2025-01-20 ミシガン大学
This is a two-dimensional slice of a 3D map of the universe generated by the Dark Energy Spectroscopic Instrument. In the inset, the web-like structure of galaxies is visible. New research from the University of Michigan and the Max Planck Institute for Astrophysics shows a new method of analyzing such maps outperforms the standard methods. Image credit: Claire Lamman/DESI collaboration (Custom colormap package by cmastro)
＜関連情報＞
- https://news.umich.edu/getting-the-most-out-of-cosmic-maps/
- https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.133.221006
銀河クラスタリングからどの程度の情報を抽出できるか？ How Much Information Can Be Extracted from Galaxy Clustering at the Field Level?
Nhat-Minh Nguyen, Fabian Schmidt, Beatriz Tucc, Martin Reinecke, and Andrija Kostić
Physical Review Letters Published 27 November, 2024
DOI:https://doi.org/10.1103/PhysRevLett.133.221006.
Abstract
We present optimal Bayesian field-level cosmological constraints from nonlinear tracers of cosmic large-scale structure, specifically the amplitude 8 of linear matter fluctuations inferred from rest-frame simulated dark matter halos in a comoving volume of 8 (ℎ−1 Gpc)3. Our constraint on 8 is entirely due to nonlinear information, and obtained by explicitly sampling the initial conditions along with tracer bias and noise parameters via a Lagrangian effective field theory-based forward model, leftfield. The comparison with a simulation-based inference of the power spectrum and bispectrum—likewise using the leftfield forward model—shows that, when including precisely the same modes of the same data up to max=0.10 ℎ Mpc−1 (0.12 ℎ Mpc−1), the field-level approach yields a factor of 3.5 (5.2) improvement in the 8 constraint, going from 20.0% to 5.7% (17.0% to 3.3%). This study provides direct insights into cosmological information encoded in galaxy clustering beyond low-order -point functions.
