work done on inferring the rate of gamma-ray bursts by Loredo & Wasserman (Part I, Part II, Part III), as well as by Petit, Kavelaars, Gladman & Loredo on trans-Neptunian objects, and we made sure to add as much work as possible in revisions. There’s no excuse for not properly citing useful work!

Third, the referee didn’t understand how we could be certain of the distribution of signal-to-noise ratio \rho without also worrying about the distribution of parameters like the black hole masses. The signal-to-noise ratio is inversely proportional to distance, and we expect sources to be uniformly distributed in volume. Putting these together (and ignoring corrections from cosmology) gives a distribution for signal-to-noise ratio of p(\rho) \propto \rho^{-4} (Schulz 2011).  This is sufficiently well known within the gravitational-wave community that we forgot that those outside wouldn’t appreciate it without some discussion. Therefore, it was useful that the referee did point this out.

Fourth, the referee thought we had made an error in our approach. They provided an alternative derivation which

if useful, should not be used directly without some kind of attribution

Unfortunately, they were missing some terms in their expressions. When these were added in, their approach reproduced our own (I had a go at checking this myself). Given that we had annoyed the referee on so many other points, it was tricky trying to convince them of this. Most of the time spent responding to the referees was actually working on the referee response and not on the paper.

Finally, the referee was unhappy that we didn’t make all our data public so that they could check things themselves. I think it would be great, and it will happen, it was just too early at the time.

LIGO Document Control Center

Papers in the LIGO Document Control Center are assigned a number starting with P (for “paper”) and then several digits. The Discover Paper’s reference is P150914. I only realised why this was the case on the day of submission.

The überbank

The set of templates used in the searches is designed to be able to catch binary neutron stars, neutron star–black hole binaries and binary neutron stars. It covers component masses from 1 to 99 solar masses, with total masses less than 100 solar masses. The upper cut off is chosen for computational convenience, rather than physical reasons: we do look for higher mass systems in a similar way, but they are easier to confuse with glitches and so we have to be more careful tuning the search. Since bank of templates is so comprehensive, it is known as the überbank. Although it could find binary neutron stars or neutron star–black hole binaries, we only discuss binary black holes here.

The template bank doesn’t cover the full parameter space, in particular it assumes that spins are aligned for the two components. This shouldn’t significantly affect its efficiency at finding signals, but gives another reason (together with the coarse placement of templates) why we need to do proper parameter estimation to measure properties of the source.

Alphabet soup

In the calculation of rates, the probabilistic means for counting sources is known as the FGMC method after its authors (who include two Birmingham colleagues and my former supervisor). The means of calculating rates assuming that the population is divided into one class to match each observation is also named for the initial of its authors as the KKL approach. The combined FGMCKKL method for estimating merger rates goes by the name alphabet soup, as that is much easier to swallow.

Multi-band gravitational wave astronomy

The prospect of detecting a binary black hole with a space-based detector and then seeing the same binary merger with ground-based detectors is especially exciting. My officemate Alberto Sesana (who’s not in LIGO) has just written a paper on the promise of multi-band gravitational wave astronomy. Black hole binaries like GW150914 could be spotted by eLISA (if you assume one of the better sensitivities for a detector with three arms). Then a few years to weeks later they merge, and spend their last moments emitting in LIGO’s band. The evolution of some binary black holes is sketched in the plot below.

Binary black hole mergers across the eLISA and LIGO frequency bands

The evolution of binary black hole mergers (shown in blue). The eLISA and Advanced LIGO sensitivity curves are shown in purple and orange respectively. As the black holes inspiral, they emit gravitational waves at higher frequency, shifting from the eLISa band to the LIGO band (where they merge). The scale at the top gives the approximate time until merger. Fig. 1 of Sesana (2016).

Seeing the signal in two bands can help in several ways. First it can increase our confidence in detection, potentially picking out signals that we wouldn’t otherwise. Second, it gives us a way to verify the calibration of our instruments. Third, it lets us improve our parameter-estimation precision—eLISA would see thousands of cycles, which lets it pin down the masses to high accuracy, these results can be combined with LIGO’s measurements of the strong-field dynamics during merger to give a fantastic overall picture of the system. Finally, since eLISA can measure the signal for a considerable time, it can well localise the source, perhaps just to a square degree; since we’ll also be able to predict when the merger will happen, you can point telescopes at the right place ahead of time to look for any electromagnetic counterparts which may exist. Opening up the gravitational wave spectrum is awesome!

The LALInference sky map

One of my jobs as part of the Parameter Estimation group was to produce the sky maps from our parameter-estimation runs. This is a relatively simple job of just running our sky area code. I had done it many times while were collecting our results, so I knew that the final versions were perfectly consistent with everything else we had seen. While I was comfortable with running the code and checking the results, I was rather nervous uploading the results to our database to be shared with our observational partners. I somehow managed to upload three copies by accident. D’oh! Perhaps future historians will someday look back at the records for G184098/GW150914 and wonder what was this idiot Christopher Berry doing? Probably no-one would every notice, but I know the records are there…

Advanced LIGO detects gravitational waves!

The first observing run (O1) of Advanced LIGO was scheduled to start 9 am GMT (10 am BST), 14 September 2015. Both gravitational-wave detectors were running fine, but there were few a extra things the calibration team wanted to do and not all the automated analysis had been set up, so it was decided to postpone the start of the run until 18 September. No-one told the Universe. At 9:50 am, 14 September there was an event. To those of us in the Collaboration, it is known as The Event.

Measured strain

The Event’s signal as measured by LIGO Hanford and LIGO Livingston. The shown signal has been filtered to make it more presentable. The Hanford signal is inverted because of the relative orientations of the two interferometers. You can clearly see that both observatories see that same signal, and even without fancy analysis, that there are definitely some wibbles there! Part of Fig. 1 from the Discovery Paper.

Detection

The detectors were taking data and the coherent WaveBurst (cWB) detection pipeline was set up analysing this. It finds triggers in near real time, and so about 3 minutes after the gravitational wave reached Earth, cWB found it. I remember seeing the first few emails… and ignoring them—I was busy trying to finalise details for our default parameter-estimation runs for the start of O1. However, the emails kept on coming. And coming. Something exciting was happening. The detector scientists at the sites swung in to action and made sure that the instruments would run undisturbed so we could get lots of data about their behaviour; meanwhile, the remaining data analysis codes were set running with ruthless efficiency.

The cWB algorithm doesn’t search for a particular type of signal, instead it looks for the same thing in both detectors—it’s what we call a burst search. Burst searches could find supernova explosions, black hole mergers, or something unexpected (so long as the signal is short). Looking at the data, we saw that the frequency increased with time, there was the characteristic chirp of a binary black hole merger! This meant that the searches that specifically look for the coalescence of binaries (black hole or neutron stars) should find it too, if the signal was from a binary black hole. It also meant that we could analyse the data to measure the parameters.

Time–frequency plot of The Event

A time–frequency plot that shows The Event’s signal power in the detectors. You can see the signal increase in frequency as time goes on: the characteristic chirp of a binary merger! The fact that you can spot the signal by eye shows how loud it is. Part of Fig. 1 from the Discovery Paper.

The signal was quite short, so it was quick for us to run parameter estimation on it—this makes a welcome change as runs on long, binary neutron-star signals can take months. We actually had the first runs done before all the detection pipelines had finished running. We kept the results secret: the detection people didn’t want to know the results before they looked at their own results (it reminded me of the episode of Whatever Happened to the Likely Lads where they try to avoid hearing the results of the football until they can watch the match). The results from each of the detection pipelines came in [bonus note]. There were the other burst searches: LALInferenceBurst found strong evidence for a signal, and BayesWave classified it clearly as a signal, not noise or a glitch; then the binary searches: both GstLAL and PyCBC found the signal (the same signal) at high significance. The parameter-estimation results were beautiful—we had seen the merger of two black holes!

At first, we couldn’t quite believe that we had actually made the detection. The signal seemed too perfect. Famously, LIGO conducts blind injections: fake signals are secretly put into the data to check that we do things properly. This happened during the run of initial LIGO (an event known as the Big Dog), and many people still remembered the disappointment. We weren’t set up for injections at the time (that was part of getting ready for O1), and the heads of the Collaboration said that there were no plans for blind injections, but people wanted to be sure. Only three or four people in the Collaboration can perform a blind injection; however, it’s a little publicised fact that you can tell if there was an injection. The data from the instruments is recorded at many stages, so there’s a channel which records the injected signal. During a blind-injection run, we’re not allowed to look at this, but this wasn’t a blind-injection run, so this was checked and rechecked. There was nothing. People considered other ways of injecting the signal that wouldn’t be recorded (perhaps splitting the signal up and putting small bits in lots of different systems), but no-one actually understands all the control systems well enough to get this to work. There were basically two ways you could fake the signal. The first is hack into the servers at both sites and CalTech simultaneously and modify the data before it got distributed. You would need to replace all the back-ups and make sure you didn’t leave any traces of tampering. You would also need to understand the control system well enough that all the auxiliary channels (the signal as recorded at over 30 different stages throughout the detectors’ systems) had the right data. The second is to place a device inside the interferometers that would inject the signal. As long as you had a detailed understanding of the instruments, this would be simple: you’d just need to break into both interferometers without being noticed. Since the interferometers are two of the most sensitive machines ever made, this is like that scene from Mission:Impossible, except on the actually impossible difficulty setting. You would need to break into the vacuum tube (by installing an airlock in the concrete tubes without disturbing the seismometers), not disturb the instrument while working on it, and not scatter any of the (invisible) infra-red laser light. You’d need to do this at both sites, and then break in again to remove the devices so they’re not found now that O1 is finished. The devices would also need to be perfectly synchronised. I would love to see a movie where they try to fake the signal, but I am convinced, absolutely, that the easiest way to inject the signal is to collide two black holes a billion years ago. (Also a good plot for a film?)

