16 papers
OASIS: Observation-Aware Simulation-Based Inference via Distributional Matching
Arya Farahi, Conghao Zhou, Ritwik Vashistha
We introduce OASIS, a simulation-based inference framework for scientific settings where observations are distorted by measurement error, selection effects, and other survey-specif…
Nonparametric Deconvolution and Denoising using Simulation Based Inference
Ritwik Vashistha, Abhra Sarkar, Arya Farahi
Latent signals are often obscured by measurement noise, yet encode the underlying laws and dynamics of complex systems; learning both the signals and their distributions remains a…
Cosmo3DFlow: Wavelet Flow Matching for Spatial-to-Spectral Compression in Reconstructing the Early Universe
Md. Khairul Islam, Zeyu Xia, Ryan Goudjil +3
Reconstructing the early universe from the evolved present-day universe is a challenging and computationally demanding problem in modern astrophysics. We devise a novel generative…
Convolutional Maximum Mean Discrepancy for Inference in Noisy Data
Ritwik Vashistha, Jeff M. Phillips, Abhra Sarkar +1
Modern data analyses frequently encounter settings where samples of variables are contaminated by measurement error. Ignoring measurement noise can substantially degrade statistica…
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…
Two Point Correlation Function Estimation with Contaminated Data
Arya Farahi
The two-point correlation function (2PCF) is a cornerstone of precision cosmology, yet its estimation from imaging surveys is vulnerable to contamination and incompleteness arising…