1 citations · 1 across the 11 of their papers we have counts for
12 papers
Optimal and exact wide-angle power spectrum estimation
Noah Sailer, Kendrick Smith, Yurii Kvasiuk +2
What is the optimal power spectrum estimator on ultra-large scales where the plane-parallel approximation breaks down? Conventional estimators, such as the Yamamoto estimator, are…
MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models
Yurii Kvasiuk, Tianyi Li, Owen Colegrove +1
We explore the application of LLM-driven algorithm optimization to several common tasks in quantitative finance. MadEvolve, a general-purpose algorithm optimization framework inspi…
Fine-Tuning Small Reasoning Models for Quantum Field Theory
Nathaniel S. Woodward, Zhiqi Gao, Yurii Kvasiuk +3
Despite the growing application of large language models (LLMs) to theoretical physics, there has been little academic exploration of how domain-specific physics reasoning ability…
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,…
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…
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…
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…
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…
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…
Reconstruction of Continuous Cosmological Fields from Discrete Tracers with Graph Neural Networks
Yurii Kvasiuk, Jordan Krywonos, Matthew C. Johnson +1
We develop a hybrid GNN-CNN architecture for the reconstruction of 3-dimensional continuous cosmological matter fields from discrete point clouds, provided by observed galaxy catal…
A Tale of Two Fields: Neural Network-Enhanced non-Gaussianity Search with Halos
Yurii Kvasiuk, Moritz Münchmeyer, Kendrick Smith
It was recently shown that neural networks can be combined with the analytic method of scale-dependent bias to obtain a measurement of local primordial non-Gaussianity, which is op…
An Auto-Differentiable Likelihood Pipeline for the Cross-Correlation of CMB and Large-Scale Structure due to the Kinetic Sunyaev-Zeldovich Effect
Yurii Kvasiuk, Moritz Münchmeyer
We develop an optimization-based maximum likelihood approach to analyze the cross-correlation of the Cosmic Microwave Background (CMB) and large-scale structure induced by the kine…