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arXiv:1904.12318 · Quantum Science and Technology

Validating multi-photon quantum interference with finite data

Fulvio Flamini, Mattia Walschaers, Nicolò Spagnolo, Nathan Wiebe, Andreas Buchleitner, Fabio Sciarrino

Published Jun 25, 2020• 0 citations
arXivHTMLPDF

Abstract

Abstract 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 benchmark as most favorable protocols for small- and large-scale applications, respectively. We numerically investigate their operation with finite sample size, extending previous tests to larger dimensions, and against two adversarial algorithms for classical simulation: the mean-field sampler and the metropolized independent sampler. To evidence the actual need for refined validation techniques, we show how the assessment of numerically simulated data depends on the available sample size, as well as on the internal hyper-parameters and other practically relevant constraints. Our analyses provide general insights into the challenge of validation, and can inspire the design of algorithms with a measurable quantum advantage.

DOI
10.1088/2058-9565/aba03a

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Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC)•Jun 1, 2017•0 citations
Abstract 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 benchmark as most favorable protocols for small- and large-scale applications, respectively. We numerically investigate their operation with finite sample size, extending previous tests to larger dimensions, and against two adversarial algorithms for classical simulation: the mean-field sampler and the metropolized independent sampler. To evidence the actual need for refined validation techniques, we show how the assessment of numerically simulated data depends on the available sample size, as well as on the internal hyper-parameters and other practically relevant constraints. Our analyses provide general insights into the challenge of validation, and can inspire the design of algorithms with a measurable quantum advantage.
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 benchmark as most favorable protocols for small- and large-scale applications, respectively. We numerically investigate their operation with finite sample size, extending previous tests to larger dimensions, and against two adversarial algorithms for classical simulation: the mean-field sampler and the metropolized independent sampler. To evidence the actual need for refined validation techniques, we show how the assessment of numerically simulated data depends on the available sample size, as well as on the internal hyper-parameters and other practically relevant constraints. Our analyses provide general insights into the challenge of validation, and can inspire the design of algorithms with a measurable quantum advantage.
The progressive development of quantum technologies in many areas, ranging from investigation on foundamentals of quantum of mechanics to quantum information and computation, has increased the interest on those problems that can exhibit a quantum advantage. The Boson Sampling problem is a clear example where traditional computers fail in the task of sampling from the distribution of n indistinguishable photons after a propagation in a m-mode optical interferometer. In this context, in the absence of classical algorithms able to simulate efficiently multi-photon interference, the validation of Boson Sampling is still an open problem. Here we investigate a novel approach to Boson Sampling validation based on statistical properties of correlation functions. In particular we discuss its feasibility in actual proof-of-principle experiments. Furthermore we provide an extensive study of the physical resources required to validate experiments, investigating also the role of bosonic bunching in high-dimensional applications. Our investigation confirms the goodness of the validation protocol, paving the way to use this toolbox for the validation of Boson Sampling devices.
Quantum algorithms provide advantages for specific computational and sampling tasks, though little attention has so far been dedicated to the validation of the output of experimental implementations of such algorithms. In this work we address this issue for the Boson Sampling problem, and propose an operational definition of validation. To evidence the actual need for refined validation techniques, we examine two recent protocols: Metropolized independent sampling, to classically simulate Boson Sampling, and a statistical benchmark to validate quantum interference. We show how the acceptance or rejection of numerically simulated data depends on the available sample size, as well as on the internal hyper-parameters and other practically relevant constraints. Our analysis provides general insights into the challenge of validation, and may inspire further research into the design of algorithms with a measurable quantum advantage.
Achieving a quantum computational advantage regime, and thus providing evidence against the extended Church-Turing thesis, remains one of the key challenges of modern science. Boson sampling seems to be a very promising platform in this regard, but to be confident of attaining the advantage regime, one must provide evidence of operating with a correct boson sampling distribution, rather than with a pathological classically simulatable one. This problem is often called the validation problem, and it poses a major challenge to demonstrating unambiguous quantum advantage. In this work, using the recently proposed wave function network approach, we study the sample space filling behavior with increasing the number of collected samples. We show that due to the intrinsic nature of the boson sampling wave function, its filling behavior can be computationally efficiently distinguished from classically simulated cases. Therefore, we propose a new validation protocol based on the sample space filling analysis and test it for problems of up to 202020 photons injected into a 400400400-mode interferometer. Due to its simplicity and computational efficiency, it can be used among other protocols to validate future experiments to provide more convincing results.
Abstract An important challenge with the current generation of noisy, large-scale quantum computers is the question of validation. Does the hardware generate correct answers? If not, what are the errors? This issue is often combined with questions of computational advantage, but it is a fundamentally distinct issue. In current experiments, complete validation of the output statistics is generally not possible because it is exponentially hard to do so. Here, we apply phase-space simulation methods to partially verify recent experiments on Gaussian boson sampling (GBS) implementing photon-number resolving detectors. The positive-P phase-space distribution is employed, as it uses probabilistic sampling to reduce complexity. It is ∼ 10 18 times faster than direct classical simulation for experiments on 288 modes where quantum computational advantage is claimed. When combined with binning and marginalization to improve statistics, multiple validation tests are efficiently computable, of which some tests can be carried out on experimental data. We show that the data as a whole has discrepancies with theoretical predictions for perfect squeezing. However, a modification of the GBS parameters greatly improves agreement for some tests. We suggest that such validation tests could form the basis of feedback methods to improve GBS experiments.
Summary form only given. