Information content of weak lensing power spectrum and bispectrum: including the non-Gaussian error covariance matrix
Issha Kayo (1), Masahiro Takada (2), Bhuvnesh Jain (3) ((1) Toho U.,, (2) Kavli IPMU, (3) UPenn)

TL;DR
This paper models the non-Gaussian covariance matrices of weak lensing power spectra and bispectra, including a new halo sample variance term, to assess their impact on cosmological information content.
Contribution
It introduces a formalism for covariance matrices of all triangle configurations, including the novel halo sample variance contribution, validated against simulations.
Findings
HSV dominates covariance at high multipoles > 10^3
Adding bispectrum increases information content by 20-50%
Non-Gaussian covariances significantly affect cosmological parameter estimation
Abstract
We address the amount of information in the non-Gaussian regime of weak lensing surveys by modelling all relevant covariances of the power spectra and bispectra, using 1000 ray-tracing simulation realizations for a Lambda-CDM model and an analytical halo model. We develop a formalism to describe the covariance matrices of power spectra and bispectra of all triangle configurations. In addition to the known contributions which extend up to six-point correlation functions, we propose a new contribution `the halo sample variance (HSV)' arising from the coupling of the lensing Fourier modes with large-scale mass fluctuations on scales comparable with the survey region via halo bias theory. We show that the model predictions are in good agreement with the simulation once we take the HSV into account. The HSV gives a dominant contribution to the covariance matrices at multipoles l > 10^3,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
