Anisotropic redshift distributions in photometric galaxy clustering and their cosmological impact
Abstract
Photometric galaxy clustering is a major probe of large-scale structure whose interpretation relies on accurate characterization of the galaxy redshift distribution, n(z). Standard analyses assume the n(z) of a selected lens sample to be isotropic, whereas observational systematics can imprint spatial variations. We quantify how this anisotropy biases angular galaxy clustering, internal consistency, and cosmological inference. We develop an analytical formalism for clustering under spatially varying n(z) and forward-model realistic observational systematics, galaxy selection, and tomographic binning. For a fiducial magnitude-limited sample, modeling w(θ) with a single global n̅(z) underestimates the clustering signal by up to ∼10% at small scales in the highest-redshift bin, decreasing towards lower redshift. In a 2×2pt analysis, cosmological parameter shifts remain below 1σ for KiDS-like and DES-like setups. For an LSST-like setup retaining KiDS-like selection and observing-condition variation, σ8 is biased low by 1.7σ and Ωm high by 1.4σ, while the high-redshift galaxy bias shifts by up to ∼4σ. The anisotropy also affects whether the probes are consistent enough to combine: a calibrated posterior-predictive internal-consistency test finds the contaminated angular clustering improbable given the joint cosmic-shear and galaxy--galaxy-lensing constraints (median calibrated p̃≈8×10−4 under LSST-like noise). Anisotropic redshift distributions are therefore a potentially significant systematic for future photometric clustering analyses. Our forward model can be used to mitigate it given a realistic selection function and galaxy population model.
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BibTeX
@misc{zhang2026anisotropic,
title = {{Anisotropic redshift distributions in photometric galaxy clustering and their cosmological impact}},
author = {Zekang Zhang and Yunhe Wang and Daniel Gruen and Hui Kong and Luca Tortorelli and Silvan Fischbacher and Ziang Yan},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.15542},
eprint = {2609.15542},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.15542},
}
RIS
TY - UNPB
TI - Anisotropic redshift distributions in photometric galaxy clustering and their cosmological impact
AU - Zekang Zhang
AU - Yunhe Wang
AU - Daniel Gruen
AU - Hui Kong
AU - Luca Tortorelli
AU - Silvan Fischbacher
AU - Ziang Yan
PY - 2026
DA - 2026/09/14
PB - arXiv
DO - 10.48550/arxiv.2609.15542
UR - https://arxiv.org/abs/2609.15542
AB - Photometric galaxy clustering is a major probe of large-scale structure whose interpretation relies on accurate characterization of the galaxy redshift distribution, n(z). Standard analyses assume the n(z) of a selected lens sample to be isotropic, whereas observational systematics can imprint spatial variations. We quantify how this anisotropy biases angular galaxy clustering, internal consistency, and cosmological inference. We develop an analytical formalism for clustering under spatially varying n(z) and forward-model realistic observational systematics, galaxy selection, and tomographic binning. For a fiducial magnitude-limited sample, modeling w(θ) with a single global n̅(z) underestimates the clustering signal by up to ∼10% at small scales in the highest-redshift bin, decreasing towards lower redshift. In a 2×2pt analysis, cosmological parameter shifts remain below 1σ for KiDS-like and DES-like setups. For an LSST-like setup retaining KiDS-like selection and observing-condition variation, σ_8 is biased low by 1.7σ and Ω_m high by 1.4σ, while the high-redshift galaxy bias shifts by up to ∼4σ. The anisotropy also affects whether the probes are consistent enough to combine: a calibrated posterior-predictive internal-consistency test finds the contaminated angular clustering improbable given the joint cosmic-shear and galaxy--galaxy-lensing constraints (median calibrated p̃≈8×10^−4 under LSST-like noise). Anisotropic redshift distributions are therefore a potentially significant systematic for future photometric clustering analyses. Our forward model can be used to mitigate it given a realistic selection function and galaxy population model.
ER -