.png){kind=icon}
返回
Quantum Metropolis Solver: a quantum walks approach to optimization problems
.png){kind=icon}
OA
AI
DOI：10.1007/s42484-023-00119-y.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The efficient resolution of optimization problems is one of the key issues in today's industry. This task relies mainly on classical algorithms that present scalability problems and processing limitations. Quantum computing has emerged to challenge these types of problems. In this paper, we focus on the Metropolis-Hastings quantum algorithm, which is based on quantum walks. We use this algorithm to build a quantum software tool called Quantum Metropolis Solver (QMS). We validate QMS with the N-Queen problem to show a potential quantum advantage in an example that can be easily extrapolated to an Artificial Intelligence domain. We carry out different simulations to validate the performance of QMS and its configuration.
期刊
Q
IF:
4.4
论文数:
439
被引数:
796
机构
引用论文
分享收藏Patient and Healthcare Provider Barriers to Hypertension Awareness, Treatment and Follow Up: A Systematic Review and Meta-Analysis of Qualitative and Quantitative Studies.png)
PLoS ONE
OAAI
PLoS ONEIF0
OAAI分享收藏分享收藏
查看更多内容