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We introduce a new method for estimating the covariance matrix for the galaxy correlation function in surveys of large-scale structure. Our method combines simple theoretical results with a realistic characterization of the survey to…

Cosmology and Nongalactic Astrophysics · Physics 2016-08-31 Ross O'Connell , Daniel Eisenstein , Mariana Vargas , Shirley Ho , Nikhil Padmanabhan

We present a simple analytic approximation for the covariance between pre-reconstruction galaxy power spectrum measurements and post-reconstruction two-point correlation functions. This cross-covariance is essential for joint analyses that…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-29 M. Maus , A. Baleato Lizancos , M. White , A. de Mattia , S. Chen

We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. We aim to produce mock…

We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of large-scale structure (LSS) catalogs from these samples, which include…

Cosmology and Nongalactic Astrophysics · Physics 2025-07-15 DESI Collaboration , A. G. Adame , J. Aguilar , S. Ahlen , S. Alam , D. M. Alexander , M. Alvarez , O. Alves , A. Anand , U. Andrade , E. Armengaud , S. Avila , A. Aviles , H. Awan , S. Bailey , C. Baltay , A. Bault , J. Behera , S. BenZvi , F. Beutler , D. Bianchi , C. Blake , R. Blum , S. Brieden , A. Brodzeller , D. Brooks , Z. Brown , E. Buckley-Geer , E. Burtin , R. Calderon , R. Canning , A. Carnero Rosell , R. Cereskaite , J. L. Cervantes-Cota , S. Chabanier , E. Chaussidon , J. Chaves-Montero , S. Chen , X. Chen , T. Claybaugh , S. Cole , A. Cuceu , T. M. Davis , K. Dawson , A. de la Macorra , A. de Mattia , N. Deiosso , R. Demina , A. Dey , B. Dey , Z. Ding , P. Doel , J. Edelstein , S. Eftekharzadeh , D. J. Eisenstein , A. Elliott , P. Fagrelius , K. Fanning , S. Ferraro , J. Ereza , N. Findlay , B. Flaugher , A. Font-Ribera , D. Forero-Sánchez , J. E. Forero-Romero , C. S. Frenk , C. Garcia-Quintero , E. Gaztañaga , H. Gil-Marín , S. Gontcho A Gontcho , A. X. Gonzalez-Morales , V. Gonzalez-Perez , C. Gordon , D. Green , D. Gruen , R. Gsponer , G. Gutierrez , J. Guy , B. Hadzhiyska , C. Hahn , M. M. S Hanif , H. K. Herrera-Alcantar , K. Honscheid , J. Hou , C. Howlett , D. Huterer , V. Iršič , M. Ishak , S. Juneau , N. G. Karaçaylı , R. Kehoe , S. Kent , D. Kirkby , F. -S. Kitaura , H. Kong , A. Kremin , A. Krolewski , Y. Lai , T. -W. Lan , M. Landriau , D. Lang , J. Lasker , J. M. Le Goff , L. Le Guillou , A. Leauthaud , M. E. Levi , T. S. Li , K. Lodha , C. Magneville , M. Manera , D. Margala , P. Martini , M. Maus , P. McDonald , L. Medina-Varela , A. Meisner , J. Mena-Fernández , R. Miquel , J. Moon , S. Moore , J. Moustakas , N. Mudur , E. Mueller , A. Muñoz-Gutiérrez , A. D. Myers , S. Nadathur , L. Napolitano , R. Neveux , J. A. Newman , N. M. Nguyen , J. Nie , G. Niz , H. E. Noriega , N. Padmanabhan , E. Paillas , N. Palanque-Delabrouille , J. Pan , S. Penmetsa , W. J. Percival , M. M. Pieri , M. Pinon , C. Poppett , A. Porredon , F. Prada , A. Pérez-Fernández , I. Pérez-Ràfols , D. Rabinowitz , A. Raichoor , C. Ramírez-Pérez , S. Ramirez-Solano , M. Rashkovetskyi , C. Ravoux , M. Rezaie , J. Rich , A. Rocher , C. Rockosi , N. A. Roe , A. Rosado-Marin , A. J. Ross , G. Rossi , R. Ruggeri , V. Ruhlmann-Kleider , L. Samushia , E. Sanchez , C. Saulder , E. F. Schlafly , D. Schlegel , D. Scholte , M. Schubnell , H. Seo , R. Sharples , J. Silber , A. Slosar , A. Smith , D. Sprayberry , T. Tan , G. Tarlé , S. Trusov , R. Vaisakh , D. Valcin , F. Valdes , M. Vargas-Magaña , L. Verde , M. Walther , B. Wang , M. S. Wang , B. A. Weaver , N. Weaverdyck , R. H. Wechsler , D. H. Weinberg , M. White , M. J. Wilson , J. Yu , Y. Yu , S. Yuan , C. Yèche , E. A. Zaborowski , P. Zarrouk , H. Zhang , C. Zhao , R. Zhao , R. Zhou , H. Zou

