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Main Authors: Takeuchi, Tsutomu T., Kuriki, Satoshi, Yano, Keisuke
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.23872
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author Takeuchi, Tsutomu T.
Kuriki, Satoshi
Yano, Keisuke
author_facet Takeuchi, Tsutomu T.
Kuriki, Satoshi
Yano, Keisuke
contents Galaxy surveys provide finite catalogs of objects observed within bounded volumes, yet clustering statistics are often interpreted using theoretical frameworks developed for infinite point processes. In this work, we formulate key statistical quantities directly for finite point processes and examine the structural consequences of finite-number and finite-window constraints. We show that several well-known features of galaxy survey analysis arise naturally from finiteness alone. In particular, non-vanishing higher-order connected correlations can occur even in statistically independent samples when the total number of points is fixed, and the integral constraint in two-point statistics appears as an exact identity implied by the finite-number condition rather than as an estimator artifact. We further demonstrate that counts-in-cells and point-centered environmental measures correspond to distinct statistical ensembles. Using Palm conditioning, we derive an exact relation between random-cell and point-centered statistics, showing that the latter probe a tilted version of the underlying distribution. These results provide a probabilistic framework for separating structural effects imposed by finite sampling from correlations reflecting genuine astrophysical processes. The formulation presented here remains valid for realistic survey geometries and finite data sets and clarifies the interpretation of commonly used clustering statistics in galaxy surveys.
format Preprint
id arxiv_https___arxiv_org_abs_2603_23872
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Rigorous Formulation of Finite-Sample and Finite-Window Effects in Galaxy Clustering
Takeuchi, Tsutomu T.
Kuriki, Satoshi
Yano, Keisuke
Astrophysics of Galaxies
Statistics Theory
Galaxy surveys provide finite catalogs of objects observed within bounded volumes, yet clustering statistics are often interpreted using theoretical frameworks developed for infinite point processes. In this work, we formulate key statistical quantities directly for finite point processes and examine the structural consequences of finite-number and finite-window constraints. We show that several well-known features of galaxy survey analysis arise naturally from finiteness alone. In particular, non-vanishing higher-order connected correlations can occur even in statistically independent samples when the total number of points is fixed, and the integral constraint in two-point statistics appears as an exact identity implied by the finite-number condition rather than as an estimator artifact. We further demonstrate that counts-in-cells and point-centered environmental measures correspond to distinct statistical ensembles. Using Palm conditioning, we derive an exact relation between random-cell and point-centered statistics, showing that the latter probe a tilted version of the underlying distribution. These results provide a probabilistic framework for separating structural effects imposed by finite sampling from correlations reflecting genuine astrophysical processes. The formulation presented here remains valid for realistic survey geometries and finite data sets and clarifies the interpretation of commonly used clustering statistics in galaxy surveys.
title Rigorous Formulation of Finite-Sample and Finite-Window Effects in Galaxy Clustering
topic Astrophysics of Galaxies
Statistics Theory
url https://arxiv.org/abs/2603.23872