Prospects for observing and localizing gravitational-wave transients with Advanced LIGO and Advanced Virgo

The week beginning February 8th was a big one for the LIGO and Virgo Collaborations. You might remember something about a few papers on the merger of a couple of black holes; however, those weren’t the only papers we published that week. In fact, they aren’t even (currently) the most cited

Prospects for Observing and Localizing Gravitational-Wave Transients with Advanced LIGO and Advanced Virgo is known within the Collaboration as the Observing Scenarios Document. It has a couple of interesting aspects

  • Its content is a mix of a schedule for detector commissioning and an explanation of data analysis. It is a rare paper that spans both the instrumental and data-analysis sides of the Collaboration.
  • It is a living review: it is intended to be periodically updated as we get new information.

There is also one further point of interest for me: I was heavily involved in producing this latest version.

In this post I’m going to give an outline of the paper’s content, but delve a little deeper into the story of how this paper made it to print.

The Observing Scenarios

The paper is divided up into four sections.

  1. It opens, as is traditional, with the introduction. This has no mentions of windows, which is a good start.
  2. Section 2 is the instrumental bit. Here we give a possible timeline for the commissioning of the LIGO and Virgo detectors and a plausible schedule for our observing runs.
  3. Next we talk about data analysis for transient (short) gravitational waves. We discuss detection and then sky localization.
  4. Finally, we bring everything together to give an estimate of how well we expect to be able to locate the sources of gravitational-wave signals as time goes on.

Packaged up, the paper is useful if you want to know when LIGO and Virgo might be observing or if you want to know how we locate the source of a signal on the sky. The aim was to provide a guide for those interested in multimessenger astronomy—astronomy where you rely on multiple types of signals like electromagnetic radiation (light, radio, X-rays, etc.), gravitational waves, neutrinos or cosmic rays.

The development of the detectors’ sensitivity is shown below. It takes many years of tweaking and optimising to reach design sensitivity, but we don’t wait until then to do some science. It’s just as important to practise running the instruments and analysing the data as it is to improve the sensitivity. Therefore, we have a series of observing runs at progressively higher sensitivity. Our first observing run (O1), featured just the two LIGO detectors, which were towards the better end of the expected sensitivity.

Possible advanced detector sensitivity

Plausible evolution of the Advanced LIGO and Advanced Virgo detectors with time. The lower the sensitivity curve, the further away we can detect sources. The distances quoted is range we could see binary neutrons stars (BNSs) to. The BNS-optimized curve is a proposal to tweak the detectors for finding BNSs. Fig. 1 of the Observing Scenarios Document.

It’s difficult to predict exactly how the detectors will progress (we’re doing many things for the first time ever), but the plot above shows our current best plan.

I’ll not go into any more details about the science in the paper as I’ve already used up my best ideas writing the LIGO science summary.

If you’re particularly interested in sky localization, you might like to check out the data releases for studies using (simulated) binary neutron star and burst signals. The binary neutron star analysis is similar to that we do for any compact binary coalescence (the merger of a binary containing neutron stars or black holes), and the burst analysis works more generally as it doesn’t require a template for the expected signal.

The path to publication

Now, this is the story of how a Collaboration paper got published. I’d like to take a minute to tell you how I became responsible for updating the Observing Scenarios…

In the beginning

The Observing Scenarios has its origins long before I joined the Collaboration. The first version of the document I can find is from July 2012. Amongst the labyrinth of internal wiki pages we have, the earliest reference I’ve uncovered was from August 2012 (the plan was to have a mature draft by September). The aim was to give a road map for the advanced-detector era, so the wider astronomical community would know what to expect.

I imagine it took a huge effort to bring together all the necessary experts from across the Collaboration to sit down and write the document.

Any document detailing our plans would need to be updated regularly as we get a better understanding of our progress on commissioning the detectors (and perhaps understanding what signals we will see). Fortunately, there is a journal that can cope with just that: Living Reviews in Relativity. Living Reviews is designed so that authors can update their articles so that they never become (too) out-of-date.

