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A major difficulty in quantum simulation is the adequate treatment of a large collection of entangled particles, synonymous with electron correlation in electronic structure theory, with coupled cluster (CC) theory being the leading…

Chemical Physics · Physics 2024-06-06 Zachary W. Windom , Daniel Claudino , Rodney J. Bartlett

The relative energies of different phases or polymorphs of molecular solids can be small, less than a kiloJoule/mol. Reliable description of such energy differences requires high quality treatment of electron correlations, typically beyond…

Chemical Physics · Physics 2024-02-19 Khanh Ngoc Pham , Marcin Modrzejewski , Jiří Klimeš

This article aims to seek a selection and estimation procedure for a class of tensor regression problems with multivariate covariates and matrix responses, which can provide theoretical guarantees for model selection in finite samples.…

Statistics Theory · Mathematics 2023-10-10 Yang Chen , Ziyan Luo

Adaptive stretching, where the post compression signal is iteratively stretched to maximize the correlation between the pre and post compression rf echo frames, has demonstrated superior performance compared to gradient based methods. At…

Tissues and Organs · Quantitative Biology 2022-10-25 Shaiban Ahmed , Rasheed Abid , S. Kaisar Alam

We consider a variant of regression problem, where the correspondence between input and output data is not available. Such shuffled data is commonly observed in many real world problems. Taking flow cytometry as an example, the measuring…

Machine Learning · Computer Science 2021-02-12 Yujia Xie , Yixiu Mao , Simiao Zuo , Hongteng Xu , Xiaojing Ye , Tuo Zhao , Hongyuan Zha

In chemical processing and bioprocessing, conventional online sensors are limited to measure only basic process variables like pressure and temperature, pH, dissolved O and CO$_2$ and viable cell density (VCD). The concentration of other…

Quantitative Methods · Quantitative Biology 2020-05-07 Semion Rozov

We introduce an algorithm that is simultaneously memory-efficient and low-scaling for applying ab initio molecular Hamiltonians to matrix-product states (MPS) via the tensor-hypercontraction (THC) format. These gains carry over to Krylov…

Strongly Correlated Electrons · Physics 2025-11-19 Yu Wang , Maxine Luo , Matthias Reumann , Christian B. Mendl

For molecules and solids, we developed efficient MPI-parallel algorithms for evaluating the second-order exchange term with bare, statically screened, and dynamically screened interactions. We employ the resulting term in a fully…

Strongly Correlated Electrons · Physics 2024-12-30 Pavel Pokhilko , Chia-Nan Yeh , Miguel A. Morales , Dominika Zgid

Coupled-cluster theory with single and double excitations (CCSD) is a promising ab initio method for the electronic structure of three-dimensional metals, for which second-order perturbation theory (MP2) diverges in the thermodynamic limit.…

Materials Science · Physics 2021-06-16 James M. Callahan , Malte F. Lange , Timothy C. Berkelbach

We present regression and compression algorithms for lattice QCD data utilizing the efficient binary optimization ability of quantum annealers. In the regression algorithm, we encode the correlation between the input and output variables…

High Energy Physics - Lattice · Physics 2021-12-07 Boram Yoon , Chia Cheng Chang , Garrett T. Kenyon , Nga T. T. Nguyen , Ermal Rrapaj

We consider the rank-reduced coupled-cluster theory with single and double excitations (RR-CCSD) introduced recently [Parrish \emph{et al.}, J. Chem. Phys. {\bf 150}, 164118 (2019)]. The main feature of this method is the decomposed form of…

Chemical Physics · Physics 2022-02-21 Michał Lesiuk

In this paper, we adapt triplet neural networks (TNNs) to a regression task, music emotion prediction. Since TNNs were initially introduced for classification, and not for regression, we propose a mechanism that allows them to provide…

Sound · Computer Science 2020-07-22 Kin Wai Cheuk , Yin-Jyun Luo , Balamurali B , T , Gemma Roig , Dorien Herremans

High dimensional integration is essential to many areas of science, ranging from particle physics to Bayesian inference. Approximating these integrals is hard, due in part to the difficulty of locating and sampling from regions of the…

Machine Learning · Statistics 2020-05-25 Thomas Foster , Chon Lok Lei , Martin Robinson , David Gavaghan , Ben Lambert

High-dimensional linear regression under heavy-tailed noise or outlier corruption is challenging, both computationally and statistically. Convex approaches have been proven statistically optimal but suffer from high computational costs,…

Statistics Theory · Mathematics 2023-05-11 Yinan Shen , Jingyang Li , Jian-Feng Cai , Dong Xia

In computational homogenization, a fast solution of the microscopic problem can be achieved by model order reduction in combination with hyper-reduction. Such a technique, which has recently been proposed in the context of magnetostatics,…

Computational Physics · Physics 2025-01-24 Stephan Wulfinghoff , Jan Hauck

Tensor decompositions are promising tools for big data analytics as they bring multiple modes and aspects of data to a unified framework, which allows us to discover complex internal structures and correlations of data. Unfortunately most…

Numerical Analysis · Computer Science 2014-12-30 Guoxu Zhou , Andrzej Cichocki , Shengli Xie

Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to…

Chemical Physics · Physics 2023-04-14 Raghunathan Ramakrishnan , Pavlo O. Dral , Matthias Rupp , O. Anatole von Lilienfeld

A complete calculation of the ${\cal O}(\alpha_s^4)$ perturbative QCD corrections to the hadronic decay width of the $Z$-boson has recently been performed by Baikov et al.[1]. In their analysis, Baikov et al. relied on the conventional…

High Energy Physics - Phenomenology · Physics 2014-08-29 Sheng-Quan Wang , Xing-Gang Wu , Stanley J. Brodsky

In high-energy particle physics, complex Monte Carlo (MC) simulations are needed to compare theory predictions to measurable quantities. Many and large MC samples are needed to be generated to take into account all the systematics.…

High Energy Physics - Experiment · Physics 2022-11-15 Valentina Guglielmi

High-throughput characterization often requires estimating parameters and model dimension from experimental data of limited quantity and quality. Such data may result in an ill-posed inverse problem, where multiple sets of parameters and…

Quantum Physics · Physics 2026-04-08 Abigail N. Poteshman , Jiwon Yun , Tim H. Taminiau , Giulia Galli
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