CN114730385A - 一种量子玻尔兹曼机的训练方法及混合计算机 - Google Patents

一种量子玻尔兹曼机的训练方法及混合计算机 Download PDF

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CN114730385A
CN114730385A CN202080081890.7A CN202080081890A CN114730385A CN 114730385 A CN114730385 A CN 114730385A CN 202080081890 A CN202080081890 A CN 202080081890A CN 114730385 A CN114730385 A CN 114730385A
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quantum
sample
samples
layer
loss function
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张文
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Huawei Technologies Co Ltd
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Abstract

本申请实施例提供一种量子玻尔兹曼机的训练方法及混合计算机，涉及量子计算领域。该方法能够用于半监督学习，包括：获取量子玻尔兹曼机的第一损失函数；获取第一损失函数对量子玻尔兹曼机的哈密顿量的预定参数的第一偏导数，预定参数包括量子玻尔兹曼机中两个量子单元的连接权重或者量子单元的偏置；对第一偏导数执行梯度算法更新预定参数，获取更新的量子玻尔兹曼机，其中，更新的量子玻尔兹曼机的哈密顿量使用更新后的预定参数。

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PCT国内申请，说明书已公开。

Claims (17)

  1. PCT国内申请，权利要求书已公开。
CN202080081890.7A 2020-02-28 2020-02-28 一种量子玻尔兹曼机的训练方法及混合计算机 Pending CN114730385A (zh)

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PCT/CN2020/077208 WO2021168798A1 (zh) 2020-02-28 2020-02-28 一种量子玻尔兹曼机的训练方法及混合计算机

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CN114861928B (zh) * 2022-06-07 2023-05-30 北京大学 一种量子测量方法及装置和计算设备

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EP3227837A1 (en) * 2014-12-05 2017-10-11 Microsoft Technology Licensing, LLC Quantum deep learning
EP3362952A4 (en) * 2015-10-16 2018-10-03 D-Wave Systems Inc. Systems and methods for creating and using quantum boltzmann machines
CN109886342A (zh) * 2019-02-26 2019-06-14 视睿（杭州）信息科技有限公司 基于机器学习的模型训练方法和装置

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