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We present optimized tight-binding models with atomic orbitals to improve \textit{ab initio} tight-binding models constructed by truncating full density functional theory (DFT) Hamiltonian based on localized orbitals. Retaining qualitative…

Mesoscale and Nanoscale Physics · Physics 2024-02-20 Sejoong Kim

This work presents the formalism and implementation of excited state nuclear forces within density functional linear response theory (TDDFT) using a plane wave basis set. An implicit differentiation technique is developed for computing…

Other Condensed Matter · Physics 2009-11-11 Nikos L. Doltsinis , D. S. Kosov

Dynamical mean field theory (DMFT) combined with the local density approximation (LDA) is widely used in solids to predict properties of correlated systems. In this paper, its application to one of the simplest strongly correlated systems,…

Strongly Correlated Electrons · Physics 2015-05-18 Juho Lee , Kristjan Haule

Density functional theory (DFT) is an exact alternative formulation of quantum mechanics, in which it is possible to calculate the total energy, the spin and the charge density of many-electron systems in the ground state. In practice, it…

Atomic Physics · Physics 2014-03-25 Uri Argaman , Guy Makov , Eli Kraisler

We present an orbital-resolved extension of the Hubbard $U$ correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly…

Materials Science · Physics 2024-09-18 Eric Macke , Iurii Timrov , Nicola Marzari , Lucio Colombi Ciacchi

Deep learning has been recently applied to physical layer processing in digital communication systems in order to improve end-to-end performance. In this work, we introduce a novel deep learning solution for soft bit quantization across…

Signal Processing · Electrical Eng. & Systems 2021-10-20 Marius Arvinte , Jonathan I. Tamir

We study the accuracy of Kohn-Sham density functional theory (DFT) for warm- and hot-dense matter (WDM and HDM). Specifically, considering a wide range of systems, we perform accurate ab initio molecular dynamics simulations with…

Computational Physics · Physics 2024-11-21 Phanish Suryanarayana , Arpit Bhardwaj , Xin Jing , Shashikant Kumar , John E. Pask

The Forward-Forward (FF) algorithm presents a compelling, bio-inspired alternative to backpropagation. However, while efficient in training, it has a computationally prohibitive inference process that requires a separate forward pass for…

Machine Learning · Computer Science 2026-05-04 Shalini Sarode , Brian Moser , Joachim Folz , Federico Raue , Tobias Nauen , Stanislav Frolov , Andreas Dengel

Electronic band structure is a cornerstone of condensed matter physics and materials science. Conventional methods like Wannier interpolation (WI), which are commonly used to interpolate band structures onto dense k-point grids, often…

Materials Science · Physics 2025-06-04 Kai Wu , Yingzhou Li , Wentiao Wu , Lin Lin , Wei Hu , Jinlong Yang

A method is presented, which employs the density matrix renormalization group technique in order to construct exact ground state exchange correlation functionals for models of correlated electron systems coupled to external reservoirs. The…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Peter Schmitteckert , Ferdinand Evers

Screened spherical wave (SSW) of the Hankel function features the complete, minimal and short-ranged basis set, presenting a compact representation for electronic systems. In this work, we report the implementation of full-potential (FP)…

Materials Science · Physics 2025-03-11 Aixia Zhang , Qingyun Zhang , Zhiyi Chen , Yong Wu , Youqi Ke

Orbital-Free Density Functional Theory (OFDFT) has re-emerged as a viable alternative to Kohn-Sham DFT, driven by recent advances in kinetic energy density functionals (KEDFs). Nonlocal (NL) KEDFs have significantly extended OFDFT's…

Materials Science · Physics 2025-12-24 Abhishek Bhattacharjee , Hemanadhan Myneni , Manoj K. Harbola , Prasanjit Samal

Density functional theory (DFT) underpins modern atomistic simulations of transition-metal surfaces. It can predict key properties linked to catalytic performance, such as adsorption energies and barrier heights, enabling new paradigms in…

Materials Science · Physics 2026-03-23 Benjamin X. Shi , Timothy C. Berkelbach

While standard computational protocols for density functional theory (DFT) have universal applicability, differences exist in code implementations. Specific applications require manual parameter optimization, whereas high-throughput…

Materials Science · Physics 2025-08-12 Chenxi Lu , Musen Li , Jeffrey R. Reimers

We report a local, weight-dependent correlation density-functional approximation that incorporates information about both ground and excited states in the context of density-functional theory for ensembles (eDFT). This density-functional…

Chemical Physics · Physics 2020-06-05 Pierre-François Loos , Emmanuel Fromager

Hydrogen bonding is an important non-covalent interaction that plays a major role in molecular self-organization and supramolecular structures. It can be described accurately with ab initio quantum chemical wave function methods, which…

Chemical Physics · Physics 2025-05-16 Usman Ahmed , Mikael P. Johansson , Susi Lehtola , Dage Sundholm

We introduce a deep learning (DL) based network and an associated exact recovery theory for imaging from intensity-only measurements. The network architecture uses a recurrent structure that unrolls the Wirtinger Flow (WF) algorithm with a…

Signal Processing · Electrical Eng. & Systems 2022-10-13 Samia Kazemi , Bariscan Yonel , Birsen Yazici

Linear-response time-dependent (TD) density-functional theory (DFT) has been implemented in the pseudopotential wavelet-based electronic structure program BigDFT and results are compared against those obtained with the all-electron…

Seismic full-waveform inversion (FWI) techniques aim to find a high-resolution subsurface geophysical model provided with waveform data. Some recent effort in data-driven FWI has shown some encouraging results in obtaining 2D velocity maps.…

Machine Learning · Computer Science 2022-05-04 Qili Zeng , Shihang Feng , Brendt Wohlberg , Youzuo Lin

Accurate computational predictions of metal-organic frameworks (MOFs) and their properties is crucial for discovering optimal compositions and applying them in relevant technological areas. This work benchmarks density functional theory…

Materials Science · Physics 2025-03-11 Joshua Edzards , Julia Santana Andreo , Holger-Dietrich Saßnick , Caterina Cocchi