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The Cosmological Bootstrap: Theory and Observations

04/17 2024 Seminar
  • Title The Cosmological Bootstrap: Theory and Observations
  • Speaker Dong-Gang Wang (University of Cambridge)
  • Date 14:30 Apr. 17, 2024
  • Venue 6620
  • Abstract

    Our understanding of the primordial Universe largely depends on the information from spatial correlations of matter distributions. Recently, the advances of the ”cosmological bootstrap” program offer new perspectives and powerful tools to study these cosmological correlators. In this talk, I will first review the developments of this exciting new direction. Then I will apply the bootstrap approach to systematically classify the primary observational target — primordial non-Gaussianities (bispectrum) from cosmic inflation. For the first time, we derive a complete set of scalar bispectra with analytical shapes and large signals, incorporating three leading scenarios: single field inflation, cosmological collider physics, and multi-field inflation. Remarkably, the bootstrap analysis predict novel phenomenologies, which are testable even in today’s observations. In the end, guided by the theoretical studies, I will present a comprehensive data analysis of these predictions using the latest CMB observation from Planck satellite. As the first attempt, we bridge the gap between theories and observations, and demonstrate how the cosmological bootstrap paves the way towards the discovery of new high energy physics in the very early Universe.

    Biography

    Dong-Gang Wang is a postdoctoral researcher as a Rubicon Fellow at the Department of Applied Mathematics and Theoretical Physics in the University of Cambridge, UK. Before that, he did his PhD in Leiden University in the Netherlands as a de Sitter Fellow from 2016 to 2020. Before that, he was a master student in USTC from 2013 to 2016. His research mainly focuses on an emerging interdisciplinary direction that applies theoretical methods of high energy physics in the studies of the primordial Universe.?

    Inviter

    Shi Pi