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Found 6 papers, 3 papers with code
Robust field-level inference with dark matter halos
More importantly, we find that our models are very robust: they can infer the value of $\Omega_{\rm m}$ and $\sigma_8$ when tested using halo catalogues from thousands of N-body simulations run with five different N-body codes: Abacus, CUBEP$^3$M, Enzo, PKDGrav3, and Ramses.
Machine Learning and Cosmology
Methods based on machine learning have recently made substantial inroads in many corners of cosmology.
Corrfunc: Blazing fast correlation functions with AVX512F SIMD Intrinsics
Corrfunc is an existing open-source, high-performance software package for efficiently computing a multitude of correlation functions.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Data Structures and Algorithms
Corrfunc --- A Suite of Blazing Fast Correlation Functions on the CPU
Since the distribution of galaxies is determined by galaxy formation physics as well as the underlying cosmology, fitting an observed correlation function yields valuable insights into both.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Computational Physics
A Hybrid Deep Learning Approach to Cosmological Constraints From Galaxy Redshift Surveys
We present a deep machine learning (ML)-based technique for accurately determining $\sigma_8$ and $\Omega_m$ from mock 3D galaxy surveys.
Cosmology and Nongalactic Astrophysics
Exploring the squeezed three-point galaxy correlation function with generalized halo occupation distribution models
We identify generalized HOD prescriptions that are nearly degenerate in the projected 2PCF and demonstrate that these degeneracies are broken in the redshift-space anisotropic 2PCF and the squeezed 3PCF.
Cosmology and Nongalactic Astrophysics
