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Precision cosmology has recently triggered new attention on the topic of approximate methods for the clustering of matter on large scales, whose foundations date back to the period from late '60s to early '90s. Indeed, although the prospect…

Cosmology and Nongalactic Astrophysics · Physics 2016-10-10 Pierluigi Monaco

Bootstrap is a popular methodology for simulating input uncertainty. However, it can be computationally expensive when the number of samples is large. We propose a new approach called \textbf{Orthogonal Bootstrap} that reduces the number of…

Methodology · Statistics 2024-05-02 Kaizhao Liu , Jose Blanchet , Lexing Ying , Yiping Lu

Cosmological parameter inference from galaxy clustering relies critically on accurate estimates of the covariance and precision matrices. These are often obtained from a limited number of mock catalogs, introducing noise and bias in the…

Cosmology and Nongalactic Astrophysics · Physics 2026-04-16 Antonio Farina , Massimo Guidi , Alfonso Veropalumbo , Claudio Guida

An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-$C_\ell$ estimates of tomographic cosmic shear power spectra. Using two…

The methods for studying the epoch of cosmic reionization vary from full radiative transfer simulations to purely analytical models. While numerical approaches are computationally expensive and are not suitable for generating many mock…

Cosmology and Nongalactic Astrophysics · Physics 2016-11-15 Alexander A. Kaurov

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

Covariance matrix estimation is a fundamental statistical task in many applications, but the sample covariance matrix is sub-optimal when the sample size is comparable to or less than the number of features. Such high-dimensional settings…

Methodology · Statistics 2022-06-06 Huiqin Xin , Sihai Dave Zhao

We propose small-variance asymptotic approximations for the inference of tumor heterogeneity (TH) using next-generation sequencing data. Understanding TH is an important and open research problem in biology. The lack of appropriate…

Methodology · Statistics 2015-11-17 Yanxun Xu , Peter Mueller , Yuan Yuan , Kamalakar Gulukota , Yuan Ji

Galaxy clusters are one of the most powerful probes to study extensions of General Relativity and the Standard Cosmological Model. Upcoming surveys like the Vera Rubin Observatory's Legacy Survey of Space and Time are expected to…

Cosmology and Nongalactic Astrophysics · Physics 2024-06-19 Markus Michael Rau , Florian Kéruzoré , Nesar Ramachandra , Lindsey Bleem

We assess the performance of a perturbation theory inspired method for inferring cosmological parameters from the joint measurements of galaxy-galaxy weak lensing ($\Delta\Sigma$) and the projected galaxy clustering ($w_{\rm p}$). To do…

Cosmology and Nongalactic Astrophysics · Physics 2020-10-21 Sunao Sugiyama , Masahiro Takada , Yosuke Kobayashi , Hironao Miyatake , Masato Shirasaki , Takahiro Nishimichi , Youngsoo Park

Data analysis from upcoming large galaxy redshift surveys, such as Euclid and DESI will significantly improve constraints on cosmological parameters. To optimally extract the information from these galaxy surveys, it is important to control…

Cosmology and Nongalactic Astrophysics · Physics 2025-01-22 S. Gouyou Beauchamps , P. Baratta , S. Escoffier , W. Gillard , J. Bel , J. Bautista , C. Carbone

We consider the problem of joint estimation of structured covariance matrices. Assuming the structure is unknown, estimation is achieved using heterogeneous training sets. Namely, given groups of measurements coming from centered…

Statistics Theory · Mathematics 2016-04-20 Ilya Soloveychik , Ami Wiesel

We apply the inverse-Gaussianization method proposed in \citealt{arXiv:1607.05007} to fast produce weak lensing convergence maps and investigate the peak statistics, including the peak height counts and peak steepness counts, in these…

Cosmology and Nongalactic Astrophysics · Physics 2024-09-13 Zhao Chen , Yu Yu , Xiangkun Liu , Zuhui Fan

We present a control-variate method for reducing the variance of power spectrum covariance matrix estimates from simulations of large-scale structure. The key idea is to pair each mock simulation with a cheap Zeldovich-approximation…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-28 Boryana Hadzhiyska , Martin White

Galaxy distances and derived radial peculiar velocity catalogs constitute valuable datasets to study the dynamics of the Local Universe. However, such catalogs suffer from biases whose effects increase with the distance. Malmquist biases…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 Jenny G. Sorce

Recovering credible cosmological parameter constraints in a weak lensing shear analysis requires an accurate model that can be used to marginalize over nuisance parameters describing potential sources of systematic uncertainty, such as the…

Cosmology and Nongalactic Astrophysics · Physics 2023-04-20 Tianqing Zhang , Markus Michael Rau , Rachel Mandelbaum , Xiangchong Li , Ben Moews

We present a novel method to significantly speed up cosmological parameter sampling. The method relies on constructing an interpolation of the CMB-log-likelihood based on sparse grids, which is used as a shortcut for the…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-18 Mona Frommert , Dirk Pflueger , Thomas Riller , Martin Reinecke , Hans-Joachim Bungartz , Torsten Ensslin

We present the calibration of the Dark Energy Survey Year 3 (DES Y3) weak lensing source galaxy redshift distributions $n(z)$ from clustering measurements. In particular, we cross-correlate the weak lensing (WL) source galaxies sample with…

A resampling scheme provides a way to switch low-weight particles for sequential Monte Carlo with higher-weight particles representing the objective distribution. The less the variance of the weight distribution is, the more concentrated…

Computation · Statistics 2023-09-19 Xiongming Dai , Gerald Baumgartner

We present a clustering analysis of the BOSS DR12 CMASS galaxy sample, combining measurements of the galaxy two-point correlation function and density-split clustering down to a scale of $1\,h^{-1}{\rm Mpc}$. Our theoretical framework is…

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