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YMSC-BIMSA Quantum Information Seminar
YMSC-BIMSA Quantum Information Seminar
Quantum variational learning for quantum error-correcting codes
Quantum variational learning for quantum error-correcting codes
Organizer
Speaker
Chenfeng Cao
Time
Friday, June 10, 2022 9:30 AM - 10:30 AM
Venue
Shuangqing-A626
Online
Zoom 388 528 9728
(BIMSA)
Abstract
Quantum error-correcting codes (QECCs) are believed to be a necessity for large-scale fault-tolerant quantum computation. In the past two decades, various methods of QECC constructions have been developed, leading to many good families of codes. However, the majority of these codes are not suitable for near-term quantum devices. Here we present VarQEC, a noise-resilient variational quantum algorithm to search for quantum codes with a hardware-efficient encoding circuit. Given the target noise channel (or the target code parameters) and the hardware connectivity graph, we optimize a shallow variational quantum circuit to prepare the basis states of an eligible code. We have verified its effectiveness by (re)discovering some symmetric and asymmetric codes, e.g., ((n,2n−6,3))2 for n from 7 to 14. We also found new ((6,2,3))2 and ((7,2,3))2 codes that are not equivalent to any stabilizer code, and extensive numerical evidence with VarQEC suggests that a ((7,3,3))2 code does not exist. Furthermore, we found many new channel-adaptive codes for error models involving nearest-neighbor correlated errors. Our work sheds new light on the understanding of QECC in general, which may also help to enhance near-term device performance with channel-adaptive error-correcting codes.
Speaker Intro
Chenfeng is a Humboldt Research Fellow at Freie Universität Berlin, working with Prof. Jens
Eisert. He obtained his Ph.D. in Physics from the Hong Kong University of Science and Technology
in 2024 under the supervision of Prof. Bei Zeng and received his B.S. in Physics from the University
of Chinese Academy of Sciences in 2019. From 2023 to 2024, he worked as a research consultant
at Phasecraft, hosted by Prof. Ashley Montanaro. Chenfeng’s research interests encompass various
theoretical aspects of quantum information, with a focus on near-term quantum advantage, including
quantum sampling advantage, quantum simulation, quantum error mitigation, and quantum machine
learning.