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Deep learning techniques have opened a new venue for electronic structure theory in recent years. In contrast to traditional methods, deep neural networks provide much more expressive and flexible wave function ansatz, resulting in better…

Chemical Physics · Physics 2021-09-08 Xiang Li , Cunwei Fan , Weiluo Ren , Ji Chen

A van der Waals (vdW) density functional was implemented in the mixed basis approach previously developed for studying two dimensional systems, in which the vdW interaction plays an important role. The basis functions here are taken to be…

Computational Physics · Physics 2017-12-27 Chung-Yuan Ren , Yia-Chung Chang , Chen-Shiung Hsue

Electroencephalography (EEG)-based brain-computer interfaces (BCIs) enable neural interaction by decoding brain activity for external communication. Motor imagery (MI) decoding has received significant attention due to its intuitive…

Signal Processing · Electrical Eng. & Systems 2025-08-01 Ziwei Wang , Siyang Li , Xiaoqing Chen , Dongrui Wu

Proper inclusion of van der Waals (vdW) interactions in theoretical simulations based on standard density functional theory (DFT) is crucial to describe the physics and chemistry of systems such as organic and layered materials. Many…

Materials Science · Physics 2023-07-19 Jinwoo Park , Byung Deok Yu , Suklyun Hong

This technical note presents a framework for investigating the underlying mechanisms of neurovascular coupling in the human brain using multi-modal magnetoencephalography (MEG) and functional magnetic resonance (fMRI) neuroimaging data.…

Quantitative Methods · Quantitative Biology 2019-03-19 Amirhossein Jafarian , Vladimir Litvak , Hayriye Cagnan , Karl J. Friston , Peter Zeidman

Electronic band structure (BS) and crystal structure are the two complementary identifiers of solid state materials. While convenient instruments and reconstruction algorithms have made large, empirical, crystal structure databases…

We introduce an electron-photon exchange-correlation functional for quantum electrodynamical density-functional theory (QEDFT). The approach, photon MBD (pMBD), is inspired by the many-body dispersion (MBD) method for weak intermolecular…

Chemical Physics · Physics 2025-12-23 Cankut Tasci , Leonardo A. Cunha , Johannes Flick

The atomic and electronic structures of Pd3N, PdN and PdN2 were investigated using ab initio density-functional theory (DFT). We studied cohesive energy vs. volume equation of states (EOS) for a set of reported and hypothetical structures.…

Materials Science · Physics 2013-10-11 Mohammed S. H. Suleiman , Daniel P. Joubert

We report a systematic study of the weak chemical bond between two benzene molecules. We first show that it is possible to obtain a very good description of the C_2 dimer and the benzene molecule, by using pseudopotentials for the…

Other Condensed Matter · Physics 2009-11-13 Sandro Sorella , Michele Casula , Dario Rocca

Density-functional theory is a formally exact description of a many-body quantum system in terms of its density; in practice, however, approximations to the universal density functional are required. In this work, a model based on deep…

Computational Physics · Physics 2016-08-02 Jeffrey M. McMahon

Obtaining an accurate ground state wave function is one of the great challenges in the quantum many-body problem. In this paper, we propose a new class of wave functions, neural network backflow (NNB). The backflow approach, pioneered…

Disordered Systems and Neural Networks · Physics 2019-06-19 Di Luo , Bryan K. Clark

Neural quantum states (NQS) provide a flexible and highly expressive parameterization of wave functions for strongly correlated problems in quantum chemistry. Despite rapid advances in network architectures, the evaluation of electronic…

Chemical Physics · Physics 2026-02-16 Marco Julian Solanki , Lexin Ding , Markus Reiher

We describe N-body networks, a neural network architecture for learning the behavior and properties of complex many body physical systems. Our specific application is to learn atomic potential energy surfaces for use in molecular dynamics…

Machine Learning · Computer Science 2018-03-06 Risi Kondor

Traditional image segmentation methods, such as variational models based on partial differential equations (PDEs), offer strong mathematical interpretability and precise boundary modeling, but often suffer from sensitivity to parameter…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Kaili Qi , Wenli Yang , Ye Li , Zhongyi Huang

We introduce the idea that the electronic band structure of a charge density wave system may mimic the electronic structure of graphene. In that case a class of materials quite different from graphene might be opened up to exploit…

Mesoscale and Nanoscale Physics · Physics 2017-11-22 John M. Vail , Oscar J. Hernandez , Ming-Su Si , Zhoufei Wang

Peridynamic (PD) theories have gained widespread diffusion among various research areas, due to the ability of modeling discontinuities formation and evolution in materials. Bond-Based Peridynamics (BB-PD), notwithstanding some modeling…

Numerical Analysis · Mathematics 2022-10-12 Nunzio Dimola , Alessandro Coclite , Giuseppe Fanizza , Tiziano Politi

Anatomical shape analysis plays a pivotal role in clinical research and hypothesis testing, where the relationship between form and function is paramount. Correspondence-based statistical shape modeling (SSM) facilitates population-level…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Jadie Adams , Krithika Iyer , Shireen Elhabian

Equilibrium polyethylene crystal structure, cohesive energy, and elastic constants are calculated by density-functional theory applied with a recently proposed density functional (vdW-DF) for general geometries [Phys. Rev. Lett. 92, 246401…

Materials Science · Physics 2009-11-11 Jesper Kleis , Bengt I. Lundqvist , David C. Langreth , Elsebeth Schroder

Density functional theory underlies the most successful and widely used numerical methods for electronic structure prediction of solids. However, it has the fundamental shortcoming that the universal density functional is unknown. In…

Disordered Systems and Neural Networks · Physics 2020-09-23 M. Michael Denner , Mark H. Fischer , Titus Neupert

Multicomponent methods are a conceptually simple way to include nuclear quantum effects into quantum chemistry calculations. In multicomponent methods, the electronic molecular orbitals are described using the linear combination of atomic…

Chemical Physics · Physics 2022-12-02 Irina Samsonova , Gabrielle B. Tucker , Naresh Alaal , Kurt R. Brorsen
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