most citedThe Escape Velocity Profile of the Milky Way from Gaia DR3

15 citations · 15 across the 3 of their papers we have counts for

collaborators

11 papers

astro-ph.IM2026

Deep Learning for Astrophysics: An Open Textbook from the NASA Cosmic Origins AI/ML Science and Technology Interest Group

Yuan-Sen Ting, Digvijay Wadekar, Phill Cargile +21

Recent community assessments identify education as a principal barrier to adopting modern machine learning in astronomy. We present Deep Learning for Astrophysics, a freely availab…

astro-ph.GA2026

Dark Matter in Draco and Boötes I: Hints of a Core in an Ultra-Faint Dwarf from Simulation-Based Inference

Tri Nguyen, Lina Necib, Ting S. Li +8

The density profiles of dwarf spheroidal galaxies are among the most sensitive probes of dark matter physics, yet extracting them from noisy stellar kinematics remains a fundamenta…

astro-ph.GA202615 cited

The Escape Velocity Profile of the Milky Way from Gaia DR3

Cian Roche, Lina Necib, Tongyan Lin +2

The escape velocity profile of the Milky Way offers a crucial and independent measurement of its underlying mass distribution and dark matter properties. Using a sample of stars fr…

astro-ph.GA2026

The DREAMS Project: Disentangling the Impact of Halo-to-Halo Variance and Baryonic Feedback on Milky Way Dark Matter Density Profiles

Alex M. Garcia, Jonah C. Rose, Paul Torrey +23

In this work, we utilize a new suite of Milky Way-mass halos from the DREAMS Project, simulated with Cold Dark Matter (CDM), to quantify the influence of baryon feedback and intrin…

astro-ph.GA2025

Forecasting Dark Matter Subhalo Constraints from Stellar Streams using Implicit Likelihood Inference

Tri Nguyen, Rutong Pei, Zhuofu Li +9

The evidence for dark matter (DM) remains compelling, although attempts to understand its particle nature remain inconclusive. One promising method to study DM is detecting DM subh…

astro-ph.GA2025

LIMFAST. IV. Learning High-Redshift Galaxy Formation from Multiline Intensity Mapping with Implicit Likelihood Inference

Guochao Sun, Tri Nguyen, Claude-André Faucher-Giguère +5

By opening up new avenues to statistically constrain astrophysics and cosmology with large-scale structure observations, the line intensity mapping (LIM) technique calls for novel…