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We develop a range-separated stochastic resolution of identity approach for the $4$-index electron repulsion integrals, where the larger terms (above a predefined threshold) are treated using a deterministic resolution of identity and the…

Chemical Physics · Physics 2020-05-27 Wenjie Dou , Ming Chen , Tyler Y. Takeshita , Roi Baer , Daniel Neuhauser , Eran Rabani

This paper studies Difference-in-Differences (DiD) setups with repeated cross-sectional data and potential compositional changes across time periods. We begin our analysis by deriving the efficient influence function and the semiparametric…

Econometrics · Economics 2025-11-17 Pedro H. C. Sant'Anna , Qi Xu

The Dubna Gas-Filled Recoil Separator (DGFRS) is the mostly effective setup in use for the field of synthesis of superheavy elements. Application of DSSSD detector provides more precise energy and position detection for both implanted…

Instrumentation and Detectors · Physics 2015-07-31 Yu. Tsyganov

We assess a variant of linear-response range-separated time-dependent density-functional theory (TDDFT), combining a long-range Hartree-Fock (HF) exchange kernel with a short-range adiabatic exchange-correlation kernel in the local-density…

Chemical Physics · Physics 2013-05-22 Julien Toulouse , Elisa Rebolini , Tim Gould , John F. Dobson , Prasenjit Seal , János G. Angyán

Reduced density-matrix functional theory (RDMFT) has become an appealing alternative to density-functional theory to describe electronic properties of highly-correlated systems. Here we derive exact conditions for the suitability of RDMFT…

Strongly Correlated Electrons · Physics 2012-04-19 A. Putaja , E. Rasanen

A variant of consensus based distributed gradient descent (\textbf{DGD}) is studied for finite sums of smooth but possibly non-convex functions. In particular, the local gradient term in the fixed step-size iteration of each agent is…

Optimization and Control · Mathematics 2026-05-27 Lei Qin , Michael Cantoni , Ye Pu

Distributed Stein Variational Gradient Descent (DSVGD) is a non-parametric distributed learning framework for federated Bayesian learning, where multiple clients jointly train a machine learning model by communicating a number of non-random…

Machine Learning · Computer Science 2023-03-14 Jiarong Yang , Yuan Liu , Rahif Kassab

The performance of music source separation (MSS) models has been greatly improved in recent years thanks to the development of novel neural network architectures and training pipelines. However, recent model designs for MSS were mainly…

Audio and Speech Processing · Electrical Eng. & Systems 2022-10-03 Yi Luo , Jianwei Yu

We extend the previously proposed one-parameter double-hybrid density-functional theory [K. Sharkas, J. Toulouse, and A. Savin, J. Chem. Phys. 134, 064113 (2011)] to meta-generalized-gradient-approximation (meta-GGA) exchange-correlation…

Chemical Physics · Physics 2014-02-27 Sidi Ould Souvi , Kamal Sharkas , Julien Toulouse

The beryllium dimer and trimer are, despite their small number of electrons, excellent systems for assessing electronic-structure computational methods. With reference data provided by multi-reference averaged coupled-pair functional…

Chemical Physics · Physics 2018-09-25 Peter Reinhardt , Julien Toulouse , Andreas Savin

Multi-configuration range-separated density-functional theory is extended to the time-dependent regime. An exact variational formulation is derived. The approximation, which consists in combining a long-range…

Chemical Physics · Physics 2013-02-27 Emmanuel Fromager , Stefan Knecht , Hans Jørgen Aa. Jensen

A Full Duplex Base Station (FD-BS) can be used to serve simultaneously two Half-Duplex (HD) Mobile Stations (MSs), one working in the uplink and one in the downlink, respectively. The same functionality can be realized by having two…

Information Theory · Computer Science 2016-11-17 Henning Thomsen , Dong Min Kim , Petar Popovski , Nuno K. Pratas , Elisabeth de Carvalho

In this paper, we apply a specifically designed dissipative spatial filter as sub-grid scale model within the increasingly popular discontinuous Galerkin methods and the closely related flux reconstruction high order methods for large eddy…

Computational Engineering, Finance, and Science · Computer Science 2020-02-19 David G Flad , Andrea D Beck , Philipp Guthke

Standard density functional theory (DFT) routinely misclassifies the electronic ground state of correlated and structurally complex compounds, predicting metallic behaviour for materials that experiments report as semiconductors. Each such…

Materials Science · Physics 2026-04-30 Yue Li , Bijun Tang

Compared to the error diffusion, dot diffusion provides an additional pixel-level parallelism for digital halftoning. However, even though its periodic and blocking artifacts had been eased by previous works, it was still far from…

Multimedia · Computer Science 2015-10-28 Yun-Fu Liu , Jing-Ming Guo

We assess the performance of nonempirical, truly nonlocal and semi-local functionals with regard to structural and thermal properties of $3d$, $4d$, and $5d$ non-magnetic transition metals. We focus on constraint-based functionals and…

Materials Science · Physics 2021-01-14 Leili Gharaee , Paul Erhart , Per Hyldgaard

The journey of theoretical study on semiconductors is reviewed in a non-conventional way. We have started with the basic introduction of Hartree-Fock method and introduce the fundamentals of Density Functional Theory (DFT). From the oldest…

Materials Science · Physics 2021-05-04 Sujoy Datta , Debnarayan Jana

Photoabsorption in the low-energy region for C$_{60}$ and PTCDA molecular complexes is studied within linear response TDDFT. For the PBE, B3LYP and HSE exchange-correlation (xc) functionals the dependence of the accuracy of the exciton…

Mesoscale and Nanoscale Physics · Physics 2026-04-16 N. L. Matsko , Mahmoud A. Salem

This paper proposes SplitSGD, a new dynamic learning rate schedule for stochastic optimization. This method decreases the learning rate for better adaptation to the local geometry of the objective function whenever a stationary phase is…

Machine Learning · Statistics 2024-02-20 Matteo Sordello , Niccolò Dalmasso , Hangfeng He , Weijie Su

We show that the middle-range exchange-correlation hybrid of Henderson, Izmaylov, Scuseria and Savin (HISS) performs extremely well for elemental and binary semiconductors with narrow or visible spectrum band gaps, as well as some wider gap…

Materials Science · Physics 2012-04-27 Melissa J. Lucero , Thomas M. Henderson , Gustavo E. Scuseria
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