The current generation of large galaxy surveys will test the cosmological model by combining multiple types of observational probes. Realising the statistical promise of these new datasets requires rigorous attention to all aspects of…

We study the covariance properties of real space correlation function estimators -- primarily galaxy-shear correlations, or galaxy-galaxy lensing -- using SDSS data for both shear catalogs and lenses (specifically the BOSS LOWZ sample).…

Cosmology and Nongalactic Astrophysics · Physics 2017-08-30 Sukhdeep Singh , Rachel Mandelbaum , Uroš Seljak , Anže Slosar , Jose Vazquez Gonzalez

This paper is the first in a set that analyses the covariance matrices of clustering statistics obtained from several approximate methods for gravitational structure formation. We focus here on the covariance matrices of anisotropic…

This note is concerned with accurate and computationally efficient approximations of moments of Gaussian random variables passed through sigmoid or softmax mappings. These approximations are semi-analytical (i.e. they involve the numerical…

Machine Learning · Statistics 2017-03-07 Jean Daunizeau

We use the full-sky ray-tracing weak lensing simulations to generate 2268 mock catalogues for the Subaru Hyper Suprime-Cam (HSC) survey first-year shear catalogue. Our mock catalogues take into account various effects as in the real data:…

Cosmology and Nongalactic Astrophysics · Physics 2019-03-27 Masato Shirasaki , Takashi Hamana , Masahiro Takada , Ryuichi Takahashi , Hironao Miyatake

We present configuration-space estimators for the auto- and cross-covariance of two- and three-point correlation functions (2PCF and 3PCF) in general survey geometries. These are derived in the Gaussian limit (setting higher-order…

Cosmology and Nongalactic Astrophysics · Physics 2019-10-23 Oliver H. E. Philcox , Daniel J. Eisenstein

Semi-analytic models are a widely used approach to simulate galaxy properties within a cosmological framework, relying on simplified yet physically motivated prescriptions. They have also proven to be an efficient alternative for generating…

We derive analytic covariance matrices for the $N$-Point Correlation Functions (NPCFs) of galaxies in the Gaussian limit. Our results are given for arbitrary $N$ and projected onto the isotropic basis functions of Cahn & Slepian (2020),…

Cosmology and Nongalactic Astrophysics · Physics 2022-08-31 Jiamin Hou , Robert N. Cahn , Oliver H. E. Philcox , Zachary Slepian

Weak lensing has become a powerful tool for probing the matter distribution in the Universe and constraining cosmological parameters. This paper aims to explore the fast mock generation pipeline to obtain the covariance matrix of the…

Cosmology and Nongalactic Astrophysics · Physics 2025-06-17 Yiming Hu , Yu Yu

The Emission Line Galaxy survey made by the Dark Energy Spectroscopic Instrument (DESI) survey will be created from five passes of the instrument on the sky. On each pass, the constrained mobility of the ends of the fibres in the DESI focal…

