In order to substantiate claims of quantum computational advantage, it is crucial to develop efficient methods for validating the experimental data. We propose a test of the correct functioning of a boson sampler with single-photon inputs that is based on how photons distribute among partitions of the output modes. Our method is versatile and encompasses previous validation tests based on bunching phenomena, marginal distributions, and even some suppression laws. We show via theoretical arguments and numerical simulations that binned-mode photon number distributions can be used in practical scenarios to efficiently distinguish ideal boson samplers from those affected by realistic imperfections, especially partial distinguishability of the photons.
Extended validations on photon number resolving detector based Gaussian boson sampling with low noises
The 32nd Research Institute of China Electronics Technology Group Corporation（中国电子科技集团公司第三十二研究所）；Shanghai Research Center for Quantum Sciences（上海量子科学研究中心）
Simulating lossy and partially distinguishable quantum optical circuits: theory, algorithms and applications to experiment validation and state preparation
Sapienza Università di Roma（罗马第一大学）；Politecnico di Milano（米兰理工大学）；Microsoft Research（微软研究院）
The difficulty of validating large-scale quantum devices, such as Boson Samplers, poses a major challenge for any research program that aims to show quantum advantages over classical hardware. To address this problem, we propose a novel data-driven approach wherein models are trained to identify common pathologies using unsupervised machine learning methods. We illustrate this idea by training a classifier that exploits K-means clustering to distinguish between Boson Samplers that use indistinguishable photons from those that do not. We train the model on numerical simulations of small-scale B…
A boson sampling device is a specialised quantum computer that solves a problem which is strongly believed to be computationally hard for classical computers. Recently a number of small-scale implementations have been reported, all based on multi-photon interference in multimode interferometers. In the hard-to-simulate regime, even validating the device's functioning may pose a problem . In a recent paper, Gogolin et al. showed that so-called symmetric algorithms would be unable to distinguish the experimental distribution from the trivial, uniform distribution. Here we report new boson sampli…
The demonstration of quantum speedup, also known as quantum computational supremacy, that is the ability of quantum computers to outperform dramatically their classical counterparts, is an important milestone in the field of quantum computing. While quantum speedup experiments are gradually escaping the regime of classical simulation, they still lack efficient verification protocols and rely on partial validation. Here we derive an efficient protocol for verifying with single-mode Gaussian measurements the output states of a large class of continuous-variable quantum circuits demonstrating qua…
Boson sampling is a sub-universal model used to show quantum speed-up. However, the methods of validation to prove quantum speedup are not robust and accurate. All verification methods involve additional or little studied assumptions. Here, we use the protocols given in the paper [arXiv:2006.03520] to construct a boson sampling experiment using discrete quantum states on IBM quantum computer and verify the fidelity of the output states using heterodyne detection. We demonstrate the protocols for single mode fidelity estimation, multi mode fidelity estimation and a verification protocol using I…
Boson sampling is a promising candidate for quantum supremacy. It requires to sample from a complicated distribution, and is trusted to be intractable on classical computers. Among the various classical sampling methods, the Markov chain Monte Carlo method is an important approach to the simulation and validation of boson sampling. This method however suffers from the severe sample loss issue caused by the autocorrelation of the sample sequence. Addressing this, we propose the sample caching Markov chain Monte Carlo method that eliminates the correlations among the samples, and prevents the sa…
Multi-particle interference is a key resource for quantum information processing, as exemplified by Boson Sampling. Hence, given its fragile nature, an essential desideratum is a solid and reliable framework for its validation. However, while several protocols have been introduced to this end, the approach is still fragmented and fails to build a big picture for future developments. In this work, we propose an operational approach to validation that encompasses and strengthens the state of the art for these protocols. To this end, we consider the Bayesian hypothesis testing and the statistical…
Identifying the boundary beyond which quantum machines provide a computational advantage over their classical counterparts is a crucial step in charting their usefulness. Gaussian Boson Sampling (GBS), in which photons are measured from a highly entangled Gaussian state, is a leading approach in pursuing quantum advantage. State-of-the-art quantum photonics experiments that, once programmed, run in minutes, would require 600 million years to simulate using the best pre-existing classical algorithms. Here, we present substantially faster classical GBS simulation methods, including speed and acc…
