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Related papers: SPARC: Simulation Package for Ab-initio Real-space…

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To leverage the redundancy between the electronic structure computed at each step of first-principles molecular dynamics, we present a data-driven modeling framework for Kohn-Sham Density Functional Theory that bypasses the explicit…

Numerical Analysis · Mathematics 2026-02-27 Siu Wun Cheung , Youngsoo Choi , Jean-Luc Fattebert , Jonas Kaufman , Daniel Osei-Kuffuor

Unambiguously identifying molecules in spectra is of fundamental importance for a variety of scientific and industrial uses. Interpreting atmospheric spectra for the remote detection of volatile compounds requires information about the…

Chemical Physics · Physics 2019-11-12 Clara Sousa-Silva , Janusz J Petkowski , Sara Seager

The spark plasma sintering (SPS) process, a key technology for advanced material manufacturing, demands accurate and efficient simulation tools to capture the complex electro-thermal-mechanical interactions inherent in powder materials.…

Computational Physics · Physics 2024-12-03 A. Kumar , Z. Zhang , M. Bambach , M. Afrasiabi

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and…

An extremely scalable linear-algebraic algorithm was developed for quantum material simulation (electronic state calculation) with 10$^8$ atoms or 100-nm-scale materials. The mathematical foundation is generalized shifted linear equations…

Recent increases in supercomputing power, driven by the multi-core revolution and accelerators such as the IBM Cell processor, graphics processing units (GPUs) and Intel's Many Integrated Core (MIC) technology have enabled kinetic…

Recently, we introduced a class of molecular representations for kernel-based regression methods -- the spectrum of approximated Hamiltonian matrices (SPA$^\mathrm{H}$M) -- that takes advantage of lightweight one-electron Hamiltonians…

Chemical Physics · Physics 2024-02-21 Ksenia R. Briling , Yannick Calvino Alonso , Alberto Fabrizio , Clemence Corminboeuf

State preparation and measurement errors are commonly regarded as indistinguishable. The problem of distinguishing state preparation (SPAM) errors from measurement errors is important to the field of characterizing quantum processors. In…

Quantum Physics · Physics 2022-08-17 Raymond Laflamme , Junan Lin , Tal Mor

A new method is presented that allows for efficient evaluation of spin-orbit coupling (SOC) in density-functional theory calculations. In the so-called second-variational scheme, where Kohn-Sham functions obtained in a scalar-relativistic…

Materials Science · Physics 2023-06-06 Cecilia Vona , Sven Lubeck , Hannah Kleine , Andris Gulans , Claudia Draxl

We achieve a quantum speed-up of fully polynomial randomized approximation schemes (FPRAS) for estimating partition functions that combine simulated annealing with the Monte-Carlo Markov Chain method and use non-adaptive cooling schedules.…

Quantum Physics · Physics 2013-06-12 Pawel Wocjan , Chen-Fu Chiang , Anura Abeyesinghe , Daniel Nagaj

In this paper, we demonstrate the efficiency of simulations via direct computation of the partition function under various macroscopic conditions, such as different temperatures or volumes. The method can compute partition functions by…

Statistical Mechanics · Physics 2011-11-09 Cheng Zhang , Jianpeng Ma

First-principles particle-in-cell (PIC) simulation is a powerful tool for understanding plasma behavior, but this power often comes at great computational expense. Artificially reducing the ion/electron mass ratio is a time-honored practice…

Plasma Physics · Physics 2022-01-14 Gregory R. Werner , Scott Robertson , Thomas G. Jenkins , Andrew M. Chap , John R. Cary

Recent progress in logic programming (e.g., the development of the Answer Set Programming paradigm) has made it possible to teach it to general undergraduate and even middle/high school students. Given the limited exposure of these students…

Artificial Intelligence · Computer Science 2018-09-25 Elias Marcopoulos , Yuanlin Zhang

Irregularly sampled AR(1) processes appear in many computationally demanding applications. This text provides an analytical expression for the precision matrix of such a process, and gives efficient algorithms for density evaluation and…

Methodology · Statistics 2018-05-30 Benjamin Allévius

We have developed and implemented a new quantum molecular dynamics approximation that allows fast and accurate simulations of dense plasmas from cold to hot conditions. The method is based on a carefully designed orbital-free implementation…

Plasma Physics · Physics 2015-06-22 Travis Sjostrom , Jerome Daligault

SPARC processors have many applications in mission-critical industries such as aviation and space engineering. Hence, it is important to provide formal frameworks that facilitate the verification of hardware and software that run on or…

Logic in Computer Science · Computer Science 2019-06-27 Zhe Hou , David Sanan , Alwen Tiu , Yang Liu , Jin Song Dong

The atomization energies of molecules from first-principles density functional approximations improve from the local spin-density approximation (LSDA) to the Perdew-Burke-Ernzerhof (PBE)) generalized gradient approximation (GGA) to the…

Chemical Physics · Physics 2024-06-19 Shah Tanvir ur Rahman Chowdhury , John P. Perdew

Modeling open quantum systems -- quantum systems coupled to a bath -- is of value in condensed matter theory, cavity quantum electrodynamics, nanosciences and biophysics. The real-time simulation of open quantum systems was advanced…

Quantum Physics · Physics 2023-07-14 Hanggai Nuomin , David N. Beratan , Peng Zhang

This chapter presents controlled approximations of Kohn-Sham density functional theory (DFT) that enable very large scale simulations. The work is motivated by the study of defects in crystalline solids, though the ideas can be used in…

Materials Science · Physics 2021-12-14 Kaushik Bhattacharya , Vikram Gavini , Michael Ortiz , Mauricio Ponga , Phanish Suryanarayana

Hyperspectral images provide abundant spatial and spectral information that is very valuable for material detection in diverse areas of practical science. The high-dimensions of data lead to many processing challenges that can be addressed…

Computer Vision and Pattern Recognition · Computer Science 2020-05-19 Saeideh Ghanbari Azar , Saeed Meshgini , Tohid Yousefi Rezaii , Soosan Beheshti