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A new method for improving the resolution of astronomical images is presented. It is based on the principle that sampled data cannot be fully deconvolved without violating the sampling theorem. Thus, the sampled image should not be…

天体物理学 · 物理学 2009-10-30 P. Magain , F. Courbin , S. Sohy

Ongoing and future spectroscopic surveys will measure numerous galaxy redshifts within tens of thousands of galaxy clusters. However, the sampling within these clusters will be low, 15 < N < 50 per cluster. With such data, it will be…

宇宙学与河外天体物理 · 物理学 2017-01-18 Daniel Gifford , Nicholas Kern , Christopher J. Miller

Consider a Gaussian memoryless multiple source with $m$ components with joint probability distribution known only to lie in a given class of distributions. A subset of $k \leq m$ components are sampled and compressed with the objective of…

信息论 · 计算机科学 2018-03-16 Vinay Praneeth Boda

Multi-wavelength astronomical studies brings a wealth of science within reach. One way to achieve a cross-wavelength analysis is via `stacking', i.e. combining precise positional information from an image at one wavelength with data from…

宇宙学与河外天体物理 · 物理学 2017-09-14 Song Chen , Jonathan T. L. Zwart , Mario G. Santos

We show how to obtain a Bayesian estimate of the rates or numbers of signal and background events from a set of events when the shapes of the signal and background distributions are known, can be estimated, or approximated; our method works…

天体物理仪器与方法 · 物理学 2015-06-15 Will M. Farr , Jonathan R. Gair , Ilya Mandel , Curt Cutler

Spaces of convex and concave functions appear naturally in theory and applications. For example, convex regression and log-concave density estimation are important topics in nonparametric statistics. In stochastic portfolio theory, concave…

概率论 · 数学 2021-05-25 Peter Baxendale , Ting-Kam Leonard Wong

This paper analyses the effect of preferential sampling in Geostatistics when the choice of new sampling locations is the main interest of the researcher. A Bayesian criterion based on maximizing utility functions is used. Simulated studies…

统计理论 · 数学 2015-09-23 Gustavo da Silva Ferreira , Dani Gamerman

Two commonly arising computational tasks in Bayesian learning are Optimization (Maximum A Posteriori estimation) and Sampling (from the posterior distribution). In the convex case these two problems are efficiently reducible to each other.…

机器学习 · 计算机科学 2019-11-07 Kunal Talwar

Counting galaxy number density with wide range sky surveys has been well adopted in researches focusing on revealing evolution pattern of different types of galaxies. As understood intuitively the astrophysics environment physics is…

宇宙学与河外天体物理 · 物理学 2015-08-26 K. J. Shen , Q. Zhang , Xin-he Meng

The number density of galaxy clusters across mass and redshift has been established as a powerful cosmological probe. Cosmological analyses with galaxy clusters traditionally employ scaling relations. However, many challenges arise from…

宇宙学与河外天体物理 · 物理学 2025-01-08 M. Kosiba , N. Cerardi , M. Pierre , F. Lanusse , C. Garrel , N. Werner , M. Shalak

For galaxy clustering to provide robust constraints on cosmological parameters and galaxy formation models, it is essential to make reliable estimates of the errors on clustering measurements. We present a new technique, based on a spatial…

宇宙学与河外天体物理 · 物理学 2015-05-28 Peder Norberg , Enrique Gaztanaga , Carlton M. Baugh , Darren J. Croton

The incredible variety of galaxy shapes cannot be summarized by human defined discrete classes of shapes without causing a possibly large loss of information. Dictionary learning and sparse coding allow us to reduce the high dimensional…

星系天体物理 · 物理学 2014-07-01 Giuseppe Vinci , Peter Freeman , Jeffrey Newman , Larry Wasserman , Christopher Genovese

We consider Bayesian linear regression with sparsity-inducing prior and design efficient sampling algorithms leveraging posterior contraction properties. A quasi-likelihood with Gaussian spike-and-slab (that is favorable both statistically…

统计计算 · 统计学 2023-07-13 Qijia Jiang

In certain situations that shall be undoubtedly more and more common in the Big Data era, the datasets available are so massive that computing statistics over the full sample is hardly feasible, if not unfeasible. A natural approach in this…

机器学习 · 统计学 2015-01-12 Stéphan Clémençon , Patrice Bertail , Emilie Chautru , Guillaume Papa

The Shannon entropy, and related quantities such as mutual information, can be used to quantify uncertainty and relevance. However, in practice, it can be difficult to compute these quantities for arbitrary probability distributions,…

统计计算 · 统计学 2017-10-11 Brendon J. Brewer

In particle-in-cell simulations and some other statistical computations, the representation of modelled distributions with tracked macro-particles can become locally excessive. Merging or resampling dense clusters or highly-populated phase…

计算物理 · 物理学 2020-12-21 Arkady Gonoskov

With the advent of galaxy surveys which provide large samples of galaxies or galaxy clusters over a volume comparable to the horizon size (SDSS-III, HETDEX, Euclid, JDEM, LSST, Pan-STARRS, CIP etc.) or mass-selected large cluster samples…

宇宙学与河外天体物理 · 物理学 2015-05-18 Licia Verde

It is well known that the clustering of galaxies depends on galaxy type.Such relative bias complicates the inference of cosmological parameters from galaxy redshift surveys, and is a challenge to theories of galaxy formation and evolution.…

We theoretically study semi-supervised clustering in sparse graphs in the presence of pairwise constraints on the cluster assignments of nodes. We focus on bi-cluster graphs, and study the impact of semi-supervision for varying constraint…

数据分析、统计与概率 · 物理学 2011-11-01 Greg Ver Steeg , Aram Galstyan , Armen E. Allahverdyan

The joint analysis of galaxy clustering and galaxy-shear cross-correlations (galaxy-galaxy lensing) in imaging surveys constitutes one of the main avenues to obtain cosmological information. Analyses from Stage III surveys have assumed…

宇宙学与河外天体物理 · 物理学 2023-10-03 Shivam Pandey , Carles Sánchez , Bhuvnesh Jain , The LSST Dark Energy Science Collaboration