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A minimal solution using two affine correspondences is presented to estimate the common focal length and the fundamental matrix between two semi-calibrated cameras - known intrinsic parameters except a common focal length. To the best of…

Computer Vision and Pattern Recognition · Computer Science 2017-06-07 Daniel Barath , Tekla Toth , Levente Hajder

The decomposition of the cosmic shear field into E- and B-mode is an important diagnostic in weak gravitational lensing. However, commonly used techniques to perform this separation suffer from mode-mixing on very small or very large…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-13 Liping Fu , Martin Kilbinger

We investigate, in dark matter and galaxy mocks, the effects of approximating the galaxy power spectrum-bispectrum estimated covariance as a diagonal matrix, for an analysis that aligns with the specifications of recent and upcoming galaxy…

Cosmology and Nongalactic Astrophysics · Physics 2024-01-12 Sergi Novell-Masot , Héctor Gil-Marín , Licia Verde

We establish a practical method for the joint analysis of anisotropic galaxy two- and three-point correlation functions (2PCF and 3PCF) on the basis of the decomposition formalism of the 3PCF using tri-polar spherical harmonics. We perform…

Cosmology and Nongalactic Astrophysics · Physics 2021-04-16 Naonori S. Sugiyama , Shun Saito , Florian Beutler , Hee-Jong Seo

We apply two compression methods to the galaxy power spectrum monopole/quadrupole and bispectrum monopole measurements from the BOSS DR12 CMASS sample. Both methods reduce the dimension of the original data-vector to the number of…

Cosmology and Nongalactic Astrophysics · Physics 2019-01-07 Davide Gualdi , Héctor Gil-Marín , Robert L. Schuhmann , Marc Manera , Benjamin Joachimi , Ofer Lahav

Measuring the two-point correlation function of the galaxies in the Universe gives access to the underlying dark matter distribution, which is related to cosmological parameters and to the physics of the primordial Universe. The estimation…

This paper introduces the jackknife+, which is a novel method for constructing predictive confidence intervals. Whereas the jackknife outputs an interval centered at the predicted response of a test point, with the width of the interval…

Methodology · Statistics 2020-06-02 Rina Foygel Barber , Emmanuel J. Candes , Aaditya Ramdas , Ryan J. Tibshirani

A class of improved estimators is proposed for N-point correlation functions of galaxy clustering, and for discrete spatial random processes in general. In the limit of weak clustering, the variance of the unbiased estimator converges to…

Astrophysics · Physics 2007-05-23 István Szapudi , Alexander S. Szalay

Uncertainty quantification is essential for deploying machine learning models in high-stakes domains such as scientific discovery and healthcare. Conformal Prediction (CP) provides finite-sample coverage guarantees under exchangeability, an…

Machine Learning · Computer Science 2026-03-30 Siddhartha Laghuvarapu , Rohan Deb , Jimeng Sun

We consider the problem of computation of the correlation functions for the z-measures with the deformation (Jack) parameters 2 or 1/2. Such measures on partitions are originated from the representation theory of the infinite symmetric…

Mathematical Physics · Physics 2009-11-13 Eugene Strahov

Constraining cosmological parameters from measurements of the Integrated Sachs-Wolfe effect requires developing robust and accurate methods for computing statistical errors in the cross-correlation between maps. This paper presents a…

Astrophysics · Physics 2009-11-13 Anna Cabre , Pablo Fosalba , Enrique Gaztanaga , Marc Manera

Cosmological observables rely heavily on summary statistics such as two-point correlation functions. In many practical cases (e.g. the weak-lensing cosmic shear), those correlation functions are estimated from a finite, discrete sample of…

Cosmology and Nongalactic Astrophysics · Physics 2025-06-24 Pierre Fleury

We study the minimal sample size N=N(n) that suffices to estimate the covariance matrix of an n-dimensional distribution by the sample covariance matrix in the operator norm, with an arbitrary fixed accuracy. We establish the optimal bound…

Probability · Mathematics 2013-10-04 Nikhil Srivastava , Roman Vershynin

Sparse covariance matrices play crucial roles by encoding the interdependencies between variables in numerous fields such as genetics and neuroscience. Despite substantial studies on sparse covariance matrices, existing methods face several…

