Ising Models for Solving the N-Queens Puzzle Based on the Domain-Wall Vectors

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Concurrency and Computation-Practice & Experience Pub Date : 2025-01-16 DOI:10.1002/cpe.8364
Shunsuke Tsukiyama, Koji Nakano, Yasuaki Ito, Takumi Kato, Yuya Kawamata
{"title":"Ising Models for Solving the N-Queens Puzzle Based on the Domain-Wall Vectors","authors":"Shunsuke Tsukiyama,&nbsp;Koji Nakano,&nbsp;Yasuaki Ito,&nbsp;Takumi Kato,&nbsp;Yuya Kawamata","doi":"10.1002/cpe.8364","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>An Ising model is a mathematical model defined by an objective function comprising a quadratic formula of multiple spin variables, each taking values of either <span></span><math>\n <semantics>\n <mrow>\n <mo>−</mo>\n <mn>1</mn>\n </mrow>\n <annotation>$$ -1 $$</annotation>\n </semantics></math> or <span></span><math>\n <semantics>\n <mrow>\n <mo>+</mo>\n <mn>1</mn>\n </mrow>\n <annotation>$$ +1 $$</annotation>\n </semantics></math>. The task of determining a spin value assignment to these variables that minimizes the resulting value of an Ising model is a challenging optimization problem. Recently, quantum annealers, consisting of qubit cells interconnected according to principles of quantum mechanics, have emerged as a solution for tackling such problems. Ising models characterized by fewer quadratic terms are preferable as they reduce the resource requirements of quantum annealers. Additionally, it is advantageous for the absolute values of coefficients associated with linear and quadratic terms to be small to facilitate the discovery of good solutions, given the inherent limitations in the resolution of quantum annealers. The primary contribution of this article lies in presenting Ising models tailored for solving the <span></span><math>\n <semantics>\n <mrow>\n <mi>n</mi>\n </mrow>\n <annotation>$$ n $$</annotation>\n </semantics></math>-Queens puzzle. The conventional Ising model for this puzzle involves <span></span><math>\n <semantics>\n <mrow>\n <mfrac>\n <mrow>\n <mn>5</mn>\n </mrow>\n <mrow>\n <mn>3</mn>\n </mrow>\n </mfrac>\n <msup>\n <mrow>\n <mi>n</mi>\n </mrow>\n <mrow>\n <mn>3</mn>\n </mrow>\n </msup>\n <mo>−</mo>\n <mn>2</mn>\n <msup>\n <mrow>\n <mi>n</mi>\n </mrow>\n <mrow>\n <mn>2</mn>\n </mrow>\n </msup>\n <mo>+</mo>\n <mfrac>\n <mrow>\n <mi>n</mi>\n </mrow>\n <mrow>\n <mn>3</mn>\n </mrow>\n </mfrac>\n </mrow>\n <annotation>$$ \\frac{5}{3}{n}^3-2{n}^2+\\frac{n}{3} $$</annotation>\n </semantics></math> quadratic terms, with the maximum absolute value of coefficients being <span></span><math>\n <semantics>\n <mrow>\n <mn>4</mn>\n <mi>n</mi>\n <mo>+</mo>\n <mo>(</mo>\n <mi>n</mi>\n <mspace></mspace>\n <mo>mod</mo>\n <mspace></mspace>\n <mn>2</mn>\n <mo>)</mo>\n <mo>−</mo>\n <mn>7</mn>\n </mrow>\n <annotation>$$ 4n+\\left(n\\kern0.2em \\operatorname{mod}\\kern0.2em 2\\right)-7 $$</annotation>\n </semantics></math>. Our novel Ising model significantly reduces the number of quadratic terms to only <span></span><math>\n <semantics>\n <mrow>\n <mn>12</mn>\n <msup>\n <mrow>\n <mi>n</mi>\n </mrow>\n <mrow>\n <mn>2</mn>\n </mrow>\n </msup>\n <mo>−</mo>\n <mn>24</mn>\n <mi>n</mi>\n <mo>+</mo>\n <mn>12</mn>\n </mrow>\n <annotation>$$ 12{n}^2-24n+12 $$</annotation>\n </semantics></math>, with a maximum absolute coefficient of 6. Furthermore, we provide embedding results for a quantum annealer D-Wave Advantage utilizing a Pegasus graph <span></span><math>\n <semantics>\n <mrow>\n <mi>P</mi>\n <mo>(</mo>\n <mn>16</mn>\n <mo>)</mo>\n </mrow>\n <annotation>$$ P(16) $$</annotation>\n </semantics></math>. We succeeded in embedding our novel Ising model for up to the 21-Queens puzzle, while the conventional Ising model can be embedded only for up to the 14-Queens puzzle.</p>\n </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 3","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Concurrency and Computation-Practice & Experience","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpe.8364","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0