A version was submitted to Living Reviews early in 2013, around the same time as a version was posted to the arXiv. We had referee reports (from two referees), and were preparing to resubmit. Unfortunately, Living Reviews suspended operations before we could. However, work continued.

Updating sky localization

I joined the LIGO Scientific Collaboration when I started at the University of Birmingham in October 2013. I soon became involved in a variety of activities of the Parameter Estimation group (my boss, Alberto Vecchio, is the chair of the group).

Sky localization was a particularly active area as we prepared for the first runs of Advanced LIGO. The original version of the Observing Scenarios Document used a simple approximate means of estimating sky localization, using just timing triangulation (it didn’t even give numbers for when we only had two detectors running). We knew we could do better.

We had all the code developed, but we needed numbers for a realistic population of signals. I was one of the people who helped running the analyses to get these. We had the results by the summer of 2014; we now needed someone to write up the results. I have a distinct recollection of there being silence on our weekly teleconference. Then Alberto asked me if I would do it? I said yes: it would probably only take me a week or two to write a short technical note.

Saying yes is a slippery slope.

That note became Parameter estimation for binary neutron-star coalescences with realistic noise during the Advanced LIGO era, a 24-page paper (it considers more than just sky localization).

Numbers in hand, it was time to update the Observing Scenarios. Even if things were currently on hold with Living Reviews, we could still update the arXiv version. I thought it would be easiest if I put them in, with a little explanation, myself. I compiled a draft and circulated in the Parameter Estimation group. Then it was time to present to the Data Analysis Council.

The Data Analysis Council either sounds like a shadowy organisation orchestrating things from behind the scene, or a place where people bicker over trivial technical issues. In reality it is a little of both. This is the body that should coordinate all the various bits of analysis done by the Collaboration, and they have responsibility for the Observing Scenarios Document. I presented my update on the last call before Christmas 2014. They were generally happy, but said that the sky localization on the burst side needed updating too! There was once again a silence on the call when it came to the question of who would finish off the document. The Observing Scenarios became my responsibility.

(I had though that if I helped out with this Collaboration paper, I could take the next 900 off. This hasn’t worked out.)

The review

With some help from the Burst group (in particular Reed Essick, who had lead their sky localization study), I soon had a new version with fully up-to-date sky localization. This was ready for our March Collaboration meeting. I didn’t go (I was saving my travel budget for the summer), so Alberto presented on my behalf. It was now agreed that the document should go through internal review.

It’s this which I really want to write about. Peer review is central to modern science. New results are always discussed by experts in the community, to try to understand the value of the work; however, peer review is formalised in the refereeing of journal articles, when one or more (usually anonymous) experts examine work before it can be published. There are many ups and down with this… For Collaboration papers, we want to be sure that things are right before we share them publicly. We go through internal peer review. In my opinion this is much more thorough than journal review, and this shows how seriously the Collaboration take their science.

Unfortunately, setting up the review was also where we hit a hurdle—it took until July. I’m not entirely sure why there was a delay: I suspect it was partly because everyone was busy assembling things ahead of O1 and partly because there were various discussions amongst the high-level management about what exactly we should be aiming for. Working as part of a large collaboration can mean that you get to be involved in wonderful science, but it can means lots of bureaucracy and politics. However, in the intervening time, Living Reviews was back in operation.

The review team consisted of five senior people, each of whom had easily five times as much experience as I do, with expertise in each of the areas covered in the document. The chair of the review was Alan Weinstein, head of the Caltech LIGO Laboratory Astrophysics Group, who has an excellent eye for detail. Our aim was to produce the update for the start of O1 in September. (Spolier: We didn’t make it)

The review team discussed things amongst themselves and I got the first comments at the end of August. The consensus was that we should not just update the sky localization, but update everything too (including the structure of the document). This precipitated a flurry of conversations with the people who organise the schedules for the detectors, those who liaise with our partner astronomers on electromagnetic follow-up, and everyone who does sky localization. I was initially depressed that we wouldn’t make our start of O1 deadline; however, then something happened that altered my perspective.

On September 14, four days before the official start of O1, we made a detection. GW150914 would change everything.

First, we could no longer claim that binary neutron stars were expected to be our most common source—instead they became the source we expect would most commonly have an electromagnetic counterpart.

