The goal of qubit mapping is to map a logical circuit to a physical device by introducing additional gates as few as possible in an acceptable amount of time.We present an effective approach called Tabu Search Based A...The goal of qubit mapping is to map a logical circuit to a physical device by introducing additional gates as few as possible in an acceptable amount of time.We present an effective approach called Tabu Search Based Adjustment(TSA)algorithm to construct the mappings.It consists of two key steps:one is making use of a combined subgraph isomorphism and completion to initialize some candidate mappings,and the other is dynamically modifying the mappings by TSA.Our experiments show that,compared with state-of-the-art methods,TSA can generate mappings with a smaller number of additional gates and have better scalability for large-scale circuits.展开更多
As cloud quantum computing gains broader acceptance,a growing quantity of researchers are directing their focus towards this domain.Nevertheless,the rapid surge in demand for cloud-based quantum computing resources ha...As cloud quantum computing gains broader acceptance,a growing quantity of researchers are directing their focus towards this domain.Nevertheless,the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity,which in turn hampers users from achieving optimal satisfaction.Therefore,cloud quantum computing service providers require a unified analysis and scheduling framework for their quantumresources and user jobs to meet the ever-growing usage demands.This paper introduces a new multi-programming scheduling framework for quantum computing in a cloud environment.The framework addresses the issue of limited quantum computing resources in cloud environments and ensures a satisfactory user experience.It introduces three innovative designs:1)Our framework automatically allocates tasks to different quantum backends while ensuring fairness among users by considering both the cloud-based quantum resources and the user-submitted tasks.2)Multi-programming mechanism is employed across different quantum backends to enhance the overall throughput of the quantum cloud.In comparison to conventional task schedulers,our proposed framework achieves a throughput improvement of more than two-fold in the quantum cloud.3)The framework can balance fidelity and user waiting time by adaptively adjusting scheduling parameters.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos.61832015,62072176,12271172 and 11871221the Research Funds of Happiness Flower of East China Normal University under Grant No.2020ECNU-XFZH005+1 种基金the Fundamental Research Funds for the Central Universities of China under Grant No.2021JQRH014Shanghai Trusted Industry Internet Software Collaborative Innovation Center,and the “Digital Silk Road”Shanghai International Joint Lab of Trustworthy Intelligent Software under Grant No.22510750100.
文摘The goal of qubit mapping is to map a logical circuit to a physical device by introducing additional gates as few as possible in an acceptable amount of time.We present an effective approach called Tabu Search Based Adjustment(TSA)algorithm to construct the mappings.It consists of two key steps:one is making use of a combined subgraph isomorphism and completion to initialize some candidate mappings,and the other is dynamically modifying the mappings by TSA.Our experiments show that,compared with state-of-the-art methods,TSA can generate mappings with a smaller number of additional gates and have better scalability for large-scale circuits.
文摘As cloud quantum computing gains broader acceptance,a growing quantity of researchers are directing their focus towards this domain.Nevertheless,the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity,which in turn hampers users from achieving optimal satisfaction.Therefore,cloud quantum computing service providers require a unified analysis and scheduling framework for their quantumresources and user jobs to meet the ever-growing usage demands.This paper introduces a new multi-programming scheduling framework for quantum computing in a cloud environment.The framework addresses the issue of limited quantum computing resources in cloud environments and ensures a satisfactory user experience.It introduces three innovative designs:1)Our framework automatically allocates tasks to different quantum backends while ensuring fairness among users by considering both the cloud-based quantum resources and the user-submitted tasks.2)Multi-programming mechanism is employed across different quantum backends to enhance the overall throughput of the quantum cloud.In comparison to conventional task schedulers,our proposed framework achieves a throughput improvement of more than two-fold in the quantum cloud.3)The framework can balance fidelity and user waiting time by adaptively adjusting scheduling parameters.
