在量子退火炉上建立弦模型

IF 5.6 3区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY
Steven Abel, Luca A. Nutricati, John Rizos
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引用次数: 0

摘要

首次探索了在量子退火炉上直接构造弦模型,并研究了它们在模型发现过程中的效率和有效性。通过与模拟退火、随机扫描和遗传算法等传统方法的全面比较,强调了量子退火提供的潜在优势,在本研究中承诺量子退火比随机扫描和遗传算法快约50倍,比模拟退火快约4倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

String Model Building on Quantum Annealers

String Model Building on Quantum Annealers

For the first time the direct construction of string models on quantum annealers has been explored and has been investigated their efficiency and effectiveness in the model discovery process. Through a thorough comparison with traditional methods such as simulated annealing, random scans, and genetic algorithms, it is highlighted the potential advantages offered by quantum annealers, which in this study promised to be roughly 50 times faster than random scans and genetic algorithm and approximately four times faster than simulated annealing.

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来源期刊
CiteScore
6.70
自引率
7.70%
发文量
75
审稿时长
6-12 weeks
期刊介绍: The journal Fortschritte der Physik - Progress of Physics is a pure online Journal (since 2013). Fortschritte der Physik - Progress of Physics is devoted to the theoretical and experimental studies of fundamental constituents of matter and their interactions e. g. elementary particle physics, classical and quantum field theory, the theory of gravitation and cosmology, quantum information, thermodynamics and statistics, laser physics and nonlinear dynamics, including chaos and quantum chaos. Generally the papers are review articles with a detailed survey on relevant publications, but original papers of general interest are also published.
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