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arXiv · 2606.18744

Exploring Primordial Non-Gaussianity Measurements in the CSST Spectroscopic Survey

Jiangnan Duan·Yan Gong·Qi Xiong·Xuelei Chen·Qi Guo·Ming Li·Yun Liu·Wenxiang Pei
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Abstract

Primordial non-Gaussianity (PNG) is a fundamental probe of the physics of the early Universe and inflation. Here we present a comprehensive study of the constraints on the local-type PNG parameter, $f_{\rm NL}$, for the spectroscopic galaxy survey of the upcoming Chinese Space-station Survey Telescope (CSST). Utilizing the high-resolution Jiutian N-body simulation suite, we construct realistic mock catalogs for emission line galaxies (ELGs) at three representative redshifts $z=0.3$, 0.6, and 0.9. The expected CSST observational characteristics are also considered, including redshift uncertainties and selection functions based on signal-to-noise ratios of emission lines. We develop a robust analysis framework for the redshift-space galaxy power spectrum and bispectrum that accounts for redshift-space distortions, scale-dependent bias, and nonlinear effects. Through a joint Markov Chain Monte Carlo (MCMC) analysis, we find that the power spectrum alone provides competitive constraints, while the inclusion of the bispectrum, specifically targeting the squeezed-limit configurations, improves the $f_{\rm NL}$ constraint precision by approximately 5%-6%. Our joint analysis yields a constraint result of $f_{\rm NL}=-20\pm52$ for the mock data in the 1~($h^{-1}$Gpc)$^3$ comoving volume at the three redshifts, and the constraint accuracy is expected to be improved by several times or even one order of magnitude for the CSST full spectroscopic survey. This work demonstrates the potential of the Stage~IV surveys like CSST to probe inflationary physics, and highlights the importance of higher-order statistics in extracting information from large-scale structure surveys.

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Jiangnan Duan, Yan Gong, Qi Xiong, Xuelei Chen, Qi Guo, Ming Li, Yun Liu, Wenxiang Pei. 2026-06-17. Exploring Primordial Non-Gaussianity Measurements in the CSST Spectroscopic Survey. https://arxiv.org/abs/2606.18744

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