Вход на сайт

Просмотр новости

Найдите то, что Вас интересует

Probing the limits of cosmological information from the Lyman-α forest 2-point correlation functions

Дата публикации: 04-08-2026 00:00:00

The standard cosmological analysis with the Lyα forest relies on a continuum fitting procedure that suppresses information on large scales and distorts the three-dimensional correlation function on all scales. In this work, we present the first cosmological forecasts without continuum fitting distortion in the Lyα forest, focusing on the recovery of large-scale information. Using idealized synthetic data, we compare the constraining power of the full shape of the Lyα forest auto-correlation and its cross-correlation with quasars using the baseline continuum fitting analysis versus the true continuum. We find that knowledge of the true continuum enables a ∼ 10% reduction in uncertainties on the Alcock-Paczyński (AP) parameter and the matter density, Ωm. We also explore the impact of large-scale information by extending the analysis up to separations of 240 h -1Mpc along and across the line of sight. The combination of these analysis choices can recover significant large-scale information,...

Схожие новости

#Наименование новостиТональностьИнформативностьДата публикации
1DESI DR1 Lyα 1D power spectrum: Validation of estimators08.9804-08-2026
2Measurements of Quasar Proximity Zones with the Lyα Forest of DESI Y1 Quasars07.6704-08-2026
3Galaxy Phase-space and Field-level Cosmology: The Strength of Semianalytic Models08.6118-08-2026
4The DESI DR1 peculiar velocity survey: growth rate measurements from the maximum likelihood fields method09.0104-08-2026
5BICEP/Keck XXI: Constraints on early-Universe parity violation from multipole-dependent birefringence012.618-08-2026
6A Unified Photometric Redshift Calibration for Weak Lensing Surveys Using the Dark Energy Spectroscopic Instrument07.204-08-2026
7Clustering analysis of medium-band selected high-redshift galaxies012.3804-08-2026
8H 0 without the sound horizon (or supernovae): A 2% measurement in DESI DR106.9304-08-2026
9Combined tracer analysis for DESI 2024 BAO010.2704-08-2026
10Predicting galaxy bias using machine learning08.7918-08-2026

Классификация: Наука. Схожих патентов: 0. Схожих новостей: 10. Тональность: 0. Информативность: 5.84. Источник: escholarship.org.