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Lossy compression has become an important technique to reduce data size in many domains. This type of compression is especially valuable for large-scale scientific data, whose size ranges up to several petabytes. Although Autoencoder-based…

Machine Learning · Computer Science 2024-07-03 Hieu Le , Jian Tao

Analyses of the cosmic 21-cm signal are hampered by astrophysical foregrounds that are far stronger than the signal itself. These foregrounds, typically confined to a wedge-shaped region in Fourier space, often necessitate the removal of a…

Cosmology and Nongalactic Astrophysics · Physics 2024-08-02 Nashwan Sabti , Ram Reddy , Julian B. Muñoz , Siddharth Mishra-Sharma , Taewook Youn

Context. Weak lensing and clustering statistics beyond two-point functions can capture non-Gaussian information about the matter density field, thereby improving the constraints on cosmological parameters relative to the mainstream methods…

There is currently a discrepancy in the measured value of the amplitude of matter clustering, parameterised using $\sigma_8$, inferred from galaxy weak lensing, and cosmic microwave background data, which could be an indication of new…

Cosmology and Nongalactic Astrophysics · Physics 2019-04-15 Thomas D. Kitching , Licia Verde , Alan F. Heavens , Raul Jimenez

We simultaneously constrain cosmology and galaxy bias using measurements of galaxy abundances, galaxy clustering and galaxy-galaxy lensing taken from the Sloan Digital Sky Survey. We use the conditional luminosity function (which describes…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-05 Marcello Cacciato , Frank C. van den Bosch , Surhud More , Houjun Mo , Xiaohu Yang

The statistical power of weak lensing measurements is principally driven by the number of high redshift galaxies whose shapes are resolved. Conventional wisdom and physical intuition suggest this is optimised by deep imaging at long (red or…

We present GLIMPSE - Gravitational Lensing Inversion and MaPping with Sparse Estimators - a new algorithm to generate density reconstructions in three dimensions from photometric weak lensing measurements. This is an extension of earlier…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-16 Adrienne Leonard , François Lanusse , Jean-Luc Starck

We address key points for an efficient implementation of likelihood codes for modern weak lensing large-scale structure surveys. Specifically, we focus on the joint weak lensing convergence power spectrum-bispectrum probe and we tackle the…

Cosmology and Nongalactic Astrophysics · Physics 2020-04-02 Matteo Rizzato , Karim Benabed , Francis Bernardeau , Fabien Lacasa

A stationary stochastic geometric model is proposed for analyzing the data compression method used in one-bit compressed sensing. The data set is an unconstrained stationary set, for instance all of $\mathbb{R}^n$ or a stationary Poisson…

Probability · Mathematics 2018-10-16 François Baccelli , Eliza O'Reilly

A common task in single particle electron cryomicroscopy (cryo-EM) is the rigid alignment of images and/or volumes. In the context of images, a rigid alignment involves estimating the inner-product between one image of $N\times N$ pixels…

Numerical Analysis · Mathematics 2022-12-07 Aaditya V. Rangan

Studies of cosmological objects should take into account their positions within the cosmic web of large-scale structure. Unfortunately, the cosmic web has only been extensively mapped at low-redshifts ($z<1$), using galaxy redshifts as…

Cosmology and Nongalactic Astrophysics · Physics 2016-11-08 Khee-Gan Lee , Martin White

We study the prospects for three-dimensional mapping of the dark matter to high redshift through the shearing of faint galaxies images at multiple distances by gravitational lensing. Such maps could provide invaluable information on the…

Astrophysics · Physics 2009-08-12 Wayne Hu , Charles R. Keeton

Radio observation of the large-scale structure (LSS) of our Universe faces major challenges from foreground contamination, which is many orders of magnitude stronger than the cosmic signal. While other foreground removal techniques struggle…

Cosmology and Nongalactic Astrophysics · Physics 2025-03-27 Tian-Cheng Luan , Xin Wang , Jiacheng Ding , Qian Li , Xiao-Dong Li , Weishan Zhu

The accuracy of photometric redshifts (photo-zs) particularly affects the results of the analyses of galaxy clustering with photometrically-selected galaxies (GCph) and weak lensing. In the next decade, space missions like Euclid will…