Methodology · Statistics 2026-03-03 Rakheon Kim , Irina Gaynanova

We propose \textbf{JAWS}, a series of wrapper methods for distribution-free uncertainty quantification tasks under covariate shift, centered on the core method \textbf{JAW}, the \textbf{JA}ckknife+ \textbf{W}eighted with data-dependent…

Machine Learning · Computer Science 2022-11-28 Drew Prinster , Anqi Liu , Suchi Saria

We present measurements of weak gravitational lensing cosmic shear two-point statistics using Dark Energy Survey Science Verification data. We demonstrate that our results are robust to the choice of shear measurement pipeline, either ngmix…

Cosmology and Nongalactic Astrophysics · Physics 2016-07-28 M. R. Becker , M. A. Troxel , N. MacCrann , E. Krause , T. F. Eifler , O. Friedrich , A. Nicola , A. Refregier , A. Amara , D. Bacon , G. M. Bernstein , C. Bonnett , S. L. Bridle , M. T. Busha , C. Chang , S. Dodelson , B. Erickson , A. E. Evrard , J. Frieman , E. Gaztanaga , D. Gruen , W. Hartley , B. Jain , M. Jarvis , T. Kacprzak , D. Kirk , A. Kravtsov , B. Leistedt , E. S. Rykoff , C. Sabiu , C. Sanchez , H. Seo , E. Sheldon , R. H. Wechsler , J. Zuntz , T. Abbott , F. B. Abdalla , S. Allam , R. Armstrong , M. Banerji , A. H. Bauer , A. Benoit-Levy , E. Bertin , D. Brooks , E. Buckley-Geer , D. L. Burke , D. Capozzi , A. Carnero Rosell , M. Carrasco Kind , J. Carretero , F. J. Castander , M. Crocce , C. E. Cunha , C. B. D'Andrea , L. N. da Costa , D. L. DePoy , S. Desai , H. T. Diehl , J. P. Dietrich , P. Doel , A. Fausti Neto , E. Fernandez , D. A. Finley , B. Flaugher , P. Fosalba , D. W. Gerdes , R. A. Gruendl , G. Gutierrez , K. Honscheid , D. J. James , K. Kuehn , N. Kuropatkin , O. Lahav , T. S. Li , M. Lima , M. A. G. Maia , M. March , P. Martini , P. Melchior , C. J. Miller , R. Miquel , J. J. Mohr , R. C. Nichol , B. Nord , R. Ogando , A. A. Plazas , K. Reil , A. K. Romer , A. Roodman , M. Sako , E. Sanchez , V. Scarpine , M. Schubnell , I. Sevilla-Noarbe , R. C. Smith , M. Soares-Santos , F. Sobreira , E. Suchyta , M. E. C. Swanson , G. Tarle , J. Thaler , D. Thomas , V. Vikram , A. R. Walker , The DES Collaboration

We introduce CO2, an efficient algorithm to produce convexly-weighted coresets with respect to generic smooth divergences. By employing a functional Taylor expansion, we show a local equivalence between sufficiently regular losses and their…

Machine Learning · Statistics 2025-05-21 Alex Kokot , Alex Luedtke

The two point correlation function (2PCF) is a powerful statistical tool to measure galaxy clustering. Although 2PCF has also been used to study the clustering of stars on parsec and sub-parsec scales, its physical implication is not clear…

Astrophysics of Galaxies · Physics 2024-02-02 Yike Zhang , Wenting Wang , Jiaxin Han , Xiaohu Yang , Vicente Rodriguez-Gomez , Carles G. Palau , Zhenlin Tan

We introduce an optimized data vector of cosmic shear measures (N). This data vector has high information content, is not sensitive against B-mode contamination and only shows small correlation between data points of different angular…

Astrophysics · Physics 2009-11-13 T. Eifler , M. Kilbinger , P. Schneider

Stage-IV galaxy surveys will measure correlations at small cosmological scales with high signal-to-noise ratio. One of the main challenges of extracting information from small scales is devising accurate models, as well as characterizing…

Cosmology and Nongalactic Astrophysics · Physics 2025-05-20 Abdias Aires , Nickolas Kokron , Rogerio Rosenfeld , Felipe Andrade-Oliveira , Vivian Miranda
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