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QUANTUM MACHINE LEARNING FRAMEWORK CONSTRUCTION METHOD AND APPARATUS, AND QUANTUM COMPUTER AND COMPUTER STORAGE MEDIUM

机译:量子机器学习框架的构建方法和装置,量子计算机和计算机存储介质

摘要

Disclosed are a quantum machine learning framework construction method and apparatus, and a quantum computer and a computer storage medium. The quantum machine learning framework construction method comprises: obtaining Hamiltonian corresponding to a set question (S110) and the number of quantum bits required by the set question, and obtaining target bits according to the number of quantum bits (S120); obtaining a parameter-containing quantum line of the set question based on the target bits and the Hamiltonian (S130); determining a quantum bit to be measured from among the target bits, and constructing, based on the quantum bit to be measured, the Hamiltonian and the parameter-containing quantum line, a quantum operation node class that provides an expected value solving interface and a gradient solving interface (S140); and invoking the gradient solving interface and the expected value solving interface of the quantum operation node class inserted into a preset machine learning framework to solve the set question, so as to construct a quantum machine learning framework (S150). By means of the method, the quantum machine learning framework can be applied to a quantum computer, thereby realizing the effect of performing hybrid programming on a neural network and quantum computation, and the quantum computer can perform machine learning.
机译:公开了一种量子机器学习框架的构建方法和装置,量子计算机和计算机存储介质。量子机器学习框架的构建方法包括:获取与设定问题对应的哈密顿量(S110)和设定问题所需的量子位数;根据量子位数获取目标位数(S120);基于目标比特和哈密顿量,获得所设置问题的包含参数的量子线(S130);从目标位中确定要测量的量子位,并基于要测量的量子位构造哈密顿量和包含参数的量子线,该量子操作节点类提供期望值求解接口和梯度解决界面(S140);并调用插入到预设机器学习框架中的量子运算节点类的梯度求解接口和期望值求解接口,以解决所设置的问题,从而构建量子机器学习框架(S150)。通过该方法,可以将量子机器学习框架应用于量子计算机,从而实现对神经网络进行混合编程和进行量子计算的效果,并且量子计算机可以进行机器学习。

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