Towards testing the theory of gravity with DESI: summary statistics, model predictions and future simulation requirements

Abstract

Shortly after its discovery, General Relativity (GR) was applied to predict the behavior of our Universe on the largest scales, and later became the foundation of modern cosmology. Its validity has been verified on a range of scales and environments from the Solar system to merging black holes. However, experimental confirmations of GR on cosmological scales have so far lacked the accuracy one would hope for — its applications on those scales being largely based on extrapolation and its validity there sometimes questioned in the shadow of the discovery of the unexpected cosmic acceleration. Future astronomical instruments surveying the distribution and evolution of galaxies over substantial portions of the observable Universe, such as the Dark Energy Spectroscopic Instrument (DESI), will be able to measure the fingerprints of gravity and their statistical power will allow strong constraints on alternatives to GR.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 01, 2021
Source ID
10.1088/1475-7516/2021/11/050

Entities

People

  • Alejandro Aviles
  • Alejo Stark
  • Alexander Eggemeier
  • Alma X. Gonzalez-morales
  • Axel De La Macorra
  • Baojiu Li
  • Carolina Cuesta-lazaro
  • Christian Arnold
  • Christopher J. Miller
  • Cristiano G. Sabiu
  • César Hernández-aguayo
  • Eva-maria Mueller
  • Georgios Valogiannis
  • Gong-bo Zhao
  • Gustavo Niz
  • Hans A. Winther
  • Jennifer Meneses Rizo
  • Jian-hua He
  • Jorge L. Cervantes-cota
  • Kazuya Koyama
  • Mariana Vargas-magaña
  • Marius Cautun
  • Matia Rodríguez Otero
  • Mustapha Ishak
  • N. Chandrachani Devi
  • Octavio Valenzuela
  • Pauline Zarrouk
  • Pierros Ntelis
  • Rachel Bean
  • Sebastien Fromenteau
  • Shadab Alam
  • Vitali Halenka
  • Wojciech A. Hellwing
  • Yan-chuan Cai
  • Yi Zheng
  • Zachary Slepian

Tags

Fields of Study

  • Physics

Readers

  • Astronomy/Astrophysics
  • Computational Modeling and Simulation
  • Systems Analysis and Design