Second, we needed to be careful how we described engineering runs. GW150914 occurred in our final engineering run (ER8). Practically, there was difference between the state of the detector then and in O1. The point of the final engineering run was to get everything running smoothly so all we needed to do at the official start of O1 was open the champagne. However, we couldn’t make any claims about being able to make detections during engineering runs without being krass and letting the cat out of the bag. I’m rather pleased with the sentence

Engineering runs in the commissioning phase allow us to understand our detectors and analyses in an observational mode; these are not intended to produce astrophysical results, but that does not preclude the possibility of this happening.

I don’t know if anyone noticed the implication. (Checking my notes, this was in the September 18 draft, which shows how quickly we realised the possible significance of The Event).

Finally, since the start of observations proved to be interesting, and because the detectors were running so smoothly, it was decided to extend O1 from three months to four so that it would finish in January. No commissioning was going to be done over the holidays, so it wouldn’t affect the schedule. I’m not sure how happy the people who run the detectors were about working over this period, but they agreed to the plan. (No-one asked if we would be happy to run parameter estimation over the holidays).

After half-a-dozen drafts, the review team were finally happy with the document. It was now October 20, and time to proceed to the next step of review: circulation to the Collaboration.

Collaboration papers go through a sequence of stages. First they are circulated to the everyone for comments. This can be pointing out typos, suggesting references or asking questions about the analysis. This lasts two weeks. During this time, the results must also be presented on a Collaboration-wide teleconference. After comments are addressed, the paper is sent for examination Executive Committees of the LIGO and Virgo Collaborations. After approval from them (and the review team check any changes), the paper is circulated to the Collaboration again for any last comments and checking of the author list. At the same time it is sent to the Gravitational Wave International Committee, a group of all the collaborations interested in gravitational waves. This final stage is a week. Then you can you can submit the paper.

Peer review for the journal doesn’t seem to arduous in comparison does it?

Since things were rather busy with all the analysis of GW150914, the Observing Scenario took a little longer than usual to clear all these hoops. I presented to the Collaboration on Friday 13 November. (This was rather unlucky as I was at a workshop in Italy and I had to miss the tour of the underground Laboratori Nazionali del Gran Sasso). After addressing comments from everyone (the Executive Committees do read things carefully), I got the final sign-off to submit December 21. At least we made it before the end of O1.

Good things come…

This may sound like a tale of frustration and delay. However, I hope that it is more than that, and it shows how careful the Collaboration is. The Observing Scenarios is really a review: it doesn’t contain new science. The updated sky localization results are from studies which have appeared in peer-reviewed journals, and are based upon codes that have been separately reviewed. Despite this, every statement was examined and every number checked and rechecked, and every member of the Collaboration had opportunity to examine the results and comment on the document.

I guess this attention to detail isn’t surprising given that our work is based on measuring a change in length of one part in 1,000,000,000,000,000,000,000.

Since this is how we treat review articles, can you imagine how much scrutiny the Discovery Paper had? Everything had at least one extra layer of review, every number had to be signed-off individually by the appropriate review team, and there were so many comments on the paper that the editors had to switch to using a ticketing system we normally use for tracking bugs in our software. This level of oversight helped me to sleep a little more easily: there are six numbers in the abstract alone I could have potentially messed up.

Of course, all this doesn’t mean we can’t make mistakes…

Looking forward

The Living Reviews version was accepted January 22, just after the end of O1. We made had to make a couple of tweaks to correct tenses. The final version appeared February 8, in time to be the last paper of the pre-discovery era.

It is now time to be thinking about the next update! There are certainly a few things on the to-do list (perhaps even some news on LIGO-India). We are having a Collaboration meeting in a couple of weeks’ time, so hopefully I can start talking to people about it then. Perhaps it’ll be done by the start of O2?

arXiv: 1304.0670 [gr-qc]
Journal: Living Reviews In Relativity; 19:1(39); 2016
Science summary: Planning for a Bright Tomorrow: Prospects for Gravitational-wave Astronomy with Advanced LIGO and Advanced Virgo
Bonus fact:
 This is the only paper whose arXiv ID I know by heart [update].

arXiv IDs

Papers whose arXiv numbers I know by heart are: 1304.0670, 1602.03840 (I count to other GW150914 companion papers from here), 1606.04856 and 1706.01812. These might tell you something about my reading habits.

