Testing the theory of gravity

  • August 22, 2013
Testing the theory of gravity

Erin Kara has won the Murdin Prize for her paper on supermassive black holes.

A Gates Cambridge Scholar has been awarded a prestigious prize by her department for the best graduate student paper of 2013 on research which allows the closest ever look at supermassive black holes and which could ultimately be used to test our theory of gravity.

Erin Kara [2011], who is doing a PhD in Astronomy, won the Murdin Prize for a paper that was published earlier this year in the UK’s main Astronomy journal: Monthly Notices of the Royal Astronomical Society.

The £500 prize is named after Emeritus Professor Paul Murdin, who established the award.

Erin says: “In this paper, I am using signal processing techniques to measure time delays in the X-ray signals that originate just outside of the event horizon of supermassive black holes. Using the fact that the speed of light is constant, we can convert these time delays into distances to put constraints on the geometrical structure of the complex environments around black holes, where gravity is at its most extreme.  In this particular study, we are probing distances equivalent to 30 light-seconds around a black hole that is 500 million light-years away.  If we can understand these extreme environments, we can use astrophysical black holes to test our best theory of gravity, Einstein’s General Relativity.”

For her PhD, Erin is researching the timing properties of the X-ray emission from supermassive black holes that are a million or a billion times the mass of the sun. To understand what the environments look like she is developing new tools as current telescopes are not good enough to take a picture of these systems and resolve the complex structure. The tools she uses are X-ray photons emitted very close to the event horizon of the black hole. As material falls into the black hole, its gravitational potential energy is released, thus heating up the surrounding material that remains. That material – mostly gas – gets so hot, that it radiates light.  

The light gets scattered off other particles, gravitationally pulled by the black hole, absorbed and re-emitted by atoms, but eventually, some of that light escapes. Hundreds of millions of years later, that light can be detected on Earth, and astronomers try to piece together the history of that light in order to understand what is happening around the black hole.  She says: “The only information we have from the light is its energy and the time that it finally hit our detector.”

Using signal processing techniques to  measure time lags of tens of seconds between X-rays in supermassive black hole systems is a new field of research that has only become possible in the last decade.

Picture credit: Dana Berry, NASA.

Latest News

Gates Cambridge Trust seeks new Provost

The Gates Cambridge Trust is seeking to appoint a Provost following the successful tenure of Professor Barry Everitt. The position of the Provost is held for five years in the first instance. The person appointed to the role would be expected to take up the position on 1 October 2022. The role The Provost is […]

Making offices safer and more efficient

A new white paper, co-authored by a Gates Cambridge Scholar, has been published which aims to improve the safety and efficiency of office buildings – a key issue during the pandemic. The paper,  A Virtual Reality-Based Digital Twin of workspaces, was published in January in collaboration with British Telecom and was co-authored by Pradipta Biswas, Assistant […]

Scholar heads to Winter Olympics

A Gates Cambridge Scholar is heading for Beijing where he will coach the Australian mixed doubles curling team in the Winter Olympics. The Australian Olympic Committee announced their selection of Tahli Gill and Dean Hewitt for the mixed doubles curling event at the Winter Olympics over the weekend, and Pete Manasantivongs as their coach. The […]

More trustworthy diagnoses through better algorithms

Mateo Espinosa is interested in exploring the medical applications of machine learning, specifically how machine learning can be used to provide trustworthy and interpretable diagnosis and prognosis predictions. His aim is to understand the decision-making process in order to reduce the room for error and develop better treatments. He says that over the course of […]