Gravity is a familiar force and is central to astrophysics. Our best theory of gravitation is Einstein’s general relativity (GR). This tells us that gravity is the bending of spacetime by matter. I am working on finding out what we could learn from observations of strong gravitational fields, where the curvature of spacetime is greatest. Of particular interest to me is what we may be able to learn by measuring gravitational waves (ripples in spacetime).

Detecting gravitational waves is extremely challenging. I am currently working as a member of the Laser Interferometer Gravitational-wave Observatory (LIGO) Scientific Collaboration. Advanced LIGO started observations in 2015 and made the first observation of gravitational waves from a binary black hole merger, since then we have been joined by Advanced Virgo and made many more discoveries. During my PhD, I was interested in what we could measure with the planned Laser Interferometer Space Antenna (LISA), a space-based detector. In a few years, we may be able to do multi-band gravitational-wave astronomy!

I want to know both what we could learn about astrophysical objects, such as black holes or neutron stars, from gravitational tests, and what we may be able to learn about the nature of gravity itself. More detailed information can be found in my publications, blog, or by following the activities of my awesome research group.

Compact binaries

Having measured a gravitational wave, it is a difficult task to work out the properties of its source system. There are a number of techniques used for estimating the parameters of the gravitational waves, such as Markov-chain Monte Carlo. Most of my time is spent working as part of LIGO’s Parameter Estimation group on inferring the properties of compact binary coalescences. I analysed the first detections made by LIGO, and led the analysis of GW170104.

Detecting a gravitational wave is exciting, it is even more exciting to find an electromagnetic counterpart. Pointing telescopes in time for there still to be something to see is difficult. I have studied how well we can locate gravitational-wave sources on the sky, and cunning techniques for three-dimensional localization.

We need models for the waveforms, but we are not certain of their exact form. I have investigated how to include our uncertainty in the waveforms into our parameter-estimation codes.

The information we obtain from gravitational waves can potentially teach us about how their sources formed. Ilya Mandel likes to say that with observations of black hole and neutron star binaries we are doing stellar paleontology—we are inferring how stars live and die from the remains they leave behind. With a population of sources we can start to map out the formation channels for compact binaries, and understand the uncertain physics of binary evolution.

In CIERA, we are working on building more accurate models for how binary systems form and evolve, and how to decode the information provided by the population of our gravitational wave observations. I am excited about figuring out what we can learn from our gravitational wave observations, and how we can combine these with other astronomical data such as chemical abundances, gamma-ray bursts and X-ray binaries. One of our big projects is building a new binary population synthesis code POSYDON. This combines detailed simulations of the evolution of binary stars with machine-learning to interpolate betweens results in order to rapidly build entire populations of systems.

Extreme mass-ratio events

One of the main sources of gravitational waves for LISA will be extreme mass-ratio (EMR) events. These form when a compact object, such as a neutron star or stellar mass black hole, orbits close to the massive black hole found in the centre of a galaxy. As the compact object orbits, it generates gravitational waves. These carry away energy and momentum, making the orbit shrink, as well as encoding information about the shape of the spacetime background.

I have studied EMR bursts, short gravitational waves emitted when the orbit is still highly eccentric. These could be a useful way of learning about the massive black hole at the centre of the Milky Way. Unfortunately, I calculated that the event rate is low, so we would have to be lucky to observe one. EMR inspirals, longer signals emitted as the binary gets closer to merging are potentially more exciting.

As the orbit evolves its frequencies change. When the frequencies of the radial and polewards motion become multiples of each other, the system undergoes a transient resonance. There is a small glitch in the inspiral. I have found that this shouldn’t significantly impact our ability to detect inspirals, but could have interesting consequences for measuring their properties.

We’re currently uncertain of the rate of inspirals. This is great, as it means when we’ve measured the rate, we will have learnt a lot! We have performed a systematic study of all our astrophysical uncertainties, and concluded that even under the most pessimistic assumptions, there should be a few signals LISA will spot. Using these, we can start to reconstruct the distribution of massive black holes lurking in galactic centres.

Alternative theories of gravity

Prior to the detection of gravitational waves, general relativity had passed every observational test so far. However, these tests were confined to weak fields; the most exciting tests are the ones that probe strong fields, where spacetime is highly dynamic and the objects are extremely relativistic. These are the regions where GR is most likely to break down, and are exactly the region that gravitational waves probe.

I have therefore investigated what differences might be observed in an alternate theory of gravity: -gravity. This is one of the simplest extensions to GR. For the class of theories I studied, I concluded that laboratory tests are more sensitive than astrophysical ones, although both are useful as they probe different regions.

With our LIGO and Virgo detections, we perform many tests to check for any deviations from our expectations, such as checking that the low-frequency part of the signal form the inspiral and the higher-frequency part from merger and ringdown yield consistent results for the estimated mass and spin. So far, we have yet to discover anything unexpected, but we’ll keep looking.

Data quality

One of the difficulties in analysing gravitational-wave data, whether to detect signals or infer source parameters is understanding the properties of the noise. Our detectors are extremely complicated machines, and they don’t always behave perfectly. Our data often contain noise transients (glitches). A glitch greatly complicated our analysis of GW170817. Understanding glitches can both help us improve the detectors to remove them and also aid our understanding of how to analyse data featuring them.

Gravity Spy is a project designed to better understand glitches in our data. It combines machine learning and public powered research (citizen science) in order to produce the best results. We have even created tools to enable our volunteers to help identify new classes of glitch—I am incredibly impressed by the results. I am interested in both better understanding how to identify glitches and how we can use our knowledge to improve our data analysis.