当前位置: X-MOL 学术arXiv.cs.ET › 论文详情
A quantum-classical cloud platform optimized for variational hybrid algorithms
arXiv - CS - Emerging Technologies Pub Date : 2020-01-13 , DOI: arxiv-2001.04449
Peter J. Karalekas; Nikolas A. Tezak; Eric C. Peterson; Colm A. Ryan; Marcus P. da Silva; Robert S. Smith

In order to support near-term applications of quantum computing, a new compute paradigm has emerged--the quantum-classical cloud--in which quantum computers (QPUs) work in tandem with classical computers (CPUs) via a shared cloud infrastructure. In this work, we enumerate the architectural requirements of a quantum-classical cloud platform, and present a framework for benchmarking its runtime performance. In addition, we walk through two platform-level enhancements, parametric compilation and active qubit reset, that specifically optimize a quantum-classical architecture to support variational hybrid algorithms (VHAs), the most promising applications of near-term quantum hardware. Finally, we show that integrating these two features into the Rigetti Quantum Cloud Services (QCS) platform results in considerable improvements to the latencies that govern algorithm runtime.
更新日期:2020-01-14

 

全部期刊列表>>
2020新春特辑
限时免费阅读临床医学内容
ACS材料视界
科学报告最新纳米科学与技术研究
清华大学化学系段昊泓
自然科研论文编辑服务
中国科学院大学楚甲祥
上海纽约大学William Glover
中国科学院化学研究所
课题组网站
X-MOL
北京大学分子工程苏南研究院
华东师范大学分子机器及功能材料
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug