25 citations · 199 across the 40 of their papers we have counts for
42 papers
On the sum of eccentric subgraph numbers of the vertices of a connected graph
Akash De, Kamal Lochan Patra
Let be a connected graph. The eccentric subgraph number of a vertex of is defined as , where is the number of connec…
Cool Embeddings: Predicting Galaxy Cluster Cooling Times in IllustrisTNG and TNG-Cluster with AstroCLIP
Rawan Karam, Carter Lee Rhea, Julie Hlavacek-Larrondo +4
Foundation models trained on optical astronomical data have not previously been applied to X-ray cluster thermodynamics. We show that embeddings from AstroCLIP, a contrastive visio…
Microlensing Detection and Inference via Learned Bayes Factors
Nolan Smyth, Laurence Perreault-Levasseur, Yashar Hezaveh
We present a unified framework for gravitational microlensing event detection and parameter inference. Traditional pipelines use deterministic hard cuts on photometric statistics,…
Strong Gravitational Lensing Posterior Sampling in Pixel-Space Using Diffusion Models and Recurrent Inference Machines
Guillaume Payeur, Laurence Perreault-Levasseur, Gabriel Missael Barco +1
Modeling galaxy-galaxy strong gravitational lenses to infer the brightness of the source galaxy and the mass distribution of the foreground galaxy is computationally challenging, p…
MIRA: A Score for Conditional Distribution Accuracy and Model Comparison
Sammy Sharief, Justine Zeghal, Gabriel Missael Barco +3
We introduce Mira, a sample-based score for assessing the accuracy of a candidate conditional distribution using only joint samples from the true data-generating process. Relying o…
Transformer Embeddings for Fast Microlensing Inference
Nolan Smyth, Laurence Perreault-Levasseur, Yashar Hezaveh
The search for free-floating planets (FFPs) is a key science driver for upcoming microlensing surveys like the Nancy Grace Roman Galactic Exoplanet Survey. These rogue worlds are t…
Neural Deprojection of Galaxy Stellar Mass Profiles
M. J. Yantovski-Barth, Hengyue Zhang, Nolan Smyth +4
We introduce a neural approach to dynamical modeling of galaxies that replaces traditional imaging-based deprojections with a differentiable mapping. Specifically, we train a neura…
Mind the Information Gap: Unveiling Detailed Morphologies of z 0.5-1.0 Galaxies with SLACS Strong Lenses and Data-Driven Analysis
Ronan Legin, Connor Stone, Alexandre Adam +5
We present new state-of-the-art lens models for strong gravitational lensing systems from the Sloan Lens ACS (SLACS) survey, developed within a Bayesian framework that employs high…
Blind Strong Gravitational Lensing Inversion: Joint Inference of Source and Lens Mass with Score-Based Models
Gabriel Missael Barco, Ronan Legin, Connor Stone +2
Score-based models can serve as expressive, data-driven priors for scientific inverse problems. In strong gravitational lensing, they enable posterior inference of a background gal…
Predicting the Subhalo Mass Functions in Simulations from Galaxy Images
Andreas Filipp, Tri Nguyen, Laurence Perreault-Levasseur +5
Strong gravitational lensing provides a powerful tool to directly infer the dark matter (DM) subhalo mass function (SHMF) in lens galaxies. However, comparing observationally infer…
The spatially-resolved effect of mergers on the stellar mass assembly of MaNGA galaxies
Eirini Angeloudi, Marc Huertas-Company, Jesús Falcón-Barroso +3
Understanding the origin of stars within a galaxy - whether formed in-situ or accreted from other galaxies (ex-situ) - is key to constraining its evolution. Spatially resolving the…
Massive Extremely High-Velocity Outflow in the Quasar J164653.72+243942.2
Paola Rodríguez Hidalgo, Hyunseop Choi, Patrick B. Hall +6
We present the analysis of one of the most extreme quasar outflows found to date in our survey of extremely high velocity outflows (EHVO). J164653.72+243942.2 (z ~ 3.04) shows vari…
Field-Level Comparison and Robustness Analysis of Cosmological N-body Simulations
Adrian E. Bayer, Francisco Villaescusa-Navarro, Sammy Sharief +6
We present the first field-level comparison of cosmological N-body simulations, considering various widely used codes: Abacus, CUBEPM, Enzo, Gadget, Gizmo, PKDGrav, and Ramses.…
Solving Bayesian inverse problems with diffusion priors and off-policy RL
Luca Scimeca, Siddarth Venkatraman, Moksh Jain +14
This paper presents a practical application of Relative Trajectory Balance (RTB), a recently introduced off-policy reinforcement learning (RL) objective that can asymptotically sol…
Robustness of Neural Ratio and Posterior Estimators to Distributional Shifts for Population-Level Dark Matter Analysis in Strong Gravitational Lensing
Andreas Filipp, Yashar Hezaveh, Laurence Perreault-Levasseur
We investigate the robustness of Neural Ratio Estimators (NREs) and Neural Posterior Estimators (NPEs) to distributional shifts in the context of measuring the abundance of dark ma…
Gravitational-Wave Parameter Estimation in non-Gaussian noise using Score-Based Likelihood Characterization
Ronan Legin, Maximiliano Isi, Kaze W. K. Wong +2
Gravitational-wave (GW) parameter estimation typically assumes that instrumental noise is Gaussian and stationary. Obvious departures from this idealization are typically handled o…
Causal Discovery in Astrophysics: Unraveling Supermassive Black Hole and Galaxy Coevolution
Zehao Jin, Mario Pasquato, Benjamin L. Davis +9
Correlation does not imply causation, but patterns of statistical association between variables can be exploited to infer a causal structure (even with purely observational data) w…
Deconvolving X-ray Galaxy Cluster Spectra Using a Recurrent Inference Machine
Carter Rhea, Julie Hlavacek-Larrondo, Alexandre Adam +4
Recent advances in machine learning algorithms have unlocked new insights in observational astronomy by allowing astronomers to probe new frontiers. In this article, we present a m…
Inpainting Galaxy Counts onto N-Body Simulations over Multiple Cosmologies and Astrophysics
Antoine Bourdin, Ronan Legin, Matthew Ho +3
Cosmological hydrodynamical simulations, while the current state-of-the art methodology for generating theoretical predictions for the large scale structures of the Universe, are a…
Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations
Connor Stone, Alexandre Adam, Adam Coogan +9
Gravitational lensing is the deflection of light rays due to the gravity of intervening masses. This phenomenon is observed in a variety of scales and configurations, involving any…
Multi-phase black-hole feedback and a bright [CII] halo in a Lo-BAL quasar at
Manuela Bischetti, Hyunseop Choi, Fabrizio Fiore +18
Although the mass growth of supermassive black holes during the Epoch of Reionisation is expected to play a role in shaping the concurrent growth of their host-galaxies, observatio…
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
Pablo Lemos, Sammy Sharief, Esmeralda S. Whitammer +4
We propose a likelihood-free method for comparing two distributions given samples from each, with the goal of assessing the quality of generative models. The proposed approach, PQM…
Improving Gradient-guided Nested Sampling for Posterior Inference
Pablo Lemos, Nikolay Malkin, Will Handley +3
We present a performant, general-purpose gradient-guided nested sampling algorithm, , combining the state of the art in differentiable programming, Hamiltonian slice sa…
Learning an Effective Evolution Equation for Particle-Mesh Simulations Across Cosmologies
Nicolas Payot, Pablo Lemos, Laurence Perreault-Levasseur +3
Particle-mesh simulations trade small-scale accuracy for speed compared to traditional, computationally expensive N-body codes in cosmological simulations. In this work, we show ho…