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SUMMARY:Cosmological Constraints from the Thermal Sunyaev-Zel’dovich Pow
 er Spectrum — A Simulation-Based Inference approach - Licong Xu / IoA
DTSTART:20251126T131500Z
DTEND:20251126T134000Z
UID:TALK241258@talks.cam.ac.uk
CONTACT:Xander Byrne
DESCRIPTION:The thermal Sunyaev-Zel’dovich (tSZ) power spectrum serves a
 s a critical probe of large-scale structure\, providing sensitive constrai
 nts on the amplitude of matter fluctuations\, σ_8​\, and the matter den
 sity\, Ω_m​. However\, standard statistical analyses of this observable
  conventionally rely on a Gaussian likelihood approximation\, an assumptio
 n that is physically challenged at large angular scales due to the Poisson
  nature of cluster number counts. In this talk\, I will present a framewor
 k for extracting cosmological information from the tSZ power spectrum usin
 g Simulation-Based Inference (SBI) using Neural Likelihood Estimation (NLE
 ) trained on halo-based forward models. We demonstrate that the standard G
 aussian likelihood approximation yields unbiased constraints on the derive
 d cosmological parameters\, even in the presence of significant skewness i
 n the power spectrum distribution at low multipoles. Finally\, I will very
  briefly discuss the extensibility of our forward-modelling pipeline to al
 ternative summary statistics\, such as Cluster Number Counts (CNC) and the
  Wavelet Scattering Transform (WST)\, to better exploit the full informati
 on content of Compton-y maps.
LOCATION:Hoyle Lecture theatre + Zoom 
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