尹璋琦 科研等 2 个话题下的优秀答主 一篇综述,记录一下:Noisy intermediate-scale quantum (NISQ) algorithms 链接 发布于 2021-01-28 16:40 7 人喜欢 分享 收藏举报 登录知乎,您可以享受以下权益: 更懂你的优质内容 更专业的大咖答主 ...
Benchmarking machine learning algorithms for adaptive quantum phase estimation with noisy intermediate-scale quantum sensorsMachine learningQuantum phase estimationQubitQuantum phase estimation is a paradigmatic problem in quantum sensing and metrology. Here we show that adaptive methods based on classical ...
Software mitigation of crosstalk on noisy intermediate-scale quantum computers, in Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1001–1016 (2020). Balatsky, A. V., Vekhter, I. & Zhu, J.-X. Impurity-induced...
Benchmarking machine learning algorithms for adaptive quantum phase estimation with noisy intermediate-scale quantum sensors 来自 EBSCO 喜欢 0 阅读量: 34 作者:NF Costa,Y Omar,A Sultanov,GS Paraoanu 摘要: Quantum phase estimation is a paradigmatic problem in quantum sensing and metrology. Here we ...
In practice, the applicability of quantum algorithms to classical systems are limited by the short coherence time of noisy quantum hardware in the so-called Noisy Intermediate-Scale Quantum (NISQ) era23 and the difficulty in executing the input and output of classical data. Other roadblocks toward...
A Python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits. - quantumlib/Cirq
Security Insights Additional navigation options master 1Branch Tags Code Qiskit Qiskitis an open-source framework for working with noisy intermediate-scale quantum computers (NISQ) at the level of pulses, circuits, and algorithms. Qiskit is made up elements that each work together to enable quantum ...
meaning the state of some qubits must be put “on hold” at intermediate times. In other words, if the quantum computer is working on a subset of qubits, we want to keep the other qubits in the system idle in the state we’ve prepared. This may sound relatively straightforward, but in...
$${\\mathrm{log}}_{2}N$$\\end{document}encoding increases predictive performance with up to+2% area under the receiver operator characteristics curve across all quantum machine learning approaches, thus, making it ideal for machine learning tasks executed in Noisy Intermediate Scale Quantum ...
Noisy Intermediate-Scale Quantum (NISQ)1,2,3devices hold a promise to deliver a practical quantum advantage by harnessing the complexity of quantum systems. Despite being several years away from having fault-tolerant quantum computing4,5,6, researchers have been hopeful to achieve this task. Perhap...