New Optimised Estimators for the Primordial Trispectrum
Dipak Munshi, Alan Heavens, Asantha Cooray, Joseph Smidt, Peter Coles,, Paolo Serra

TL;DR
This paper develops optimized estimators for the primordial trispectrum in cosmic microwave background data, enabling better detection of early universe non-Gaussianity despite observational complexities.
Contribution
It extends the skew spectrum approach to the trispectrum, creating nearly optimal estimators that handle realistic data complexities for improved non-Gaussianity analysis.
Findings
Constructed nearly optimal estimators for the trispectrum.
Linked higher-order statistics to inflationary potential coefficients.
Demonstrated the estimators' effectiveness with realistic data simulations.
Abstract
Cosmic microwave background studies of non-Gaussianity involving higher-order multispectra can distinguish between early universe theories that predict nearly identical power spectra. However, the recovery of higher-order multispectra is difficult from realistic data due to their complex response to inhomogeneous noise and partial sky coverage, which are often difficult to model analytically. A traditional alternative is to use one-point cumulants of various orders, which collapse the information present in a multispectrum to one number. The disadvantage of such a radical compression of the data is a loss of information as to the source of the statistical behaviour. A recent study by Munshi & Heavens (2009) has shown how to define the skew spectrum (the power spectra of a certain cubic field, related to the bispectrum) in an optimal way and how to estimate it from realistic data. The…
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