There is no doubt. We have detected gravitational waves. (I cannot articulate how happy I was to hit the button to update that page! [bonus note])

I still remember the exact moment this hit me. I was giving a public talk on black holes. It was a talk similar to ones I have given many times before. I start with introducing general relativity and the curving of spacetime, then I talk about the idea of a black hole. Next I move on to evidence for astrophysical black holes, and I showed the video zooming into the centre of the Milky Way, ending with the stars orbiting around Sagittarius A*, the massive black hole in the centre of our galaxy (shown below). I said that the motion of the stars was our best evidence for the existence of black holes, then I realised that this was no longer the case. Now, we have a whole new insight into the properties of black holes.

Gravitational-wave astronomy

Having caught a gravitational wave, what do you do with it? It turns out that there’s rather a lot of science you can do. The last few months have been exhausting. I think we’ve done a good job as a Collaboration of assembling all the results we wanted to go with the detection—especially since lots of things were being done for the first time! I’m sure we’ll update our analysis with better techniques and find new ways of using the data, but for now I hope everyone can enjoy what we have discovered so far.

I will write up a more technical post on the results, here we’ll run through some of the highlights. For more details of anything, check out the data release.

The source

The results of our parameter-estimation runs tell us about the nature of the source. We have a binary with objects of masses 36^{+5}_{-4} M_\odot and 29^{+4}_{-4} M_\odot, where M_\odot indicates the mass of our Sun (about 2 \times 10^{30} kilograms). If you’re curious what’s going with these numbers and the pluses and minuses, check out this bonus note.

Binary black hole masses

Estimated masses for the two black holes in the binary. m_1^\mathrm{source} is the mass of the heavier black hole and m_2^\mathrm{source} is the mass of the lighter black hole. The dotted lines mark the edge of our 90% probability intervals. The different coloured curves show different models: they agree which made me incredibly happy! Fig. 1 from the Parameter Estimation Paper.

We know that we’re dealing with compact objects (regular stars could never get close enough together to orbit fast enough to emit gravitational waves at the right frequency), and the only compact objects that can be as massive as these object are black holes. This means we’re discovered the first stellar-mass black hole binary! We’ve also never seen stellar-mass black holes (as opposed to the supermassive flavour that live in the centres of galaxies) this heavy, but don’t get too attached to that record.

Black holes have at most three properties. This makes them much simpler than a Starbucks Coffee (they also stay black regardless of how much milk you add). Black holes are described by their mass, their spin (how much they rotate), and their electric charge. We don’t expect black holes out in the Universe to have much electric charge because (i) its very hard to separate lots of positive and negative charge in the first place, and (ii) even if you succeed at (i), it’s difficult to keep positive and negative charge apart. This is kind of like separating small children and sticky things that are likely to stain. Since the electric charge can be ignored, we just need mass and spin. We’ve measured masses, can we measure spins?

Black hole spins are defined to be between 0 (no spin) and 1 (the maximum amount you can have). Our best estimates are that the bigger black hole has spin 0.3_{-0.3}^{+0.5}, and the small one has spin 0.5_{-0.4}^{+0.5} (these numbers have been rounded). These aren’t great measurements. For the smaller black hole, its spin is almost equally probable to take any allowed value; this isn’t quite the case, but we haven’t learnt much about its size. For the bigger black hole, we do slightly better, and it seems that the spin is on the smaller side. This is interesting, as measurements of spins for black holes in X-ray binaries tend to be on the higher side: perhaps there are different types of black holes?

We can’t measure the spins precisely for a few reasons. The signal is short, so we don’t see lots of wibbling while the binaries are orbiting each other (the tell-tale sign of spin). Results for the orientation of the binary also suggest that we’re looking at it either face on or face off, which makes any wobbles in the orbit that are there less visible. However, there is one particular combination of the spins, which we call the effective spin, that we can measure. The effective spin controls how the black holes spiral together. It has a value of 1 if both black holes have max spin values, and are rotating the same way as the binary is orbiting. It has a value of −1 if the black holes have max spin values and are both rotating exactly the opposite way to the binary’s orbit. We find that the effective spin is small, -0.06_{-0.18}^{+0.17}. This could mean that both black holes have small spins, or that they have larger spins that aren’t aligned with the orbit (or each other). We have learnt something about the spins, it’s just not too easy to tease that apart to give values for each of the black holes.

As the two black holes orbit each other, they (obviously, given what we’ve seen) emit gravitational waves. These carry away energy and angular momentum, so the orbit shrinks and the black holes inspiral together. Eventually they merge and settle down into a single bigger black hole. All this happens while we’re watching (we have great seats). A simulation of this happening is below. You can see that the frequency of the gravitational waves is twice that of the orbit, and the video freezes around the merger so you can see two become one.

What are the properties of the final black hole? The mass of the remnant black holes is 62^{+4}_{-4} M_\odot. It is the new record holder for the largest observed stellar-mass black hole!

If you do some quick sums, you’ll notice that the final black hole is lighter than the sum of the two initial black holes. This is because of that energy that was carried away by the gravitational waves. Over the entire evolution of the system, 3.0^{+0.5}_{-0.4} M_\odot c^2 \simeq 5.3_{-0.8}^{+0.9} \times 10^{47}~\mathrm{J} of energy was radiated away as gravitational waves (where c is the speed of light as in Einstein’s famous equation). This is a colossal amount of energy. You’d need to eat over eight billion times the mass of the Sun in butter to get the equivalent amount of calories. (Do not attempt the wafer-thin mint afterwards). The majority of that energy is radiated within the final second. For a brief moment, this one black hole merger outshines the whole visible Universe if you compare its gravitational-wave luminosity, to everything else’s visible-light luminosity!

We’ve measured mass, what about spin? The final black hole’s spin in 0.67^{+0.05}_{-0.07}, which is in the middling-to-high range. You’ll notice that we can deduce this to a much higher precisely than the spins of the two initial black holes. This is because it is largely fixed by the orbital angular momentum of the binary, and so its value is set by orbital dynamics and gravitational physics. I think its incredibly satisfying that we we can such a clean measurement of the spin.

We have measured both of the properties of the final black hole, and we have done this using spacetime itself. This is astounding!

Final black hole mass and spin

Estimated mass M_\mathrm{f}^\mathrm{source} and spin a_\mathrm{f}^\mathrm{source} for the final black hole. The dotted lines mark the edge of our 90% probability intervals. The different coloured curves show different models: they agree which still makes me incredibly happy! Fig. 3 from the Parameter Estimation Paper.

How big is the final black hole? My colleague Nathan Johnson-McDaniel has done some calculations and finds that the total distance around the equator of the black hole’s event horizon is about 1100~\mathrm{km} (about six times the length of the M25). Since the black hole is spinning, its event horizon is not a perfect sphere, but it bulges out around the equator. The circumference going over the black hole’s poles is about 1000~\mathrm{km} (about five and a half M25s, so maybe this would be the better route for your morning commute). The total area of the event horizon is about 37000~\mathrm{km}^2. If you flattened this out, it would cover an area about the size of Montana. Neil Cornish (of Montana State University) said that he’s not sure which we know more accurately: the area of the event horizon or the area of Montana!

OK, we’ve covered the properties of the black holes, perhaps it’s time for a celebratory biscuit and a sit down? But we’re not finished yet, where is the source?

We infer that the source is at a luminosity distance of 410^{+160}_{-180}~\mathrm{Mpc}, a megaparsec is a unit of length (regardless of what Han Solo thinks) equal to about 3 million light-years. The luminosity distance isn’t quite the same as the distance you would record using a tape measure because it takes into account the effects of the expansion of the Universe. But it’s pretty close. Using our 90% probability range, the merger would have happened sometime between 700 million years and 1.6 billion years ago. This coincides with the Proterozoic Eon on Earth, the time when the first oxygen-dependent animals appeared. Gasp!

With only the two LIGO detectors in operation, it is difficult to localise where on the sky source came from. To have a 90% chance of finding the source, you’d need to cover 600~\mathrm{deg^2} of the sky. For comparison, the full Moon is about 0.2~\mathrm{deg^2}. This is a large area to cover with a telescope, and we don’t expect there to be anything to see for a black hole merger, but that hasn’t stopped our intrepid partners from trying. For a lovely visualisation of where we think the source could be, marvel at the Gravoscope.

Astrophysics

The detection of this black hole merger tells us:

  • Black holes 30 times the mass of our Sun do form These must be the remains of really massive stars. Stars lose mass throughout their lifetime through stellar winds. How much they lose depends on what they are made from. Astronomers have a simple periodic table: hydrogen, helium and metals. (Everything that is not hydrogen or helium is a metal regardless of what it actually is). More metals means more mass loss, so to end up with our black holes, we expect that they must have started out as stars with less than half the fraction of metals found in our Sun. This may mean the parent stars were some of the first stars to be born in the Universe.
  • Binary black holes exist There are two ways to make a black hole binary. You can start with two stars in a binary (stars love company, so most have at least one companion), and have them live their entire lives together, leaving behind the two black holes. Alternatively, you could have somewhere where there are lots of stars and black holes, like a globular cluster, and the two black holes could wander close enough together to form the binary. People have suggested that either (or both) could happen. You might be able to tell the two apart using spin measurements. The spins of the black holes are more likely to be aligned (with each other and the way that the binary orbits) if they came from stars formed in a binary. The spins would be randomly orientated if two black holes came together to form a binary by chance. We can’t tell the two apart now, but perhaps when we have more observations!
  • Binary black holes merge Since we’ve seen a signal from two black holes inspiralling together and merging, we know that this happens. We can also estimate how often this happens, given how many signals we’ve seen in our observations. Somewhere in the observable Universe, a similar binary could be merging about every 15 minutes. For LIGO, this should mean that we’ll be seeing more. As the detectors’ sensitivity improves (especially at lower frequencies), we’ll be able to detect more and more systems [bonus note]. We’re still uncertain in our predictions of exactly how many we’ll see. We’ll understand things better after observing for longer: were we just lucky, or were we unlucky not to have seen more? Given these early results, we estimate that the end of the third observing run (O3), we could have over 30. It looks like I will be kept busy over the next few years…

Gravitational physics

Black holes are the parts of the Universe with the strongest possible gravity. They are the ideal place to test Einstein’s theory of general relativity. The gravitational waves from a black hole merger let us probe right down to the event horizon, using ripples in spacetime itself. This makes gravitational waves a perfect way of testing our understanding of gravity.

