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Tensor decompositions have rich applications in statistics and machine learning, and developing efficient, accurate algorithms for the problem has received much attention recently. Here, we present a new method built on Kruskal's uniqueness…

Machine Learning · Computer Science 2017-04-20 Miaoyan Wang , Yun S. Song

Within the framework of imaginary-time evolution for matrix product states, we introduce a cluster version of the infinite time-evolving block decimation algorithm for simulating quantum many-body systems, addressing the computational…

Strongly Correlated Electrons · Physics 2025-09-01 Tao Yang , Rui Wang , Z. Y. Xie , Baigeng Wang

Molecular fragment or embedding methods are powerful techniques for overcoming scalability limitations in electronic structure theory by dividing large molecular systems into individual units that are small enough to be treated using…

Chemical Physics · Physics 2017-08-14 Jason N. Byrd , Robert W. Molt, , Rodney J. Bartlett , Beverly A. Sanders

Modern smart distribution system requires storage, transmission and processing of big data generated by sensors installed in electric meters. On one hand, this data is essentially required for intelligent decision making by smart grid but…

Signal Processing · Electrical Eng. & Systems 2018-07-19 Syed Muhammad Atif , Anees Ahmed , Sameer Qazi

The accurate description of nuclear quantum effects, such as zero-point energy, is important for modeling a wide range of chemical and biological processes. Within the nuclear-electronic orbital (NEO) approach, such effects are incorporated…

Chemical Physics · Physics 2022-09-07 Fabijan Pavošević , Sharon Hammes-Schiffer

The coupled cluster method is considered a gold standard in quantum chemistry, reliably giving energies that are exact within chemical accuracy (1.6 mHartree). However, even in the CCSD approximation, where the cluster operator is truncated…

Chemical Physics · Physics 2023-03-10 Simon Elias Schrader , Simen Kvaal

We present a basis set correction scheme for the coupled-cluster singles and doubles (CCSD) method. The scheme is based on employing frozen natural orbitals (FNOs) and diagrammatically decomposed contributions to the electronic correlation…

Materials Science · Physics 2021-06-18 Andreas Irmler , Alejandro Gallo , Andreas Grüneis

We present a simple method for \emph{a posteriori} removal of a significant fraction of the density-fitting error from the calculated total coupled-cluster energies. The method treats the difference between the exact and density-fitted…

Chemical Physics · Physics 2020-02-20 Michał Lesiuk

Recently, there has been a lot of research into tensor singular value decomposition (t-SVD) by using discrete Fourier transform (DFT) matrix. The main aims of this paper are to propose and study tensor singular value decomposition based on…

Computer Vision and Pattern Recognition · Computer Science 2019-02-11 Wen-Hao Xu , Xi-Le Zhao , Michael Ng

Many real-world datasets are represented as tensors, i.e., multi-dimensional arrays of numerical values. Storing them without compression often requires substantial space, which grows exponentially with the order. While many tensor…

Machine Learning · Computer Science 2023-09-21 Taehyung Kwon , Jihoon Ko , Jinhong Jung , Kijung Shin

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has…

Materials Science · Physics 2026-04-01 Jacob Jeffries , Bochuan Sun , Enrique Martinez

We propose a strategy to compress and store large volumes of scientific data represented on unstructured grids. Approaches utilizing tensor decompositions for data compression have already been proposed. Here, data on a structured grid is…

Numerical Analysis · Mathematics 2024-09-23 Prashant Rai , Hemanth Kolla , Lewis Cannada , Alex Gorodetsky

When the number of strongly correlated electrons becomes larger, the single-reference coupled-cluster (CC) CCSD, CCSDT, etc. hierarchy displays an erratic behavior, while traditional multi-reference approaches may no longer be applicable…

Chemical Physics · Physics 2025-12-12 Ilias Magoulas , Jun Shen , Piotr Piecuch

We tackle the challenge of estimating grouping structures and factor loadings in asset pricing models, where traditional regressions struggle due to sparse data and high noise. Existing approaches, such as those using fused penalties and…

Methodology · Statistics 2025-12-30 Liyuan Cui , Guanhao Feng , Yuefeng Han , Jiayan Li

We present a massive-parallel implementation of the resolution-of-identity (RI) coupled-cluster approach that includes single, double and perturbatively triple excitations, namely RI-CCSD(T), in the FHI-aims package for molecular systems. A…

Computational Physics · Physics 2018-10-19 Tonghao Shen , Igor Ying Zhang , Matthias Scheffler

Modeling charge transfer well can require treating post-excitation orbital relaxations and handling medium to large molecules in realistic environments. By combining a state-specific correlation treatment with such orbital relaxations,…

Chemical Physics · Physics 2025-07-28 Harrison Tuckman , Eric Neuscamman

We consider evaluation of matrix elements with the coupled-cluster method. Such calculations formally involve infinite number of terms and we devise a method of partial summation (dressing) of the resulting series. Our formalism is built…

Atomic Physics · Physics 2009-11-10 Andrei Derevianko , Sergey Porsev

We present an ab initio study of electronically excited states of three-dimensional solids using Gaussian-based periodic equation-of-motion coupled-cluster theory with single and double excitations (EOM-CCSD). The explicit use of…

Materials Science · Physics 2020-01-31 Xiao Wang , Timothy C. Berkelbach

A new perturbative approach to canonical equation-of-motion coupled-cluster theory is presented using coupled-cluster perturbation theory. A second-order M{\o}ller-Plesset partitioning of the Hamiltonian is used to obtain the well known…

Chemical Physics · Physics 2015-07-09 Jason N. Byrd , Varun Rishi , Ajith Perera , Rodney J. Bartlett

We investigate the efficient combination of the canonical polyadic decomposition (CPD) and tensor hyper-contraction (THC) approaches. We first present a novel low-cost CPD solver which leverages a precomputed THC factorization of an…

Chemical Physics · Physics 2025-05-28 Karl Pierce , Miguel Morales
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