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Efficient estimators of Fourier-space statistics for large number of objects rely on Fast Fourier Transforms (FFTs), which are affected by aliasing from unresolved small scale modes due to the finite FFT grid. Aliasing takes the form of a…

Cosmology and Nongalactic Astrophysics · Physics 2017-10-09 Emiliano Sefusatti , Martin Crocce , Roman Scoccimarro , Hugh Couchman

In this paper extensions of the classical Fourier, fractional Fourier and Radon transforms to superspace are studied. Previously, a Fourier transform in superspace was already studied, but with a different kernel. In this work, the…

Classical Analysis and ODEs · Mathematics 2008-05-14 Hendrik De Bie

In this note we address the exact solutions of a time-dependent Hamiltonian composed by an oscillator-like interaction with both a frequency and a mass term that depend on time. The latter is achieved by constructing the appropriate point…

Quantum Physics · Physics 2020-02-26 Kevin Zelaya , Véronique Hussin

Periodic signals are critical for representing physical and perceptual phenomena. Scalar, real angular measures, e.g., radians and degrees, result in difficulty processing and distinguishing nearby angles, especially when their absolute…

Machine Learning · Computer Science 2026-05-13 Jakeb Chouinard

Fractional statistical moments are utilized for various tasks of uncertainty quantification, including the estimation of probability distributions. However, an estimation of fractional statistical moments of costly mathematical models by…

Methodology · Statistics 2024-03-05 Lukáš Novák , Marcos Valdebenito , Matthias Faes

Many astrophysical phenomena are time-varying, in the sense that their intensity, energy spectrum, and/or the spatial distribution of the emission suddenly change. This paper develops a method for modeling a time series of images. Under the…

Instrumentation and Methods for Astrophysics · Physics 2021-03-24 Cong Xu , Hans Moritz Günther , Vinay L. Kashyap , Thomas C. M. Lee , Andreas Zezas

The aperture mass statistic is a common tool used in weak lensing studies. By convolving lensing maps with a filter function of a specific scale, chosen to be larger than the scale on which the noise is dominant, the lensing signal may be…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-04 Adrienne Leonard , Sandrine Pires , Jean-Luc Starck

Source apportionment analysis, which aims to quantify the attribution of observed concentrations of multiple air pollutants to specific sources, can be formulated as a non-negative matrix factorization (NMF) problem. However, NMF is…

Statistics Theory · Mathematics 2025-10-08 Bora Jin , Abhirup Datta

A Fourier transform technique is introduced for counting the number of solutions of holomorphic moment map equations over a finite field. This in turn gives information on Betti numbers of holomorphic symplectic quotients. As a consequence…

Algebraic Geometry · Mathematics 2009-11-11 Tamas Hausel

Space-time is one of the most essential, yet most mysterious concepts in physics. In quantum mechanics it is common to understand time as a marker of instances of evolution and define states around all the space but at one time; while in…

Quantum Physics · Physics 2020-12-01 Tian Zhang , Oscar Dahlsten , Vlatko Vedral

Image subtraction in astronomy is a tool for transient object discovery such as asteroids, extra-solar planets and supernovae. To match point spread functions (PSFs) between images of the same field taken at different times a convolution…

Instrumentation and Methods for Astrophysics · Physics 2013-05-30 Steven Hartung , Hemant Shukla , J. Patrick Miller , Carlton Pennypacker

We formulate and discuss the affine-invariant matrix midrange problem on the cone of $n\times n$ positive definite Hermitian matrices $\mathbb{P}(n)$, which is based on the Thompson metric. A particular computationally efficient midpoint of…

Optimization and Control · Mathematics 2022-06-29 Cyrus Mostajeran , Christian Grussler , Rodolphe Sepulchre

The goal of this paper is to quantitatively describe some statistical properties of higher-dimensional determinantal point processes with a primary focus on the nearest-neighbor distribution functions. Toward this end, we express these…

Statistical Mechanics · Physics 2009-11-13 A. Scardicchio , C. E. Zachary , S. Torquato

Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications. Recent successful learning-based approaches include per-pixel cell segmentation with subsequent pixel grouping, or…

Computer Vision and Pattern Recognition · Computer Science 2018-11-09 Uwe Schmidt , Martin Weigert , Coleman Broaddus , Gene Myers

Since molecules are ubiquitous in space, the study of the 'Molecular Universe' could unfold the mystery of the existing Interstellar medium. Star formation is linked to the chemical evolution processes. Thus, an analysis of the formation of…

Astrophysics of Galaxies · Physics 2024-05-29 Bratati Bhat

Intermediate-mass stars are often fast rotators, and hence are centrifugally flattened and affected by gravity darkening. To analyse this kind of stars properly, one must turn to 2D models to compute the visible radiative flux and to take…

Solar and Stellar Astrophysics · Physics 2024-02-28 Axel Lazzarotto , Alain Hui-Bon-Hoa , Michel Rieutord

This paper develops a unified and computationally efficient method for change-point estimation along the time dimension in a non-stationary spatio-temporal process. By modeling a non-stationary spatio-temporal process as a piecewise…

Methodology · Statistics 2023-10-09 Zifeng Zhao , Ting Fung Ma , Wai Leong Ng , Chun Yip Yau

HERMES (High Energy Rapid Modular Ensemble of Satellites) pathfinder is an in-orbit demonstration consisting of a constellation of six 3U nano-satellites hosting simple but innovative detectors for the monitoring of cosmic high-energy…

High Energy Astrophysical Phenomena · Physics 2023-09-06 Riccardo Crupi , Giuseppe Dilillo , Kester Ward , Elisabetta Bissaldi , Fabrizio Fiore , Andrea Vacchi

In this paper we describe a probabilistic method for estimating the position of an object along with its covariance matrix using neural networks. Our method is designed to be robust to outliers, have bounded gradients with respect to the…

Computer Vision and Pattern Recognition · Computer Science 2021-11-22 David Mohlin , Gerald Bianchi , Josephine Sullivan

Without imposing prior distributional knowledge underlying multivariate time series of interest, we propose a nonparametric change-point detection approach to estimate the number of change points and their locations along the temporal axis.…

Methodology · Statistics 2021-05-13 Xiaodong Wang , Fushing Hsieh
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