We have run some tests on the signal to see how well it matches our expectations. We find no reason to doubt that Einstein was right.

The first check is that if we try to reconstruct the signal, without putting in information about what gravitational waves from a binary merger look like, we find something that agrees wonderfully with our predictions. We can reverse engineer what the gravitational waves from a black hole merger look like from the data!

Estimated waveforms from different models

Recovered gravitational waveforms from our analysis of The Event. The dark band shows our estimate for the waveform without assuming a particular source (it is build from wavelets, which sound adorable to me). The light bands show results if we assume it is a binary black hole (BBH) as predicted by general relativity. They match really well! Fig. 6 from the Parameter Estimation Paper.

As a consistency test, we checked what would happen if you split the signal in two, and analysed each half independently with our parameter-estimation codes. If there’s something weird, we would expect to get different results. We cut the data into a high frequency piece and a low frequency piece at roughly where we think the merger starts. The lower frequency (mostly) inspiral part is more similar to the physics we’ve tested before, while the higher frequency (mostly) merger and ringdown is new and hence more uncertain. Looking at estimates for the mass and spin of the final black hole, we find that the two pieces are consistent as expected.

In general relativity, gravitational waves travel at the speed of light. (The speed of light is misnamed, it’s really a property of spacetime, rather than of light). If gravitons, the theoretical particle that carries the gravitational force, have a mass, then gravitational waves can’t travel at the speed of light, but would travel slightly slower. Because our signals match general relativity so well, we can put a limit on the maximum allowed mass. The mass of the graviton is less than 1.2 \times 10^{-22}~\mathrm{eV\,c^{-2}} (in units that the particle physicists like). This is tiny! It is about as many times lighter than an electron as an electron is lighter than a teaspoon of water (well, 4~\mathrm{g}, which is just under a full teaspoon), or as many times lighter than the almost teaspoon of water is than three Earths.

Limits on the Compton wavelength of the graviton

Bounds on the Compton wavelength \lambda_g of the graviton from The Event (GW150914). The Compton wavelength is a length defined by the mass of a particle: smaller masses mean large wavelengths. We place much better limits than existing tests from the Solar System or the double pulsar. There are some cosmological tests which are stronger still (but they make assumptions about dark matter). Fig. 8 from the Testing General Relativity Paper.

Overall things look good for general relativity, it has passed a tough new test. However, it will be extremely exciting to get more observations. Then we can combine all our results to get the best insights into gravity ever. Perhaps we’ll find a hint of something new, or perhaps we’ll discover that general relativity is perfect? We’ll have to wait and see.

Conclusion

100 years after Einstein predicted gravitational waves and Schwarzschild found the equations describing a black hole, LIGO has detected gravitational waves from two black holes orbiting each other. This is the culmination of over forty years of effort. The black holes inspiral together and merge to form a bigger black hole. This is the signal I would have wished for. From the signal we can infer the properties of the source (some better than others), which makes me exceedingly happy. We’re starting to learn about the properties of black holes, and to test Einstein’s theory. As we continue to look for gravitational waves (with Advanced Virgo hopefully joining next year), we’ll learn more and perhaps make other detections too. The era of gravitational-wave astronomy has begun!

After all that, I am in need of a good nap! (I was too excited to sleep last night, it was like a cross between Christmas Eve and the night before final exams). For more on the story from scientists inside the LIGO–Virgo Collaboration, check out posts by:

  • Matt Pitkin (the tireless reviewer of our parameter-estimation work)
  • Brynley Pearlstone (who’s just arrived at the LIGO Hanford site)
  • Amber Stuver (who  blogged through LIGO’s initial runs too)
  • Rebecca Douglas (a good person to ask about what build a detector out of)
  • Daniel Williams (someone fresh to the Collaboration)
  • Sean Leavey (a PhD student working on on interferometry)
  • Andrew Williamson (who likes to look for gravitational waves that coincide with gamma-ray bursts)
  • Shane Larson (another fan of space-based gravitational-wave detectors)
  • Roy Williams (who helps to make all the wonderful open data releases for LIGO)
  • Chris North (creator of the Gravoscope amongst other things)

There’s also this video from my the heads of my group in Birmingham on their reactions to the discovery (the credits at the end show how large an effort the detection is).

Discovery paper: Observation of Gravitational Waves from a Binary Black Hole Merger
Date release:
LIGO Open Science Center

Bonus notes

Search pipelines

At the Large Hadron Collider, there are separate experiments that independently analyse data, and this is an excellent cross-check of any big discoveries (like the Higgs). We’re not in a position to do this for gravitational waves. However, the different search pipelines are mostly independent of each other. They use different criteria to rank potential candidates, and the burst and binary searches even look for different types of signals. Therefore, the different searches act as a check of each other. The teams can get competitive at times, so they do check each other’s results thoroughly.

The announcement

Updating Have we detected gravitational waves yet? was doubly exciting as I had to successfully connect to the University’s wi-fi. I managed this with about a minute to spare. Then I hovered with my finger on the button until David Reitze said “We. Have detected. Gravitational waves!” The exact moment is captured in the video below, I’m just off to the left.

Univeristy of Birmingham detection announcement

The moment of the announcement of the first observation of gravitational waves at the University of Birmingham. Credit: Kat Grover

Parameters and uncertainty

We don’t get a single definite number from our analysis, we have some uncertainty too. Therefore, our results are usually written  as the median value (which means we think that the true value is equally probable to be above or below this number), plus the range needed to safely enclose 90% of the probability (so there’s a 10% chance the true value is outside this range. For the mass of the bigger black hole, the median estimate is 36 M_\odot, we think there’s a 5% chance that the mass is below 32 M_\odot =(36 - 4) M_\odot, and a 5% chance it’s above 41 M_\odot =(36 + 5) M_\odot, so we write our result as 36^{+5}_{-4} M_\odot.

Sensitivity and ranges

Gravitational-wave detectors measure the amplitude of the wave (the amount of stretch and squash). The measured amplitude is smaller for sources that are further away: if you double the luminosity distance of a source, you halve its amplitude. Therefore, if you improve your detectors’ sensitivity by a factor of two, you can see things twice as far away. This means that we observe a volume of space (2 × 2 × 2) = 8 times as big. (This isn’t exactly the case because of pesky factors from the expansion of the Universe, but is approximately right). Even a small improvement in sensitivity can have a considerable impact on the number of signals detected!

Neutrino oscillations and Nobel Prizes

This year’s Nobel Prize in Physics was awarded to Takaaki Kajita and Arthur McDonald for the discovery of neutrino oscillations. This is some really awesome physics which required some careful experimentation and some interesting new theory; it is also one of the things that got me interested in astrophysics.

Neutrinos

Neutrinos are an elusive type of subatomic particle. They are sometimes represented by the Greek letter nu \nu, and their antiparticle equivalents (antineutrinos) are denoted by \bar{\nu}. We’ll not worry about the difference between the two. Neutrinos are rather shy. They are quite happy doing their own thing, and don’t interact much with other particles. They don’t have an electric charge (they are neutral), so they don’t play with the electromagnetic force (and photons), they also don’t do anything with the strong force (and gluons). They only get involved with the weak force (W and Z bosons). As you might expect from the name, the weak force doesn’t do much (it only operates over short distances), so spotting a neutrino is a rare occurrence.

Particle Zoo

The charming bestiary of subatomic particles made by Particle Zoo.

There is a large family of subatomic particles. The electron is one of the most familiar, being a component of atoms (and hence you, me, cake and even marshmallows). The electron has two cousins: the muon (not to be confused with the moo-on) and the tau particle. All three have similar characteristics, with the only real difference being their mass. Electrons are the lightest, muons are about 207 times heavier, and tau are about 17 times heavier still (3477 times the mass of the electron). Each member of the electron family has a neutrino counterpart: there’s the electron-neutrino \nu_e, the muon-neutrino \nu_\mu (\mu is the Greek letter mu) and the tau-neutrino \nu_\tau (\tau is the Greek letter tau).

Neutrinos are created and destroyed in in certain types of nuclear reactions. Each flavour of neutrino is only involved in reactions that involve their partner from the electron family. If an electron-neutrino is destroyed in a reaction, an electron is created; if a muon is destroyed, a muon-neutrino is created, and so on.

Solar neutrinos

Every second, around sixty billion neutrinos pass through every square centimetre on the Earth. Since neutrinos so rarely interact, you would never notice them. The source of these neutrinos is the Sun. The Sun is powered by nuclear fusion. Hydrogen is squeezed into helium through a series of nuclear reactions. As well as producing the energy that keeps the Sun going, these create lots of neutrinos.

The pp chain

The nuclear reactions that power the Sun. Protons (p), which are the nuclei of hydrogen, are converted to Helium nuclei after a sequence of steps. Electron neutrinos \nu_e are produced along the way. This diagram is adapted from Giunti & Kim. The traditional names of the produced neutrinos are given in bold and the branch names are given in parentheses and percentages indicate branching fractions.

The neutrinos produced in the Sun are all electron-neutrinos. Once made in the core of the Sun, they are free to travel the 700,000 km to the surface of the Sun and then out into space (including to us on Earth). Detecting these neutrinos therefore lets you see into the very heart of the Sun!

