检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

64 篇 期刊文献
28 篇 会议

馆藏范围

92 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

65 篇 工学
- 50 篇 计算机科学与技术...
- 18 篇 电气工程
- 11 篇 信息与通信工程
- 6 篇 软件工程
- 4 篇 动力工程及工程热...
- 3 篇 电子科学与技术（可...
- 3 篇 化学工程与技术
- 2 篇 力学（可授工学、理...
- 2 篇 控制科学与工程
- 2 篇 土木工程
- 2 篇 石油与天然气工程
- 1 篇 机械工程
- 1 篇 材料科学与工程（可...
- 1 篇 测绘科学与技术
40 篇 理学
- 26 篇 物理学
- 13 篇 数学
- 1 篇 化学
- 1 篇 地理学
15 篇 管理学
- 15 篇 管理科学与工程(可...
2 篇 医学
- 2 篇 临床医学
- 1 篇 基础医学(可授医学...
1 篇 经济学
- 1 篇 理论经济学
1 篇 法学
- 1 篇 法学

主题

92 篇 quadratic uncons...
28 篇 quantum annealin...
21 篇 quantum computin...
12 篇 ising model
9 篇 optimization
9 篇 ising machine
8 篇 combinatorial op...
8 篇 combinatorial op...
7 篇 annealing
7 篇 quantum approxim...
5 篇 quantum optimiza...
5 篇 integer programm...
5 篇 heuristics
4 篇 pseudo-boolean o...
4 篇 digital annealer
4 篇 adiabatic quantu...
4 篇 adiabatic quantu...
3 篇 d-wave
3 篇 discrete optimiz...
3 篇 linear programmi...

机构

4 篇 waseda univ dept...
3 篇 waseda univ gree...
3 篇 waseda univ gree...
3 篇 waseda univ dept...
3 篇 politecn torino ...
2 篇 city univ hong k...
2 篇 syracuse univ de...
2 篇 rutgers state un...
2 篇 toyota cent res ...
2 篇 missouri western...
2 篇 los alamos natl ...
2 篇 beihang univ ins...
2 篇 delft univ techn...
2 篇 city univ hong k...
2 篇 univ porto fac s...
2 篇 univ porto fac s...
2 篇 beijing qboson q...
1 篇 entanglement inc...
1 篇 software archite...
1 篇 khalifa univ ctr...

作者

7 篇 togawa nozomu
6 篇 tanaka shu
5 篇 volpe deborah
4 篇 baioletti marco
4 篇 turvani giovanna
3 篇 lewis mark
3 篇 santini francesc...
3 篇 linnhoff-popien ...
3 篇 glover fred
3 篇 cirillo giovanni...
2 篇 silva carla
2 篇 wang xiaojun
2 篇 dutra ines
2 篇 deng zhipeng
2 篇 matsumori tadayo...
2 篇 wen kai
2 篇 wang zhenghuan
2 篇 kawamura kazushi
2 篇 wang xuezheng
2 篇 hammer peter l.

语言

86 篇 英文
6 篇 其他

检索条件"主题词=quadratic unconstrained binary optimization"

共 92 条记录，以下是61-70 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Solving Max-3SAT Using QUBO Approximation 5

Solving Max-3SAT Using QUBO Approximation

引用

2024 International Conference on Quantum Computing and Engineering

作者： Zielinski, Sebastian Nuesslein, Jonas Koelle, Michael Gabor, Thomas Linnhoff-Popien, Claudia Feld, Sebastian Ludwig Maximilians Univ Munchen Inst Informat Munich Germany Delft Univ Technol Quantum & Comp Engn Delft Netherlands

