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This paper addresses the problem of active learning of a multi-output Gaussian process (MOGP) model representing multiple types of coexisting correlated environmental phenomena. In contrast to existing works, our active learning problem…

Machine Learning · Statistics 2015-11-25 Yehong Zhang , Trong Nghia Hoang , Kian Hsiang Low , Mohan Kankanhalli

The problem of radiation by the charged particles of the intergalactic medium (IGM) when a passing gravitational wave (GW) accelerate them is investigated. The largest acceleration (taking a charge from rest to a maximum speed which remains…

General Relativity and Quantum Cosmology · Physics 2022-04-13 Richard Lieu , Kristen Lackeos , Bing Zhang

With advances in scientific computing and mathematical modeling, complex scientific phenomena such as galaxy formations and rocket propulsion can now be reliably simulated. Such simulations can however be very time-intensive, requiring…

Methodology · Statistics 2024-02-29 Yi Ji , Simon Mak , Derek Soeder , J-F Paquet , Steffen A. Bass

A grid-based real-space implementation of the Projector Augmented Wave (PAW) method of P. E. Blochl [Phys. Rev. B 50, 17953 (1994)] for Density Functional Theory (DFT) calculations is presented. The use of uniform 3D real-space grids for…

Materials Science · Physics 2009-11-10 J. J. Mortensen , L. B. Hansen , K. W. Jacobsen

Using an eikonal analysis, we simultaneously fit a QCD-inspired parameterization of all accelerator data on forward proton-proton and antiproton-proton scattering amplitudes, together with cosmic ray data (using Glauber theory), to predict…

High Energy Physics - Phenomenology · Physics 2009-11-07 M. M. Block , F. Halzen

We investigate truncation schemes to reduce the computational cost of calculating correlations by the generator coordinate method based on mean-field wave functions. As our test nuclei, we take examples for which accurate calculations are…

Nuclear Theory · Physics 2009-11-10 M. Bender , G. Bertsch , P. -H. Heenen

We develop a formalism that allows one to systematically calculate the WIMP annihilation rate into gamma rays whose energy far exceeds the weak scale. A factorization theorem is presented which separates the radiative corrections stemming…

High Energy Physics - Phenomenology · Physics 2015-10-09 Matthew Baumgart , Ira Z. Rothstein , Varun Vaidya

We consider the problem of calibrating an imperfect computer model using experimental data. To compensate the misspecification of the computer model and make more accurate predictions, a discrepancy function is often included and modeled…

Methodology · Statistics 2018-05-04 Mengyang Gu , Long Wang

Material characterization in nano-mechanical tests requires precise interatomic potentials for the computation of atomic energies and forces with near-quantum accuracy. For such purposes, we develop a robust neural-network interatomic…

The $GW$ approximation is a well-established method for calculating ionization potentials and electron affinities in solids and molecules. For numerous years, obtaining self-consistent $GW$ total energies in solids has been a challenging…

Chemical Physics · Physics 2023-06-28 Adam Hassan Denawi , Fabien Bruneval , Marc Torrent , Mauricio Rodríguez-Mayorga

Cardiac cells exhibit variability in the shape and duration of their action potentials in space within a single individual. To create a mathematical model of cardiac action potentials (AP) which captures this spatial variability and also…

In geostatistical problems with massive sample size, Gaussian processes can be approximated using sparse directed acyclic graphs to achieve scalable $O(n)$ computational complexity. In these models, data at each location are typically…

Statistics Theory · Mathematics 2024-06-24 Yichen Zhu , Michele Peruzzi , Cheng Li , David B. Dunson

The purpose of this short contribution is to report on the development of a Spectral Neighbor Analysis Potential (SNAP) for tungsten. We have focused on the characterization of elastic and defect properties of the pure material in order to…

Computational Physics · Physics 2017-02-24 Mitchell A. Wood , Aidan P. Thompson

The search for new materials, based on computational screening, relies on methods that accurately predict, in an automatic manner, total energy, atomic-scale geometries, and other fundamental characteristics of materials. Many…

Materials Science · Physics 2017-10-25 M. J. van Setten , M. Giantomassi , X. Gonze , G. -M. Rignanese , G. Hautier

In principle, the Luttinger-Ward Green's function formalism allows one to compute simultaneously the total energy and the quasiparticle band structure of a many-body electronic system from first principles. We present approximate and exact…

Materials Science · Physics 2015-05-18 Sohrab Ismail-Beigi

Extended defects such as dislocation networks and general grain boundaries are ubiquitous in metals, and accurately modeling these extensive defects is crucial for understanding their deformation mechanisms. Existing machine learning…

Materials Science · Physics 2025-06-10 Fei Shuang , Kai Liu , Yucheng Ji , Wei Gao , Luca Laurenti , Poulumi Dey

Understanding and accurately predicting hydrogen diffusion in materials is challenging due to the complex interactions between hydrogen defects and the crystal lattice. These interactions span large length and time scales, making them…

This paper addresses the adaptive radar target detection problem in the presence of Gaussian interference with unknown statistical properties. To this end, the problem is first formulated as a binary hypothesis test, and then we derive a…

Signal Processing · Electrical Eng. & Systems 2025-03-05 Chaoran Yin , Tianqi Wang , Linjie Yan , Chengpeng Hao , Alfonso Farina , Danilo Orlando

For materials which are incorrectly predicted by density functional theory to be metallic, an iterative procedure must be adopted in order to perform GW calculations. In this paper we test two iterative schemes based on the quasi-particle…

Materials Science · Physics 2007-05-23 V. A. Popa , G. Brocks , P. J. Kelly

The computational efficiency of approximate Bayesian computation (ABC) has been improved by using surrogate models such as Gaussian processes (GP). In one such promising framework the discrepancy between the simulated and observed data is…

Machine Learning · Statistics 2020-08-07 Marko Järvenpää , Aki Vehtari , Pekka Marttinen
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