Solar neutrinos were first detected by the Homestake experiment. This looked for the end results of nuclear reactions caused when an electron-neutrino is absorbed. Basically, it was a giant tub of dry-cleaning fluid. This contains chlorine, which turns to argon when a neutrino is absorbed. The experiment had to count how many atoms of argon where produced. In 1968, the detection was announced. However, we could only say that there were neutrinos around, not that they were coming from the Sun…

To pin down where the neutrinos were coming from required a new experiment. Deep in the Kamioka Mine, Kamiokande looked for interactions between neutrinos and electrons. Very rarely a neutrino will bump into an electron. This can give the electron a big kick (since the neutrino has a lot of momentum). Kamiokande had a large tank of water (and so lots of electrons to hit). If one got a big enough kick, it could travel faster than the speed of light in water (about 2/3 of the speed of light in vacuum). It then emits a flash of light called Cherenkov radiation, which is the equivalent of the sonic boom created when a plane travels faster than the speed of sound. Looking where the light comes from tells you where the electron was coming from and so where the neutrino came from. Tracing things back, it was confirmed that the neutrinos were coming from the Sun!

This discovery confirmed that the Sun was powered by fusion. I find it remarkable that it was only in the late 1980s that we had hard evidence for what was powering the Sun (that’s within my own lifetime). This was a big achievement, and Raymond Davies Jr., the leader of the Homestake experiment, and Masatoshi Koshiba, the leader of the Kamiokande experiment, were awarded the 2002 Nobel Prize in Physics for pioneering neutrino astrophysics. This also led to one of my all-time favourite pictures: the Sun at night.

The Sun at night!

The Sun at night. Solar neutrinos as detected by Super-Kamioknade looking through the Earth. I think this is the astronomical equivalent of checking if the fridge light does go off when you close the door. Credit: Marcus Chown & Super-Kamiokande.

The mystery of the missing neutrinos

Detecting solar neutrinos was a big success, but there was a problem. There were only a fraction of the predicted number. This became known as the solar neutrino problem. There were two possibilities, either solar physicists had got their models wrong, or particle physicists were missing a part of the Standard Model.

The solar models were recalculated and tweaked, with much work done by John Bahcall and collaborators. More sophisticated calculations were performed, even folding in new data from helioseismology, the study of waves in the Sun, but the difference could not be resolved.

However, there was an idea in particle physics by Bruno Pontecorvo and Vladimir Gribov: that neutrinos could change flavour, a phenomena known as neutrino oscillations. This was actually first suggested before the first Homestake results were announced, perhaps it deserved further attention?

The first evidence in favour of neutrino oscillations comes from Super-Kamiokande, the successor to the original Kamiokande. This evidence came from looking at neutrinos produced by cosmic rays. Cosmic rays are highly energetic particles that come from space. As they slam into the atmosphere, and collide with molecules in the air, they produce a shower of particles. These include muons and muon-neutrinos. Super-Kamiokande could detect muon-neutrinos from cosmic rays. Cosmic rays come from all directions, so Super-Kamiokande should see muon-neutrinos from all directions too. Just like we can see the solar neutrinos through the Earth, we should see muon-neutrinos both from above and below. However, more were detected from above than below.

Something must happen to muon-neutrinos during their journey through the Earth. Super-Kamiokande could detect them as electron-neutrinos or muon-neutrinos, but is not sensitive to tau-neutrinos. This is evidence that muon-neutrinos were changing flavour to tau-neutrinos.

Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory detector, a 12-metre sphere containing 1000 tonnes of heavy water which is two kilometres underground. Credit: SNOLAB.

The solar neutrino problem was finally solved in 2001 through measurements of the Sudbury Neutrino Observatory (SNO). SNO is another Cherenkov detector like (Super-)Kamiokande, but it used heavy water instead of regular water. (High-purity heavy water is extremely expensive, it would have cost hundreds of millions of dollars for SNO to buy the 1000 tonnes it used, so it managed to secure it on loan from Atomic Energy of Canada Limited). Using heavy water meant that SNO was sensitive to all flavours of neutrinos. Like previous experiments, SNO found that there were not as many electron-neutrinos from the Sun as expected. However, there were also muon-neutrinos and tau-neutrinos, and when these were added, the total worked out!

The solar astrophysicists had been right all along, what was missing was that neutrinos oscillate between flavours. Studying the Sun had led to a discovery about some of the smallest particles in Nature.

Neutrino oscillations

Experiments have shown that neutrino oscillations occur, but how does this work? We need to delve into quantum mechanics.

The theory of neutrino oscillations say that each of the neutrino flavours corresponds to a different combination of neutrino mass states. This is weird, it means that if you were to somehow weight an electron-, muon- or tau-neutrino, you would get one of three values, but which one is random (although on average, each flavour would have a particular mass). By rearranging the mass states into a different combination you can get a different neutrino flavour. While neutrinos are created as a particular flavour, when they travel, the mass states rearrange relative to each other, so when they arrive at their destination, they could have changed flavour (or even changed flavour and then changed back again).

To get a more detailed idea of what’s going on, we’ll imagine the simpler case of there being only two neutrino flavours (and two neutrino mass states). We can picture a neutrino as a clock face with an hour hand and a minute hand. These represent the two mass states. Which neutrino flavour we have depends upon their relative positions. If they point in the same direction, we have one flavour (let’s say mint) and if they point in opposite directions, we have the other (orange). We’ll create a mint neutrino at 12 noon and watch it evolve. The hands more at different speeds, so at ~12:30 pm, they are pointing opposite ways, and our neutrino has oscillated into an orange neutrino. At ~1:05 pm, the hands are aligned again, and we’re back to mint. Which neutrino you have depends when you look. At 3:30 am, you’ll have a roughly even chance of finding either flavour and at 6:01 pm, you’ll be almost certain to have orange neutrino, but there’s still a tiny chance of finding an mint one. As time goes on, the neutrino oscillates back and forth.

With three neutrinos flavours, things are more complicated, but the idea is similar. You can imagine throwing in a second hand and making different flavours based upon the relative positions of all three hands.

We can now explain why Super-Kamiokande saw different numbers of muon-neutrinos from different sides of the Earth. Those coming from above only travel a short distance, there’s little time between when they were created and when they are detected, so there’s not much chance they’ll change flavour. Those coming through the Earth have had enough time to switch flavour.

A similar thing happens as neutrinos travel from the core of the Sun out to the surface. (There’s some interesting extra physics that happens here too. A side effect of there being so much matter at the centre of the Sun, the combination of mass states that makes up the different flavours is different than at the outside. This means that even without the hands on the clock going round, we can get a change in flavour).

Neutrino oscillations happen because neutrino mass states are not the same as the flavour states. This requires that neutrinos have mass. In the Standard Model, neutrinos are massless, so the Standard Model had to be extended.

2015 Physics Nobel laureates

2015 Physics Nobel laureates, Takaaki Kajita and Arthur B. McDonald. Credit: Nobel Foundation.

Happy ending

For confirming that neutrinos have mass, Takaaki Kajita of Super-Kamiokande and Arthur McDonald of SNO won this year’s Nobel Prize. It is amazing how much physics has been discovered from trying to answer as simple a question as how does the Sun shine?

Even though neutrinos are shy, they are really interesting characters when you get to know them.

Now that the mystery of the missing neutrinos is solved, what is next? Takaaki Kajita is now involved in another project in the Kamioka Mine, the construction of KAGRA, a gravitational-wave detector.

KAGRA control room

The control room of KAGRA, the gravitational-wave detector in the Hida Mountains, Japan. I visited June 2015. Could a third Nobel come out of the Kamioka Mine?

General relativity at 100

General relativity, our best theory of gravitation, turns 100 this week!

Where is the cake?

Happy birthday general relativity! Einstein presented his field equations to the Prussian Academy of Science on 25 November 1915.

Gravity is the force which pulls us down towards the ground and keeps the Earth in orbit around the Sun. It is the most important force in astrophysics, causing gas clouds to collapse down to become stars; binding gas, stars and dark matter to become galaxies, and governing the overall evolution of the Universe.

Our understanding of gravity dates back to Isaac Newton. Newton realised that the same force that makes apples fall from trees also controls the motion of the planets. Realising that we could use physics to explain the everyday and the entire cosmos was a big leap! Newton’s theory was hugely successful, but he was never quite satisfied with it. In his theory gravity acted between distant objects (the Earth and an apple or the Earth and the Sun) instantaneously, without any explanation of what was linking them. The solution to this would come over 200 years later from Albert Einstein.

Einstein’s first big idea didn’t come from thinking about gravity, but thinking about electromagnetism. Electromagnetism is the force that is responsible for fridge magnets sticking, atoms binding to form molecules and the inner workings of whatever device you are currently reading this on. According to the rules of electromagnetism, ripples in electromagnetic fields (better known as light) always travel at a particular speed. This tweaked Einstein’s curiosity, as the rules didn’t say what this speed was relative to: you should measure the same speed if standing still, travelling at 100 miles per hour in a train or at a million miles per hour in a spacecraft. Speed is the distance travelled divided by the time taken, so Einstein realised that if the speed is always the same, then distances and times must appear different depending upon how you are moving! Moving clocks tick slower; at everyday speeds this effect is tiny, but we have confirmed that this is indeed the case. These ideas about space and time became known as Einstein’s theory of special relativity. Special relativity has a couple of important consequences, one is the infamous equation, the other is that the speed of light becomes a universal speed limit.

Special relativity says that no information can travel faster than the speed of light; this is a problem for Newton’s theory of gravitation, where the effects of gravity are transmitted instantaneously. Einstein knew that he would have to extend his theory to include gravity and freely falling objects, and he spend almost 11 years pondering on the problem. The result was general relativity.

In special relativity, space and time become linked, merging into one another depending upon how you are moving relative to what you are measuring. General relativity takes this further and has space–time distorted by the energy and matter. This idea can be a little tricky to explain.

In Newtonian mechanics, things (apples, light, billiard balls, etc.) like to travel in straight lines. They keep going at a constant speed in the same direction unless there is a force acting on them. Gravity is a force which pulls things away from their straight line, pulling the Earth into its circular orbit around the Sun, and accelerating an apple towards the ground. In general relativity, we take a different view. Things still travel in a straight line, but the effect of gravity is to bend space–time! A straight line in a curved space is a curve. If we don’t know about the curvature, it looks like the object is pulled off its straight line and there must be a force doing this, which we call gravity. Alternatively, we can say that gravity curves the space–time, and that the object follows its straight line in this. In general relativity, space–time tells matter how to move; matter tells space–time how to curve.