ISBN: (纸本)9798331541378

As contemporary quantum computers do not possess error correction, any calculation performed by these devices can be considered an involuntary approximation. To solve a problem on a quantum annealer, it has to be expressed as an instance of quadratic unconstrained binary optimization (QUBO). In this work, we thus study whether systematically approximating QUBO representations of the MAX-3SAT problem can improve the solution quality when solved on contemporary quantum hardware, compared to using exact, non-approximated QUBO representations. For a MAX-3SAT instance consisting of a 3SAT formula with n variables and m clauses, we propose a method of systematically creating approximate QUBO representations of dimension (nxn), which is significantly smaller than the QUBO matrices of any exact, non-approximated MAX-3SAT QUBO transformation. In an empirical evaluation, we demonstrate that using our QUBO approximations for solving MAX-3SAT problems on D-Wave's quantum annealer Advantage System6.4 can yield better results than using state-of-the-art exact QUBO transformations. Furthermore, we demonstrate that using naive QUBO approximation methods, based on removing values from exact (n + m) x (n + m)-dimensional QUBO representations of MAX-3SAT instances, is ineffective.

关键词： quadratic unconstrained binary optimization Combinatorial optimization Max-3SAT Approximation

来源：评论

学校读者我要写书评

暂无评论

Visiting-Route Recommendation in Amusement Parks and its Evaluations by an Ising Machine

Visiting-Route Recommendation in Amusement Parks and its Eva...

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Mukasa, Yosuke Wakaizumi, Tomoya Tanaka, Shu Togawa, Nozomu Waseda Univ Dept Comp Sci & Commun Engn Tokyo Japan Keio Univ Dept Appl Phys & Phys Informat Tokyo Japan Waseda Univ Green Comp Syst Res Org Tokyo Japan

ISBN: (纸本)9781728197661

In an amusement park, an attraction-visiting route considering the waiting time and traveling time improves visitors' satisfaction and experience. We focus on Ising machines to solve the problem, which are recently expected to solve combinatorial optimization problems at high speed by mapping the problems to Ising models or quadratic unconstrained binary optimization (QUBO) models. We propose a mapping of the visiting-route recommendation problem in amusement parks to a QUBO model for solving it using Ising machines. By using an actual Ising machine, we could obtain feasible solutions 15 times faster with almost the same accuracy as the simulated annealing method for the visiting-route recommendation problem.

关键词： Ising machine visiting-route recommendation in amusement parks combinatorial optimization problem Ising model quadratic unconstrained binary optimization

来源：评论

学校读者我要写书评

暂无评论

Constrained quadratic Model for Optimizing Join Orders 1

Constrained Quadratic Model for Optimizing Join Orders

引用

1st Workshop on Quantum Computing and Quantum-Inspired Technology for Data-Intensive Systems and Applications (Q-Data)

作者： Saxena, Pranshi Sabek, Ibrahim Spedalieri, Federico Univ Southern Calif Inst Informat Sci Los Angeles CA USA Univ Southern Calif Dept Comp Sci Los Angeles CA USA

ISBN: (纸本)9798400705533

We present a quantum-based approach for the optimization of join orders in database applications. Our approach relies on a hybrid framework, where classical heuristics are combined with a quantum processor to accelerate the search over the set of solutions to a constrained problem. By taking advantage of a previously introduced formulation of the join order optimization as a quadratic unconstrained binary optimization (QUBO) problem, we implement it using the Constrained quadratic Model (CQM), a hybrid classical-quantum solver that interfaces classical heuristics with D-Wave's quantum annealer. We show that even a generic implementation of this classical-quantum hybrid framework produces competitive results for the join order problem, suggesting that better-tailored hybrid solvers could produce a computational advantage.

关键词： Join Order Query optimization Quantum Computing quadratic unconstrained binary optimization Constrained quadratic Model

来源：评论

学校读者我要写书评

暂无评论

Evidence that PUBO outperforms QUBO when solving continuous optimization problems with the QAOA

Evidence that PUBO outperforms QUBO when solving continuous ...

