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Lattice studies of spontaneous supersymmetry breaking suffer from a sign problem that in principle can be evaded through novel methods enabled by quantum computing. Focusing on lower-dimensional lattice systems with more modest resource…

High Energy Physics - Lattice · Physics 2024-10-16 David Schaich , Christopher Culver

The present work is a proof of concept of the capabilities of paralellization in the calculation of metamaterials in a non-linear regime. In this work we subdivided the bulk material into subregions where the mechanical properties are…

Materials Science · Physics 2023-11-28 Antonio Tabanera , Luis Saucedo-Mora , Miguel Angel Sanz , Francisco J. Montans

This paper proposes a parallel numerical algorithm to simulate the flow and the transport in a discrete fracture network taking into account the mass exchanges with the surrounding matrix. The discretization of the Darcy fluxes is based on…

Numerical Analysis · Mathematics 2016-11-18 Feng Xing , Roland Masson , Simon Lopez

Quantum heuristics have shown promise in solving various optimization problems, including lattice protein folding. Equally relevant is the inverse problem, protein design, where one seeks sequences that fold to a given target structure. The…

An efficient numerical method is developed using the matrix product formalism for computing the properties at finite energy densities in one-dimensional (1D) many-body localized (MBL) systems. Arguing that any efficient (possibly quantum)…

Disordered Systems and Neural Networks · Physics 2015-08-20 Yichen Huang

Calculating bounds of properties of many-body quantum systems is of paramount importance, since they guide our understanding of emergent quantum phenomena and complement the insights obtained from estimation methods. Recent semidefinite…

Quantum Physics · Physics 2026-01-16 Luke Mortimer , Leonardo Zambrano , Antonio Acín , Donato Farina

When training large machine learning models with many variables or parameters, a single machine is often inadequate since the model may be too large to fit in memory, while training can take a long time even with stochastic updates. A…

Machine Learning · Statistics 2014-06-19 Seunghak Lee , Jin Kyu Kim , Xun Zheng , Qirong Ho , Garth A. Gibson , Eric P. Xing

Due to the significant increase in the size of spatial data, it is essential to use distributed parallel processing systems to efficiently analyze spatial data. In this paper, we first study learned spatial data partitioning, which…

Databases · Computer Science 2023-06-21 Keizo Hori , Yuya Sasaki , Daichi Amagata , Yuki Murosaki , Makoto Onizuka

We derive and implement an alternative formulation of the Stochastic Lanczos algorithm to be employed in connection with the Many-Body Dispersion model (MBD). Indeed, this formulation, which is only possible due to the Stochastic Lanczos'…

Chemical Physics · Physics 2023-10-23 Pier P. Poier , Louis Lagardère , Jean-Philip Piquemal

Characterization of qubit couplings in many-body quantum systems is essential for benchmarking quantum computation and simulation. We propose a tomographic measurement scheme to determine all the coupling terms in a general many-body…

Quantum Physics · Physics 2015-10-06 Sheng-Tao Wang , Dong-Ling Deng , Lu-Ming Duan

With the growing reliance of modern supercomputers on accelerator-based architectures such a GPUs, the development and optimization of electronic structure methods to exploit these massively parallel resources has become a recent priority.…

We analyze the method for calculation of properties of non-relativistic quantum systems based on exact diagonalization of space-discretized short-time evolution operators. In this paper we present a detailed analysis of the errors…

Statistical Mechanics · Physics 2011-08-08 Ivana Vidanovic , Aleksandar Bogojevic , Aleksandar Belic

This thesis develops signal-processing algorithms and implementation schemes under constraints of minimal parallelism and memory space, with the goal of improving energy efficiency of low-power computing hardware. We propose (i) a…

Signal Processing · Electrical Eng. & Systems 2025-12-30 Sergey Salishev

The paper describes a sparse direct solver for the linear systems that arise from the discretization of an elliptic PDE on a two dimensional domain. The scheme decomposes the domain into thin subdomains, or ``slabs'' and uses a two-level…

Numerical Analysis · Mathematics 2025-09-01 Anna Yesypenko , Per-Gunnar Martinsson

In this work, we consider alternative discretizations for PDEs which use expansions involving integral operators to approximate spatial derivatives. These constructions use explicit information within the integral terms, but treat boundary…

Computational Physics · Physics 2024-11-12 Andrew J. Christlieb , Pierson T. Guthrey , William A. Sands , Mathialakan Thavappiragasm

We present a hybrid classical/quantum algorithm for efficiently solving the eigenvalue problem of many-particle Hamiltonians on quantum computers with limited resources by splitting the workload between classical and quantum processors.…

Quantum Physics · Physics 2022-03-01 John P. T. Stenger , Daniel Gunlycke , C. Stephen Hellberg

We present a technique for reducing the computational requirements by several orders of magnitude in the evaluation of semidefinite relaxations for bounding the set of quantum correlations arising from finite-dimensional Hilbert spaces. The…

Quantum Physics · Physics 2019-02-22 Armin Tavakoli , Denis Rosset , Marc-Olivier Renou

We describe quantum many--body systems in terms of projected entangled--pair states, which naturally extend matrix product states to two and more dimensions. We present an algorithm to determine correlation functions in an efficient way. We…

Strongly Correlated Electrons · Physics 2007-05-23 F. Verstraete , J. I. Cirac

Optimization problems associated with the interaction of linked particles are at the heart of polymer science, protein folding and other important problems in the physical sciences. In this review we explain how to recast these problems as…

We propose a parallel algorithm for the numerical solution of a class of second order semi-linear equations coming from stochastic optimal control problems, by means of a dynamic domain decomposition technique. The new method is an…

Numerical Analysis · Mathematics 2016-02-11 Simone Cacace , Maurizio Falcone
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