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We review some recent progress on applications of Cluster Expansions. We focus on a system of classical particles living in a continuous medium and interacting via a stable and tempered pair potential. We review the cluster expansion in…

Mathematical Physics · Physics 2023-04-26 Dimitrios Tsagkarogiannis

In this work, we extend the dual triply irreducible local expansion (D-TRILEX) approach for correlated electronic systems by introducing a cluster reference system for the diagrammatic expansion. This framework allows us to consistently…

Strongly Correlated Electrons · Physics 2026-02-26 Félix Fossati , Evgeny A. Stepanov

We apply the Tensor Train (TT) approximation to construct the Polynomial Chaos Expansion (PCE) of a random field, and solve the stochastic elliptic diffusion PDE with the stochastic Galerkin discretization. We compare two strategies of the…

Numerical Analysis · Mathematics 2014-06-12 Sergey Dolgov , Boris N. Khoromskij , Alexander Litvinenko , Hermann G. Matthies

Recent years have seen the development of two types of non-local extensions to the single-site dynamical mean field theory. On one hand, cluster approximations, such as the dynamical cluster approximation, recover short-range…

Strongly Correlated Electrons · Physics 2018-03-21 Sergei Iskakov , Hanna Terletska , Emanuel Gull

We present an unsupervised data processing workflow that is specifically designed to obtain a fast conformational clustering of long molecular dynamics simulation trajectories. In this approach we combine two dimensionality reduction…

Chemical Physics · Physics 2023-08-09 Simon Hunkler , Kay Diederichs , Oleksandra Kukharenko , Christine Peter

The coupled cluster method (CCM) is a method of quantum many-body theory that may provide accurate results for the ground-state properties of lattice quantum spin systems even in the presence of strong frustration and for lattices of…

Strongly Correlated Electrons · Physics 2009-11-11 D. J. J. Farnell , J. Schulenburg , J. Richter , K. A. Gernoth

Tensor contraction (TC) is an important computational kernel widely used in numerous applications. It is a multi-dimensional generalization of matrix multiplication (GEMM). While Strassen's algorithm for GEMM is well studied in theory and…

Mathematical Software · Computer Science 2017-04-12 Jianyu Huang , Devin A. Matthews , Robert A. van de Geijn

Quantum embedding methods have recently developed significantly to model large molecular structures. This work proposes a novel wave function theory in density functional theory (WTF-in-DFT) embedding scheme based on pair-coupled cluster…

Chemical Physics · Physics 2024-01-10 Rahul Chakraborty , Katharina Boguslawski , Paweł Tecmer

Modern high-performance computing architectures (Multicore, GPU, Manycore) are based on tightly-coupled clusters of processing elements, physically implemented as rectangular tiles. Their size and aspect ratio strongly impact the achievable…

Hardware Architecture · Computer Science 2022-09-05 Gianna Paulin , Matheus Cavalcante , Paul Scheffler , Luca Bertaccini , Yichao Zhang , Frank Gürkaynak , Luca Benini

We derive an adaptive hierarchical method of estimating high dimensional probability density functions. We call this method of density estimation the "adaptive cluster expansion" or ACE for short. We present an application of this approach,…

Neural and Evolutionary Computing · Computer Science 2010-12-17 Stephen Luttrell

We investigate the convergence of coupled-cluster correlation energies and related quantities with respect to the employed basis set size for the uniform electron gas to gain a better understanding of the basis set incompleteness error. To…

Materials Science · Physics 2024-02-27 Nikolaos Masios , Felix Hummel , Andreas Grüneis , Andreas Irmler

We propose an algorithm that aims at minimizing the inter-node communication volume for distributed and memory-efficient tensor contraction schemes on modern multi-core compute nodes. The key idea is to define processor grids that optimize…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-07-19 Andreas Irmler , Raghavendra Kanakagiri , Sebastian T. Ohlmann , Edgar Solomonik , Andreas Grüneis

Coupling of cluster and deformed structures are important for dynamics of nuclear structure. Threshold energy has been discussed to explain cluster structures coupling to deformed states but relation between threshold energy and excitation…

Nuclear Theory · Physics 2019-06-12 Yasutaka Taniguchi

The Atomic Cluster Expansion provides local, complete basis functions that enable efficient parametrization of many-atom interactions. We extend the Atomic Cluster Expansion to incorporate graph basis functions. This naturally leads to…

Materials Science · Physics 2024-01-23 Anton Bochkarev , Yury Lysogorskiy , Ralf Drautz

Density functional theory stems from the Hohenberg-Kohn-Sham-Mermin (HKSM) theorem in the grand canonical ensemble (GCE). However, as recent work shows, although its extension to the canonical ensemble (CE) is not straightforward, work in…

Statistical Mechanics · Physics 2009-11-07 J. A. Hernando

We report the formulation of a new, cost-effective approximation method in the time-dependent optimized coupled-cluster (TD-OCC) framework [T. Sato et al., J. Chem. Phys. 148, 051101 (2018)] for first-principles simulations of multielectron…

Chemical Physics · Physics 2022-08-11 Himadri Pathak , Takeshi Sato , Kenichi L. Ishikawa

A method to simulate local properties and processes in crystals with impurities via constructing cluster models within the frame of the compound-tunable embedding potential (CTEP) and highly-accurate {\it ab initio} relativistic…

Linked cluster expansions provide a useful tool for both analytical and numerical investigations of lattice field theories. The expansion parameter(s) being the interaction strength(s) fields at neighboured lattice sites are coupled, they…

High Energy Physics - Lattice · Physics 2009-10-28 Thomas Reisz

We present the working equations for a reduced-scaling method of evaluating the perturbative triples (T) energy in coupled-cluster theory, through the tensor hypercontraction (THC) of the triples amplitudes ($t_{ijk}^{abc}$). Through our…

Chemical Physics · Physics 2024-06-12 Andy Jiang , Justin M. Turney , Henry F. Schaefer

The central question in representation learning is what constitutes a good or meaningful representation. In this work we argue that if we consider data with inherent cluster structures, where clusters can be characterized through different…

Machine Learning · Computer Science 2022-12-05 Pascal Mattia Esser , Satyaki Mukherjee , Mahalakshmi Sabanayagam , Debarghya Ghoshdastidar