Shotest distance between London and New York

The shortest way to travel from London Heathrow airport to JFK International airport. On a long-distance flight, you may have noticed that it appears that you are moving along a curved line, but that is because the shortest distance across the Earth’s curved surface is a curve. We call this a geodesic, and the same idea applies to curved space–time in general relativity. Credit: Mr Reid.

General relativity solves Newton’s original worries. Objects are connected by space–time. This is not the rigid background of Newtonian physics, but a dynamic object, that is shaped by its contents. Space–time is curved by mass, and when the mass moves or reshapes itself, it takes time for the curvature everywhere else to readjust. When you drop a pebble into a pond, you disturb the surface, but it takes a while for the water further away to know about the splash; there’s a ripple that travels outwards, carrying the information about the disturbance. A similar thing happens for changes in gravity, there are ripples in space–time. Ripples in electromagnetic fields are electromagnetic waves, and these ripples in the gravitational fields are gravitational waves: both travel at the speed of light, in agreement with special relativity.

General relativity is not only a beautiful theory, it has so far passed every experimental test. Right from the start Einstein looked for checks of his theory. One of the calculations he did while formulating his theory was how the orbit of Mercury would change. Mercury is the planet closest to the Sun and so experiences the strongest gravity. Its orbit isn’t a perfect circle, but an ellipse so that Mercury is sometimes a little closer to the Sun, and is sometimes a little further. In Newtonian gravity, each orbit should trace out exactly the same path, but in general relativity there is some extra rotation. Each orbit is slightly shifted with respect to the last, so if you traced out many orbits, you’d end up with a Spirograph-like pattern. This is known as precession of the orbit, and is a consequence of there being slightly greater curvature closer to the Sun. This evolution of Mercury’s orbit had already been measured. Some thought it indicated there was a new planet inside Mercury’s orbit (which was called Vulcan but isn’t Spock’s home) that was giving it a little pull. However, Einstein calculated the general relativity predicted exactly the right amount of extra rotation!

The next test came in 1919. General relativity predicts that the path of light is bent by massive objects. This is gravitational lensing. At the time, the only object that could cause measurable bending was the Sun. If we could measure a change in the position of background stars when the Sun was in front of them, we could check if the amount of bending was as expected. There’s an obvious problem here: the Sun’s so bright that you can’t see stars around it. Arthur Eddington had the idea of making the measurement during an eclipse. He mounted an expedition and confirmed the prediction. This was big news and made Einstein a superstar.

Now, 100 years after Einstein proposed his theory, we are poised to make the most precise tests. There is currently a global effort to directly detect gravitational waves. Measuring the gravitational waves will tell us if ripples in space–time behave as Einstein predicted. The waves will also tell us about the systems that created them, this will give us an up-close glimpse of black holes. Black holes are the regions of strongest gravity; they are where the curvature of space–time becomes so immense that all straight lines lead inwards. Checking that the black holes of Nature match what we expect from general relativity, will test the theory in the most extreme conditions possible.

The Advanced LIGO detectors are currently listening for gravitational-wave signals from merging neutron stars or black holes, and next year Advanced Virgo plans join the hunt too. We don’t (yet) know how often such signals occur, so we can’t say when the first detection will be made. Perhaps this will be soon and we will learn something more about gravitation…

Ripples in space time

Merging black holes create ripples in space time. These can be detected with a laser interferometer. Credit: Gravitational Wave Group.

Searches for continuous gravitational waves from nine young supernova remnants

The LIGO Scientific Collaboration is busy analysing the data we’re currently taking with Advanced LIGO at the moment. However, the Collaboration is still publishing results from initial LIGO too. The most recent paper is a search for continuous waves—signals that are an almost constant hum throughout the observations. (I expect they’d be quite annoying for the detectors). Searching for continuous waves takes a lot of computing power (you can help by signing up for Einstein@Home), and is not particularly urgent since the sources don’t do much, hence it can take a while for results to appear.

Supernova remnants

Massive stars end their lives with an explosion, a supernova. Their core collapses down and their outer layers are blasted off. The aftermath of the explosion can be beautiful, with the thrown-off debris forming a bubble expanding out into the interstellar medium (the diffuse gas, plasma and dust between stars). This structure is known as a supernova remnant.

The bubble of a supernova remnant

The youngest known supernova remnant, G1.9+0.3 (it’s just 150 years old), observed in X-ray and optical light. The ejected material forms a shock wave as it pushes the interstellar material out of the way. Credit: NASA/CXC/NCSU/DSS/Borkowski et al.

At the centre of the supernova remnant may be what is left following the collapse of the core of the star. Depending upon the mass of the star, this could be a black hole or a neutron star (or it could be nothing). We’re interested in the case it is a neutron star.

Neutron stars

Neutron stars are incredibly dense. One teaspoon’s worth would have about as much mass as 300 million elephants. Neutron stars are like giant atomic nuclei. We’re not sure how matter behaves in such extreme conditions as they are impossible to replicate here on Earth.

If a neutron star rotates rapidly (we know many do) and has an uneven or if there are waves in the the neutron star that moves lots of material around (like Rossby waves on Earth), then it can emit continuous gravitational waves. Measuring these gravitational waves would tell you about how bumpy the neutron star is or how big the waves are, and therefore something about what the neutron star is made from.

Neutron stars are most likely to emit loud gravitational waves when they are young. This is for two reasons. First, the supernova explosion is likely to give the neutron star a big whack, this could ruffle up its surface and set off lots of waves, giving rise to the sort of bumps and wobbles that emit gravitational waves. As the neutron star ages, things can quiet down, the neutron star relaxes, bumps smooth out and waves dissipate. This leaves us with smaller gravitational waves. Second, gravitational waves carry away energy, slowing the rotation of the neutron star. This also means that the signal gets quieter (and harder) to detect as the  neutron star ages.

Since young neutron stars are the best potential sources, this study looked at nine young supernova remnants in the hopes of finding continuous gravitational waves. Searching for gravitational waves from particular sources is less computationally expensive than searching the entire sky. The search included Cassiopeia A, which had been previously searched in LIGO’s fifth science run, and G1.9+0.3, which is only 150 years old, as discovered by Dave Green. The positions of the searched supernova remnants are shown in the map of the Galaxy below.

Galactic map of supernova remnants

The nine young supernova remnants searched for continuous gravitational waves. The yellow dot marks the position of the Solar System. The green markers show the supernova remnants, which are close to the Galactic plane. Two possible positions for Vela Jr (G266.2−1.2) were used, since we are uncertain of its distance. Original image: NASA/JPL-Caltech/ESO/R. Hurt.

Gravitational-wave limits

No gravitational waves were found. The search checks how well template waveforms match up with the data. We tested that this works by injecting some fake signals into the data.  Since we didn’t detect anything, we can place upper limits on how loud any gravitational waves could be. These limits were double-checked by injecting some more fake signals at the limit, to see if we could detect them. We quoted 95% upper limits, that is where we expect that if a signal was present we could see it 95% of the time. The results actually have a small safety margin built in, so the injected signals were typically found 96%–97% of the time. In any case, we are fairly sure that there aren’t gravitational waves at or above the upper limits.

These upper limits are starting to tell us interesting things about the size of neutron-star bumps and waves. Hopefully, with data from Advanced LIGO and Advanced Virgo, we’ll actually be able to make a detection. Then we’ll not only be able to say that these bumps and waves are smaller than a particular size, but they are this size. Then we might be able to figure out the recipe for making the stuff of neutron stars (I think it might be more interesting than just flour and water).

arXiv: 1412.5942 [astro-ph.HE]
Journal: Astrophysical Journal; 813(1):39(16); 2015
Science summary: Searching for the youngest neutron stars in the Galaxy
Favourite supernova remnant:
 Cassiopeia A

Advanced LIGO: O1 is here!

The LIGO sites

Aerial views of LIGO Hanford (left) and LIGO Livingston (right). Both have 4 km long arms (arranged in an L shape) which house the interferometer beams. Credit: LIGO/Caltech/MIT.

The first observing run (O1) of Advanced LIGO began just over a week ago. We officially started at 4 pm British Summer Time, Friday 18 September. It was a little low key: you don’t want lots of fireworks and popping champagne corks next to instruments incredibly sensitive to vibrations. It was a smooth transition from our last engineering run (ER8), so I don’t even think there were any giant switches to throw. Of course, I’m not an instrumentalist, so I’m not qualified to say. In any case, it is an exciting time, and it is good to see some media attention for the Collaboration (with stories from Nature, the BBC and Science).

I would love to keep everyone up to date with the latest happenings from LIGO. However, like everyone in the Collaboration, I am bound by a confidentiality agreement. (You don’t want to cross people with giant lasers). We can’t have someone saying that we have detected a binary black hole (or that we haven’t) before we’ve properly analysed all the data, finalised calibration, reviewed all the code, double checked our results, and agreed amongst ourselves that we know what’s going on. When we are ready, announcements will come from the LIGO Spokespreson Gabriela González and the Virgo Spokesperson Fulvio Ricci. Event rates are uncertain and we’re not yet at final sensitivity, so don’t expect too much of O1.

There are a couple of things that I can share about our status. Whereas normally everything I write is completely unofficial, these are suggested replies to likely questions.

Have you started taking data?
We began collecting science quality data at the beginning of September, in preparation of the first Observing Run that started on Friday, September 18, and are planning on collecting data for about 4 months

We certainly do have data, but there’s nothing new about that (other than the improved sensitivity). Data from the fifth and sixth science runs of initial LIGO are now publicly available from the Gravitational Wave Open Science Center. You can go through it and try to find anything we missed (which is pretty cool).

Have you seen anything in the data yet?
We analyse the data “online” in an effort to provide fast information to astronomers for possible follow up of triggers using a relatively low statistical significance (a false alarm rate of ~1/month). We have been tuning the details of the communication procedures, and we have not yet automated all the steps that can be, but we will send alerts to astronomers above the threshold agreed as soon as we can after those triggers are identified. Since analysis to validate and candidate in gravitational-wave data can take months, we will not be able to say anything about results in the data on short time scales. We will share any and all results when ready, though probably not before the end of the Observing Run. 

