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The two-point correlation function (2PCF) is the most widely used tool for quantifying the spatial distribution of galaxies. Since the distribution of galaxies is determined by galaxy formation physics as well as the underlying cosmology,…

Cosmology and Nongalactic Astrophysics · Physics 2020-01-08 Manodeep Sinha , Lehman H. Garrison

This paper introduces nucleus clustering in Voronoi tessellations of plane surfaces with applications in the geometry of digital images. A \emph{nucleus cluster} is a collection of Voronoi regions that are adjacent to a Voronoi region…

Metric Geometry · Mathematics 2016-02-15 J. F. Peters , E. Inan

We consider a system of particles which interact through a jump process. The jump intensities are functions of the proximity rank of the particles, a type of interaction referred to as topological in the literature. Such interactions have…

Probability · Mathematics 2022-12-20 Pierre Degond , Mario Pulvirenti , Stefano Rossi

We revisit the role of attractions in liquids and apply these concepts to colloidal suspensions. Two means are used to investigate the structure; the pair correlation function and a recently developed topological method. The latter…

Soft Condensed Matter · Physics 2011-01-11 Jade Taffs , Alex Malins , Stephen R. Williams , C. Patrick Royall

Background:Typically, proteins perform key biological functions by interacting with each other. As a consequence, predicting which protein pairs interact is a fundamental problem. Experimental methods are slow, expensive, and may be error…

Biomolecules · Quantitative Biology 2022-02-08 Leonardo Martini , Adriano Fazzone , Luca Becchetti

The Voronoi diagrams are an important tool having theoretical and practical applications in a large number of fields. We present a new procedure, implemented as a set of CUDA kernels, which detects, in a general and efficient way,…

Soft Condensed Matter · Physics 2017-03-08 Massimo Bernaschi , Matteo Lulli , Mauro Sbragaglia

Under the assumption of a void-filled Universe we investigate if the characteristic scale of voids can be determined from existing surveys. We use the Voronoi tessellation to create mock surveys and study the properties of the first…

Astrophysics · Physics 2015-06-24 Dalia S. Goldwirth , Luiz Nicolaci da Costa , Rien Van de Weygaert

Femtoscopy with photon pairs is a particularly attractive tool for studying high-energy nuclear collisions. Proposed and extensively discussed in several influential theory articles, it has seen only few applications in experiment because…

Nuclear Experiment · Physics 2026-02-24 Dariusz Miśkowiec , Klaus Reygers

The Theory of Functional Connections (TFC) is a functional interpolation framework founded upon the so-called constrained expression: a functional that expresses the family of all possible functions that satisfy some user-specified, linear…

Analysis of PDEs · Mathematics 2021-10-25 Carl Leake

A systematic comparison is conducted for pairing properties of finite systems at nonzero temperature as predicted by the exact solutions of the pairing problem embedded in three principal statistical ensembles, as well as the unprojected…

Nuclear Theory · Physics 2009-06-30 N. Quang Hung , N. Dinh Dang

Using molecular dynamics simulations, we perform the first direct tests of three proposed models for the pair correlation functions of strongly coupled plasmas with species of unequal temperature. The models are all extensions of the…

Plasma Physics · Physics 2017-09-13 Nathaniel R. Shaffer , Sanat Kumar Tiwari , Scott D. Baalrud

The multi-component density functional theory is faced with the challenge of capturing various types of inter- and intra-particle exchange-correlation effects beyond those introduced by the conventional electronic exchange-correlation…

Atomic and Molecular Clusters · Physics 2023-12-27 Nahid Sadat Riyahi , Mohammad Goli , Shant Shahbazian

Principal component analysis (PCA) is often used for analyzing data in the most diverse areas. In this work, we report an integrated approach to several theoretical and practical aspects of PCA. We start by providing, in an intuitive and…

Computational Engineering, Finance, and Science · Computer Science 2021-06-09 Felipe L. Gewers , Gustavo R. Ferreira , Henrique F. de Arruda , Filipi N. Silva , Cesar H. Comin , Diego R. Amancio , Luciano da F. Costa

The simplicity of a question such as wondering if correlations characterize or not a certain system collides with the experimental difficulty of accessing such information. Here we present a low demanding experimental approach which refers…

Pairing correlations in nuclei play a decisive role in determining nuclear drip-lines, binding energies, and many collective properties. In this work a new Configuration-Space Monte-Carlo (CSMC) method for treating nuclear pairing…

Nuclear Theory · Physics 2015-03-23 Mark Lingle , Alexander Volya

Context. A novel high-performance exact pair counting toolkit called Fast Correlation Function Calculator (FCFC) is presented, which is publicly available at https://github.com/cheng-zhao/FCFC. Aims. As the rapid growth of modern…

Instrumentation and Methods for Astrophysics · Physics 2023-04-05 Cheng Zhao

We discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis…

Materials Science · Physics 2012-06-13 Alexander Stukowski

Topological properties of solid states have sparked considerable recent interest due to their importance in the physics of lattices with a non-trivial basis and their potential in the design of novel materials. Here we describe an…

Applied Physics · Physics 2020-02-19 Henning U. Voss , Douglas J. Ballon

Two-particle rapidity (or pseudorapidity) correlation function $C(y_1, y_2)$ was used in analysing fluctuation of particle density distribution in rapidity in high-energy heavy-ion collisions. In our research, we argue that for a centrality…

Nuclear Theory · Physics 2017-05-22 Ronghua He , Jing Qian , Lei Huo

A probabilistic circuit (PC) succinctly expresses a function that represents a multivariate probability distribution and, given sufficient structural properties of the circuit, supports efficient probabilistic inference. Typically a PC…

Machine Learning · Computer Science 2024-08-09 Oliver Broadrick , William Cao , Benjie Wang , Martin Trapp , Guy Van den Broeck