Rescaling merger trees with a halo-profile correction enables cheap generation of galaxy summary statistics across cosmologies using semi-analytic models, matching dedicated simulation accuracy with far fewer base runs.
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6 Pith papers cite this work. Polarity classification is still indexing.
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SHAMe-SF modeling of small-scale DESI ELG clustering delivers 6% precision on σ8 and Ωm h², matching full DR1 results with 1% volume.
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.
Symbolic emulators approximate key Lambda CDM functions to 0.001-0.05% accuracy across relevant redshifts and Omega_m values, enabling faster 3x2pt inference with consistent results.
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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Learning the Universe with cosmological rescaling of merger trees and semi-analytic galaxy formation models
Rescaling merger trees with a halo-profile correction enables cheap generation of galaxy summary statistics across cosmologies using semi-analytic models, matching dedicated simulation accuracy with far fewer base runs.
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Cosmological constraints from the small scale clustering of Emission Line Galaxies
SHAMe-SF modeling of small-scale DESI ELG clustering delivers 6% precision on σ8 and Ωm h², matching full DR1 results with 1% volume.
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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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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.