公开(公告)号：US20220036230A1

公开(公告)日：2022-02-03

申请号：US17501755

申请日：2021-10-14

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Xin WANG ,  Xuanqiang Zhao ,  Benchi Zhao ,  Zihe Wang ,  Zhixin Song ,  Renyu Liu

IPC: G06N10/00

Abstract: A quantum entangled state processing method, a device, and a storage medium are provided, which are related to a field of quantum calculation. The specific implementation scheme includes: determining n initial quantum states to be processed; determining at least two nodes associated with the initial quantum state; acquiring at least one first parameterized quantum circuit required by the first node and at least one second parameterized quantum circuit required by the second node matched with a preset processing scenario; controlling, based on an initial quantum operation strategy, the first node to perform a local quantum operation to obtain a first measurement result, controlling the second node to perform a local quantum operation to obtain a second measurement result; obtaining an output quantum state meeting a preset requirement of the preset processing scenario at least based on the first measurement result and the second measurement result.

公开(公告)号：US20230186138A1

公开(公告)日：2023-06-15

申请号：US18081555

申请日：2022-12-14

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Xin WANG ,  Hongshun Yao ,  Sizhuo Yu ,  Xuanqiang Zhao

IPC: G06N10/60 ,  G06N10/20

CPC classification number: G06N10/60 ,  G06N10/20

Abstract: A method is provided. The method includes: determining L+1 parameterized quantum circuits and L data encoding circuits; obtaining a plurality of training data pairs including independent variable data and dependent variable data. The method further includes, for each of the training data pairs: cascading the parameterized quantum circuits and the data encoding circuits alternately to form a quantum neural network, where the data encoding circuits code the independent variable data in the training data pair; and operating the quantum neural network from an initial quantum state and performing measurement on the output of the quantum neural network, to obtain a measurement result. The method further includes, computing a loss function based on measurement results corresponding to all the training data pairs and corresponding dependent variable data; and adjusting parameters to be trained of the parameterized quantum circuits and the data encoding circuits to minimize the loss function.