Cosmology and Nongalactic Astrophysics · Physics 2018-10-15 Davide Bianchi , Angela Burden , Will J. Percival , David Brooks , Robert N. Cahn , Jaime E. Forero-Romero , Michael Levi , Ashley J. Ross , Gregory Tarle

With current and upcoming experiments such as WFIRST, Euclid and LSST, we can observe up to billions of galaxies. While such surveys cannot obtain spectra for all observed galaxies, they produce galaxy magnitudes in color filters. This data…

Astrophysics of Galaxies · Physics 2022-10-19 Melanie Simet , Nima Chartab , Yu Lu , Bahram Mobasher

Together with larger spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI), the precision of large scale structure studies and thus the constraints on the cosmological parameters are rapidly improving. Therefore, one…

We study the properties of galaxy cluster 2-point correlation function covariance matrices estimated using the linear-construction (LC) method, which is computationally up to 20 times faster than the standard sample-covariance method. Our…

Cosmology and Nongalactic Astrophysics · Physics 2026-03-12 V. Lindholm , E. Sihvola , J. Valiviita , A. Fumagalli , B. Altieri , S. Andreon , N. Auricchio , C. Baccigalupi , M. Baldi , S. Bardelli , P. Battaglia , A. Biviano , E. Branchini , M. Brescia , S. Camera , V. Capobianco , C. Carbone , V. F. Cardone , J. Carretero , S. Casas , M. Castellano , G. Castignani , S. Cavuoti , K. C. Chambers , A. Cimatti , C. Colodro-Conde , G. Congedo , L. Conversi , Y. Copin , F. Courbin , H. M. Courtois , A. Da Silva , H. Degaudenzi , G. De Lucia , H. Dole , F. Dubath , X. Dupac , S. Dusini , S. Escoffier , M. Farina , R. Farinelli , S. Ferriol , F. Finelli , P. Fosalba , S. Fotopoulou , M. Frailis , E. Franceschi , M. Fumana , S. Galeotta , K. George , B. Gillis , C. Giocoli , J. Gracia-Carpio , A. Grazian , F. Grupp , S. V. H. Haugan , W. Holmes , F. Hormuth , A. Hornstrup , K. Jahnke , M. Jhabvala , S. Kermiche , A. Kiessling , B. Kubik , M. Kunz , H. Kurki-Suonio , A. M. C. Le Brun , S. Ligori , P. B. Lilje , I. Lloro , G. Mainetti , E. Maiorano , O. Mansutti , S. Marcin , O. Marggraf , M. Martinelli , N. Martinet , F. Marulli , R. J. Massey , E. Medinaceli , S. Mei , M. Melchior , M. Meneghetti , E. Merlin , G. Meylan , A. Mora , M. Moresco , L. Moscardini , R. Nakajima , C. Neissner , S. -M. Niemi , C. Padilla , S. Paltani , F. Pasian , K. Pedersen , V. Pettorino , S. Pires , G. Polenta , M. Poncet , L. A. Popa , F. Raison , A. Renzi , J. Rhodes , G. Riccio , E. Romelli , M. Roncarelli , C. Rosset , R. Saglia , Z. Sakr , A. G. Sánchez , D. Sapone , P. Schneider , T. Schrabback , A. Secroun , G. Seidel , P. Simon , C. Sirignano , G. Sirri , L. Stanco , P. Tallada-Crespí , A. N. Taylor , I. Tereno , S. Toft , R. Toledo-Moreo , F. Torradeflot , I. Tutusaus , T. Vassallo , G. Verdoes Kleijn , Y. Wang , J. Weller , G. Zamorani , E. Zucca , T. Castro , J. Martín-Fleitas , P. Monaco , A. Pezzotta , V. Scottez , M. Sereno , M. Viel , D. Sciotti

We present a fast method of producing mock galaxy catalogues that can be used to compute covariance matrices of large-scale clustering measurements and test the methods of analysis. Our method populates a 2nd-order Lagrangian Perturbation…

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