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We have proposed a density-matrix renormalization group (DMRG) scheme to optimize the one-electron basis states of molecules. It improves significantly the accuracy and efficiency of the DMRG in the study of quantum chemistry or other…

Strongly Correlated Electrons · Physics 2010-10-20 H. -G. Luo , M. -P. Qin , T. Xiang

Residual Dipolar Couplings (RDCs) acquired by Nuclear Magnetic Resonance (NMR) spectroscopy can be an indispensable source of information in investigation of molecular structures and dynamics. Here we present a complete strategy for…

Numerical Analysis · Mathematics 2021-03-22 Casey A. Cole , Rishi Mukhapadhyay , Hanin Omar , Mirko Hennig , Homayoun Valafar

The variational determination of the two-fermion reduced density matrix is described for harmonically trapped, ultracold few-fermion systems in one dimension with equal spin populations. This is accomplished by formulating the problem as a…

Quantum Gases · Physics 2022-11-11 Mitchell J. Knight , Harry M. Quiney , Andy M. Martin

Reduced density-matrix functional theory (RDMFT) provides a variational route to electronic correlations beyond conventional density-functional approximations, but explicit evaluations of density-matrix functionals still scale exponentially…

Chemical Physics · Physics 2026-05-19 Konstantin Tamoev , Robert Schade , Thomas D. Kühne

High-resolution structure determination by cryo-electron microscopy (cryo-EM) requires the accurate fitting of an atomic model into an experimental density map. Traditional refinement pipelines such as Phenix.real_space_refine and Rosetta…

Biomolecules · Quantitative Biology 2026-03-10 Fuyao Huang , Xiaozhu Yu , Kui Xu , Qiangfeng Cliff Zhang

A promising approach to study condensed-matter systems is to simulate them on an engineered quantum platform. However, achieving the accuracy needed to outperform classical methods has been an outstanding challenge. Here, using eighteen…

In this paper, conditional denoising diffusion probabilistic models (DDPMs) are proposed to enhance the data transmission and reconstruction over wireless channels. The underlying mechanism of DDPM is to decompose the data generation…

Information Theory · Computer Science 2024-11-21 Mehdi Letafati , Samad Ali , Matti Latva-aho

Unified recombination cross sections and rates are computed for (e + Fe XVIII) --> Fe XVII including non-resonant and resonant (radiative and di-electronic recombination, RR and DR) processes in an ab initio manner with relativistic fine…

Astrophysics · Physics 2009-10-31 Anil K. Pradhan , Sultana N. Nahar , Hong Lin Zhang

High-fidelity electron microscopy simulations required for quantitative crystal structure refinements face a fundamental challenge: while physical interactions are well-described theoretically, real-world experimental effects are…

Two-dimensional angular correlation of annihilation radiation (2D-ACAR) and Compton scattering are both powerful techniques to investigate the bulk electronic structure of crystalline solids through the momentum density of the electrons.…

Electron microscopy (EM) images exhibit anisotropic axial resolution due to the characteristics inherent to the imaging modality, presenting challenges in analysis and downstream tasks.In this paper, we propose a diffusion-model-based…

Computer Vision and Pattern Recognition · Computer Science 2023-08-04 Kyungryun Lee , Won-Ki Jeong

This study presents a noise-robust framework for 1-bit diffraction tomography, a novel imaging approach that relies on intensity-only binary measurements obtained through coded apertures. The proposed reconstruction scheme leverages random…

Information Theory · Computer Science 2025-05-27 Pengwen Chen , Albert Fannjiang

The weakness of electron-electron correlations in the itinerant antiferromagnet Cr doped with V has long been considered the reason that neither new collective electronic states or even non Fermi liquid behaviour are observed when…

Strongly Correlated Electrons · Physics 2014-08-13 D. A. Sokolov , M. C. Aronson , L. Wu , Y. Zhu , C. Nelson , J. F. Mansfield , K. Sun , R. Erwin , J. W. Lynn , M. Lumsden , S. E. Nagler

The Ragot-Cortona model of local correlation energy (J. Chem. Phys. 121, 7671 (2004)) revisits the initial approach of Colle and Salvetti [Theo. Chim. Acta 37, 329 (1975)] in order to reinstate the kinetic contribution Tc to the total…

Chemical Physics · Physics 2015-05-14 Sebastien Ragot

The density matrix renormalization group (DMRG) method allows an efficient computation of the properties of interacting 1D quantum systems. Two-dimensional (2D) systems, capable of displaying much richer quantum behavior, generally lie…

Strongly Correlated Electrons · Physics 2014-08-06 Samuel Moukouri , Eytan Grosfeld

Model-free data-driven computational mechanics (DDCM) is a new paradigm for simulations in solid mechanics. The modeling step associated to the definition of a material constitutive law is circumvented through the introduction of an…

Materials Science · Physics 2023-10-23 Sacha Wattel , Jean-François Molinari , Michael Ortiz , Joaquin Garcia-Suarez

Single-particle cryo-electron microscopy (cryo-EM) has recently joined X-ray crystallography and NMR spectroscopy as a high-resolution structural method to resolve biological macromolecules. In a cryo-EM experiment, the microscope produces…

Information Theory · Computer Science 2022-10-28 Tamir Bendory , Nicolas Boumal , William Leeb , Eitan Levin , Amit Singer

A fundamental problem in applying machine learning techniques for chemical problems is to find suitable representations for molecular and crystal structures. While the structure representations based on atom connectivities are prevalent for…

Machine Learning · Statistics 2016-08-23 Dipti Jasrasaria , Edward O. Pyzer-Knapp , Dmitrij Rappoport , Alan Aspuru-Guzik

The Density Matrix Renormalization Group (DMRG) method has become a prominent tool for simulating strongly correlated electronic systems characterized by dominant static correlation effects. However, capturing the full scope of electronic…

Chemical Physics · Physics 2024-11-13 Nicholas Bauman , Libor Veis , Karol Kowalski , Jiri Brabec

A restricted Boltzmann machine (RBM) is a two-layer neural network with shared weights and has been extensively studied for dimensionality reduction, data representation and recommendation systems in the literature. The traditional RBM…

Machine Learning · Computer Science 2026-05-27 Jiangsheng You , Chun-Yen Liu
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