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Stein, Jonas Chamanian, Farbod Zorn, Maximilian Nuesslein, Jonas Zielinski, Sebastian Koelle, Michael Linnhoff-Popien, Claudia Ludwig Maximilians Univ Munchen Munich Bavaria Germany

ISBN: (纸本)9798400701207

Quantum computing provides powerful algorithmic tools that have been shown to outperform established classical solvers in specific optimization tasks. A core step in solving optimization problems with known quantum algorithms such as the Quantum Approximate optimization Algorithm (QAOA) is the problem formulation. While quantum optimization has historically centered around quadratic unconstrained optimization (QUBO) problems, recent studies show, that many combinatorial problems such as the TSP can be solved more efficiently in their native Polynomial unconstrained optimization (PUBO) forms. As many optimization problems in practice also contain continuous variables, our contribution investigates the performance of the QAOA in solving continuous optimization problems when using PUBO and QUBO formulations. Our extensive evaluation on suitable benchmark functions, shows that PUBO formulations generally yield better results, while requiring less qubits. As the multi-qubit interactions needed for the PUBO variant have to be decomposed using the hardware gates available, i.e., currently single- and two-qubit gates, the circuit depth of the PUBO approach outscales its QUBO alternative roughly linearly in the order of the objective function. However, incorporating the planned addition of native multi-qubit gates such as the global Molmer-Sorenson gate, our experiments indicate that PUBO outperforms QUBO for higher order continuous optimization problems in general.

关键词： Quantum Computing Continuous optimization Quantum Approximate optimization Algorithm quadratic unconstrained binary optimization Polynomial unconstrained binary optimization

来源：评论

学校读者我要写书评

暂无评论

Engineering Discrete Simulated Bifurcation for an FPGA Digital Ising Machine 5

Engineering Discrete Simulated Bifurcation for an FPGA Digit...

引用

2024 International Conference on Quantum Computing and Engineering

作者： Orlando, Fabrizio Volpe, Deborah Orlandi, Giacomo RientO, Fabrizio Vacca, Marco Grazianot, Mariagrazia Politecnico Torino Italy Dept Elect & Telecommun Turin Italy Politecnico Torino Italy Dept Appl Sci & Technol Turin Italy

ISBN: (纸本)9798331541378

Simulated Adiabatic Bifurcation (aSB) is a quantum-inspired algorithm that provides approximate solutions for large-scale optimization problems using the Ising model. It emulates the quantum adiabatic evolution of a network of non-linear Kerr oscillators on classical platforms. These oscillators undergo bifurcation, where each branch corresponds to a spin state, with the network creating an energy imbalance to determine the optimal solution. This approach is highly parallelizable, making it suitable for implementation on CPUs and FPGAs. However, classical emulation introduces analog errors, potentially compromising performance. To address this, alternative methods like ballistic (bSB) and discrete (dSB) evolutions were developed, with the ballistic approach further enhanced by thermal fluctuations (HhSB). Our comprehensive analysis of bSB, dSB, and IlbSB using benchmark Max-Cut and knapsack problems aimed to identify the best balance of speed, area, and accuracy. We found that fixed-point number representation allows more algorithm iterations within the same timeframe as floating-point representation. The proposed FPGA architecture implements dSB and its heated version. leveraging high parallelizability and efficient memory organization. This design supports larger coefficients and improves problem-solving efficiency without multipliers for matrix-vector evaluation. Challenges include mitigating data dependency between matrix-vector multiplication and time evolution, and developing a preconditioning method for adapting problem coefficients, making the architecture suitable for real-world applications and potential ASIC release.

关键词： Ising Machines Simulated Bifurcation quadratic unconstrained binary optimization quantum inspired optimization Ising

来源：评论

学校读者我要写书评

暂无评论

Quantum hobbit routing: Annealer implementation of generalized Travelling Salesperson Problem

Quantum hobbit routing: Annealer implementation of generaliz...

