activity
20232026
most citedAn Auto-Differentiable Likelihood Pipeline for the Cross-Correlation of CMB and Large-Scale Structure due to the Kinetic Sunyaev-Zeldovich Effect

1 citations · 1 across the 11 of their papers we have counts for

collaborators
Showing 2025Show all

6 papers · 1 filter

astro-ph.CO2025

The Simons Observatory: forecasted constraints on primordial gravitational waves with the expanded array of Small Aperture Telescopes

The Simons Observatory Collaboration, I. Abril-Cabezas, S. Adachi +479

We present updated forecasts for the scientific performance of the degree-scale (0.5 deg FWHM at 93 GHz), deep-field survey to be conducted by the Simons Observatory (SO). By 2027,…

astro-ph.CO2025

QML-FAST -- A Fast Code for low- Tomographic Maximum Likelihood Power Spectrum Estimation

Yurii Kvasiuk, Anderson Lai, Moritz Münchmeyer +1

We present a novel implementation for the quadratic maximum likelihood (QML) power spectrum estimator for multiple correlated scalar fields on the sphere. Our estimator supports ar…

astro-ph.CO2025

Reconstruction of Dark Matter and Baryon Density From Galaxies: A Comparison of Linear, Halo Model and Machine Learning-Based Methods

Jordan Krywonos, Yurii Kvasiuk, Matthew C. Johnson +1

For many analyses in cosmology it is necessary to reconstruct the likely distribution of unobserved fields, such as dark matter or non-luminous baryons, from observed luminous trac…

astro-ph.CO2025

KSZ Velocity Reconstruction with ACT and DESI-LS using a Tomographic QML Power Spectrum Estimator

Anderson C. M. Lai, Yurii Kvasiuk, Moritz Münchmeyer

We perform kinetic Sunyaev-Zel'dovich (kSZ) velocity reconstruction on data from ACT DR6 and DESI-LS DR9. To estimate the cross-power between kSZ velocity reconstruction and galaxy…

cs.LG2025

Test-time Scaling Techniques in Theoretical Physics -- A Comparison of Methods on the TPBench Dataset

Zhiqi Gao, Tianyi Li, Yurii Kvasiuk +5

Large language models (LLMs) have shown strong capabilities in complex reasoning, and test-time scaling techniques can enhance their performance with comparably low cost. Many of t…

cs.LG2025

Theoretical Physics Benchmark (TPBench) -- a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics

Daniel J. H. Chung, Zhiqi Gao, Yurii Kvasiuk +5

We introduce a benchmark to evaluate the capability of AI to solve problems in theoretical physics, focusing on high-energy theory and cosmology. The first iteration of our benchma…