Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor

Ming Gong; He-Liang Huang; Shiyu Wang; Chu Guo; Shaowei Li; Yulin Wu; Qingling Zhu; Youwei Zhao; Shaojun Guo; Haoran Qian; Yangsen Ye; Chen Zha; Fusheng Chen; Chong Ying; Jiale Yu; Daojin Fan; Dachao Wu; Hong Su; Hui Deng; Hao Rong; Kaili Zhang; Sirui Cao; Jin Lin; Yu Xu; Lihua Sun; Cheng Guo; Na Li; Futian Liang; Akitada Sakurai; Kae Nemoto; William J Munro; Yong-Heng Huo; Chao-Yang Lu; Cheng-Zhi Peng; Xiaobo Zhu; Jian-Wei Pan

doi:10.1016/j.scib.2023.04.003

Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor

Sci Bull (Beijing). 2023 May 15;68(9):906-912. doi: 10.1016/j.scib.2023.04.003. Epub 2023 Apr 7.

Authors

Ming Gong¹, He-Liang Huang², Shiyu Wang¹, Chu Guo², Shaowei Li¹, Yulin Wu¹, Qingling Zhu¹, Youwei Zhao¹, Shaojun Guo¹, Haoran Qian¹, Yangsen Ye¹, Chen Zha¹, Fusheng Chen¹, Chong Ying¹, Jiale Yu¹, Daojin Fan¹, Dachao Wu¹, Hong Su¹, Hui Deng¹, Hao Rong¹, Kaili Zhang¹, Sirui Cao¹, Jin Lin¹, Yu Xu¹, Lihua Sun¹, Cheng Guo¹, Na Li¹, Futian Liang¹, Akitada Sakurai³, Kae Nemoto⁴, William J Munro⁵, Yong-Heng Huo¹, Chao-Yang Lu¹, Cheng-Zhi Peng¹, Xiaobo Zhu⁶, Jian-Wei Pan⁷

Affiliations

¹ Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences, University of Science and Technology of China, Hefei 230026, China; Shanghai Research Center for Quantum Science and CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Shanghai 201315, China; Hefei National Laboratory, University of Science and Technology of China, Hefei 230088, China.
² Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences, University of Science and Technology of China, Hefei 230026, China; Shanghai Research Center for Quantum Science and CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Shanghai 201315, China; Hefei National Laboratory, University of Science and Technology of China, Hefei 230088, China; Henan Key Laboratory of Quantum Information and Cryptography, Zhengzhou 450000, China.
³ Okinawa Institute of Science and Technology Graduate University, Onna-son 904-0495, Japan; National Institute of Informatics, Chiyoda-ku 101-8430, Japan.
⁴ National Institute of Informatics, Chiyoda-ku 101-8430, Japan; School of Multidisciplinary Science, Department of Informatics, SOKENDAI (the Graduate University for Advanced Studies), Chiyoda-ku 101-8430, Japan; Okinawa Institute of Science and Technology Graduate University, Onna-son 904-0495, Japan.
⁵ NTT Basic Research Laboratories and Research Center for Theoretical Quantum Physics, Atsugi 243-0198, Japan; National Institute of Informatics, Chiyoda-ku 101-8430, Japan. Electronic address: bill.munro@me.com.
⁶ Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences, University of Science and Technology of China, Hefei 230026, China; Shanghai Research Center for Quantum Science and CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Shanghai 201315, China; Hefei National Laboratory, University of Science and Technology of China, Hefei 230088, China. Electronic address: xbzhu16@ustc.edu.cn.
⁷ Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences, University of Science and Technology of China, Hefei 230026, China; Shanghai Research Center for Quantum Science and CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Shanghai 201315, China; Hefei National Laboratory, University of Science and Technology of China, Hefei 230088, China. Electronic address: pan@ustc.edu.cn.

PMID: 37085397
DOI: 10.1016/j.scib.2023.04.003

Abstract

Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here, we propose a new approach called quantum neuronal sensing. Utilizing a 61-qubit superconducting quantum processor, we show that our scheme can efficiently classify two different types of many-body phenomena: namely the ergodic and localized phases of matter. Our quantum neuronal sensing process allows us to extract the necessary information coming from the statistical characteristics of the eigenspectrum to distinguish these phases of matter by measuring only one qubit and offers better phase resolution than conventional methods, such as measuring the imbalance. Our work demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems.

Keywords: Quantum many-body state; Quantum neural network; Superconducting qubit; Variational quantum eigensolver.