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).

BritGrav 15

April was a busy month. Amongst other adventures, I organised the 15th British Gravity (BritGrav) Meeting. This is a conference for everyone involved with research connected to gravitation. I was involved in organising last year’s meeting in Cambridge, and since there were very few fatalities, it was decided that I could be trusted to organise it again. Overall, I think it actually went rather well.

Before I go on to review the details of the meeting, I must thank everyone who helped put things together. Huge thanks to my organisational team who helped with every aspect of the organisation. They did wonderfully, even if Hannah seems to have developed a slight sign-making addiction. Thanks go to Classical & Quantum Gravity and the IOP Gravitational Physics Group for sponsoring the event, and to the College of  Engineering & Physical Sciences’ marketing team for advertising. Finally, thanks to everyone who came along!

Talks

BritGrav is a broad meeting. It turns out there’s rather a lot of research connected to gravity! This has both good and bad aspects. On the plus side, you can make connections with people you wouldn’t normally run across and find out about new areas you wouldn’t hear about at a specialist meeting. On the negative side, there can some talks which go straight-over your head (no matter how fast your reaction are). The 10-minute talk format helps a little here. There’s not enough time to delve into details (which only specialists would appreciate) so speakers should stick to giving an overview that is generally accessible. Even in the event that you do get completely lost, it’s only a few minutes until the next talk, so it’s not too painful. The 10-minute time slot also helps us to fit in a large number of talks, to cover all the relevant areas of research.

Open quantum gravitational systems

Slide from Teodora Oniga’s BritGrav 15 talk on gauge invariant quantum gravitational decoherence. There are not enough cats featured in slides on gravitational physics.

I’ve collected together tweets and links from the science talks: it was a busy two days! We started with Chris Collins talking about testing the inverse-square law here at Birmingham. There were a couple more experimental talks leading into a session on gravitational waves, which I enjoyed particularly. I spoke on a soon-to-be published paper, and Birmingham PhDs Hannah Middleton and Simon Stevenson gave interesting talks on what we could learn about black holes from gravitational waves.

Detecting neutron star–black hole binaries

Slides demonstrating the difficulty of detecting gravitational-wave signals from Alex Nielsen’s talk on searching for neutron star–black hole binaries with gravitational waves. Fortunately we don’t do it by eye (although if you flick between the slides you can notice the difference).

In the afternoon, there were some talks on cosmology (including a nice talk from Maggie Lieu on hierarchical modelling) and on the structure of neutron stars. I was especially pleased to see a talk by Alice Harpole, as she had been one of my students at Cambridge (she was always rather good). The day concluded with some numerical relativity and the latest work generating gravitational-waveform templates (more on that later).

The second day was more theoretical, and somewhat more difficult for me. We had talks on modified gravity and on quantum theories. We had talks on the properties of various spacetimes. Brien Nolan told us that everyone should have a favourite spacetime before going into the details of his: McVittie. That’s not the spacetime around a biscuit, sadly, but could describe a black hole in an expanding Universe, which is almost as cool.

The final talks of the day were from the winners of the Gravitational Physics Group’s Thesis Prize. Anna Heffernan (2014 winner) spoke on the self-force problem. This is important for extreme-mass-ratio systems, such as those we’ll hopefully detect with eLISA. Patricia Schmidt (2105 winner) spoke on including precession in binary black hole waveforms. In general, the spins of black holes won’t be aligned with their orbital angular momentum, causing them to precess. The precession modulates the gravitational waveform, so you need to include this when analysing signals (especially if you want to measure the black holes’ spins). Both talks were excellent and showed how much work had gone into the respective theses.

