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The DGEMM function is a widely used implementation of the matrix product. While the asymptotic complexity of the algorithm only depends on the sizes of the matrices, we show that the performance is significantly impacted by the matrices…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-12-12 Tom Cornebize , Arnaud Legrand

Modern quantum computers rely heavily on real-time control systems for operation. Software for these systems is becoming increasingly more complex due to the demand for more features and more real-time devices to control. Unfortunately,…

Quantum Physics · Physics 2022-11-30 Leon Riesebos , Kenneth R. Brown

This paper discusses an innovative adaptive heterogeneous fusion algorithm based on estimation of the mean square error of all variables used in real time processing. The algorithm is designed for a fusion between derivative and absolute…

Robotics · Computer Science 2017-01-27 Dusan Nemec , Ales Janota , Marian Hrubos , Vojtech Simak

Experiments in coherent nuclear and electron magnetic resonance,and quantum computing in general correspond to control of quantum mechanical systems, guiding them from initial to final target states by unitary transformations. The control…

Quantum Physics · Physics 2015-06-17 Haidong Yuan , Daxiu Wei , Yajuan Zhang , Steffen Glaser , Navin Khaneja

Understanding the spin-relaxation mechanism of single adatoms is an essential step towards creating atomic magnetic memory bits or even qubits. Here we present an essentially parameter-free theory by combining \textit{ab-initio} electronic…

Mesoscale and Nanoscale Physics · Physics 2023-04-26 Haritz Garai-Marin , Manuel dos Santos Dias , Samir Lounis , Julen Ibañez-Azpiroz , Asier Eiguren

The widespread proliferation of deep learning applications has triggered the need to accelerate them directly in hardware. General Matrix Multiplication (GEMM) kernels are elemental deep-learning constructs and they inherently map onto…

Hardware Architecture · Computer Science 2023-09-14 C. Peltekis , D. Filippas , G. Dimitrakopoulos , C. Nicopoulos

In this paper a library for spin--angular integration in LS-coupling for many-electron atoms is presented. The software is an implementation of a methodology based on the second quantization in coupled tensorial form, the angular momentum…

Atomic Physics · Physics 2007-05-23 G. Gaigalas

CPU scheduling has valiant effect on resource utilization as well as overall quality of the system. Round Robin algorithm performs optimally in time shared systems, but it performs more number of context switches, larger waiting time and…

Operating Systems · Computer Science 2015-06-17 Neetu Goel , R. B. Garg

Quantum computers are increasingly accessible, yet demonstrations of physically meaningful simulations for real materials remain scarce. In our work we simulate low-energy magnetic excitations, specifically spin-wave spectra, of chromium…

Laser-cooled and trapped atomic ions form an ideal standard for the simulation of interacting quantum spin models. Effective spins are represented by appropriate internal energy levels within each ion, and the spins can be measured with…

The conventional spin dynamics simulations are performed in direct products of state spaces of individual spins. In a general system of n spins, the total number of elements in the state basis is >4^n. A system propagation step requires an…

Computational Physics · Physics 2014-07-16 Ilya Kuprov , Nicola Wagner-Rundell , P. J. Hore

Simulation engines are widely adopted in robotics. However, they lack either full simulation control, ROS integration, realistic physics, or photorealism. Recently, synthetic data generation and realistic rendering has advanced tasks like…

Robotics · Computer Science 2023-05-29 Elia Bonetto , Chenghao Xu , Aamir Ahmad

Surface integral equation (SIE) methods are of great interest for the efficient electromagnetic modeling of various devices, from integrated circuits to antenna arrays. Existing acceleration algorithms for SIEs, such as the adaptive…

Computational Engineering, Finance, and Science · Computer Science 2021-07-13 Shashwat Sharma , Piero Triverio

The design and control of atomic-scale spin structures constitute major challenges for spin-based quantum technology platforms, including quantum dots, color centers, and molecular spins. Here, we showcase a strategy for designing the…

We establish efficient algorithms for weakly-interacting quantum spin systems at arbitrary temperature. In particular, we obtain a fully polynomial-time approximation scheme for the partition function and an efficient approximate sampling…

Quantum Physics · Physics 2026-01-30 Ryan L. Mann , Gabriel Waite

We study spin-1/2 fermions in spin dependent potentials under the \emph{spin model approximation}, in which interatomic collisions that change the total occupation of single-particle modes are ignored. The spin model approximation maps the…

Quantum Gases · Physics 2020-09-02 Michael L. Wall

Kohn-Sham density functional theory (DFT) is nowadays widely used for electronic structure theory simulations, and the accuracy and efficiency of DFT rely on approximations of the exchange-correlation functional. By inclusion of the kinetic…

Materials Science · Physics 2023-06-01 Renxi Liu , Daye Zheng , Xinyuan Liang , Xinguo Ren , Mohan Chen , Wenfei Li

An important requirement for a physical embodiment of a quantum computer is that arbitrary single-qubit operations can be performed. In the case of spin-qubits, this means that arbitrary spin rotations must be possible. Here we demonstrate…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 A. M. Tyryshkin , S. A. Lyon , W. Jantsch , F. Schaeffler

Ultrafast magnetization dynamics probes the most fundamental properties of magnetic materials, exploring questions about the fundamental interactions responsible for magnetic phenomena. Thermal effects are known to be extremely important…

Materials Science · Physics 2019-08-26 Daniel Meilak , Sarah Jenkins , Rory Pond , Richard F. L. Evans

Numerical simulation is an essential tool in many areas of science and engineering, but its performance often limits application in practice or when used to explore large parameter spaces. On the other hand, surrogate deep learning models,…

Machine Learning · Computer Science 2022-05-18 Mario Lino , Stati Fotiadis , Anil A. Bharath , Chris Cantwell