Soma Mukherjee
Professor
Ph.D. University of Calcutta (India), Physics, 1991
Post-doctoral research appointments:
Northwestern University (Visiting scholar, LIGO project, Caltech, during same period)
Pennsylvania State University
Max Planck Institur fuer Gravitationasphysik
Office: BINAB 2.139
Phone: (956) 882-6679
Email: soma.mukherjee@utrgv.edu
Courses Taught
Thesis I PHYS 7300 and Thesis II PHYS 7301
Graduate Research I PHYS 6396 and Graduate Research II PHYS 6397
Quantum Mechanics PHYS 5340
Electrodynamics PHYS 5320
Advanced Statistical Methods PHYS 5394
Special Topics in Physics (Graduate): Gravitational Wave Data Analysis PHYS 5387
Computational Physics PHYS 4390
Special Topics in Physics (Undergraduate): Gravitational Wave Data Analysis PHYS 4380
University Physics II PHYS 2426
Introduction to Astronomy II ASTR 1402
Introduction to Astronomy I ASTR 1401
Research
The first direct detection of GW happened in 2015 when GW signal from a 30 solar mass binary black hole (BBH) system located 1.3 billion light years away was detected by the LIGO interferometers. Since then several BBH signals have been detected. Yet another watershed moment came when LIGO and Virgo detectors made the first detection of GW signals from colliding binary neutron stars (BNS). This led to the Nobel Prize being awarded to Kip Thorne, Rai Weiss and Barry Barish and the Breakthrough Prize in Fundamental Physics to the LIGO Scientific Collaboration of which I have been a member since its inception. Most recently, the LIGO and Virgo detectors have discovered an object that fills the ‘mass gap’ between neutron stars and black holes that has puzzled astronomers for decades. The heaviest known neutron star is no more than 2.5 solar masses, and the lightest known black hole is about 5 solar masses. The object was found on August 14, 2019, was of 2.6 solar mass as it merged with a black hole of 23 solar masses. (See: ligo.org)
My current research interest is in the area of detection of gravitational waves (GW) from unmodeled sources, specifically that from the core collapse supernovae (CCSN). The core collapse supernovae (CCSN) in our universe are potential sources of GW that could be detected with a network of GW detectors. Several GW detectors are in operation around the world, e.g., LIGO (USA), Virgo (French-Italian collaboration), KAGRA (Japanese collaboration) and GEO600 (British-German collaboration). CCSN are rare, but the associated gravitational radiation is likely to carry profuse information about the underlying processes driving the supernovae. Calculations based on analytic models predict GW energies within the detection range of the Advanced LIGO detectors, out to tens of kiloparsec. Analysis of the GW signal of the post-bounce evolution of core-collapse supernovae using relativistic, 2D and 3D explosion models have been calculated. The waveforms show the accelerated mass motions associated with the characteristic evolutionary stages. The basic model is that a quasi-periodic modulation by prompt post-shock convection is followed by a phase of relative quiescence. Following this, the amplitudes grow again due to violent hydrodynamical activity caused by convection and the standing accretion shock instability (SASI). Finally, a high-frequency, low-amplitude variation from proto-neutron star convection below the neutrino-sphere appears superimposed on the low-frequency trend associated with the aspherical expansion of the SN shock after the onset of the explosion. The GW frequency from neutrino driven CCSN is expected to evolve from approximately 100 Hz to about 1 kHz.
