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A key motivation in the development of Distributed Model Predictive Control (DMPC) is to accelerate centralized Model Predictive Control (MPC) for large-scale systems. DMPC has the prospect of scaling well by parallelizing computations…

Optimization and Control · Mathematics 2025-04-16 Gösta Stomberg , Maurice Raetsch , Alexander Engelmann , Timm Faulwasser

We present two algorithms, one quantum and one classical, for estimating partition functions of quantum spin Hamiltonians. The former is a DQC1 (Deterministic quantum computation with one clean qubit) algorithm, and the first such for…

Quantum Physics · Physics 2023-02-01 Andrew Jackson , Theodoros Kapourniotis , Animesh Datta

Simflowny is an open platform which automatically generates efficient parallel code of scientific dynamical models for different simulation frameworks. Here we present major upgrades on this software to support simultaneously a quite…

Computational Physics · Physics 2020-12-02 C. Palenzuela , B. Miñano , A. Arbona , C. Bona-Casas , C. Bona , J. Massó

Distributed model fitting refers to the process of fitting a mathematical or statistical model to the data using distributed computing resources, such that computing tasks are divided among multiple interconnected computers or nodes, often…

Computation · Statistics 2024-06-04 Xiaofei Wu , Rongmei Liang , Fabio Roli , Marcello Pelillo , Jing Yuan

We present algorithmic improvements for fast and memory-efficient use of discrete spatial symmetries in Exact Diagonalization computations of quantum many-body systems. These techniques allow us to work flexibly in the reduced basis of…

Strongly Correlated Electrons · Physics 2018-10-05 Alexander Wietek , Andreas M. Läuchli

The accurate first-principles description of strongly-correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving compressed many-body Hamiltonians that…

Quantum Physics · Physics 2025-04-17 Antonios M. Alvertis , Abid Khan , Norm M. Tubman

Numerical algebraic geometry provides a number of efficient tools for approximating the solutions of polynomial systems. One such tool is the parameter homotopy, which can be an extremely efficient method to solve numerous polynomial…

Algebraic Geometry · Mathematics 2018-04-13 Daniel J. Bates , Danielle Brake , Matthew Niemerg

Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant…

Computational Physics · Physics 2015-05-18 Yu-Hang Tang , Shuhei Kudo , Xin Bian , Zhen Li , George E. Karniadakis

This paper introduces a novel methodology for Feature Selection for Functional Classification, FSFC, that addresses the challenge of jointly performing feature selection and classification of functional data in scenarios with categorical…

Computationally efficient and accurate quantum mechanical approximations to solve the many-electron Schr\"odinger equation are at the heart of computational materials science. In that respect the coupled cluster hierarchy of methods plays a…

Materials Science · Physics 2022-01-11 Tina N. Mihm , Tobias Schäfer , Sai Kumar Ramadugu , Andreas Grüneis , James J. Shepherd

Parallel input performance issues are often neglected in large scale parallel applications in Computational Science and Engineering. Traditionally, there has been less focus on input performance because either input sizes are small (as in…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-02 Mathew Jacob , Maya Taylor , Laxmikant Kale

We investigate the feasibility of early fault-tolerant quantum algorithms focusing on ground-state energy estimation problems. In particular, we examine the computation of the cumulative distribution function (CDF) of the spectral measure…

We present a set of programming tools (classes and functions written in C++ and based on Message Passing Interface) for fast development of generic parallel (and non-parallel) lattice simulations. They are collectively called MDP 1.2. These…

High Energy Physics - Lattice · Physics 2009-10-31 Massimo Di Pierro

Matrix Distributed Processing (MDP) is a C++ library for fast development of efficient parallel algorithms. It constitues the core of FermiQCD. MDP enables programmers to focus on algorithms, while parallelization is dealt with…

High Energy Physics - Lattice · Physics 2007-05-23 Massimo Di Pierro

Our goal is compression of massive-scale grid-structured data, such as the multi-terabyte output of a high-fidelity computational simulation. For such data sets, we have developed a new software package called TuckerMPI, a parallel C++/MPI…

Mathematical Software · Computer Science 2020-07-09 Grey Ballard , Alicia Klinvex , Tamara G. Kolda

We present the first open release of the DCA++ project, a high-performance research software framework to solve quantum many-body problems with cutting edge quantum cluster algorithms. DCA++ implements the dynamical cluster approximation…

In the High-Luminosity Large Hadron Collider (HL-LHC), one of the most challenging computational problems is expected to be finding and fitting charged-particle tracks during event reconstruction. The methods currently in use at the LHC are…

Stimulated by the successful descriptions of strongly correlated electron systems by fractionalized fermions, correspondence between interacting fermions and non-interacting multi-component fermions is formulated in examples of the Hubbard…

Strongly Correlated Electrons · Physics 2024-09-23 Masatoshi Imada

Efficient computation of molecular integrals and Hartree-Fock energy remains a central topic in quantum-chemistry algorithm development. Although many sophisticated open-source packages are available, understanding their implementations…

Chemical Physics · Physics 2025-10-30 Mario Hernández Vera

Quantum simulators have made a remarkable progress towards exploring the dynamics of many-body systems, many of which offer a formidable challenge to both theoretical and numerical methods. While state-of-the-art quantum simulators are in…