2019/05/31 by V. S. Shchesnovich, Valery Shchesnovich · 18 citations
Computer Science · Physics and Astronomy · #Artificial intelligence #Boson #Computer science #Noise (video) #Optics #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #Quantum mechanics #Quantum noise #Sampling (signal processing) #Statistical physics #cs.CC #quant-ph
paper · pdf · open access · doi:10.22331/q-2021-03-29-423
published in Quantum 5, 423 (Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften) · March 4, 2022 : In Appendix C.1 the derivation of the lower bound in Eq. (50) is simplified significantly. However, there is an additional error term in Eq. (13) of the main text
openalex publication_date 2021/03/29 · arxiv created 2022/03/07 · arxiv updated 2022/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Giving a convincing experimental evidence of the quantum supremacy over classical simulations is a challenging goal. Noise is considered to be the main problem in such a demonstration, hence it is urgent to understand the effect of noise. Recently found classical algorithms can efficiently approximate, to any small error, the output of boson sampling with finite-amplitude noise. In this work it is shown analytically and confirmed by numerical simulations that one can efficiently distinguish the output distribution of such a noisy boson sampling from the approximations accounting for low-order quantum multiboson interferences, what includes the mentioned classical algorithms. The number of samples required to tell apart the quantum and classical output distributions is strongly affected by the previously unexplored parameter: density of bosons, i.e., the ratio of total number of interfering bosons to number of input ports of interferometer. Such critical dependence is strikingly reminiscent of the quantum-to-classical transition in systems of identical particles, which sets in when the system size scales up while density of particles vanishes.