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We propose a new cross-correlation method that can recognize independent realizations of the same type of stochastic processes and can be used as a new kind of pattern recognition tool in biometrics, sensing, forensic, security and image…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Jong U. Kim , Laszlo B. Kish

We investigate the non-gaussian properties of cosmic-string-seeded linear density perturbations with cold and hot dark matter backgrounds, using high-resolution numerical simulations. We compute the one-point probability density function of…

Astrophysics · Physics 2009-10-30 P. P. Avelino , E. P. S. Shellard , J. H. P. Wu , B. Allen

The distribution of the spin directions of galaxies has been a question in the past decade, with numerous Earth-based and space-based experiments showing that the distribution is not necessarily random. These experiments were based on…

Cosmology and Nongalactic Astrophysics · Physics 2024-04-23 Lior Shamir

We provide theoretical procedures and practical recipes to simulate non-Gaussian correlated, homogeneous random fields with prescribed marginal distributions and cross-correlation structure, either in a N-dimensional Cartesian space or on…

Astrophysics · Physics 2009-11-07 R. Vio , P. Andreani , L. Tenorio , W. Wamsteker

Normalizing flows are a powerful tool to create flexible probability distributions with a wide range of potential applications in cosmology. Here we are studying normalizing flows which represent cosmological observables at field level,…

Cosmology and Nongalactic Astrophysics · Physics 2021-05-26 Adam Rouhiainen , Utkarsh Giri , Moritz Münchmeyer

Full Bayesian computational inference for model determination in undirected graphical models is currently restricted to decomposable graphs, except for problems of very small scale. In this paper we develop new, more efficient methodology…

Computation · Statistics 2012-06-05 Peter J. Green , Alun Thomas

Graphical models are commonly used to represent conditional dependence relationships between variables. There are multiple methods available for exploring them from high-dimensional data, but almost all of them rely on the assumption that…

Machine Learning · Statistics 2020-04-22 Tianxi Li , Cheng Qian , Elizaveta Levina , Ji Zhu

The accurate classification of galaxies in large-sample astrophysical databases of galaxy clusters depends sensitively on the ability to distinguish between morphological types, especially at higher redshifts. This capability can be…

Cosmology and Nongalactic Astrophysics · Physics 2014-03-21 Mercedes T. Richards , Donald St. P. Richards , Elizabeth Martinez-Gomez

We develop a statistical estimator to infer the redshift probability distribution of a photometric sample of galaxies from its angular cross-correlation in redshift bins with an overlapping spectroscopic sample. This estimator is a minimum…

Measurements of the peculiar velocities of large samples of galaxies enable new tests of the standard cosmological model, including determination of the growth rate of cosmic structure that encodes gravitational physics. With the size of…

Cosmology and Nongalactic Astrophysics · Physics 2023-10-19 Chris Blake , Ryan J. Turner

We apply Bayesian statistics to the estimation of correlation functions. We give the probability distributions of auto- and cross-correlations as functions of the data. Our procedure uses the measured data optimally and informs about the…

Data Analysis, Statistics and Probability · Physics 2022-12-27 Angel Gutierrez-Rubio , Juan S. Rojas-Arias , Jun Yoneda , Seigo Tarucha , Daniel Loss , Peter Stano

The success of present and future cosmological studies is tied to the ability to detect discrepancies in complex data sets within the framework of a cosmological model. Tensions caused by the presence of unknown systematic effects need to…

Cosmology and Nongalactic Astrophysics · Physics 2019-02-13 Marco Raveri , Wayne Hu

Weak gravitational lensing provides a unique method to map directly the dark matter in the Universe. The majority of lensing analyses uses the two-point statistics of the cosmic shear field to constrain the cosmological model yielding…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-18 S. Pires , J. -L. Starck , A. Amara , A. Refregier , R. Teyssier

Galaxy bias, the unknown relationship between the clustering of galaxies and the underlying dark matter density field is a major hurdle for cosmological inference from large-scale structure. While traditional analyses focus on the absolute…

Cosmology and Nongalactic Astrophysics · Physics 2014-02-03 Nico Hamaus , Benjamin D. Wandelt , P. M. Sutter , Guilhem Lavaux , Michael S. Warren

A method is presented for performing joint analyses of cosmological datasets, in which the weight assigned to each dataset is determined directly by it own statistical properties. The weights are considered in a Bayesian context as a set of…

Astrophysics · Physics 2009-11-07 M. P. Hobson , S. L. Bridle , O. Lahav

We present a multifrequency approach which optimizes the constraints on cosmological parameters with respect to extragalactic sources and secondary anisotropies contamination on small scales. We model with a minimal number of parameters the…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 D. Paoletti , N. Aghanim , M. Douspis , F. Finelli , G. De Zotti , G. Lagache , Aurélie Pénin

We present the calibration of the Dark Energy Survey Year 1 (DES Y1) weak lensing source galaxy redshift distributions from clustering measurements. By cross-correlating the positions of source galaxies with luminous red galaxies selected…

(Abridged) Combining cosmic shear power spectra and cluster counts is powerful to improve cosmological parameter constraints and/or test inherent systematics. However they probe the same cosmic mass density field, if the two are drawn from…

Astrophysics · Physics 2009-06-23 Masahiro Takada , Sarah Bridle

Non-Gaussian bosonic states are ubiquitous in interacting light--matter systems, many-body platforms, and relativistic quantum field settings, but their quantitative characterization is hindered by the infinite-dimensional Hilbert space and…

Quantum Physics · Physics 2026-03-17 Federico Centrone , Juan Pablo Paz , Augusto Roncaglia

Precise estimation of cross-correlation or similarity between two random variables lies at the heart of signal detection, hyperdimensional computing, associative memories, and neural networks. Although a vast literature exists on different…

Machine Learning · Computer Science 2023-11-02 Zhili Xiao , Shantanu Chakrabartty