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We model chaotic diffusion, in a symplectic 4D map by using the result of a theorem that was developed for stochastically perturbed integrable Hamiltonian systems. We explicitly consider a map defined by a free rotator (FR) coupled to a…

Chaotic Dynamics · Physics 2015-06-17 Martín F. Mestre , Armando Bazzani , Pablo M. Cincotta , Claudia M. Giordano

Gaussian random fields have been one of the most popular tools for analyzing spatial data. However, many geophysical and environmental processes often display non-Gaussian characteristics. In this paper, we propose a new class of spatial…

Applications · Statistics 2017-10-03 Minjie Fan , Debashis Paul , Thomas C. M. Lee , Tomoko Matsuo

Conventional meta-atom designs rely heavily on researchers' prior knowledge and trial-and-error searches using full-wave simulations, resulting in time-consuming and inefficient processes. Inverse design methods based on optimization…

Machine Learning · Computer Science 2023-12-11 Zezhou Zhang , Chuanchuan Yang , Yifeng Qin , Hao Feng , Jiqiang Feng , Hongbin Li

In this paper we investigate, with a detailed Monte-Carlo simulation based on Geant4, the novel approach [Nucl. Instrum. Methods A588 (2008) 457] to 3D imaging with photon scattering. A monochromatic and well collimated gamma beam is used…

Medical Physics · Physics 2011-09-23 M. Lenti , M. Veltri

We develop a fast method for optimally designing experiments in the context of statistical seismic source inversion. In particular, we efficiently compute the optimal number and locations of the receivers or seismographs. The seismic source…

Computation · Statistics 2023-07-19 Quan Long , Mohammad Motamed , Raul Tempone

The mixture of Gaussian distributions, a soft version of k-means , is considered a state-of-the-art clustering algorithm. It is widely used in computer vision for selecting classes, e.g., color, texture, and shapes. In this algorithm, each…

Machine Learning · Statistics 2016-12-30 Mahajabin Rahman , Davi Geiger

Simulated maps of the microwave background (CMB) radiation are generally created using one of two methods: all-sky simulations use the spherical harmonic transform, while maps covering small areas approximate the sky as flat, allowing the…

Cosmology and Nongalactic Astrophysics · Physics 2025-07-22 Mariona Giner Mascarell , Emory F. Bunn

Extensive air showers produce high-energy muons that can be utilized to probe hadronic interaction models in cosmic ray interactions. Most muons originate from pion and kaon decays, called $\textit{conventional}$ muons, while a smaller…

We propose a hybrid quantum-classical approach to model continuous classical probability distributions using a variational quantum circuit. The architecture of the variational circuit consists of two parts: a quantum circuit employed to…

Quantum Physics · Physics 2019-01-04 Jonathan Romero , Alan Aspuru-Guzik

We present a new version of the fast Gauss transform (FGT) for discrete and continuous sources. Classical Hermite expansions are avoided entirely, making use only of the plane-wave representation of the Gaussian kernel and a new…

Numerical Analysis · Mathematics 2023-05-15 Leslie Greengard , Shidong Jiang , Manas Rachh , Jun Wang

A coasting hadron beam with an elliptical transverse profile, uniform charge density, and small transverse four-dimensional (4D) emittance could improve accelerator performance in several contexts. A phase space painting method to generate…

Accelerator Physics · Physics 2022-09-14 A. Hoover , N. E. Evans

When measuring diameters of partially resolved sources like planetary nebulae, H II regions or galaxies, often a technique called gaussian deconvolution is used. This technique yields a gaussian diameter which subsequently has to be…

Astrophysics · Physics 2007-05-23 P. A. M. van Hoof

Generating synthetic images is a useful method for cheaply obtaining labeled data for training computer vision models. However, obtaining accurate 3D models of relevant objects is necessary, and the resulting images often have a gap in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Bram Vanherle , Brent Zoomers , Jeroen Put , Frank Van Reeth , Nick Michiels

An increased data sample of identified secondary muons is collected at detection level. Project GRAND identifies secondary cosmic ray muons from electrons utilizing a thin steel absorber and tracking (PWC) chambers. The resulting angular…

Astrophysics · Physics 2007-05-23 A. Roesch , J. Carpenter , S. Desch , J. Gress , T. F. Lin , J. Poirier

Including massive neutrinos in $N$-body simulations is a challenging task due to the large thermal velocities of the neutrinos. In particle based codes this leads to problems of shot-noise due to insufficient sampling of the neutrino…

Cosmology and Nongalactic Astrophysics · Physics 2019-04-10 Jacob Brandbyge , Steen Hannestad , Thomas Tram

Recent progress has shown that the geomagnetic field exerts a more significant impact than expected on the behavior of charged secondary particles in inclined air showers. In this study, we for the first time combine it with atmospheric…

High Energy Astrophysical Phenomena · Physics 2025-08-27 Si-Zhe Wu , Chao Zhang , Ruo-Yu Liu , Xi-Shui Tian , Zhuo Li

Considering the increasing number of experimental results in the manufacturing process of quantum dots with different geometries, and the fact that most numerical methods that can be used to investigate quantum dots with non-trivial…

Materials Science · Physics 2022-12-06 G. A. Mantashian , P. A. Mantashyan , D. B. Hayrapetyan

This paper presents a design framework for synthesizing angularly selective spatial filters using non-uniform metagratings. While traditional metagratings focus on channeling energy into higher-order Floquet modes for a fixed incidence…

Applied Physics · Physics 2026-01-29 Jinyong Kim , Minseok Kim

Directional emission of photons with designed polarizations and orbital angular momenta is crucial for exploiting full potential of quantum emitters (QEs) within quantum information technologies. Capitalizing on the concept of hybrid…

Optics · Physics 2021-12-21 Yinhui Kan , Sergey I. Bozhevolnyi

Score-based generative modelling (SGM) has proven to be a very effective method for modelling densities on finite-dimensional spaces. In this work we propose to extend this methodology to learn generative models over functional spaces. To…