Classical Modeling of a Lossy Gaussian Bosonic Sampler

被引:0
作者
Umanskii, Mikhail V. [1 ]
Rubtsov, Alexey N. [1 ,2 ]
机构
[1] Lomonosov Moscow State Univ, Dept Phys, Leninskie Gory 1, Moscow 119991, Russia
[2] Russian Quantum Ctr, Bolshoy Bulvar 30,bld 1, Moscow 121205, Russia
关键词
Gaussian boson sampling; quantum complexity; emulation of quantum devices;
D O I
10.3390/e26060493
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Gaussian boson sampling (GBS) is considered a candidate problem for demonstrating quantum advantage. We propose an algorithm for the approximate classical simulation of a lossy GBS instance. The algorithm relies on the Taylor series expansion, and increasing the number of terms of the expansion that are used in the calculation yields greater accuracy. The complexity of the algorithm is polynomial in the number of modes given the number of terms is fixed. We describe conditions for the input state squeezing parameter and loss level that provide the best efficiency for this algorithm (by efficient, we mean that the Taylor series converges quickly). In recent experiments that claim to have demonstrated quantum advantage, these conditions are satisfied; thus, this algorithm can be used to classically simulate these experiments.
引用
收藏
页数:15
相关论文
共 18 条
[1]  
Aaronson S, 2010, Arxiv, DOI [arXiv:1011.3245, 10.48550/arXiv.1011.3245, DOI 10.48550/ARXIV.1011.3245]
[2]   BosonSampling with lost photons [J].
Aaronson, Scott ;
Brod, Daniel J. .
PHYSICAL REVIEW A, 2016, 93 (01)
[3]   Experimental scattershot boson sampling [J].
Bentivegna, Marco ;
Spagnolo, Nicolo ;
Vitelli, Chiara ;
Flamini, Fulvio ;
Viggianiello, Niko ;
Latmiral, Ludovico ;
Mataloni, Paolo ;
Brod, Daniel J. ;
Galvao, Ernesto F. ;
Crespi, Andrea ;
Ramponi, Roberta ;
Osellame, Roberto ;
Sciarrino, Fabio .
SCIENCE ADVANCES, 2015, 1 (03)
[4]   Gaussian Boson Sampling with Pseudo-Photon-Number-Resolving Detectors and Quantum Computational Advantage [J].
Deng, Yu-Hao ;
Gu, Yi-Chao ;
Liu, Hua-Liang ;
Gong, Si-Qiu ;
Su, Hao ;
Zhang, Zhi-Jiong ;
Tang, Hao-Yang ;
Jia, Meng-Hao ;
Xu, Jia-Min ;
Chen, Ming-Cheng ;
Qin, Jian ;
Peng, Li-Chao ;
Yan, Jiarong ;
Hu, Yi ;
Huang, Jia ;
Li, Hao ;
Li, Yuxuan ;
Chen, Yaojian ;
Jiang, Xiao ;
Gan, Lin ;
Yang, Guangwen ;
You, Lixing ;
Li, Li ;
Zhong, Han -Sen ;
Wang, Hui ;
Liu, Nai-Le ;
Renema, Jelmer J. ;
Lu, Chao-Yang ;
Pan, Jian-Wei .
PHYSICAL REVIEW LETTERS, 2023, 131 (15)
[5]   Simulating boson sampling in lossy architectures [J].
Garcia-Patron, Raul ;
Renema, Jelmer J. ;
Shchesnovich, Valery .
QUANTUM, 2019, 3
[6]  
Gard B. T., 2015, From Atomic to Mesoscale, P167
[7]   Gaussian Boson Sampling [J].
Hamilton, Craig S. ;
Kruse, Regina ;
Sansoni, Linda ;
Barkhofen, Sonja ;
Silberhorn, Christine ;
Jex, Igor .
PHYSICAL REVIEW LETTERS, 2017, 119 (17)
[8]   CALCULATION OF PARTITION FUNCTIONS [J].
HUBBARD, J .
PHYSICAL REVIEW LETTERS, 1959, 3 (02) :77-78
[9]   Boson Sampling from a Gaussian State [J].
Lund, A. P. ;
Laing, A. ;
Rahimi-Keshari, S. ;
Rudolph, T. ;
O'Brien, J. L. ;
Ralph, T. C. .
PHYSICAL REVIEW LETTERS, 2014, 113 (10)
[10]  
Oh C, 2023, Arxiv, DOI [arXiv:2306.03709, DOI 10.48550/ARXIV.2306.03709]