Analysing the data is tricky, and requires lots of computing time, as well as carefully calibration of the instruments (including how many glitches they produce which could look like a gravitational-wave trigger). It takes a while to get everything done.

We heard that you sent a gravitational-wave trigger to astronomers already—is that true?
During O1, we will send alerts to astronomers above a relatively low significance threshold; we have been practising communication with astronomers in ER8. We are following this policy with partners who have signed agreement with us and have observational capabilities ready to follow up triggers. Because we cannot validate gravitational-wave events until we have enough statistics and diagnostics, we have confidentiality agreements about any triggers that hare shared, and we hope all involved abide by those rules.

I expect this is a pre-emptive question and answer. It would be amazing if we could see an electromagnetic (optical, gamma-ray, radio, etc.) counterpart to a gravitational wave. (I’ve done some work on how well we can localise gravitational-wave sources on the sky). It’s likely that any explosion or afterglow that is visible will fade quickly, so we want astronomers to be able to start looking straight-away. This means candidate events are sent out before they’re fully vetted: they could just be noise, they could be real, or they could be a blind injection. A blind injection is when a fake signal is introduced to the data secretly; this is done to keep us honest and check that our analysis does work as expected (since we know what results we should get for the signal that was injected). There was a famous blind injection during the run of initial LIGO called Big Dog. (We take gravitational-wave detection seriously). We’ve learnt a lot from injections, even if they are disappointing. Alerts will be sent out for events with false alarm rates of about one per month, so we expect a few across O1 just because of random noise.

While I can’t write more about the science from O1, I will still be posting about astrophysics, theory and how we analyse data. Those who are impatient can be reassured that gravitational waves have been detected, just indirectly, from observations of binary pulsars.

Periastron shift of binary pulsar

The orbital decay of the Hulse-Taylor binary pulsar (PSR B1913+16). The points are measured values, while the curve is the theoretical prediction for gravitational waves. I love this plot. Credit: Weisberg & Taylor (2005).

Update: Advanced LIGO detects gravitational waves!

LIGO Magazine: Issue 7

It is an exciting time time in LIGO. The start of the first observing run (O1) is imminent. I think they just need to sort out a button that is big enough and red enough (or maybe gather a little more calibration data… ), and then it’s all systems go. Making the first direct detection of gravitational waves with LIGO would be an enormous accomplishment, but that’s not all we can hope to achieve: what I’m really interested in is what we can learn from these gravitational waves.

The LIGO Magazine gives a glimpse inside the workings of the LIGO Scientific Collaboration, covering everything from the science of the detector to what collaboration members like to get up to in their spare time. The most recent issue was themed around how gravitational-wave science links in with the rest of astronomy. I enjoyed it, as I’ve been recently working on how to help astronomers look for electromagnetic counterparts to gravitational-wave signals. It also features a great interview with Joseph Taylor Jr., one of the discoverers of the famous Hulse–Taylor binary pulsar. The back cover features an article I wrote about parameter estimation: an expanded version is below.

How does parameter estimation work?

Detecting gravitational waves is one of the great challenges in experimental physics. A detection would be hugely exciting, but it is not the end of the story. Having observed a signal, we need to work out where it came from. This is a job for parameter estimation!

How we analyse the data depends upon the type of signal and what information we want to extract. I’ll use the example of a compact binary coalescence, that is the inspiral (and merger) of two compact objects—neutron stars or black holes (not marshmallows). Parameters that we are interested in measuring are things like the mass and spin of the binary’s components, its orientation, and its position.

For a particular set of parameters, we can calculate what the waveform should look like. This is actually rather tricky; including all the relevant physics, like precession of the binary, can make for some complicated and expensive-to-calculate waveforms. The first part of the video below shows a simulation of the coalescence of a black-hole binary, you can see the gravitational waveform (with characteristic chirp) at the bottom.

We can compare our calculated waveform with what we measured to work out how well they fit together. If we take away the wave from what we measured with the interferometer, we should be left with just noise. We understand how our detectors work, so we can model how the noise should behave; this allows us to work out how likely it would be to get the precise noise we need to make everything match up.

To work out the probability that the system has a given parameter, we take the likelihood for our left-over noise and fold in what we already knew about the values of the parameters—for example, that any location on the sky is equally possible, that neutron-star masses are around 1.4 solar masses, or that the total mass must be larger than that of a marshmallow. For those who like details, this is done using Bayes’ theorem.

We now want to map out this probability distribution, to find the peaks of the distribution corresponding to the most probable parameter values and also chart how broad these peaks are (to indicate our uncertainty). Since we can have many parameters, the space is too big to cover with a grid: we can’t just systematically chart parameter space. Instead, we randomly sample the space and construct a map of its valleys, ridges and peaks. Doing this efficiently requires cunning tricks for picking how to jump between spots: exploring the landscape can take some time, we may need to calculate millions of different waveforms!

Having computed the probability distribution for our parameters, we can now tell an astronomer how much of the sky they need to observe to have a 90% chance of looking at the source, give the best estimate for the mass (plus uncertainty), or even figure something out about what neutron stars are made of (probably not marshmallow). This is the beginning of gravitational-wave astronomy!

Monty and Carla map parameter space

Monty, Carla and the other samplers explore the probability landscape. Nutsinee Kijbunchoo drew the version for the LIGO Magazine.

Threshold concepts, learning and Pokémon

Last academic year I took a course on teaching and learning in higher education. I enjoyed learning some education theory: I could recognise habits (both good and bad) my students and I practised. I wanted to write up some of the more interesting ideas I came across, I’ve been kept busy by other things (such as writing up the assessment for the course), but here’s the first.

Pokémon PhD

My collection of qualifications.

Threshold concepts

Have you ever had that moment when something just clicked? Perhaps you’ve been struggling with a particular topic for a while, then suddenly you understand, you have that eureka moment, and you get a new view on everything. That’s one of the best moments in studying.

Threshold concepts are a particular class of these troublesome concepts that have a big impact on your development. It’s not just that these take work to come to grips with, but that you can’t master a subject until you’ve figured them out. As a teacher, they’re something to watch out for, as these are the areas where students’ progress can be held up and they need extra support.

Being a student is much like being a Pokémon. When you start out, there’s not much you can do. Then you practise and gain experience. This can be difficult, but you level up. (Sadly, as a student you don’t the nice little jingle when you do). After levelling up, things don’t seem so hard, so you can tackle more difficult battles. Every so often you’ll learn a new technique, a new move (hopefully you won’t forget an old one), and now you are even more awesome.

That’s all pretty straightforward. If you keep training, you get stronger. (It does turn out that studying helps you learn).

Mastering a threshold concept is more like evolving. You get a sudden boost to your abilities, and now you can learn moves that you couldn’t before, perhaps you’ve changed type too. Evolving isn’t straightforward. Sometimes all you need to do is keep working and level up; other times you’ll need a particular item, to learn a special move, to hone one particular aspect, or be in the right place at the right time. Some people might assimilate a threshold concept like any other new idea, while others will have to put in extra time and effort. In any case, the end effect is transformative. Congratulations, your Physics Student has evolved into a Physicist!

Do di do dum-di-dum-di-dum!

Educational evolution. Pokémon art by Ken Sugimori.

Characteristics

Every discipline has its own threshold concepts. For example, in Pokémon training there’s the idea that different types of Pokémon are have advantages over others (water is super effective against fire, which is super effective against grass, etc.), so you should pick your Pokémon (and their moves) appropriately. Threshold concepts share certain attributes, they are:

  • Transformative: Once understood they change how you view the subject (or life in general). Understanding Pokémon types changes how you view battles, if you’re going to go up against a gym leader called Lt. Surge, you know to pack some Ground types as they’re good against Electric types. It also now makes sense how Iron Man (obviously a Steel type), can take on Thor (an Electric type) in The Avengers, but gets trashed by some random henchpeople with heat powers (Fire types) in Iron Man 3.
  • Irreversible: Once learnt there’s no changing back. You know you’re going to have a bad time if you’ve only packed Fire types to go explore an underwater cave.
  • Integrative: Having conquered a threshold concept, you can spot connections to other ideas and progress to develop new skills. Once you’ve realised that your beloved Blastoise has a weakness to Electric types, you might consider teaching it Earthquake as a counter. You’ve moved on from just considering the types of Pokémon, to considering their move-sets too. Or you could make sure your team has Ground type, so you can switch out your Blastoise. Now you’re considering the entire composition of your team.
  • Troublesome: Threshold concepts are difficult. They may be conceptually challenging (how do you remember 18 types vs 18 types?), counter-intuitive (why don’t Ghost moves affect Normal types?), or be resisted as they force you to re-evaluate your (deep held) opinions (maybe Gyarados isn’t the best, despite looking ferocious, because it has a double weakness to Electric types, and perhaps using your favourite Snorlax in all situations is a bad idea, regardless of how huggable he is).

Using these criteria, you might be able to think of some threshold concepts in other areas, and possibly see why people have problems with them. For example, it might now make more sense why some people have problems accepting global warming is caused by humans. This is certainly a transformative idea, as it makes you reconsider your actions and those of society, as well as the prospects for future generations, and it is certainly troublesome, as one has to accept that the world can change, that our current lifestyle (and perhaps certain economic activities) is not sustainable, and that we are guilty of damaging our only home. The irreversible nature of threshold concepts might also make people resist coming to terms with them, as they prefer their current state of comfortable innocence.

