Mixed Quantum State Dynamics Estimation with Artificial Neural Network

被引：0

作者：

Kim, Changjun ^{[1
]}

Rhee, June-Koo Kevin ^{[1
]}

Lee, Woojun ^{[1
]}

Ahn, Jaewook ^{[1
]}

机构：

[1] Korea Adv Inst Sci & Technol, Dept Phys, Sch Elect Engn, Daejeon, South Korea

来源：

2018 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC) | 2018年

关键词：

Quantum Density Matrix; Mixed State; Deep Neural Network (DNN); Long Short Term Memory (LSTM);

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In traditional quantum measurements, the size of tomography increases exponentially with the growth of qubit counts. In this paper, we introduce machine learning techniques such as Deep Neural Network (DNN) and Long Short Term Memory (LSTM) to analyze the Quantum Density Matrix up to 4 qubits, with no assumption of governing model

引用

页码：740 / 747

页数：8

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