Finding the exact counterpart galaxies to merging black hole binaries detected in gravitational waves is one of the most pressing problems in cosmology. The redshift of the host galaxy (which has to be measured from its electromagnetic emission) combined with the luminosity distance to the gravitational wave source allows for a direct measurement of the expansion history of the Universe, an approach commonly referred to as the ‘Standard Siren’ method. To date, there are no proven techniques for accomplishing this goal.

But if X-rays are emitted at the time of the merger, a small fraction of the X-rays will be scattered off dust in our own Galaxy, producing a time-variable circular scattering halo that lingers for about a day after the gravitational waves have passed Earth. Such a halo has a highly characteristic, predictable shape; but we have no experience with searching for such unusual patterns in noisy imaging data. We want to use machine learning techniques to perform the search. The gravitational wave detectors will start operating again in early 2019. There is also a significant amount of archival X-ray imaging data that has not been investigated in the proposed manner.

This is project is NOT accepting applications.

Faculty Advisor

  • Professor Frits Paerels
  • Department/School: Astronomy/Arts and Science
  • Location: Morningside Campus
  • Research interests: High Energy Astrophysics, X-ray astronomy, the intergalactic medium, the fundamental properties of compact objects, and astrophysical instrumentation.

Project timeline

  • Earliest starting date: 03/02/2019
  • End date: 08/31/2019
  • Number of hours per week of research expected during Spring 2019: ~10
  • Number of hours per week of research expected during Summer 2019: ~35

Candidate requirements

  • Skill sets: Basic programming, Basic physics
  • Student eligibility (as of Spring 2019): freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible