To improve the performance of full-shape analyses of large-scale structure, we consider using a halo occupation distribution (HOD)-informed prior for the effective field theory (EFT) nuisance parameters. We generate 320 000 mock galaxy catalogs using 10 000 sets of HOD parameters across 32 simulation boxes with different cosmologies. We measure and fit the redshift-space power spectra using a fast emulator of the EFT model, and the resulting best-fit EFT parameter distributions are used to create the prior. This prior effectively constrains the EFT nuisance parameter space, limiting it to the space of HOD-mocks that can be well fit by a EFT model. We have tested the stability of the prior under different configurations, including the effect of varying the HOD sample distribution and the inclusion of the hexadecapole moment. We find that our HOD-informed prior and the cosmological parameter constraints derived using it are robust. While cosmological fits using the standard EFT prior suffer from prior effects, sometimes failing to recover the true cosmology within Bayesian credible intervals, the HOD-informed prior mitigates these issues and significantly improves cosmological parameter recovery for $Λ$CDM and beyond. This work lays the foundation for better full-shape large-scale structure analyses in current and upcoming galaxy surveys, making it a valuable tool for addressing key questions in cosmology.
Efficient evaluation of the dark-matter two-loop power spectrum in the EFT of LSS
Institute for Theoretical Physics, ETH Zurich（苏黎世联邦理工学院理论物理研究所）；Theoretical Physics Department, CERN（欧洲核子研究中心理论物理部）；Stanford Institute for Theoretical Physics, Physics Department, Stanford University（斯坦福大学理论物理研究所、物理系）
Halo Occupation Distribution estimation performance for LSST data
Instituto de Astronomía y Física del Espacio, CONICET-UBA（空间物理与天文学研究所，CONICET-UBA）；Instituto de Astronomía Teórica y Experimental - Observatorio Astronómico de Córdoba (IATE, UNC–CONICET)（理论与实验天文学研究所 - 科尔多瓦天文台 (IATE, UNC–CONICET)）；Observatorio Astronómico de Córdoba, Universidad Nacional de Córdoba（科尔多瓦天文台，科尔多瓦国立大学）；Facultad de Matemática, Astronomía y Física, Universidad Nacional de Córdoba (FaMAF–UNC)（数学、天文学与物理学院，科尔多瓦国立大学 (FaMAF–UNC)）；Instituto de Astronomia, Universidad Nacional Autonoma de Mexico（天文学研究所，墨西哥国立自治大学）；Center for Theoretical Physics, Polish Academy of Sciences（波兰科学院理论物理中心）；Universidad Andres Bello, Facultad de Ciencias Exactas, Departamento de Fisica y Astronomia, Instituto de Astrofisica（安德烈斯贝略大学，理学院，物理与天文学系，天体物理研究所）
Multi-tracers, multi-surveys: a joint Fisher analysis of DESI+PFS
Center for Data-Driven Discovery, Kavli IPMU (WPI), UTIAS, The University of Tokyo（东京大学 数据驱动发现中心，Kavli IPMU (WPI)，UTIAS）；Institute For Interdisciplinary Research in Science and Education, ICISE（科学与教育跨学科研究所，ICISE）
Simulation-Based Priors for HI Bias from Halo Occupation Physics
McGill University（麦吉尔大学）；Ciela—Montreal Institute for Astrophysical Data Analysis and Machine Learning（Ciela—蒙特利尔天体物理数据分析与机器学习研究所）；Arizona State University（亚利桑那州立大学）
Reanalyzing DESI DR1: 5. Cosmological Constraints with Simulation-Based Priors
Université de Genève（日内瓦大学）；Massachusetts Institute of Technology（麻省理工学院）；The NSF AI Institute for Artificial Intelligence and Fundamental Interactions（美国国家科学基金会人工智能基础相互作用研究所）；Leinweber Institute for Theoretical Physics at Stanford（斯坦福莱因韦伯理论物理研究所）；Kavli Institute for Particle Astrophysics and Cosmology（卡弗里粒子天体物理学与宇宙学研究所）
