English
Related papers

Related papers: adcc: A versatile toolkit for rapid development of…

200 papers

We present an object-oriented Python library for computation of properties of highly-excited Rydberg states of alkali atoms. These include single-body effects such as dipole matrix elements, excited-state lifetimes (radiative and black-body…

Atomic Physics · Physics 2018-05-21 N. Šibalić , J. D. Pritchard , C. S. Adams , K. J. Weatherill

We present a robust, ab initio method for addressing atom-light interactions and apply it to photoionization of argon. We use a close-coupling ansatz constructed on a multi-configurational Hartree-Fock description of localized states and…

Atomic Physics · Physics 2015-06-12 T. Carette , J. M. Dahlström , L. Argenti , E. Lindroth

Distributed computing is known as an emerging and efficient technique to support various intelligent services, such as large-scale machine learning. However, privacy leakage and random delays from straggling servers pose significant…

Information Theory · Computer Science 2023-10-31 Qicheng Zeng , Zhaojun Nan , Sheng Zhou

Analog Lagrange Coded Computing (ALCC) is a recently proposed coded computing paradigm wherein certain computations over analog datasets can be efficiently performed using distributed worker nodes through floating point implementation.…

Information Theory · Computer Science 2024-05-14 Rimpi Borah , J. Harshan

An overview is given of the QCDOC architecture, a massively parallel and highly scalable computer optimized for lattice QCD using system-on-a-chip technology. The heart of a single node is the PowerPC-based QCDOC ASIC, developed in…

High Energy Physics - Lattice · Physics 2007-05-23 P. A. Boyle , C. Jung , T. Wettig

An efficient excited state method, named xCDFCI, in the configuration interaction framework, is proposed. xCDFCI extends the unconstrained nonconvex optimization problem in coordinate descent full configuration interaction~(CDFCI) to a…

Chemical Physics · Physics 2023-08-23 Zhe Wang , Zhiyuan Zhang , Jianfeng Lu , Yingzhou Li

Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes. However, for large and comprehensive models, the computational cost of simulating or calibrating can be…

Quantitative Methods · Quantitative Biology 2023-11-29 Fabian Fröhlich , Daniel Weindl , Yannik Schälte , Dilan Pathirana , Łukasz Paszkowski , Glenn Terje Lines , Paul Stapor , Jan Hasenauer

We present analytic gradients and derivative couplings for the simplest possible multireference configuration interaction method, CIS-1D, an electronic structure ansatz that includes all single excitations and one lone double excitation on…

Chemical Physics · Physics 2021-02-15 Hung-Hsuan Teh , Joseph E. Subotnik

We present a neuromorphic Analogue-to-Digital Converter (ADC), which uses integrate-and-fire (I&F) neurons as the encoders of the analogue signal, with modulated inhibitions to decohere the neuronal spikes trains. The architecture consists…

Neural and Evolutionary Computing · Computer Science 2015-09-04 Ying Xu , Chetan Singh Thakur , Tara Julia Hamilton , Jonathan Tapson , Runchun Wang , Andre van Schaik

Arbitrary high order numerical methods for time-harmonic acoustic scattering problems originally defined on unbounded domains are constructed. This is done by coupling recently developed high order local absorbing boundary conditions (ABCs)…

Numerical Analysis · Mathematics 2020-06-17 Vianey Villamizar , Dane Grundvig , Otilio Rojas , Sebastian Acosta

A distributed computing scenario is considered, where the computational power of a set of worker nodes is used to perform a certain computation task over a dataset that is dispersed among the workers. Lagrange coded computing (LCC),…

Information Theory · Computer Science 2021-02-02 Mahdi Soleymani , Hessam Mahdavifar , A. Salman Avestimehr

This paper presents the new approach in implementation of analog-to-digital converter (ADC) that is based on Hopfield neural-network architecture. Hopfield neural ADC (NADC) is a type of recurrent neural network that is effective in solving…

Emerging Technologies · Computer Science 2018-01-03 Aigerim Tankimanova , Akshay Kumar Maan , Alex Pappachen James

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and…

Coded distributed computing (CDC) introduced by Li \emph{et al.} can greatly reduce the communication load for MapReduce computing systems. In the general cascaded CDC with $K$ workers, $N$ input files and $Q$ Reduce functions, each input…

Information Theory · Computer Science 2023-11-22 Minquan Cheng , Youlong Wu , Xianxian Li , Dianhua Wu

DIRAC is a freely distributed general-purpose program system for 1-, 2- and 4-component relativistic molecular calculations at the level of Hartree--Fock, Kohn--Sham (including range-separated theory), multiconfigurational…

In this study, an active disturbance rejection control (ADRC) toolbox for MATLAB/Simulink is introduced. Although ADRC has already been established as a powerful robust control framework with successful industrial implementations and strong…

Systems and Control · Electrical Eng. & Systems 2022-06-09 Krzysztof Lakomy , Wojciech Giernacki , Jacek Michalski , Rafal Madonski

We present a new theoretical approach for the simulations of X-ray photoelectron spectra of strongly correlated molecular systems that combines multireference algebraic diagrammatic construction theory (MR-ADC) [J. Chem. Phys., 2018, 149,…

Chemical Physics · Physics 2022-05-31 Carlos E. V. de Moura , Alexander Yu. Sokolov

Projected Hartree-Fock theory provides an accurate description of many kinds of strong correlations but does not properly describe weakly-correlated systems. On the other hand, single-reference methods such as configuration interaction or…

Strongly Correlated Electrons · Physics 2022-04-06 Ruiheng Song , Thomas M. Henderson , Gustavo E. Scuseria

The curse of dimensionality (COD) limits the current state-of-the-art {\it ab initio} propagation methods for non-relativistic quantum mechanics to relatively few particles. For stationary structure calculations, the coupled-cluster (CC)…

Quantum Physics · Physics 2015-06-03 Simen Kvaal

Dedicated tensor accelerators demonstrate the importance of linear algebra in modern applications. Such accelerators have the potential for impressive performance gains, but require programmers to rewrite code using vendor APIs - a barrier…