The meeting closed with the awarding of the best student-talk prize, kindly sponsored by Classical & Quantum Gravity. Runners up were Viraj Sanghai and Umberto Lupo. The winner was Christopher Moore from Cambridge. Chris gave a great talk on how to include uncertainty about your gravitational waveform (which is important if you don’t have all the physics, like precession, accurately included) into your parameter estimation: if your waveform is wrong, you’ll get the wrong answer. We’re currently working on building waveform uncertainty into our parameter-estimation code. Chris showed how you can think about this theoretical uncertainty as another source of noise (in a certain limit).

There was one final talk of the day: Jim Hough gave a public lecture on gravitational-wave detection. I especially enjoyed Jim’s explanation that we need to study gravitational waves to be prepared for the 24th century, and hearing how Joe Weber almost got into a fist fight arguing about his detectors (hopefully we’ll avoid that with LIGO). I hope this talk enthused our audience for the first observations of Advanced LIGO later this year: there were many good questions from the audience and there was considerable interest in our table-top Michelson interferometer afterwards. We had 114 people in the audience (one of the better turn outs for recent outreach activities), which I was delighted with.

Attendance

We had a fair amount of interest in the meeting. We totalled 81 (registered) participants at the meeting: a few more registered but didn’t make it in the end for various reasons and I suspect a couple of Birmingham people sneaked in without registering.

Looking at the attendance in more detail, we can break down the participants by their career-level. One of the aims of BritGrav is to showcase to research of early-career researchers (PhD students and post-docs), so we ask for this information on the registration form. The proportions are shown in the pie-chart below.

Attendance at BritGrav 15 by career level

Proportion of participants at BritGrav 15 by (self-reported) career level.

PhD students make up the largest chunk; there are a few keen individuals who are yet to start a PhD, and a roughly even split between post-docs and permanent staff. We do need to encourage more senior researchers to come along, even if they are not giving talks, so that they can see the research done by others.

We had a total of 50 talks across the two days (including the two thesis-prize talks); the distribution of talks by career level as shown below.

Talks at BritGrav 15 by career level

Proportion of talks at BritGrav 15 by (self-reported) career level. The majority are by PhD students.

PhDs make up an even larger proportion of talks here, and we see that there are many more talks from post-docs than permanent staff members. This is exactly what we’re aiming for! For comparison, at the first BritGrav Meeting only 26% of talks were by PhD students, and 17% of talks were by post-docs. There’s been a radical change in the distribution of talks, shifting from senior to junior, although the contribution by post-docs ends up about the same.

We can also consider at the proportion of participants from different institutions, which is shown below.

Attendance at BritGrav 15 by institution

Proportion of participants at BritGrav 15 by institution. Birmingham, as host, comes out top.

Here, any UK/Ireland institution which has one or no speakers is lumped together under “Other”, all these institutions had fewer than four participants. It’s good to see that we are attracting some international participants: of those from non-UK/Ireland institutions, two are from the USA and the rest are from Europe (France, Germany, The Netherlands and Slovenia). Birmingham makes up the largest chunk, which probably reflects the convenience. The list of top institutions closely resembles the list of institutions that have hosted a BritGrav. This could show that these are THE places for gravitational research in the UK, or possibly that the best advertising for future BritGravs is having been at an institution in the past (so everyone knows how awesome they are). The distribution of talks by institution roughly traces the number of participants, as shown below.

Talks at BritGrav 15 by institution

Proportion of talks at BritGrav 15 by institution.

Again Birmingham comes top, followed by Queen Mary and Southampton. Both of the thesis-prize talks were from people currently outside the UK/Ireland, even though they studied for their PhDs locally. I think we had a good mix of participants, which is one of factors that contributed to the meeting being successful.

I’m pleased with how well everything went at BritGrav 15, and now I’m looking forward to BritGrav 16, which I will not be organising.

White lab coats, pink tutus and camouflage fatigues

In this post I contemplate the effects of stereotypes and biases. I hope that this will encourage you to examine these ideas too. I promise I’ll get back to more science soon.

Just over a week ago, I helped with an outreach event for year nine students. Some of the astrophysics PhD students and I ran an interactive lecture on gravity and its importance in astrophysics. These type of events are fun: you get to teach some physics to a (usually) enthusiastic audience, and hopefully inspire them to consider studying the subject. I also get to play with our Lycra Universe. I think it’s especially important to show students what a university environment is like and have them interact with real scientists. It is important to counter the stereotype that studying science means that you’ll spend all day in a lab wearing a white lab coat. (Although that would be cool. I’d want goggles too, and maybe a doomsday device).