Loss of Arctic ice over 15 years

National Geographic atlases from 1999 to 2014, showing how Arctic ice has melted. At this rate, ice type Pokémon will be extinct in the wild by the end of the century (they’re already the rarest type). It’s super depressing…

Summary

Threshold concepts are key but troublesome concepts within a discipline. If you want to be the very best, you have to master them all. They are so called as they can be thought of as doorways, through which a student must step in order to progress. After moving passed the threshold, they enter a new (larger) room, the next stage in their development. From here, they can continue to the next threshold. Looking back, they also get a new perspective on what they have learnt; they can now see new ways of connecting together old ideas. Students might be hesitant to step through because they are nervous about leaving their current state behind. They might also have problems just because the door is difficult to open. If you are planning teaching, you should consider what threshold concepts you’ll cover, and then how to build your lessons around threshold concepts so no-one gets left behind.

I especially like the idea of threshold concepts, as it shows learning to be made up of a journey through different stages of understanding, rather than building a pile of knowledge. (Education should be more about understanding how to figure out the right answer than knowing what it is). If you’d like to learn more about threshold concepts, I’d recommend browsing the resources compiled by Michael Flanagan of UCL.

Perks and perils of a PhD

Nijō Castle garden.

Pond in the gardens of Nijō Castle, Kyoto. A good spot for pondering. The castle has whistling floorboards, to warn you if an assassin is sneaking up on you. Modern buildings don’t do enough to warn you of assassins.

This blog has been neglected recently as I have been busy travelling, with conferences and meetings (with a little holiday in between) in Japan, Korea and Germany. I am now back in Birmingham where we have a veritable army of summer students. They are all enthusiastic, and seem to be doing well at both their projects and joining in lunchtime conversations. One asked whether it was a good idea to do a PhD? Travelling to interesting places in one of the perks of being an academic, but does it compensate all the hard work? Here are my thoughts on doing a PhD now mine is safely done but still fresh in my memory.

The third degree

A PhD is not a simple continuation of your studies. One of the things that surprised me was how different research is from study (although they may share many of the same skills). At school and undergraduate you learn: you pay attention in class, you do assignments and projects, you revise and you take assessments. If you work hard at these, you pick up new knowledge and skills, and end up doing well. (Wooh!) In research, you have to solve problems, to figure out how to do things that have never been done before (which may require picking up new knowledge and skills). This can be extremely exciting: you could be the only person in the world to know how to do something, but since you are trying something new, it could also turn out not to work… You can work hard in a particular area for days, weeks or even years, and it all come to nothing.

Research projects at an undergraduate level are different from those at postgraduate. The former are usually designed to be safely solvable, and even if things don’t work out, you come to the end of your time and be given marks for effort. It’s much harder to put together a PhD dissertation without results, and a lack of progress (perhaps especially if through no fault of your own) can be especially demotivating.

When asked about doing a PhD, the current PhDs showed varying levels of enthusiasm. This is usually correlated with how things are going and how close they are to finishing. Maggie, who is always keen on encouraging people to learn about science, has put together a list of 5 reasons why you should do a PhD. I think these neatly sum up some of main motivations for doing a PhD.

1. Freedom and flexibility

Academia enjoys a lot of freedom. And I don’t just mean that you don’t have to wear a tie

You don’t have to work standard office hours, but can often schedule things around you. This can be especially handy if you have family commitments, you don’t function well in the morning, or just fancy an afternoon off. It can also have the downside of blurring the work/life divide. Working from home gives you the flexibility to work in your pyjamas, but it can also makes it easy to work evenings and weekends—perhaps the weekends are the best time to come in to the lab because there are fewer people trying to use the most shiny equipment. It can be difficult to maintain a healthy work/life balance, and it can also lead to ridiculous expectations that you can work all the time (or should feel guilty if you’re not). Of course, sometimes you have to visit the lab every two hours to look after your experiment, and there’s no flexibility at all.

As well of freedom in when you schedule work, there is also freedom in what you do. It’s difficult to predict where a PhD will go, but you can focus in on what you are interested in and what you enjoy. Your supervisor, future examiners and potential employers may disagree with you about what’s worthwhile researching, so you do have some constraints; however, as long as solve an interesting problem, it doesn’t matter as much as in industry if it’s a different one to the one you started with. Some of the best PhD projects I have seen (or been involved with) come about because the student came across a new technique they wanted to play with, read up on a different area out or just wanted to help answer someone else’s question. Procrastination can have some useful side-effects.

2. The title

Being a doctor is pretty cool. Not as cool as being the Doctor, but still, it can command some respect. However, that doesn’t mean you receive (or deserve) any special treatment. Contrary to popular opinion, your title doesn’t go on your passport. It does indicate that you are an expert in one particular area; however, this might be an obscure and unhelpful one.  If you are ever on a flight and the attendant asks “Is there a doctor of astrophysics on board?” you are probably sufficiently doomed that you might as well just stay seated and try to finish up your peanuts in whatever time remains.

In the end, it is having completed the difficult research and produced a quality thesis that is worth the respect, and not the extra letters with your name. If you are not interested in the the former, the latter will not give you the motivation to put in the time and effort to complete it.

3. To prove you’re smart

Leading on from the last point, a doctorate is a seal of academic quality. However, I really wouldn’t suggest doing a PhD because you need to validate your intelligence. You are intelligent whether or not you decide to go to graduate school, and one should never assume that someone is less smart because they lack a PhD—first, because you do not know what opportunities they may or may not have had in life, and second, intelligence is about more than academic achievements. If you’re a lazy writer, giving a character a PhD is an easy way to establish they are clever without having to think of way for them to show it. In real life, people will soon figure out how smart you are by interacting with you (if they are only interested in titles, find someone else).

Getting a PhD isn’t just a case of being smart, it’s not a prize on a game show. As much as intelligence, a doctorate requires determination. Undergraduate is like a sprint, you can work really hard for a short stretch (around exams) and then collapse. The quickest people will come out on top, but you could still take it at a jog and make it to the end provided you don’t mind being second. A doctorate is more like a marathon, its not enough to be fast, you need to be able to keep going, to pace yourself and to pick yourself up if you trip. Both can be exhausting and painful, but it’s much more important to figure out if you can really go the distance before starting on the 26 miles.

Perhaps you are unsure if you’re up-to-scratch and want to try a PhD to see? Finding out that you can do it may be a huge confidence boost! However, academia can also batter your ego as you’ll be surrounded by other equally intelligent people. I guess you just need to be happy with who you are.

Finally, parents may like to show off the achievements of their children, and you may make your friends proud, but it’s not them who have to spend the time in the library. Making people you love proud is wonderful, but so is spending time with them. A PhD can consume huge amounts of time, energy and attention (especially while writing up). It should be something that you want to do, not something other people want you to do.

4. Broadening your horizons

Academia does give you the chance to visit new places and work with people all over the world. I really enjoyed my summer travels and Maggie is currently observing at a telescope in Chile. Of course you don’t always have that luxury: sometimes conferences aren’t in interesting places or funding could be running short. My first two conferences were in Glasgow and Cardiff. Both are lovely cities to visit, but neither was a once-in-a-lifetime opportunity. If you are really keen on travel, then there are other careers that give you better excuses to travel. Or you could take a better paid job and just pay for yourself to go on holiday. Travel, like free coffee, is a perk, but it’s not enough to justify doing a PhD.

The KAGRA detector

I visited the in-construction Kamioka Gravitational Wave Detector (KAGRA) in Japan. It is being built underground, in an old mine in the Hida Mountains. You can see part of the vacuum tubing for one of the laser-interferometer arms in the foreground, and where they’re going to suspend a mirror from the room above in the background. It’s amazing engineering and the views outside are impressive too! They’re on a tight schedule, aiming for a first run (albeit at terrible sensitivity) this year.

More importantly, a PhD gives you the opportunity to come across new ideas and ways of looking at a problem; to work with interesting, intelligent people from a range of backgrounds, and time to examine the world (or Universe) in detail in many different ways. That might all be from your cluttered desk, but it can be really exciting.

5. For knowledge

Over the course of a doctorate you will learn many things: the best seminars for free food, how to manage you supervisor and lots of transferable skills. However, the big thing is your thesis. Through your research, you will contribute something to the sum of human knowledge. It may be revolutionary, it’s more likely to be something that will go towards a bigger question (with help from lots of others), but it could also be the discovery that this particular thing doesn’t work. You research will push back the boundary of the unknown. You will become a world expert in your area: no-one will know your research as well as you do. If there is a topic that really interests you, if there is something that you want to know more about, then a PhD gives you the chance to explore this.

In my opinion, this is the only reason to do a PhD. There are other benefits and perks, but this should be your motivation. A PhD is not just a training course, but is another step towards understanding everything. I think that is amazing.

The forbidden motivation

Having been through the list, you may think there is something missing. What about doing a PhD to get a job? There are few careers that require a PhD, and it may not serve any more advantage than a Masters. Doing a PhD probably won’t make you rich. It may make you more attractive to some employers, but maybe spending the same amount of time working your way up from a lower rung would be just as effective? Extremely few employers have any kind of hiring scheme for PhDs, so in many cases you would start at a similar level as someone with an undergraduate degree. Some areas, of course, have strong industrial links, so it’s easy to move across. In this case, doing a PhD can be a great option: you can even get to work with potential future employers during your study (and possibly get some extra funding). The usefulness of a PhD strongly depends on the area.

There is one domain where a PhD is the well-established first step. Academia. Many think of academia as the logical progression, but it is not. You are not guaranteed an academic job with a PhD. In the sciences, most PhDs will not continue in academia. According to a report from the Royal Society, only 3.5% of science PhDs in the UK end up with a permanent academic position, and only 0.45% become professors. Competition is extremely tough: the number of PhDs awarded is increasing rapidly, but the number of faculty positions is remaining constant. I do not think the situation is better in the arts. A PhD student should not expect to get a job in academia.

The answer

A PhD is a big commitment, and requires careful contemplation. There are many reasons why you might be considering doing one; however, I think that if you’re going to enjoy the experience, the motivation you need is the desire to spend several years getting to know one particular area really well. You must be happy to invest years of your life without any guarantee of returns. You’ll pick up many useful skills, but that will not make you irresistibly desirable to employers—some will regard you as overqualified, and the prospects of an academic career are slim. You will receive opportunities you wouldn’t otherwise, in particular, to meet some awesome people. A PhD is a challenge, research can be both deeply rewarding and excruciatingly frustrating (sometimes in the same afternoon). On balance, if it is the right thing for you is deeply personal. As is common in research, to answer this question, we need further data.