引用

IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Perez Delgado, Inigo Garcia Markaida, Beatriz Moreno Fdez de Leceta, Aitor Ochoa Uriarte, Jon Ander Qi3B Ibermat Parque Tecnol BizkaiaIbaizabal BideEdif 501-A Derio 48160 Spain Qi3B Ibermat Parque Tecnol Alava Miano 01510 Spain Embassy Spain Econ & Commercial Off Singapore Singapore

ISBN: (纸本)9781665487689

In this paper, we present an implementation of a Job Selection Problem (JSP) - a generalization of the wellknown Travelling Salesperson Problem (TSP)- of N = 9 jobs on its quadratic unconstrained binary optimization (QUBO) form, using O(N) qubits on DWave's Advantage system4.1 quantum annealing device. The best known quantum algorithm for TSP to date uses O( N2) qubits. A solution is found using the quantum method. However, since hardware is not yet able to compensate the increase in search-space size, no present overall advantage is achieved when comparing the quantum results with either exhaustive or equiprobably sampled classical solutions of the problem.

关键词： Quantum annealing Quantum optimization Job Selection Problem Travelling Salesperson Problem quadratic unconstrained binary optimization

来源：评论

学校读者我要写书评

暂无评论

A Constraint Partition Method for Combinatorial optimization Problems 16

A Constraint Partition Method for Combinatorial Optimization...

引用

16th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)

作者： Onoda, Makoto Komatsu, Kazuhiko Kumagai, Masahito Sato, Masayuki Kobayashi, Hiroaki Tohoku Univ Grad Sch Informat Sci Sendai Miyagi Japan Tohoku Univ Cybersci Ctr Sendai Miyagi Japan

ISBN: (纸本)9798350393613

Ising machines have attracted much attention in recent years because of their potential in solving combinatorial optimization problems that are difficult to be solved using conventional computers. Ising machines solve the optimization problem that can be transformed into a quadratic unconstrained binary optimization (QUBO) problem. In the case of a problem with constraints, named a constraint problem, an objective function and constraint function with penalty coefficients are combined into a single Hamiltonian of a QUBO problem. When solving a constraint problem, the accuracy of the solution decreases compared to a QUBO problem with an objective function only. This is because penalty coefficients are set to excessively large values to prevent constraint violations. As a result, it becomes difficult to minimize the objective function. To solve this problem, this paper proposes a method that partitions constraint functions and reduces the value of the penalty coefficients. The performance evaluation using the traveling salesperson problem (TSP) with one-hot constraints demonstrates that the proposed method can improve the solution accuracy compared to the conventional method.

关键词： Ising machine penalty coefficient combinatorial optimization problem quadratic unconstrained binary optimization traveling salesperson problem

来源：评论

学校读者我要写书评

暂无评论

Quantum annealing task mapping for heterogeneous computing systems

Quantum annealing task mapping for heterogeneous computing s...

引用

Conference on Photonics for Quantum

作者： Ellenberger, Kenzie Couch, Dylan Greer, Jeffrey Gregory, Noah Sanchez, Luis Love, Kaleb Koshka, Yaroslav Khan, Samee Mississippi State Univ Mississippi State MS 39762 USA

ISBN: (纸本)9781510677906;9781510677913

Heterogeneous computing (HC) systems are essential parts of modern-day computing architectures such as cloud, cluster, grid, and edge computing. Many algorithms exist within the classical environment for mapping computational tasks to the HC system's nodes, but this problem is not well explored in the quantum area. In this work, the practicality, accuracy, and computation time of quantum mapping algorithms are compared against eleven classical mapping algorithms. The classical algorithms used for comparison include A-star (A*), Genetic Algorithm (GA), Simulated Annealing (SA), Genetic Simulated Annealing (GSA), Opportunistic Load Balancing (OLB), Minimum Completion Time (MCT), Minimum Execution Time (MET), Tabu, Min-min, Max-min, and Duplex. These algorithms are benchmarked using several different test cases to account for varying system parameters and task characteristics. This study reveals that a quantum mapping algorithm is feasible and can produce results similar to classical algorithms.

