Sukanta Bose

Professor at the Inter-University Centre for Astronomy and Astrophysics (IUCAA) and the Project Coordinator of LIGO-India at IUCAA.

Sukanta Bose is the Chair of the LIGO-India Scientific Collaboration (LISC) and a member of the LIGO Scientific Collaboration (LSC) Council. He also chairs LSC’s Review Team for the Stochastic (signals) Working Group. He is an elected member of the International Society of General Relativity and Gravitation (ISGRG) Committee. Since 2013, Bose has worked on training several LISC (formerly IndIGO) scientists in gravitational wave research, particularly, using LIGO data, and on guiding their contributions in LSC science.

In his own words:

Currently my main research interests are gravitational waves, relativistic astrophysics, and cosmology. My primary collaborations are with members of the gravitational wave group at IUCAA, Pune, the WSU Relativity Group and the LIGO Scientific collaboration.

Research

A brief synopsis of the various research projects Bose is pursuing is given below. For a more detailed description, click here.

  1. Searches for gravitational wave signals from compact object binaries and a stochastic gravitational wave background, and measuring their astrophysical and cosmological parameters. In some pursuits this activity involves incorporating inputs from Numerical Relativity.
  2. Characterization of the noise in gravitational wave detectors
  3. Constraining the nuclear equation of state of neutron stars
  4. Follow-up of gravitational-wave triggers for finding their electromagnetic counterparts
  5. Speeding up gravitational wave data analysis computationally

Scroll Below for details.

Publications

A partial list of Bose’s publications is posted here.

Students

Science popularization, public outreach and other community activities

A partial list of Bose’s science popularization, public outreach other community activities is included with various other news items here.

 

A synopsis of Bose’s research activities

 

  1. Searches for gravitational wave signals from compact object binaries and their parameter estimation

With Sanjeev Dhurandhar and Archana Pai, Bose showed how to optimally combine the data from multiple ground-based interferometers to search for gravitational-wave signals from inspiraling compact object binaries. A key result was obtaining a detection statistic that handled the scanning of four of the source parameters analytically, thereby, remarkably improving the computational feasibility of the search. This method was implemented in real data (for searches of black hole ringdown signals) in collaboration with D. Talukder, S. Caudill, and P. Baker.

With the NINJA(2) collaboration, T. Dayanga and Bose contributed to incorporating Numerical Relativity (NR) based waveforms of binary black holes in gravitational wave data analysis.

In 2018, for the first time they compared Numerical Relativity waveforms from two different NR groups for neutron star (NS) – black hole binaries and studied implications on measurement of the NS equation of state.

In a work with P. Ajith, Bose estimated how accurately the various astrophysical parameters of binary compact objects (black holes) can be measured with earth-based GW detectors. In another work, with S. Ghosh and Ajith, he showed the extent of systematic errors that can arise in these estimates when the templates are restricted to be post-Newtonian inspirals.

Ideas on how gravitational wave observations can be used to constrain higher-dimensional models of gravity (such as braneworld) can be found in a set of works on quasi-normal modes of black holes and (stable) wormholes.

  1. Aspects of cosmology and the search for a stochastic gravitational wave background

In 2018 Bose and his collaborators showed how galaxy clustering can be used with a population of binary black hole observations (in gravitational waves) to measure the Hubble parameter without recourse to the (electro-magnetic) cosmic distance ladder.

In a separate series of papers on the stochastic gravitational wave background (SGWB), they obtained an optimal statistic for searching anisotropic distributions of it using ground-based detectors, and demonstrated in simulated strain data how it can be applied to obtain sky-maps of the background. The statistic used was based on an adaptation of the radiometry technique in gravitational wave searches. It was applied to real LIGO data in D. Talukder’s PhD dissertation work to put upper limits on the GW background. Assuming that the background is produced by spinning aspherical neutron stars in our galaxy, they were able to set limits on their average ellipticity. Another interesting result found was how the discovery of a single aspherical neutron star (e.g., in a continuous wave search) and a galactic neutron star background can help estimate the number of neutron stars in the galaxy.

In the past, Bose also contributed to the end-to-end testing of the isotropic SGWB search pipeline with hardware injections, which was important in obtaining the upper limit on the cosmological GW background published in a Nature paper.

