Fixing the covariance at an incorrect cosmology in cluster count analyses leaves Ω_c, σ_8, and w estimates unbiased but distorts their uncertainties, driven by S_8 amplitude effects; a single update at the recovered best-fit cosmology restores correct normalization for LSST-like surveys.
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6 Pith papers cite this work, alongside 6 external citations. Polarity classification is still indexing.
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A minimal bias model yields unbiased LambdaCDM constraints up to k_max=0.7 h/Mpc but biases neutrino mass estimates, while higher-order bias mimics baryonic suppression in LSST 3x2pt analyses using the new MGL pipeline.
Simulated likelihood analysis shows Limber approximation, neglected RSD, and approximate nonlinear power spectra each induce cosmological biases of ~1 sigma or more (exceeding 2 sigma for Rubin) in Roman and Rubin 3x2pt studies.
Smokescreen is a Python package that blinds cosmological data vectors using Firecrown likelihoods on SACC files while encrypting the true data to avoid premature unblinding.
cloelike is a new open Python package implementing composable Gaussian likelihoods for WL, GCph, GGL, full-shape spectra, and BAO in joint probe combinations for Euclid analyses.
cloelib is a modular JAX-based Python library for cosmological observables intended as reference infrastructure for Euclid's first data release.
citing papers explorer
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Cosmology-dependent covariance in galaxy cluster number counts: consequences for parameter inference
Fixing the covariance at an incorrect cosmology in cluster count analyses leaves Ω_c, σ_8, and w estimates unbiased but distorts their uncertainties, driven by S_8 amplitude effects; a single update at the recovered best-fit cosmology restores correct normalization for LSST-like surveys.
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Balancing bias, baryons, and scale cuts in LSST 3x2pt analysis
A minimal bias model yields unbiased LambdaCDM constraints up to k_max=0.7 h/Mpc but biases neutrino mass estimates, while higher-order bias mimics baryonic suppression in LSST 3x2pt analyses using the new MGL pipeline.
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Accurate modeling for 3$\times$2pt analyses in Roman and Rubin: a study of model approximations
Simulated likelihood analysis shows Limber approximation, neglected RSD, and approximate nonlinear power spectra each induce cosmological biases of ~1 sigma or more (exceeding 2 sigma for Rubin) in Roman and Rubin 3x2pt studies.
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Smokescreen: A Python package for data vector blinding and encryption in cosmological analyses
Smokescreen is a Python package that blinds cosmological data vectors using Firecrown likelihoods on SACC files while encrypting the true data to avoid premature unblinding.
-
cloelike: A Python Library for Cosmological Likelihood Inference in the Euclid Era
cloelike is a new open Python package implementing composable Gaussian likelihoods for WL, GCph, GGL, full-shape spectra, and BAO in joint probe combinations for Euclid analyses.
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cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era
cloelib is a modular JAX-based Python library for cosmological observables intended as reference infrastructure for Euclid's first data release.