Abstract

An Ising model is a mathematical model defined by an objective function comprising a quadratic formula of multiple spin variables, each taking values of either 1 $$ -1 $$ or + 1 $$ +1 $$ . The task of determining a spin value assignment to these variables that minimizes the resulting value of an Ising model is a challenging optimization problem. Recently, quantum annealers, consisting of qubit cells interconnected according to principles of quantum mechanics, have emerged as a solution for tackling such problems. Ising models characterized by fewer quadratic terms are preferable as they reduce the resource requirements of quantum annealers. Additionally, it is advantageous for the absolute values of coefficients associated with linear and quadratic terms to be small to facilitate the discovery of good solutions, given the inherent limitations in the resolution of quantum annealers. The primary contribution of this article lies in presenting Ising models tailored for solving the n $$ n $$ -Queens puzzle. The conventional Ising model for this puzzle involves 5 3 n 3 2 n 2 + n 3 $$ \frac{5}{3}{n}^3-2{n}^2+\frac{n}{3} $$ quadratic terms, with the maximum absolute value of coefficients being 4 n + ( n mod 2 ) 7 $$ 4n+\left(n\kern0.2em \operatorname{mod}\kern0.2em 2\right)-7 $$ . Our novel Ising model significantly reduces the number of quadratic terms to only 12 n 2 24 n + 12 $$ 12{n}^2-24n+12 $$ , with a maximum absolute coefficient of 6. Furthermore, we provide embedding results for a quantum annealer D-Wave Advantage utilizing a Pegasus graph P ( 16 ) $$ P(16) $$ . We succeeded in embedding our novel Ising model for up to the 21-Queens puzzle, while the conventional Ising model can be embedded only for up to the 14-Queens puzzle.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于域-壁向量求解N-Queens难题的Ising模型
伊辛模型是一个由目标函数定义的数学模型,目标函数包含多个自旋变量的二次公式,每个自旋变量的值为−1 $$ -1 $$或+ 1 $$ +1 $$。确定这些变量的自旋值分配以使Ising模型的结果值最小化的任务是一个具有挑战性的优化问题。最近,根据量子力学原理相互连接的量子位单元组成的量子退火器作为解决这些问题的解决方案出现了。以较少的二次项为特征的Ising模型更可取,因为它们减少了量子退火炉的资源需求。此外,考虑到量子退退器分辨率的固有限制,与线性项和二次项相关的系数的绝对值较小有利于发现好的解。本文的主要贡献在于提出了为解决n $$ n $$ -Queens难题而量身定制的Ising模型。这个谜题的传统Ising模型涉及到5 3 n 3−2n2 + n2 $$ \frac{5}{3}{n}^3-2{n}^2+\frac{n}{3} $$二次项,系数的最大绝对值为4n + (n mod 2)−7 $$ 4n+\left(n\kern0.2em \operatorname{mod}\kern0.2em 2\right)-7 $$。我们的新Ising模型显著减少了二次项的数量,仅为12 n 2−24 n + 12 $$ 12{n}^2-24n+12 $$,最大绝对系数为6。此外,我们利用Pegasus图P (16) $$ P(16) $$提供了量子退火器D-Wave Advantage的嵌入结果。我们成功地将新颖的Ising模型嵌入到21个皇后的谜题中,而传统的Ising模型只能嵌入到14个皇后的谜题中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
期刊最新文献
Additional-Processing-Free Multiparty Reversible Data Hiding Over Encrypted Domain A Novel Ensemble Machine Learning Approach for Interpretable Modeling, Feature Extraction and Selection With Applications to Medical and Biomedical Signals and Data NOA-RAC: An Enhanced Nutcracker Optimization Algorithm for Optimization Tasks CG-YOLOv11: A Smoke-Removal-Enhanced Target Detection Method for Indoor Smoke Scenes A Complexity Calculation Method for Large Scale Optimization With Evolutionary Algorithms and Metaheuristics
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1