Since the signals from these sources are weak, methods that can improve the sensitivity of searches for GW signals from CCSN are desirable, especially in the advanced detector era. The GW detectors are undergoing upgrades and the fourth observation run of LIGO is expected to start in the near future. The most anticipated source as the detectors become more sensitive are the CCSN’s. The challenge lies in the low rates (2 per century in the galaxy) and weak nature of the signals, not to mention the challenges associated with detection of unmodeled signals. Several groups around the world have been working on realistic simulations of the CCSN explosion mechanism giving rise to GW’s using the supercomputers. The simulated waveform catalogs that take into account various explosion scenarios using a wide range of equations of state have been made available to the researchers. Several methods have been proposed based on various likelihood-based regulators that work on data from a network of detectors to detect burst-like signals (as is the case for signals from CCSN) from potential GW sources. To address this problem, my research group has developed and implemented a new technique of false alarm reduction in the supernova search pipeline that combines a multi-stage, high accuracy spectral estimation to effectively achieve higher signal to noise ratio (snr) and a coherent search pipeline using data from the network of GW detectors. The method is further refined by incorporation of deep learning techniques to classify and eliminate glitches that mimic GW signals. This increasingly sensitive pipelines analyze the detection probability of CCSN corresponding to these various explosion models during the observation runs to search for CCSN signals. The work is highly inter-disciplinary with integration of knowledge from astrophysics, cutting-edge applications of computation and of signal processing.
Former students:
- Mr. S.K. Faisal, Ph. D in Physics, UTRGV, 2022-23
- Ms. B. Sedhai, Master of Interdisciplinary Sciences : Science & Technology Thesis, 2021-23
- Mr. M. Benjamin, Master of Science in Physics, Thesis2021-23
- Mr. S.K. Faisal, Master of Interdisciplinary Sciences : Science & TechnologyThesis, 2020-22
- Ms. G. Nurbek, Master of Interdisciplinary Sciences : Science & TechnologyThesis, 2019-21
- Ms. G. Tukayeva, Master of Interdisciplinary Sciences : Science & Technology, 2017-18
- Ms. Z. Turymtay, Master of Interdisciplinary Sciences : Science & Technology, 2017-18
- Mr. D. Dossymbek, Master of Interdisciplinary Sciences : Science & Technology, 2017-18
- Mr. R. Stone, cooperative Ph. D in Physicsat UT Arlington, 2012-16
- Ms. W. Wang, cooperative Ph. D in Physicsat UT Arlington, 2014-17
- Mr. S. Sitmukhambetov, Master of Science in Physics, 2017
- Ms. A. Alvarez, Master of Science in Physics, 2016
- Ms. W. Wang, Master of Science in PhysicsThesis, 2014
- Mr. L. Salazar, Post-Masters research assistant, 2012-2013
- Ms. P. Rizwan, Master of Interdisciplinary Sciences (MSIS)Thesis, 2009-11
- Ms. T. Zhang, Master of Interdisciplinary Sciences (MSIS) Thesis (co-supervisor with Prof. L. R. Tang), 2011
- Mr. T. S. Weerathunga, Master of Science in PhysicsThesis, 2008-10
- Mr. C. Dannangoda, Master of Science in Physics, 2008-10
- Mr. R. Stone, Master of Science in PhysicsThesis, 2003-05
- Mr. R. Martin, Master of Interdisciplinary Sciences (MSIS)
- Mr.R. Obaid, Capstone undergraduate research, 2010
- Ms.T. Inoue, Undergraduate research, 2006
Current students:
-
Raul Espinoza, Master of Science in Physics, 2023-24
NSF REU / Summer Undergraduate students:
- Ms. Joanna Loera, REU student, University of Texas Austin, (2023)
- Mr. Michael Benjamin, REU student, Embry-Riddle Aeronautical University, Prescott, Arizona, (2019)
- Mr. Wes Lee Johnson, REU student, University of Arizona (2018)
- Ms. Shaina Rudman, REU student, Maryland University (2017)
- Ms. Lucia Illari, REU student, Barnard College New York City (2016)
- Mr. Hunter Gabbard, REU student, Mississippi State University (2015)
- Mr. Joseph Mittelstaedt, REU student, University of Chicago (2014)
- Mr. Justin Tervala, REU student, University of Maryland (2013)
- Mr. Martin Harrington, REU student, University of Alaska (2012)
- Ms. Avani Gowardhan, IISER, India, CGWA summer student (2012)