Cosmology and Nongalactic Astrophysics · Physics 2021-11-17 Euclid Collaboration , A. Pocino , I. Tutusaus , F. J. Castander , P. Fosalba , M. Crocce , A. Porredon , S. Camera , V. Cardone , S. Casas , T. Kitching , F. Lacasa , M. Martinelli , A. Pourtsidou , Z. Sakr , S. Andreon , N. Auricchio , C. Baccigalupi , A. Balaguera-Antolínez , M. Baldi , A. Balestra , S. Bardelli , R. Bender , A. Biviano , C. Bodendorf , D. Bonino , A. Boucaud , E. Bozzo , E. Branchini , M. Brescia , J. Brinchmann , C. Burigana , R. Cabanac , V. Capobianco , A. Cappi , C. S. Carvalho , M. Castellano , G. Castignani , S. Cavuoti , A. Cimatti , R. Cledassou , C. Colodro-Conde , G. Congedo , C. J. Conselice , L. Conversi , Y. Copin , L. Corcione , A. Costille , J. Coupon , H. M. Courtois , M. Cropper , J. -G. Cuby , A. Da Silva , S. de la Torre , D. Di Ferdinando , F. Dubath , C. Duncan , X. Dupac , S. Dusini , S. Farrens , P. G. Ferreira , I. Ferrero , F. Finelli , S. Fotopoulou , M. Frailis , E. Franceschi , S. Galeotta , B. Garilli , W. Gillard , B. Gillis , C. Giocoli , G. Gozaliasl , J. Graciá-Carpio , F. Grupp , L. Guzzo , W. Holmes , F. Hormuth , K. Jahnke , E. Keihanen , S. Kermiche , A. Kiessling , C. C. Kirkpatrick , M. Kunz , H. Kurki-Suonio , S. Ligori , P. B. Lilje , I. Lloro , D. Maino , E. Maiorano , O. Mansutti , O. Marggraf , N. Martinet , F. Marulli , R. Massey , S. Maurogordato , E. Medinaceli , S. Mei , M. Meneghetti , R. Benton Metcalf , G. Meylan , M. Moresco , B. Morin , L. Moscardini , E. Munari , R. Nakajima , C. Neissner , R. C. Nichol , S. Niemi , J. Nightingale , C. Padilla , S. Paltani , F. Pasian , L. Patrizii , K. Pedersen , W. J. Percival , V. Pettorino , S. Pires , G. Polenta , M. Poncet , L. Popa , D. Potter , L. Pozzetti , F. Raison , A. Renzi , J. Rhodes , G. Riccio , E. Romelli , M. Roncarelli , E. Rossetti , R. Saglia , A. G. Sánchez , D. Sapone , R. Scaramella , P. Schneider , V. Scottez , A. Secroun , G. Seidel , S. Serrano , C. Sirignano , G. Sirri , L. Stanco , F. Sureau , A. N. Taylor , M. Tenti , I. Tereno , R. Teyssier , R. Toledo-Moreo , A. Tramacere , E. A. Valentijn , L. Valenziano , J. Valiviita , T. Vassallo , M. Viel , Y. Wang , N. Welikala , L. Whittaker , A. Zacchei , G. Zamorani , J. Zoubian , E. Zucca

We describe a new non-parametric technique for reconstructing the mass distribution in galaxy clusters with strong lensing, i.e., from multiple images of background galaxies. The observed positions and redshifts of the images are considered…

Astrophysics · Physics 2020-11-25 H. M. AbdelSalam , P. Saha , L. L. R. Williams

The weak gravitational lensing distortion of distant galaxy images (defined as sources) probes the projected large-scale matter distribution in the Universe. To improve quality in the 3D mass mapping using 3D-lensing, we combine the lensing…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-04 Patrick Simon

We reanalyse the anisotropic galaxy clustering measurement from the Baryon Oscillation Spectroscopic Survey (BOSS), demonstrating that using the full shape information provides cosmological constraints that are comparable to other…

We perform a joint analysis of the abundance, the clustering and the galaxy-galaxy lensing signal of galaxies measured from Data Release 11 of the Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey (SDSS III-BOSS) in our…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-11 Surhud More , Hironao Miyatake , Rachel Mandelbaum , Masahiro Takada , David Spergel , Joel Brownstein , Donald P. Schneider

Unsupervised learning aims to capture the underlying structure of potentially large and high-dimensional datasets. Traditionally, this involves using dimensionality reduction (DR) methods to project data onto lower-dimensional spaces or…

Machine Learning · Computer Science 2025-06-30 Hugues Van Assel , Cédric Vincent-Cuaz , Nicolas Courty , Rémi Flamary , Pascal Frossard , Titouan Vayer