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Extracting non-Gaussian information from the Large-Scale Structure

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If you have a question about this talk, please contact Nathan Johnson-McDaniel .

One of the main of challenges in modern cosmology is to fully exploit datasets by extracting non-Gaussian (small scale) information. In this talk, I will present results following two different approaches. I will first present a full forward model for the neutral hydrogen counts-in-cell statistic obtained from the known matter counts-in-cell statistic together with a new non-linear bias function relating neutral hydrogen and matter. Secondly, I will show preliminary forecasts for a projected galaxy bispectrum analysis that allows to control systematics arising from non-linear redshift-space distortions.

This talk is part of the DAMTP Friday GR Seminar series.

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In person in the Max Perutz Lecture Theatre (CB2 0QH) and via Zoom, link: https://mrc-lmb-cam-ac-uk.zoom.us/j/98632322520?pwd=aDlTZy9NRGh6bHg3U0xhV1MvS3NPQT09 Zoom webinar - link above FW11, William Gates Building. Zoom link: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon

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