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The suitability of the QDL method for analyzing the performance of ac power systems has been evaluated by application to a microgrid. The QDL method is based on a combination of Quantized State Systems (QSS) methods and the Latency…

系统与控制 · 电气工程与系统科学 2023-02-28 Navid Gholizadeh , Joseph M. Hood , Roger A. Dougal

Monte Carlo simulations applied to the lattice formulation of quantum chromodynamics (QCD) enable a study of the theory from first principles, in a nonperturbative way. After over two decades of developments in the methodology for this…

高能物理 - 格点 · 物理学 2007-05-23 Tereza Mendes

Achieving high-performance computation on quantum systems presents a formidable challenge that necessitates bridging the capabilities between quantum hardware and classical computing resources. This study introduces an innovative…

量子物理 · 物理学 2024-03-19 Kuan-Cheng Chen , Xiaoren Li , Xiaotian Xu , Yun-Yuan Wang , Chen-Yu Liu

We discuss the physics and computation of lattice QCD, a space-time lattice formulation of quantum chromodynamics, and Kenneth Wilson's seminal role in its development. We start with the fundamental issue of confinement of quarks in the…

高能物理 - 格点 · 物理学 2015-06-23 Akira Ukawa

Deploying large language models (LLMs) on edge devices is crucial for delivering fast responses and ensuring data privacy. However, the limited storage, weight, and power of edge devices make it difficult to deploy LLM-powered applications.…

硬件体系结构 · 计算机科学 2025-06-04 Chunlin Tian , Xinpeng Qin , Kahou Tam , Li Li , Zijian Wang , Yuanzhe Zhao , Minglei Zhang , Chengzhong Xu

Building upon the PDFSense framework developed in Ref. [1], we perform a comprehensive analysis of the sensitivity of present and future high-energy data to a number of quantities commonly evaluated in lattice gauge theory, with a…

高能物理 - 唯象学 · 物理学 2021-06-15 T. J. Hobbs , Bo-Ting Wang , Pavel M. Nadolsky , Fredrick I. Olness

Today, many scientific and engineering areas require high performance computing to perform computationally intensive experiments. For example, many advances in transport phenomena, thermodynamics, material properties, computational…

分布式、并行与集群计算 · 计算机科学 2016-07-15 K. G. Kapanova , J. M. Sellier

The current trend of technology has brought parallel machines equipped with multiple processors and multiple memory sockets to be available off-the-shelf -- or via renting through Iaas Clouds -- at reasonable costs. This has opened the…

分布式、并行与集群计算 · 计算机科学 2025-03-26 Romolo Marotta , Francesco Quaglia

In this work, we investigate the effect of decomposition basis on primitive qudit gates on superconducting radio-frequency cavity-based quantum computers with applications to lattice gauge theory. Three approaches are tested: SNAP &…

量子物理 · 物理学 2024-10-23 Doga Murat Kürkçüoglu , Henry Lamm , Andrea Maestri

If a quantum computer is stabilized by fault-tolerant quantum error correction (QEC), then most of its resources (qubits and operations) are dedicated to the extraction of error information. Analysis of this process leads to a set of…

量子物理 · 物理学 2007-05-23 Andrew M. Steane

Systolic arrays and shared-L1-memory manycore clusters are commonly used architectural paradigms that offer different trade-offs to accelerate parallel workloads. While the first excel with regular dataflow at the cost of rigid…

硬件体系结构 · 计算机科学 2024-04-25 Sergio Mazzola , Samuel Riedel , Luca Benini

Lattice Quantum Chromodynamics (Lattice QCD) is a quantum field theory on a finite discretized space-time box so as to numerically compute the dynamics of quarks and gluons to explore the nature of subatomic world. Solving the equation of…

计算物理 · 物理学 2017-10-02 Taisuke Boku , Ken-Ichi Ishikawa , Yoshinobu Kuramashi , Lawrence Meadows

The Lattice Boltzmann Method (LBM) is a computational technique of Computational Fluid Dynamics (CFD) that has gained popularity due to its high parallelism and ability to handle complex geometries with minimal effort. Although LBM…

分布式、并行与集群计算 · 计算机科学 2024-09-26 Luigi Crisci , Biagio Cosenza , Giorgio Amati , Matteo Turisini

Over the recent years, the relatively young field of quantum simulation of lattice gauge theories - aiming at implementing simulators of gauge theories with quantum platforms, has gone through a rapid development process. It is now of…

量子物理 · 物理学 2022-01-12 Erez Zohar

For computational fluid dynamics (CFD) applications with a large number of grid points/cells, parallel computing is a common efficient strategy to reduce the computational time. How to achieve the best performance in the modern…

性能 · 计算机科学 2018-03-12 Yong-Xian Wang , Li-Lun Zhang , Wei Liu , Xing-Hua Cheng , Yu Zhuang , Anthony T. Chronopoulos

Critical goals of scientific computing are to increase scientific rigor, reproducibility, and transparency while keeping up with ever-increasing computational demands. This work presents an integrated framework well-suited for data…

分布式、并行与集群计算 · 计算机科学 2023-10-13 Paul Nuyujukian

Simulations based on particle methods, such as Smoothed Particle Hydrodynamics (SPH), are known to be computationally demanding. While such methods have for long been executed in parallel on multi-core CPUs, in recent years the increasing…

计算工程、金融与科学 · 计算机科学 2026-03-18 Xiangyu Hu , Alberto Guarnieri

Fault-tolerant quantum computing requires classical hardware to perform the decoding necessary for error correction. The Union-Find decoder is one of the best candidates for this. It has remarkably organic characteristics, involving the…

量子物理 · 物理学 2023-11-15 Tim Chan , Simon C. Benjamin

We investigate implementation of lattice Quantum Chromodynamics (QCD) code on the Intel AVX-512 architecture. The most time consuming part of the numerical simulations of lattice QCD is a solver of linear equation for a large sparse matrix…

高能物理 - 格点 · 物理学 2018-11-05 Issaku Kanamori , Hideo Matsufuru

As transistor counts in a single chip exceed tens of billions, the complexity of RTL-level simulation and verification has grown exponentially, often extending simulation campaigns to several months. In industry practice, RTL simulation is…

硬件体系结构 · 计算机科学 2025-09-04 Weigang Feng , Yijia Zhang , Zekun Wang , Zhengyang Wang , Yi Wang , Peijun Ma , Ningyi Xu
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