Quantum Computing and Machine Learning on an Integrated Photonics Platform

被引：0

作者：

Zhu, Huihui ^{[1
,2
]}

Lin, Hexiang ^{[1
]}

Wu, Shaojun ^{[3
]}

Luo, Wei ^{[2
]}

Zhang, Hui ^{[2
]}

Zhan, Yuancheng ^{[1
]}

Wang, Xiaoting ^{[3
]}

Liu, Aiqun ^{[1
,2
]}

Kwek, Leong Chuan ^{[1
,4
,5
,6
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Block S2-1,50 Nanyang Ave, Singapore 639798, Singapore

[2] Hong Kong Polytech Univ, Inst Quantum Technol IQT, Hong Kong, Peoples R China

[3] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu 610051, Peoples R China

[4] Nanyang Technol Univ, Natl Inst Educ, 1 Nanyang Walk, Singapore 637616, Singapore

[5] Natl Univ Singapore, Ctr Quantum Technol, Singapore 117543, Singapore

[6] UNS, MajuLab, CNRS, NUS,NTU Int Joint Res Unit, UMI 3654, Singapore 637616, Singapore

来源：

INFORMATION | 2024年 / 15卷 / 02期

关键词：

integrated photonic chip; quantum neural network; optical network; WAVE-GUIDE; GENERATION; COMPACT; ENTANGLEMENT; COMPUTATION; COMPLEXITY; SPLITTER; DESIGN;

D O I：

10.3390/info15020095

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Integrated photonic chips leverage the recent developments in integrated circuit technology, along with the control and manipulation of light signals, to realize the integration of multiple optical components onto a single chip. By exploiting the power of light, integrated photonic chips offer numerous advantages over traditional optical and electronic systems, including miniaturization, high-speed data processing and improved energy efficiency. In this review, we survey the current status of quantum computation, optical neural networks and the realization of some algorithms on integrated optical chips.

引用

页数：25

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