关键词： Quantum Algorithms quadratic unconstrained binary optimization Constrained quadratic Model Heterogeneous Computing Systems Mapping Quantum Annealing Algorithm

来源：评论

学校读者我要写书评

暂无评论

A Multiple Coefficients Trial Method to Solve Combinatorial optimization Problems for Simulated-annealing-based Ising Machines 9

A Multiple Coefficients Trial Method to Solve Combinatorial ...

引用

9th IEEE International Conference on Consumer Electronics (ICCE-Berlin)

作者： Takehara, Kota Oku, Daisuke Matsuda, Yoshiki Tanaka, Shu Togawa, Nozomu Waseda Univ Dept Comp Sci & Commun Engn Tokyo Japan Fixstars Corp Tokyo Japan Waseda Univ Green Comp Syst Res Org Tokyo Japan Japan Sci & Technol Agcy Precursory Res Embryon Sci & Technol Kawaguchi Saitama Japan

ISBN: (纸本)9781728127453

When solving a combinatorial optimization problem with Ising machines, we have to formulate it onto an energy function of Ising model. Here, how to determine the penalty coefficients in the energy function is a great concern if it includes constraint terms. In this paper, we focus on a traveling salesman problem (TSP, in short), one of the combinatorial optimization problems with equality constraints. Firstly, we investigate the relationship between the penalty coefficient and the accuracy of solutions in a TSP. Based on it, we propose a method to obtain a TSP quasi-optimum solution, which is called multiple coefficients trial method. In our proposed method, we use an Ising machine to solve a TSP by changing a penalty coefficient every trial, the TSP solutions can converge very fast in total. Compared to naive methods using simulated-annealing-based Ising machines, we confirmed that our proposed method can reduce the total number of annealing iterations to 1/10 to 1/1000 to obtain a quasi-optimum solution in 32-city TSPs.

关键词： Ising machine traveling salesman problem penalty coefficient combinatorial optimization problem quadratic unconstrained binary optimization

来源：评论

学校读者我要写书评

暂无评论

Reducing quantum annealing biases for solving the graph partitioning problem 21

Reducing quantum annealing biases for solving the graph part...

引用

18th ACM International Conference on Computing Frontiers (CF)

作者： Pelofske, Elijah Hahn, Georg Djidjev, Hristo N. Los Alamos Natl Lab Los Alamos NM 87545 USA Harvard Univ TH Chan Sch Publ Hlth Boston MA 02115 USA

ISBN: (纸本)9781450384049

Quantum annealers offer an efficient way to compute high quality solutions of NP-hard problems when expressed in a QUBO (quadratic unconstrained binary optimization) or an Ising form. This is done by mapping a problem onto the physical qubits and couplers of the quantum chip, from which a solution is read after a process called quantum annealing. However, this process is subject to multiple sources of biases, including poor calibration, leakage between adjacent qubits, control biases, etc., which might negatively influence the quality of the annealing results. In this work, we aim at mitigating the effect of such biases for solving constrained optimization problems, by offering a two-step method, and apply it to Graph Partitioning. In the first step, we measure and reduce any biases that result from implementing the constraints of the problem. In the second, we add the objective function to the resulting bias-corrected implementation of the constraints, and send the problem to the quantum annealer. We apply this concept to Graph Partitioning, an important NP-hard problem, which asks to find a partition of the vertices of a graph that is balanced (the constraint) and minimizes the cut size (the objective). We first quantify the bias of the implementation of the constraint on the quantum annealer, that is, we require, in an unbiased implementation, that any two vertices have the same likelihood of being assigned to the same or to different parts of the partition. We then propose an iterative method to correct any such biases. We demonstrate that, after adding the objective, solving the resulting bias-corrected Ising problem on the quantum annealer results in a higher solution accuracy.

关键词： bias correction D-Wave graph partitioning NP-hard problem quadratic unconstrained binary optimization quantum annealing

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共10页 << < 1 2 3 4 5 6 7 8 9 10 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：