  1. Characterization of the noise in gravitational wave detectors

In a 2016 paper, Bose and his collaborators described a tool they improved to detect excess noise in the gravitational wave channel arising from its bilinear or nonlinear coupling with fluctuations of various components of a GW interferometer and its environment. They also described a higher-order statistics tool they developed to characterize these couplings, e.g., by unraveling the frequencies of the fluctuations contributing to such noise, and demonstrate its utility by applying it to understand nonlinear couplings in Advanced LIGO engineering data. Once such noise is detected, it is highly desirable to remove it or correct for it. Such action in the past has been shown to improve the sensitivity of the instrument in searches of astrophysical signals. If this is not possible, then steps must be taken to mitigate its influence, e.g., by characterizing its effect on astrophysical searches. They illustrate this in another 2016 paper through a study of the effect of transient sine-Gaussian and chirping sine-Gaussian noise artifacts on a compact binary coalescence template bank.

  1. Constraining the nuclear equation of state of neutron stars

In a 2018 Physical Review Letters paper Bose and his collaborators showed how the neutron star equation of state (EOS) can be constrained from observations of the postmerger signal from the coalescence of a binary neutron star (BNS) system. He also collaborated with his colleagues in the LSC to detect GW170817 and use its signal to constrain this EOS.

As mentioned in item 1 above, in 2018 for the first time they compared Numerical Relativity waveforms from two different NR groups for neutron star (NS) – black hole binaries and studied implications on measurement of the NS equation of state.

In an earlier separate work, he had studied the proposal that Bose-Einstein condensates (BECs) are candidate states of matter for the interior of neutron stars. Specifically, Chavanis and Harko obtained the mass-radius relation for a BEC star and proposed that the recently discovered neutron stars with masses around 2M are BEC stars. They employed a barotropic equation of state (EOS), with one free parameter, that was first found by Colpi, Shapiro, and Wasserman (CSW), to describe them and derive stable equilibrium configurations of spinning BEC stars in General Relativity. In a 2015 work they showed that while it is true that BECs allow for compact object masses as heavy as the heaviest observed ones, such stars cannot simultaneously have radii that are small enough to be consistent with the latest observations, in spite of the flexibility available in the EOS in the form of the free parameter. In fact, the conclusion applies to any spinning relativistic boson star that obeys the CSW EOS.

  1. Follow-up of gravitational-wave triggers for finding their electromagnetic counterparts

Combining information channeled through both gravitational wave and electromagnetic observations can teach us much more about their common progentiors, which may include short hard gamma-ray bursts, than what any one type of observation can do. Bose worked with Varun Bhalerao, Javed Rana, Bhooshan Gadre et al. in this area of research and has published some of their findings on “An optimal method for scheduling observations of large sky error regions for finding optical counterparts to transients,” (2016). Another work along similar lines can be found here. Their methods have been adapted and used for transient observations with PTF and the VLA.

  1. Speeding up gravitational wave data analysis algorithmically and computationally

In 2018 he applied the technique of Random Projections, for the first time, to speed up the search for compact object binaries, especially, when the search parameter space, and the number of required templates, happens to be large. You can read more about it here.

In a work in 2015 with Khun Sang Phukon (IIT-Kanpur) and Vihan Pandey, Bose demonstrated the computational speed-up that can be achieved by computing the chi-squared discriminator in compact binary coalescence (CBC) searches on Graphics Processing Units (GPUs) rather than Central Processing Units (CPUs). One of the most demanding gravitational-wave searches in high-performance and high-throughput computing is that of CBC signals in multiple detectors. This is especially true for those CBCs that have the potential to produce an electromagnetic (EM) counterpart. Such a binary system will involve at least one neutron star. The second object can be another neutron star or a relatively small stellar-mass black hole. These systems not only have long-duration signals but can require a large parameter space to define them. Multiple detectors are needed to localize them in the sky for ease of EM follow-ups. Finally, since the EM counterparts may fade quickly, the searches need to be near-real-time so as to enhance the chances of GW-EM coincidences. These various factors require that the computing involved in analyzing the GW data to find them be quick and inexpensive. They corroborate past findings, but now with more modern hardware, that GPUs can provide significant speed-ups in the computation of the chi-squared discriminator in CBC searches, in comparison to not just single CPUs but also multiple MPI processes running on a CPU cluster.