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Hamiltonian simulation using product formulas is arguably the most straightforward and practical approach for algorithmic simulation of a quantum system's dynamics on a quantum computer. Here we present corrected product formulas (CPFs), a…

Multi-label feature selection serves as an effective mean for dealing with high-dimensional multi-label data. To achieve satisfactory performance, existing methods for multi-label feature selection often require the centralization of…

Machine Learning · Computer Science 2024-08-28 Yukun Song , Dayuan Cao , Jiali Miao , Shuai Yang , Kui Yu

We introduce Hamiltonian Decoded Quantum Interferometry (HDQI), a quantum algorithm that utilizes coherent Bell measurements and the symplectic representation of the Pauli group to reduce Gibbs sampling and Hamiltonian optimization to…

Simulating fermionic systems on qubit-based quantum computers often demands significant computational resources due to the requirement to map fermions to qubits. Thus, designing a fault-tolerant quantum computer that operates directly with…

Quantum Physics · Physics 2026-02-19 Chong-Yuan Xu , Ze-Chuan Liu , Yong Xu

We present Polfed$.$jl, an open-source Julia package implementing the Polynomially Filtered Exact Diagonalization (POLFED) algorithm for computing mid-spectrum eigenvalues and eigenvectors (shortly, eigenpairs) of quantum many-body…

The increasing complexity and scale of photonic and electromagnetic devices demand efficient and accurate numerical solvers. In this work, we develop a parallel overlapping domain decomposition method (DDM) based on the finite-difference…

Optics · Physics 2025-09-26 Zhanwen Wang , Chengnian Huang , Wangtao Lu , Yuntian Chen , Wei E. I. Sha

Here is presented an original program based on molecular Schrodinger equations. It is dedicated to target specific states of infrared vibrational spectrum in a very precise way with a minimal usage of memory. An eigensolver combined with a…

Computational Physics · Physics 2018-07-26 Romain Garnier

We provide fast algorithms for simulating many body Fermi systems on a universal quantum computer. Both first and second quantized descriptions are considered, and the relative computational complexities are determined in each case. In…

Quantum Physics · Physics 2009-10-30 Daniel S. Abrams , Seth Lloyd

Strongly correlated fermionic systems are of great interest in condensed matter physics and numerical methods are indispensable tools for their study. However, existing approaches such as exact diagonalization (ED) and stochastic quantum…

Strongly Correlated Electrons · Physics 2026-03-19 Finn L. Temmen , Martina Gisti , David J. Luitz , Thomas Luu , Johann Ostmeyer

In this work, a new partition-collocation strategy for the parallel execution of CFD--DEM couplings is investigated. Having a good parallel performance is a key issue for an Eulerian-Lagrangian software that aims to be applied to solve…

Computational Engineering, Finance, and Science · Computer Science 2018-10-09 Gabriele Pozzetti , Xavier Besseron , Alban Rousset , Bernhard Peters

We present EDIpack, an exact diagonalization package to solve generic quantum impurity problems. The algorithm includes a generalization of the look-up method introduced in [Lin, Gubernatis Comput. Phys., 7 (4) (1993), 400] and enables a…

Computational Physics · Physics 2022-01-06 A. Amaricci , L. Crippa , A. Scazzola , F. Petocchi , G. Mazza , L. de Medici , M. Capone

Numerical modeling of nematic liquid crystals using the tensorial Landau-de Gennes (LdG) theory provides detailed insights into the structure and energetics of the enormous variety of possible topological defect configurations that may…

Soft Condensed Matter · Physics 2019-11-19 Daniel M. Sussman , Daniel A. Beller

This paper introduces a new discrete fracture model accounting for non-isothermal compositional multiphase Darcy flows and complex networks of fractures with intersecting, immersed and non immersed fractures. The so called…

Numerical Analysis · Mathematics 2017-07-13 Feng Xing , Roland Masson , Simon Lopez

Charge Coupled Devices (CCDs) have been successfully used in several high energy physics experiments over the past two decades. Their high spatial resolution and thin sensitive layers make them an excellent tool for studying short-lived…

This study addresses the challenge of simulating realistic particle systems by proposing a novel particle decomposition scheme that improves the parallel performance of surface resolved particle simulations. Realistic particle systems often…

Fluid Dynamics · Physics 2024-03-21 J. E. Marquardt , N. Hafen , M. J. Krause

Federated Learning aims to learn a global model on the server side that generalizes to all clients in a privacy-preserving manner, by leveraging the local models from different clients. Existing solutions focus on either regularizing the…

Machine Learning · Computer Science 2023-08-08 Zhuang Qi , Lei Meng , Zitan Chen , Han Hu , Hui Lin , Xiangxu Meng

Hyperdimensional computing (HDC) is an emerging computing paradigm that represents, manipulates, and communicates data using very long random vectors (aka hypervectors). Among different hardware platforms capable of executing HDC…

Hardware Architecture · Computer Science 2022-05-24 Robert Guirado , Abbas Rahimi , Geethan Karunaratne , Eduard Alarcón , Abu Sebastian , Sergi Abadal

The stochastic simulation of biological systems is an increasingly popular technique in bioinformatics. It often is an enlightening technique, which may however result in being computational expensive. We discuss the main opportunities to…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-17 Marco Aldinucci , Mario Coppo , Ferruccio Damiani , Maurizio Drocco , Massimo Torquati , Angelo Troina

Cross-Domain Collaborative Filtering (CDCF) provides a way to alleviate data sparsity and cold-start problems present in recommendation systems by exploiting the knowledge from related domains. Existing CDCF models are either based on…

Information Retrieval · Computer Science 2019-07-22 Vijaikumar M , Shirish Shevade , M N Murty

MiMiC is a framework for modeling large-scale chemical processes that require treatment at multiple resolutions. It does not aim to implement single-handedly all methods required to treat individual subsystems, but instead, it relegates…