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This chapter discusses the importance of incorporating three-dimensional symmetries in the context of statistical learning models geared towards the interpolation of the tensorial properties of atomic-scale structures. We focus on Gaussian…

Chemical Physics · Physics 2019-04-04 Andrea Grisafi , David M. Wilkins , Michael J. Willatt , Michele Ceriotti

We study two-dimensional quantum Gaussian packets with a fixed value of mean angular momentum. This value is the sum of two independent parts: the `external' momentum related to the motion of the packet center and the `internal' momentum…

Quantum Physics · Physics 2015-10-28 V. V. Dodonov

In static and spherically symmetric spacetime, we solve the Einstein Maxwell equations. The effective gravitational potential and the electric field for charged anisotropic fluid are defined in terms of two free parameters. For such…

Solar and Stellar Astrophysics · Physics 2017-02-20 Safiqul Islam , Satadal Datta , Tapas K Das

One way of recovering information about the initial conditions of the Universe is by measuring features of the cosmological density field which are preserved during gravitational evolution and galaxy formation. In this paper we study the…

Astrophysics · Physics 2016-08-30 Rupert A. C. Croft , Enrique Gaztanaga

The high-pressure compaction of three dimensional granular packings is simulated using a bonded particle model (BPM) to capture linear elastic deformation. In the model, grains are represented by a collection of point particles connected by…

Soft Condensed Matter · Physics 2023-10-19 Joel T. Clemmer , Joseph M. Monti , Jeremy B. Lechman

Gausslets are one of the few examples of basis sets for electronic structure which allow for two-index/diagonal electron-electron interaction terms. A weakness of gausslets is that, because of their 1D origin, they have been tied to…

Chemical Physics · Physics 2026-04-09 Steven R. White

We generate random functions locally via a novel generalization of Dyson Brownian motion, such that the functions are in a desired differentiability class, while ensuring that the Hessian is a member of the Gaussian orthogonal ensemble…

High Energy Physics - Theory · Physics 2015-03-11 Thorsten Battefeld , Chirag Modi

We suggest that some observational features of high-energy radiation from pulsars should be explained in terms of three dimensional geometric models, e.g. the phase-resolved X-ray and $\gamma$-ray spectra and the energy dependent light…

Astrophysics · Physics 2009-11-10 K. S. Cheng

The affine Gaussian derivative model can in several respects be regarded as a canonical model for receptive fields over a spatial image domain: (i) it can be derived by necessity from scale-space axioms that reflect structural properties of…

Computer Vision and Pattern Recognition · Computer Science 2017-12-21 Tony Lindeberg

The propagation of boson particles in a gravitational field described by the Brans-Dicke theory of gravity is analyzed. We derive the wave function of the scalar particles, and the effective potential experienced by the quantum particles…

General Relativity and Quantum Cosmology · Physics 2015-07-15 S. Capozziello , G. Lambiase

A nonrelativistic scalar particle that is constrained to move on an asymptotically flat curved surface undergoes a geometric scattering that is sensitive to the mean and Gaussian curvatures of the surface. A careful study of possible…

Quantum Physics · Physics 2019-10-17 Hai Viet Bui , Ali Mostafazadeh

Background: Fission modes are typically characterised by fragment mass and total kinetic energy centroids, around which a distribution of these variables is observed. These distributions are usually fitted with Gaussian functions. Purpose:…

Nuclear Theory · Physics 2025-03-24 Patrick McGlynn , Cedric Simenel

We show that Gaussian process regression (GPR) allows representing multivariate functions with low-dimensional terms via kernel design. When using a kernel built with HDMR (High-dimensional model representation), one obtains a similar type…

Numerical Analysis · Mathematics 2023-01-27 Eita Sasaki , Manabu Ihara , Sergei Manzhos

The three-dimensional galaxy power spectrum is a powerful probe of primordial non-Gaussianity and additional general relativistic (GR) effects on large scales, which can be constrained by the current and upcoming large-scale structure…

Cosmology and Nongalactic Astrophysics · Physics 2024-12-03 Robin Y. Wen , Henry S. Grasshorn Gebhardt , Chen Heinrich , Olivier Doré

We study a two-dimensional spinless particle in a disordered gaussian magnetic field with short time fluctuations, by means of the evolution equation for the density matrix $<x^{(1)} |\hat{\rho} (t)| x^{(2)}>$; in this description the two…

Statistical Mechanics · Physics 2009-10-31 V. G. Benza , B. Cardinetti

We try to go beyond the geometrical optics approximation, by showing that a massless polarized particle allows a wide class of non minimal interactions with an arbitrary gravitational field. One specific example of a curvature-dependent…

General Relativity and Quantum Cosmology · Physics 2022-01-11 Alexei A. Deriglazov

We compute the intrinsic Hausdorff dimension of spacetime at the infrared fixed point of the quantum conformal factor in 4D gravity. The fractal dimension is defined by the appropriate covariant diffusion equation in four dimensions and is…

High Energy Physics - Theory · Physics 2009-10-31 Ignatios Antoniadis , Pawel O. Mazur , Emil Mottola

Obtaining a reduced description with particle and momentum flux densities outgoing from the microscopic equations of motion of the particles requires approximations. The usual method, we refer to as truncation method, is to zero Fourier…

Statistical Mechanics · Physics 2017-01-04 Hamid Seyed-Allaei , Lutz Schimansky-Geier , Mohammad Reza Ejtehadi

We study the resonant interaction of charged particles with a gravitational wave propagating in the non-empty interstellar space in the presence of a uniform magnetic field. It is found that this interaction can be cast in the form of a…

General Relativity and Quantum Cosmology · Physics 2009-10-31 K. Kleidis , H. Varvoglis , D. B. Papadopoulos

Kernel based methods including Gaussian process regression (GPR) and generally kernel ridge regression (KRR) have been finding increasing use in computational chemistry, including the fitting of potential energy surfaces and density…

Machine Learning · Statistics 2023-01-27 Sergei Manzhos , Manabu Ihara
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