Non-Gaussianity in the Weak Lensing Correlation Function Likelihood -- Implications for Cosmological Parameter Biases

Lin, Chien-Hao; Harnois-Déraps, Joachim; Eifler, Tim; Pospisil, Taylor; Mandelbaum, Rachel; Lee, Ann B.; Singh, Sukhdeep

doi:10.48550/arxiv.1905.03779

Cited by 9 publications

(9 citation statements)

References 67 publications

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“…This former statement is confirmed in Figure 9 for much narrower bins. While the Gaussian likelihood approximation may not be valid for other weak lensing summary statistics, a recent paper has shown it is also valid for two-point correlation functions [67].…”

Section: B Impact Of the Gaussian Likelihood Approximationmentioning

confidence: 99%

Cosmic shear: Inference from forward models

et al. 2019

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Density-estimation likelihood-free inference (DELFI) has recently been proposed as an efficient method for simulation-based cosmological parameter inference. Compared to the standard likelihood-based Markov Chain Monte Carlo (MCMC) approach, DELFI has several advantages: it is highly parallelizable, there is no need to assume a possibly incorrect functional form for the likelihood and complicated effects (e.g the mask and detector systematics) are easier to handle with forward models. In light of this, we present two DELFI pipelines to perform weak lensing parameter inference with lognormal realizations of the tomographic shear field -using the C summary statistic. The first pipeline accounts for the non-Gaussianities of the shear field, intrinsic alignments and photometric-redshift error. We validate that it is accurate enough for Stage III experiments and estimate that O(1000) simulations are needed to perform inference on Stage IV data. By comparing the second DELFI pipeline, which makes no assumption about the functional form of the likelihood, with the standard MCMC approach, which assumes a Gaussian likelihood, we test the impact of the Gaussian likelihood approximation in the MCMC analysis. We find it has a negligible impact on Stage IV parameter constraints. Our pipeline is a step towards seamlessly propagating all dataprocessing, instrumental, theoretical and astrophysical systematics through to the final parameter constraints. * peterllewelyntaylor@gmail.com 1 http://euclid-ec.org 2 https://www.nasa.gov/wfirst 3 https://www.lsst.org arXiv:1904.05364v2 [astro-ph.CO]

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Section: B Impact Of the Gaussian Likelihood Approximationmentioning

confidence: 99%

Cosmic shear: Inference from forward models

et al. 2019

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“…As discussed in Lin et al (2019), the impact of non-Gaussianity in the likelihood is estimated to be negligible in current and future cosmic shear surveys. The 3×2pt covariance matrix C is computed using the CosmoLike package (Krause & Eifler 2017), which calculates the relevant four-point functions in the halo model.…”

Section: • Baselinementioning

confidence: 99%

Dark Energy Survey Year 1 Results: Constraining Baryonic Physics in the Universe

Huang,

Eifler,

Mandelbaum

et al. 2020

Preprint

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Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3×2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modeling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude (Q 1 ) generally reflects the strength of baryon feedback. With the upper limit of Q 1 prior being bound by the Illustris feedback scenarios, we reach ∼ 20% improvement in the constraint of S 8 = σ 8 (Ω m /0.3) 0.5 = 0.788 +0.018 −0.021 compared to the original DES 3×2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 , which was excluded in previous DES analyses that did not model baryonic physics. We obtain S 8 = 0.781 +0.014 −0.015 for the combined DES Y1+Planck EE+BAO analysis with a non-informative Q 1 prior. In terms of the baryon constraints, we measure Q 1 = 1.14 +2.20 −2.80 for DES Y1 only and Q 1 = 1.42 +1.63 −1.48 for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than 2σ.

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“…7 At present the likelihood sampling method assumes the likelihood is Gaussian (although a more realistic likelihood could easily be used instead, as required). While the Gaussian likelihood approximation is valid at the level of parameter constraints for cosmic shear alone (Taylor et al 2019;Lin et al 2019), this must be explicitly checked for 3 × 2 point statistics.…”

Section: Fisher Forecastingmentioning

confidence: 99%

Euclid: Forecasts for k-cut 3×2 Point Statistics

Taylor¹,

Kitching²,

Cardone³

et al. 2021

TheOJA

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Modelling uncertainties at small scales, i.e. high k in the power spectrum P (k), due to baryonic feedback, nonlinear structure growth and the fact that galaxies are biased tracers poses a significant obstacle to fully leverage the constraining power of the Euclid wide-field survey. k-cut cosmic shear has recently been proposed as a method to optimally remove sensitivity to these scales while preserving usable information. In this paper we generalise the k-cut cosmic shear formalism to 3 × 2 point statistics and estimate the loss of information for different k-cuts in a 3 × 2 point analysis of the Euclid data. Extending the Fisher matrix analysis of Euclid Collaboration: Blanchard et al. ( 2019), we assess the degradation in constraining power for different k-cuts. We work in the idealised case and assume the galaxy bias is linear, the covariance is Gaussian, while neglecting uncertainties due to photo-z errors and baryonic feedback. We find that taking a k-cut at 2.6 h Mpc −1 yields a dark energy Figure of Merit (FOM) of 1018. This is comparable to taking a weak lensing cut at = 5000 and a galaxy clustering and galaxy-galaxy lensing cut at = 3000 in a traditional 3 × 2 point analysis. We also find that the fraction of the observed galaxies used in the photometric clustering part of the analysis is one of the main drivers of the FOM. Removing 50% (90%) of the clustering galaxies decreases the FOM by 19% (62%). Given that the FOM depends so heavily on the fraction of galaxies used in the clustering analysis, extensive efforts should be made to handle the real-world systematics present when extending the analysis beyond the luminous red galaxy (LRG) sample.

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Non-Gaussianity in the Weak Lensing Correlation Function Likelihood -- Implications for Cosmological Parameter Biases

Cited by 9 publications

References 67 publications

Cosmic shear: Inference from forward models

Cosmic shear: Inference from forward models

Dark Energy Survey Year 1 Results: Constraining Baryonic Physics in the Universe

Euclid: Forecasts for k-cut 3×2 Point Statistics

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