Forging quantum data: classically defeating an IQP-based quantum test
Author:
Kahanamoku-Meyer Gregory D.1
Affiliation:
1. Department of Physics, University of California at Berkeley, Berkeley, CA 94720
Abstract
Recently, quantum computing experiments have for the first time exceeded the capability of classical computers to perform certain computations – a milestone termed "quantum computational advantage." However, verifying the output of the quantum device in these experiments required extremely large classical computations. An exciting next step for demonstrating quantum capability would be to implement tests of quantum computational advantage with efficient classical verification, such that larger system sizes can be tested and verified. One of the first proposals for an efficiently-verifiable test of quantumness consists of hiding a secret classical bitstring inside a circuit of the class IQP, in such a way that samples from the circuit's output distribution are correlated with the secret. The classical hardness of this protocol has been supported by evidence that directly simulating IQP circuits is hard, but the security of the protocol against other (non-simulating) classical attacks has remained an open question. In this work we demonstrate that the protocol is not secure against classical forgery. We describe a classical algorithm that can not only convince the verifier that the (classical) prover is quantum, but can in fact can extract the secret key underlying a given protocol instance. Furthermore, we show that the key extraction algorithm is efficient in practice for problem sizes of hundreds of qubits. Finally, we provide an implementation of the algorithm, and give the secret vector underlying the "\$25 challenge" posted online by the authors of the original paper.
Publisher
Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften
Subject
Physics and Astronomy (miscellaneous),Atomic and Molecular Physics, and Optics
Reference27 articles.
1. Frank Arute et al. ``Quantum supremacy using a programmable superconducting processor''. Nature 574, 505–510 (2019). 2. Han-Sen Zhong et al. ``Quantum computational advantage using photons''. Science 370, 1460–1463 (2020). 3. Yulin Wu, Wan-Su Bao, Sirui Cao, Fusheng Chen, Ming-Cheng Chen, Xiawei Chen, Tung-Hsun Chung, Hui Deng, Yajie Du, Daojin Fan, Ming Gong, Cheng Guo, Chu Guo, Shaojun Guo, Lianchen Han, Linyin Hong, He-Liang Huang, Yong-Heng Huo, Liping Li, Na Li, Shaowei Li, Yuan Li, Futian Liang, Chun Lin, Jin Lin, Haoran Qian, Dan Qiao, Hao Rong, Hong Su, Lihua Sun, Liangyuan Wang, Shiyu Wang, Dachao Wu, Yu Xu, Kai Yan, Weifeng Yang, Yang Yang, Yangsen Ye, Jianghan Yin, Chong Ying, Jiale Yu, Chen Zha, Cha Zhang, Haibin Zhang, Kaili Zhang, Yiming Zhang, Han Zhao, Youwei Zhao, Liang Zhou, Qingling Zhu, Chao-Yang Lu, Cheng-Zhi Peng, Xiaobo Zhu, and Jian-Wei Pan. ``Strong Quantum Computational Advantage Using a Superconducting Quantum Processor''. Physical Review Letters 127, 180501 (2021). 4. Qingling Zhu, Sirui Cao, Fusheng Chen, Ming-Cheng Chen, Xiawei Chen, Tung-Hsun Chung, Hui Deng, Yajie Du, Daojin Fan, Ming Gong, Cheng Guo, Chu Guo, Shaojun Guo, Lianchen Han, Linyin Hong, He-Liang Huang, Yong-Heng Huo, Liping Li, Na Li, Shaowei Li, Yuan Li, Futian Liang, Chun Lin, Jin Lin, Haoran Qian, Dan Qiao, Hao Rong, Hong Su, Lihua Sun, Liangyuan Wang, Shiyu Wang, Dachao Wu, Yulin Wu, Yu Xu, Kai Yan, Weifeng Yang, Yang Yang, Yangsen Ye, Jianghan Yin, Chong Ying, Jiale Yu, Chen Zha, Cha Zhang, Haibin Zhang, Kaili Zhang, Yiming Zhang, Han Zhao, Youwei Zhao, Liang Zhou, Chao-Yang Lu, Cheng-Zhi Peng, Xiaobo Zhu, and Jian-Wei Pan. ``Quantum computational advantage via 60-qubit 24-cycle random circuit sampling''. Science Bulletin 67, 240–245 (2022). 5. Scott Aaronson and Alex Arkhipov. ``The computational complexity of linear optics''. In Proceedings of the forty-third annual ACM symposium on Theory of computing. Pages 333–342. STOC '11New York, NY, USA (2011). Association for Computing Machinery.
|
|