arXiv 2206.030532022-06-27quant-ph

量子计算机上基于振幅的单位阶跃函数实现

An Amplitude-Based Implementation of the Unit Step Function on a Quantum Computer

Jonas Koppe, Mark-Oliver Wolf

备注：: 11 pages, 9 figures, 1 table
发表信息：: Phys. Rev. A 107 (2023) 022606
DOI：: 10.1103/PhysRevA.107.022606

摘要：

在量子计算机上建模非线性激活函数对于全量子神经网络中使用的量子神经元至关重要，然而，仍然是一项具有挑战性的任务。我们介绍了一种基于幅度的实现，用于在量子计算机上以单位阶跃函数的形式近似非线性。我们的方法扩展了重复，直到成功的协议，建议修改，只需要一个单一的测量。我们描述了两种不同的电路类型，它们直接从经典计算机接收输入，或者在嵌入更先进的量子算法中时作为量子态接收输入。所有的量子线路理论上进行评估，使用数值模拟和噪声中等规模量子硬件上执行。我们证明，可靠的实验数据与高精度可以从我们的量子线路，涉及多达8个量子位，多达25个CX门的应用，使最先进的硬件优化技术和测量误差缓解。

英文摘要：

Modelling non-linear activation functions on quantum computers is vital for quantum neurons employed in fully quantum neural networks, however, remains a challenging task. We introduce an amplitude-based implementation for approximating non-linearity in the form of the unit step function on a quantum computer. Our approach expands upon repeat-until-success protocols, suggesting a modification that requires a single measurement only. We describe two distinct circuit types which receive their input either directly from a classical computer, or as a quantum state when embedded in a more advanced quantum algorithm. All quantum circuits are theoretically evaluated using numerical simulation and executed on Noisy Intermediate-Scale Quantum hardware. We demonstrate that reliable experimental data with high precision can be obtained from our quantum circuits involving up to 8 qubits, and up to 25 CX-gate applications, enabled by state-of-the-art hardware-optimization techniques and measurement error mitigation.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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