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Phase-Programmable Gaussian Boson Sampling Using Stimulated Squeezed Light

Authors :
Dian Wu
Jian Qin
Jian-Wei Pan
Yu-Hao Deng
Ming-Cheng Chen
Guangwen Yang
Hao Li
Xiaoyan Yang
Li-Chao Peng
Xiao Jiang
Li Li
Si-Qiu Gong
Weijun Zhang
Peng Hu
Han-Sen Zhong
Jelmer J. Renema
Zhen Wang
Yuxuan Li
Nai-Le Liu
Lixing You
Lin Gan
Yi Hu
Yi-Han Luo
Hao Su
Chao-Yang Lu
Hui Wang
Adaptieve Quantum Optica
MESA+ Institute
Source :
Physical review letters, 127(18):180502. American Physical Society, Optica Publisching Group 2022
Publication Year :
2021

Abstract

The tantalizing promise of quantum computational speedup in solving certain problems has been strongly supported by recent experimental evidence from a high-fidelity 53-qubit superconducting processor1 and Gaussian boson sampling (GBS) with up to 76 detected photons. Analogous to the increasingly sophisticated Bell tests that continued to refute local hidden variable theories, quantum computational advantage tests are expected to provide increasingly compelling experimental evidence against the Extended Church-Turing thesis. In this direction, continued competition between upgraded quantum hardware and improved classical simulations is required. Here, we report a new GBS experiment that produces up to 113 detection events out of a 144-mode photonic circuit. We develop a new high-brightness and scalable quantum light source, exploring the idea of stimulated squeezed photons, which has simultaneously near-unity purity and efficiency. This GBS is programmable by tuning the phase of the input squeezed states. We demonstrate a new method to efficiently validate the samples by inferring from computationally friendly subsystems, which rules out hypotheses including distinguishable photons and thermal states. We show that our noisy GBS experiment passes the nonclassicality test using an inequality, and we reveal non-trivial genuine high-order correlation in the GBS samples, which are evidence of robustness against possible classical simulation schemes. The photonic quantum computer, Jiuzhang 2.0, yields a Hilbert space dimension up to $10^{43}$, and a sampling rate $10^{24}$ faster than using brute-force simulation on supercomputers.<br />23 pages, 6 figures. Comments are welcome

Details

Language :
English
ISSN :
00319007
Volume :
127
Issue :
18
Database :
OpenAIRE
Journal :
Physical review letters
Accession number :
edsair.doi.dedup.....0ab455b9cd9b411ced57ec5061869759