Search Results for author: Viraj Pandya

Found 2 papers, 2 papers with code

LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology

1 code implementation • 6 Feb 2024 • Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier, Carolina Cuesta-Lazaro, Simon Ding, Axel Lapel, Pablo Lemos, Christopher C. Lovell, T. Lucas Makinen, Chirag Modi, Viraj Pandya, Shivam Pandey, Lucia A. Perez, Benjamin Wandelt, Greg L. Bryan

This paper presents the Learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline, a codebase for rapid, user-friendly, and cutting-edge machine learning (ML) inference in astrophysics and cosmology.

Benchmarking Efficient Exploration

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First results from SMAUG: Characterization of Multiphase Galactic Outflows from a Suite of Local Star-Forming Galactic Disk Simulations

1 code implementation • 29 Jun 2020 • Chang-Goo Kim, Eve C. Ostriker, Rachel S. Somerville, Greg L. Bryan, Drummond B. Fielding, John C. Forbes, Christopher C. Hayward, Lars Hernquist, Viraj Pandya

We investigate the scaling of outflow mass, momentum, energy, and metal loading factors with galactic disk properties, including star formation rate (SFR) surface density (\Sigma_SFR~10^{-4}-1 M_sun/kpc^2/yr), gas surface density (~1-100 M_sun/pc^2), and total midplane pressure (or weight) (~10^3-10^6 k_B cm^{-3} K).

Astrophysics of Galaxies

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