Should you decide to go for it, the next thing to think about is the area and the location. You should make sure you get adequate funding, and take care in picking a supervisor—always talk to their current students. Perhaps we’ll come back to these points later. Good luck!

Lanterns at the Jogyesa temple, Seoul.

Panorama of lanterns at the Jogyesa temple, Seoul. Beautiful, and you can keep following it around in circles, just like a PhD…

A level subject choices

Ofsted have recently published statistics relating to the subject choices of students starting A levels in England in 2013/2014. (For those unfamiliar with A levels, they are the qualifications taken between the ages of 16 and 18, students usually pick 3–4 subjects for the first year, which is known as AS, and normally slim down to 3 for the second year, A2; university admissions are based upon A level results). This is part of an effort to understand what drives students to pick different subjects and particularly science. Engaging students in science is a challenge, although many enjoy it or can achieve well in tests, then can struggle to see that it is for them. In Physics, we have a particular problem recruiting girls, which means we are not getting the best mix of people. I was interesting in having a look at the subject choices, so I’ve put together a few graphs.

Subject popularity

The most popular subjects at AS level are:

  1. English,
  2. Mathematics,
  3. Psychology.

English and Maths make sense, as they’ll be familiar from previous study and are of general applicability. I was surprised that Psychology came third, since it’ll be a new subject; the top ten consists of subjects familiar from pre-16 education, with the exception of the two social sciences, Psychology and Sociology (8). Physics comes in at number 7, behind both Biology (4) and Chemistry (6). This makes me sad, but at least Physics is still one of the most popular choices.

The distribution of student numbers is show in the graph below. I’ve not quite figured out what the distribution of student numbers should be, but it’s roughly exponential. There are too many subjects to label individually, so I’ve grouped them roughly by subject area. The main sciences (Biology, Chemistry and Physics) all do rather well, but modern languages are languishing towards the bottom of the list (top is French at 21). The smallest subjects have been grouped together into Other categories, these make up the bottom of the distribution, but in amongst them are Classical studies (29), German (30), and Accounting & finance (31).

Subjects ranking

Student numbers in the most popular subjects at AS level (in England 2013/2014). Data from A level subject take-up.

Gender differences

The report also lists the numbers of boys and girls taking each subject. I know that Physics is male-dominated, but I didn’t know how this compared to other subjects. To quantify the imbalance, I’m going to define the asymmetry as

\displaystyle \mathrm{Asymmetry} = \frac{\mathrm{No.\ of\ girls}\ -\ \mathrm{No.\ of\ boys}}{\mathrm{No.\ of\ students}}.

This is 0 if there are equal numbers of boys and girls, and is ±1 if completely made up of boys (−1) or girls (+1). Overall, more girls than boys are taking A levels, giving an total asymmetry of 0.0977. That’s not great, but we’ll see it’s smaller than is typically the case for individual subjects.

The most male-dominated subjects are:

  1. Computing (−0.8275),
  2. Physics (−0.5446),
  3. Further mathematics (−0.4569).

The most female-dominated subjects are:

  1. Sociology (0.5084),
  2. Art & design (0.4896),
  3. French (0.4531).

We see that Physics is in pretty poor shape, being the second most asymmetric subject overall. However, Computing is really out in a league of it’s own: there are almost 11 boys for every girl in the subject! That is not healthy. The most balanced subjects are:

  1. Geography (0.0056),
  2. Chemistry (−0.0167),
  3. Government & politics (−0.0761).

These are the only subjects with asymmetries smaller than the overall population of students. The gender balance in Chemistry shows that the Physical sciences don’t need to be male-dominated; however, this could equally reflect the compromise between male-dominated Physics and female-dominated Biology (0.2049).

The graph below plots the number of students taking a subject and its asymmetry. There’s no real trend with student numbers, it’s not the case that it’s easier for smaller subjects to become biased or that it’s easier for larger subjects to develop a reputation.

Asymmetry and number of students

Scatter plot of the number of students and gender asymmetry of AS subjects (in England 2013/2014). Higher points are more female dominated and lower points are more male dominated. The dashed line indicates gender parity and the dotted line indicates the average for all subjects. Data from A level subject take-up.

Normally, I’d expect there to be scatter in a quantity like asymmetry: some values high, some low, but more clustering in the middle than out in the extremes. Looking at the plot above, this doesn’t seem to be the case. There are relatively few subjects in the middle, but there seem to be two clusters, one at small positive asymmetries and another at small negative asymmetries. I’ve plotted the distribution of subject asymmetries below. To make it clearer to view (and to make a nice smooth, continuous distribution), I’ve smeared out the individual subjects. These means I’m actually plotting the density of subjects per unit of asymmetry, rather than the number of subjects: if you work out the area under the curve, that gives the number of subjects in that range. (For those who care, I’ve convolved with a Gaussian kernel with a standard deviation of 0.1, and made sure to renormalise them so that the total area is correct).

Asymmetry distribution.

Smoothed distribution of gender asymmetry for AS subjects (in England 2013/2014). Left is male dominated and right is female dominated. The area under the curve gives the number of subjects. The diamonds mark the locations of individual subjects. Data from A level subject take-up.

It does appear that there are two peaks: one for boys’ subjects and another for girls’. Computing is off being a clear outlier. However, if I turn up the smoothing (using a standard deviation of 0.3), this disappears. This always happens if you smooth too much…

Asymmetry distribution.

Heavily smoothed distribution of gender asymmetry for AS subjects (in England 2013/2014). Left is male dominated and right is female dominated. The area under the curve gives the number of subjects. The diamonds mark the locations of individual subjects. Data from A level subject take-up.

It looks like this is one of the cases where I should really do things properly and I should come back to look at this again later.

Regardless of whether my suspicion of there being two clusters of subjects is correct, there does appear to be a spectrum of subjects, with some being as perceived as for boys and others for girls. This differentiation exists already exists at age 16—even for subjects like Psychology and Sociology that have not been studied previously. It seems that these stereotypes are ingrained from an earlier age.

Computing and Psychology role models

Ada, Countess of Lovelace, mathematician and first computer programmer (and superheroine), and Sigmund Freud, neurologist and founder of psychoanalysis. Evidence that there really shouldn’t be divides in Computing, Psychology or any other subject.

Continuation

As well as looking at how many students take AS, we can look at how many continue to A2. The report gives the percentage that continue for both boys and girls. The distribution of all continuation percentages is shown below, again with subjects grouped by area. The average progression across all subjects is 72.7%.

Continuation ranking

Percentage continuation from AS to A2 for different subjects (in England 2013/2014). The dotted line indicates the average. Data from A level subject take-up.

The top subjects for continuation to A2 are:

  1. Other modern languages (90.4%),
  2. Drama (82.7%),
  3. Media/film/TV studies (81.4%).

Other modern languages is the smallest subject in terms of student numbers, but has the highest continuation: I guess those who opt for it are dedicated to seeing it through. However, there doesn’t seem to be a correlation between student numbers and continuation. English, the most popular subject, comes in just below Media/film/TV studies with 81.2%. The bottom subjects for continuation are:

  1. Other social sciences (45.9%),
  2. Accounting & finance (59.7%),
  3. Computing (61.4%).

I don’t know enough about these subjects to know if there might be a particular reason why just taking them for one year might be useful. In contrast to Other modern languages, German (62.7%), French (64.1%) and Spanish (65.8%) have some of the lowest continuation rates (coming in just above Computing). Physics also does poorly, with only 67.8% continuing, below both Chemistry (71.0%) and Biology (72.2%). For comparison, Further mathematics has 68.3% continuation and Mathematics has 75.4%. I would expect continuation to be lower for subjects that students find more difficult (possibly with the biggest jump from GCSE).

Now, let’s have a look at the difference in progression between the genders. In the figure below, I plot the difference in the percentage progression between boys and girls,

\mathrm{Difference} = \mathrm{Percent\ girls\ continuing}\ -\ \mathrm{Percent\ boys\ continuing},

versus the asymmetry. The two quantities show a clear correlation: more girls than boys progress in subjects that are female dominated and vice versa. Gender asymmetry gets worse with progression.

Asymmetry and progression

Scatter plot of the gender asymmetry and difference in percentage progression of AS subjects (in England 2013/2014). Left is male dominated and right is female dominated. Higher points have a higher proportion of girls than boys continuing and lower points have a higher proportion of boys than girls continuing. Data from A level subject take-up.

The subjects with the largest differences in continuation are:

  1. Physics (−14%),
  2. Other science (−12%),
  3. Psychology (11%).

That’s a really poor show for Physics. This polarising trend is not surprising. People like to be where they feel they belong. If you’re conspicuously outnumbered, you’re more likely to feel uncomfortable. Data show that girls are more likely to continue with Physics in all-girls schools. Also, as we’ve seen, there seems to be a clustering of boys’ subjects and girls’ subjects, and developing these reputations can make it difficult for people to go against stereotypes. This impacts both how people view themselves and others, potentially impacting perceived competence (e.g., for Physics, Gonslaves 2014a, 2014b). These cultural biases are something we need to work against if we’re going the get the best mix of students (I guess it’s good we have all these Psychologists and Sociologists to help figure this out).

I’d recommend trying the excellent (and adorable) Parable of the Polygons to see how biases can become magnified.

Summary

At A level, some subjects are favoured by boys or by girls. This imbalance gets larger during the transition from AS to A2. Physics is one of the most popular subjects at AS level, but lags behind the other main sciences. It has a poor gender ratio, which notably gets worse going from AS to A2. Physics is (arguably) the the most awesome subject, so we should do more to show that is for everyone. If you’d like to play around the data (and don’t fancy typing it out yourself), I have it available via Google Drive.

(For disclosure: I took Geography at AS, and Physics, Maths and Further maths at A2).