JigSaw: Boosting Fidelity of NISQ Programs via Measurement Subsetting
JigSaw: Boosting Fidelity of NISQ Programs via Measurement Subsetting
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JigSaw：通过测量子集提高 NISQ 程序的保真度
DOI：
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Moinuddin K. Qureshi
中科院分区：
文献类型：
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作者：
Poulami Das;Swamit S. Tannu;Moinuddin K. Qureshi
近期的量子计算机包含噪音很大的设备，这使得即使一个程序运行数千次也很难推断出正确的答案。在目前的机器上，量子比特测量往往是最容易出错的操作(平均错误率为4%)，并且经常限制能够在这些系统上可靠运行的量子程序的大小。当量子程序创建和操作相关态时，所有的程序量子比特都会在每次试验中被测量，因此，测量误差的严重程度随着程序的大小而增加。量子程序的保真度可以通过减少测量操作的数量来提高。我们介绍了Jigsaw，这是一个框架，通过在两种模式下运行程序来减少测量误差的影响。首先，运行整个程序，测量一半试验的所有量子比特，以生成全局(尽管有噪音)直方图。第二，运行额外的程序副本，在剩余的试验中，只测量每个副本中的量子比特的子集，以在测量的量子比特上产生局部化(更高保真度)的直方图。然后，Jigsaw采用贝叶斯后处理步骤，从而使用子集测量产生的直方图来更新全局直方图。我们使用三种不同的具有27和65量子比特的IBM量子计算机进行的评估表明，Jigsaw的成功率平均提高了3.6倍，最高可提高到8.4倍。我们的分析表明，Jigsaw的存储和时间复杂度与量子比特和试验的数量成线性关系，这使得Jigsaw适用于具有数百个量子比特的程序。
Near-term quantum computers contain noisy devices, which makes it difficult to infer the correct answer even if a program is run for thousands of trials. On current machines, qubit measurements tend to be the most error-prone operations (with an average error-rate of 4%) and often limit the size of quantum programs that can be run reliably on these systems. As quantum programs create and manipulate correlated states, all the program qubits are measured in each trial and thus, the severity of measurement errors increases with the program size. The fidelity of quantum programs can be improved by reducing the number of measurement operations. We present JigSaw, a framework that reduces the impact of measurement errors by running a program in two modes. First, running the entire program and measuring all the qubits for half of the trials to produce a global (albeit noisy) histogram. Second, running additional copies of the program and measuring only a subset of qubits in each copy, for the remaining trials, to produce localized (higher fidelity) histograms over the measured qubits. JigSaw then employs a Bayesian post-processing step, whereby the histograms produced by the subset measurements are used to update the global histogram. Our evaluations using three different IBM quantum computers with 27 and 65 qubits show that JigSaw improves the success rate on average by 3.6x and up-to 8.4x. Our analysis shows that the storage and time complexity of JigSaw scales linearly with the number of qubits and trials, making JigSaw applicable to programs with hundreds of qubits.
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DOI：
10.1145/3352460.3358313
发表时间：
2019-09
期刊：
Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture
影响因子：
--
作者：
P. Gokhale;Yongshan Ding;T. Propson;Christopher Winkler;N. Leung;Yunong Shi;D. Schuster;H. Hoffmann;F. Chong
通讯作者：
P. Gokhale;Yongshan Ding;T. Propson;Christopher Winkler;N. Leung;Yunong Shi;D. Schuster;H. Hoffmann;F. Chong
构建嘈杂的中型量子计算机：真实系统研究
影响因子：
3.6
作者：
Murali, Prakash;Linke, Norbert M.;Martonosi, Margaret;Abhari, Ali Javadi;Nguyen, Nhung Hong;Alderete, Cinthia Huerta
通讯作者：
Alderete, Cinthia Huerta
影响因子：
6.4
作者：
Preskill, John
通讯作者：
Preskill, John
通过打破抽象实现资源高效的量子计算
影响因子：
20.6
作者：
Shi, Yunong;Gokhale, Pranav;Murali, Prakash;Baker, Jonathan M.;Duckering, Casey;Ding, Yongshan;Brown, Natalie C.;Chamberland, Christopher;Javadi-Abhari, Ali;Cross, Andrew W.
通讯作者：
Cross, Andrew W.
影响因子：
12.5
作者：
Zhou, Leo;Wang, Sheng-Tao;Lukin, Mikhail D.
通讯作者：
Lukin, Mikhail D.