This event was to promote the studying of STEM subjects. That’s science, technology, engineering and mathematics, because there’s nothing like an acronym to make things accessible. It is often argued that we need more people trained in STEM subjects for the economy, industry, or just so we can finally get pizza over the Internet. I like to encourage people to study these areas as I think it’s good to have a scientifically-literate population. Also, because science is awesome! The event was aimed specifically at encouraging a group who are under-represented at university-level STEM, namely girls.

There has been much written on gender and subject choice. I would recommend the Closing Doors report by the Institute of Physics. I will not attempt to unravel this subject. In all my experience, I have never noticed any difference in aptitude between genders. I don’t believe that the ability to pee standing up gives any advantage when studying physics—one could argue for a better understanding of parabolic motion, but anyone who has paid attention to the floor in the gents (I advise against this), knows this is demonstrably not the case. I assume the dominant factors are social pressures: a vicious circle of a subject becoming more associated with one gender, which makes people feel self-conscious or out of place studying it. Also: there are always bigots. It’s a real shame to be potentially missing out on capable scientists. There have been many attempts to try to counter this trend, to break the cycle—some of them truly awful.

Good arguments have been made that the gender segregation of toys pushes girls away from science and technology from an early age. (For some reason, there seems to be a ridiculous idea that women can only relate to things that are pink). It makes sense to me that if only boys get the chemistry sets and construction toys, then they are going to be more numerous in the STEM subjects. The fact that a few female LEGO scientists merits coverage in nation newspapers, the BBC, etc. shows something isn’t quite right.

We are all influenced by our childhoods, and this got me thinking: I know of negative impacts for women from these gender biases, what are they for men? If women are under-represented in engineering, maths and physics, then men must be under-represented somewhere else to balance things: namely English, biology (conspicuous amongst the STEM subjects) and languages. We are short of male teachers and nurses. It seems that men are pushed away from caring careers or those with emphasis on communication.

The lack of men in certain professions is a problem, although I would say less so than the continued under-representation of women at senior positions (say as professors, CEOs or members of government). I was about to relax, since I hadn’t uncovered yet another unconscious bias to add to the list. Then I checked the news. I don’t know what’s in the news when you’re reading this, but at the time it was conflict in Ukraine, Iraq and Israel–Palestine—I assume things are much better in the future? One thing that struck me was that the combatants in the photos were almost exclusively men. It then occurred to me that for every girl who plays with a ballerina doll, there is a boy who plays with an action figure with a weapon. I’m not as naive as to suggest it’s a simple as growing up to be exactly like your toys (I, regrettably, am neither a dinosaur nor a cuddly elephant), but perhaps it is worth keeping in the front of our mind what identities we associate with each gender and how we project these onto children. I don’t want to say that being a ballerina isn’t a good vocation or hobby, or that being a soldier is a bad career. (Curiously, I believe that some of the requirements to be a good ballet dancer or soldier overlap, say discipline, determination, physical fitness and, perhaps, empathy). However, I think it is dangerous if we raise girls who primarily aspire to be pretty, and boys who resolve conflict through violence (men are both more likely to be victims of homicide and suicide).

In conclusion, stereotypes can be damaging, be it that scientists are all socially-awkward comic-book geeks as in The Big Bang Theory, that men can’t talk about their feelings, or that women must be mothers. There is a balance between the genders: by assigning one quality to a particular gender, you can push the other away. Mathematical ability shouldn’t be masculine and compassion shouldn’t be feminine. This is not a new idea, but conveniently coincides with Emma Watson’s wonderful speech for the UN as part of the HeForShe campaign. Cultural biases might be more significant than you think, so give them some extra attention. Sexism hurts everyone, so let’s cut it out and all go play with some LEGO.

The Big Bang Theory

The Big Bang Theory‘s popularity has been credited with encouraging more students to take physics. The cast reflects traditional stereotypes: the men are physicists, an astronomer and an engineer, the women are two biologists and Penny.

