论文标题
量子计算机上单元步骤功能的基于振幅的实现
An Amplitude-Based Implementation of the Unit Step Function on a Quantum Computer
论文作者
论文摘要
然而，对量子计算机上的非线性激活函数进行建模对于完全量子神经网络中使用的量子神经元至关重要。我们引入了一个基于振幅的实现，以在量子计算机上以单位步骤函数的形式近似非线性。我们的方法扩展了重复任命协议协议，这表明修改仅需要进行一次测量。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其输入，或者是嵌入更高级的量子算法时的量子状态。理论上使用数值模拟对所有量子电路进行了评估，并在嘈杂的中间尺度量子硬件上执行。我们证明，可以从涉及多达8个QUAT的量子电路中获得具有高精度的可靠实验数据，以及最多25个CX-GATE应用程序，通过最先进的硬件优化技术和缓解测量误差的启用。
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.
