The Impact of Cosmic Variance and Satellites on JWST Clustering Measurements at Redshift around 6

TL;DR

This paper introduces a framework using JWST/NIRCam data and simulations to accurately measure clustering and infer dark matter halo masses at redshift around 6, highlighting the importance of cosmic variance in error estimation.

Contribution

The study develops a Bayesian inference framework with realistic mock catalogs to incorporate cosmic variance, improving the accuracy of high-redshift clustering measurements.

Findings

Poisson errors underestimate true uncertainties by a factor of ~3.

Full covariance matrices reveal larger errors than Poisson estimates.

Inferred halo masses are more robust when using full covariance rather than Poisson errors.

Abstract

We present a framework for inferring the dark matter halo masses of quasars and [O III]-emitting galaxies from JWST/NIRCam Wide Field Slitless Spectroscopy (WFSS) clustering measurements at z approximately 6. Using the FLAMINGO-10k N-body simulation, we construct mock realizations of quasar and galaxy catalogs that incorporate realistic selection functions, spatial coverage, and sensitivity limits matched to the ASPIRE survey. These mocks enable accurate measurements of the quasar-galaxy cross-correlation and galaxy auto-correlation functions, with covariance matrices derived from 1000 realizations that capture both cosmic variance and bin-to-bin correlations. We employ Bayesian inference to fit the correlation functions and infer the minimum halo masses for quasars and galaxies. Our results demonstrate that Poisson pair-count uncertainties, commonly adopted in high-redshift clustering studies, significantly underestimate the true measurement errors. The dominant missing component is cosmic variance: even the diagonal of the full covariance matrix exceeds the Poisson expectation, with off-diagonal bin-to-bin correlations contributing a smaller additional correction. In particular, 1) the commonly used Poisson error on the correlation functions underestimates the true uncertainty by a factor of approximately 3; 2) the uncertainties on the inferred minimum halo masses are underestimated by a factor of approximately 1.5-3 when adopting Poisson errors instead of the full covariance matrix; 3) the inferred QSO halo mass is robust to whether central and satellite [O III]-emitters share a common mass threshold. Our framework provides a more complete error budget for JWST/WFSS clustering analyses, enabling robust constraints on the host halo masses and duty cycles of high-redshift quasars and emission-line galaxies.