How sport is like science

Athene Donald, Professor of Experimental Physics and soon-to-be Master of my old college, Churchill, recently blogged about how athletics resembles academia. She argued that both are hard careers: they require many years of training, and even then success is not guaranteed—not everyone will reach the top to become an Olympian or a Professor—there is a big element of luck too—a career can stall because of an injury or because of time invested in a study that eventually yields null results, and, conversely, a single big championship win or serendipitous discovery can land a comfortable position. These factors can make these career paths unappealing, but still most people who enter them do so because they love the area, and have a real talent for the field.

The Breakfast Club

As The Breakfast Club taught us, being into physics or sports can have similar pressures.

I find this analogy extremely appealing. There are many parallels. Both sports and academic careers are meritocratic and competitive. Most who enter them will not become rich—those who do, usually manage it by making use of their profile, either through product endorsement or through writing a book, say Stephen Hawking, or Michael Jordan (although he was still extremely well paid). Both fields have undisputed heavy-weights like Einstein or Muhammad Ali, and media superstars like Neil deGrasse Tyson or Anna Kournikova; both have inspirational figures who have overcome adversity, be they Jesse Owens or Emmy Noether, and idols whose personal lives you probably shouldn’t emulate, say Tiger Woods or Richard Feynman. However, I think the similarity can stretch beyond career paths.

Athene says that although she doesn’t participate in athletics, she does enjoy watching the sport. I’m sure many can empathise with that position. I think that this is similarly the case for research: many enjoy finding out about new discoveries or ideas, even though they don’t want to invest the time studying themselves. There are many excellent books and documentaries, many excellent communicators of research. (I shall be helping out at this year’s British Science Festival, which I’m sure will be packed with people keen to find out about current research.) However, there is undoubtedly more that could be done, both in terms of growing the market and improving the quality—reporting of science is notoriously bad. If you were to go into any pub in the country, I’d expect you’d be able to find someone to have an in-depth conversation with about how best to manage the national football team, despite them not being a professional footballer. Why not someone with similar opinions about research council funding? Can we make research as popular as sport?

Increasing engagement with and awareness of research is a popular subject, most research grants with have some mention of wider impact; however, I don’t think that this is the only goal. According to UK government research, many young students do enjoy science, they just don’t feel it is for them. The problem is that people think that science is too difficult. Given my previous ramblings, that’s perhaps understandable. However, that was for academic research; science is far broader than that! There are many careers outside the lab, and understanding science is useful even if that’s not your job, for example when discussing subjects like global warming or vaccination that affect us all. Coming back to our sports analogy, the situation is like children not wanting to play football because they won’t be a professional. It’s true that most people aren’t good enough to play for England (potentially including members of the current squad, depending upon who you ask in that pub), but that doesn’t mean you can’t enjoy a kick around, perhaps play for a local team at weekend, or even coach others. Playing sports regular keeps you physically fit, which is a good thing™; taking an interest in science (or language or literature or etceteras) keeps you mentally fit, also a good thing™.

Chocolate models

Chocolate is also a good thing™. However, neither Nobel Prizes nor Olympic Medals are made of chocolate, something I’m not sure that everyone appreciates. I’d make the gold Olympic models out of milk chocolate, silver out of white and bronze out of dark. The Nobel Prize for Medicine should contain nuts as an incentive to cure allergies; the Prize for Economics should be mint(ed) chocolate, the Peace Prize Swiss chocolate, the Chemistry Prize should contain popping candy, and the Physics Prize should be orange chocolate (that’s my favourite).

How to encourage more people to engage in science is a complicated problem. There’s no single solution, but it is something to work on. I would definitely prefer to live in a science-literate society. Stressing applications of science beyond pure research might be one avenue. I would also like to emphasis that it’s OK to find science (and maths) hard. Problem solving is difficult, like long-distance running, but if you practise, it does get easier. I can only vouch for one side of that simile from personal experience, but since I’m a theoretician, I’m happy enough to state that without direct experimental confirmation. I guess that means I should take my own advice and participate more myself: spend a little more time being physically active? Motivating myself is also a difficult problem.