113 citations · 355 across the 22 of their papers we have counts for
22 papers
High-resolution weak lensing mass mapping from DES-Y3 data using diffusion-based prior
Supranta S. Boruah, Michael Jacob, Bhuvnesh Jain +2
High-resolution mapping of cosmic mass distribution is essential for a variety of astrophysical applications including understanding cosmic structure formation, and galaxy formatio…
Inference of Hubble constant using standard sirens and reconstructed matter density field
Supranta S. Boruah, Ghazal Geshnizjani, Guilhem Lavaux
We summarise a new approach for measuring the Hubble constant using standard sirens and the reconstructed matter density field obtained from observed galaxy surveys. Specifically,…
Diffusion-based mass map reconstruction from weak lensing data
Supranta S. Boruah, Michael Jacob, Bhuvnesh Jain
Diffusion models have been used in cosmological applications as a generative model for fast simulations and to reconstruct underlying cosmological fields or astrophysical images fr…
Fast Generation of Weak Lensing Maps with Analytical Point Transformation Functions
Kunhao Zhong, Gary Bernstein, Supranta S. Boruah +2
Nonlinear cosmological fields like galaxy density and lensing convergence can be approximately related to Gaussian fields via analytic point transforms. The lognormal transform (LN…
GANSky -- fast curved sky weak lensing simulations using Generative Adversarial Networks
Supranta S. Boruah, Pier Fiedorowicz, Rafael Garcia +3
Extracting non-Gaussian information from the next generation weak lensing surveys will require fast and accurate full-sky simulations. This is difficult to achieve in practice with…
Attention-Based Neural Network Emulators for Multi-Probe Data Vectors Part II: Assessing Tension Metrics
Evan Saraivanov, Kunhao Zhong, Vivian Miranda +3
The next generation of cosmological surveys is expected to generate unprecedented high-quality data, consequently increasing the already substantial computational costs of Bayesian…
Machine Learning LSST 3x2pt analyses -- forecasting the impact of systematics on cosmological constraints using neural networks
Supranta S. Boruah, Tim Eifler, Vivian Miranda +6
Validating modeling choices through simulated analyses and quantifying the impact of different systematic effects will form a major computational bottleneck in the preparation for…
Bayesian mass mapping with weak lensing data using KARMMA -- validation with simulations and application to Dark Energy Survey Year 3 data
Supranta S. Boruah, Pier Fiedorowicz, Eduardo Rozo
We update the field-level inference code KARMMA to enable tomographic forward-modelling of shear maps. Our code assumes a lognormal prior on the convergence field, and properly acc…
Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part I: Forecasting the Growth-Geometry split
Kunhao Zhong, Evan Saraivanov, James Caputi +4
We present a new class of machine-learning emulators that accurately model the cosmic shear, galaxy-galaxy lensing, and galaxy clustering real space correlation functions in the co…
Map-based cosmology inference with weak lensing -- information content and its dependence on the parameter space
Supranta S. Boruah, Eduardo Rozo
Field-level inference is emerging as a promising technique for optimally extracting information from cosmological datasets. Indeed, previous analyses have shown field-based inferen…
KaRMMa 2.0 -- Kappa Reconstruction for Mass Mapping
Pier Fiedorowicz, Eduardo Rozo, Supranta S. Boruah
We present KaRMMa 2.0, an updated version of the mass map reconstruction code introduced in Fiedorowicz et al. (2022). KaRMMa is a full-sky Bayesian algorithm for reconstructing we…
Map-based cosmology inference with lognormal cosmic shear maps
Supranta Sarma Boruah, Eduardo Rozo, Pier Fiedorowicz
Most cosmic shear analyses to date have relied on summary statistics (e.g. and ). These types of analyses are necessarily sub-optimal, as the use of summary statistics i…
Accelerating cosmological inference with Gaussian processes and neural networks -- an application to LSST Y1 weak lensing and galaxy clustering
Supranta S. Boruah, Tim Eifler, Vivian Miranda +1
Studying the impact of systematic effects, optimizing survey strategies, assessing tensions between different probes and exploring synergies of different data sets require a large…
Reconstructing dark matter distribution with peculiar velocities: Bayesian forward modelling with corrections for inhomogeneous Malmquist bias
Supranta S. Boruah, Guilhem Lavaux, Michael J. Hudson
We present a forward-modelled velocity field reconstruction algorithm that performs the reconstruction of the mass density field using only peculiar velocity data. Our method consi…
New Constraints on Anisotropic Expansion from Supernovae Type Ia
W. Rahman, R. Trotta, S. S. Boruah +2
We re-examine the contentious question of constraints on anisotropic expansion from Type Ia supernovae (SNIa) in the light of a novel determination of peculiar velocities, which ar…
Peculiar-velocity cosmology with Types Ia and II supernovae
Benjamin E. Stahl, Thomas de Jaeger, Supranta S. Boruah +3
We present the Democratic Samples of Supernovae (DSS), a compilation of 775 low-redshift Type Ia and II supernovae (SNe Ia & II), of which 137 SN Ia distances are derived via the n…
KaRMMa -- Kappa Reconstruction for Mass Mapping
Pier Fiedorowicz, Eduardo Rozo, Supranta S. Boruah +2
We present KaRMMa, a novel method for performing mass map reconstruction from weak-lensing surveys. We employ a fully Bayesian approach with a physically motivated lognormal prior…
Peculiar velocities in the local Universe: comparison of different models and the implications for and dark matter
Supranta S. Boruah, Michael J. Hudson, Guilhem Lavaux
When measuring the value of the Hubble parameter, , it is necessary to know the recession velocity free of the effects of peculiar velocities. In this work, we study different…
Cosmic flows in the nearby Universe: new peculiar velocities from SNe and cosmological constraints
Supranta S. Boruah, Michael J. Hudson, Guilhem Lavaux
The peculiar velocity field offers a unique way to probe dark matter density field on large scales at low redshifts. In this work, we have compiled a new sample of 465 peculiar vel…
Gravitational Potential from small-scale clustering in action space: Application to Gaia DR2
Tianyi. Yang, Supranta Sarma Boruah, Niayesh. Afshordi
Most measurements of mass in Astronomy that use kinematics of stars or gas rely on assumptions of equilibrium that are often hard to verify. Instead, we develop a novel idea that u…
Cuscuton Bounce
Supranta S. Boruah, Hyung J. Kim, Michael Rouben +1
In general relativity producing a regular bounce entails violation of Null Energy Condition for a dynamical source in the model. That generically indicates existence of ghosts or o…
Theory of Cosmological Perturbations with Cuscuton
Supranta S. Boruah, Hyung J. Kim, Ghazal Geshnizjani
This paper presents the first derivation of the quadratic action for curvature perturbations, , within the framework of cuscuton gravity. We study the scalar cosmological pertur…