Simulation-based gravitational-wave population inference with normalizing flow
Abstract: Running population synthesis simulations can be time-consuming. To constrain the physical parameters characterizing the simulations we must compare them to the data at numerous sample points in the physical parameter space. This comparison requires a large number of simulations, and it is often computationally impractical. In this talk, I will present a deep learning technique (normalizing flow) to emulate population synthesis simulations at a much faster speed. The emulator can be used in the population inference process, opening up the possibility of constraining astrophysics directly using the observed gravitational-wave population.
Constraining the Major Merger Rate History of the Universe since z~3: Comprehensive Analysis of Close Pairs and Tidal Features using Observations and Simulations
Abstract: The major merger rate between similar mass galaxies (stellar-mass ratio <4:1) is theoretically predicted to increase towards earlier cosmic times and is thought to play a vital role in buildup of high-mass galaxies. Established empirical techniques (close pairs and tidal features) test the theory by measuring the rate as pair or tidal fraction divided by the time during which mergers show empirically detectable signatures (observability timescale). Yet, astronomers face two important challenges that hinder precise constraints on merger rate and feature-based major merger identification: 1) lack of rigorous calibrations quantifying the role of observational systematics when measuring the merger fractions; 2) the close-pair and tidal feature observability timescales have yet to be systematically quantified in a cosmological context. I will summarize my coordinated attempts to solve these challenges using comprehensive Hubble Space Telescope (HST) observations and forefront simulated datasets. I will discuss: i) the redshift evolution of close-pair fraction at during 0.5<z<3 using the CANDELS survey; ii) ongoing efforts to quantify the role of observational systematics (photometric redshift, stellar-mass errors, and detection incompleteness) on measurement of close-pair fractions using mock lightcones from Semi-Analytical Models; iii) a recently developed pipeline to extract and quantify the strength of plausible tidal features within parametric model-subtracted residual images; iv) future efforts towards quantifying close-pair and tidal feature timescales using a large sample of 1E5 synthetic HST H-band images of 6500 major mergers (~20 Myr timesteps) from the Horizon-AGN simulation.
Bio: I am an international doctoral student from India working with Dr. Daniel McIntosh on galaxy mergers and galaxy evolution at University of Missouri Kansas City. I am in my final stages of the degree and am actively applying for post-doc positions.
Host: Mike McDonald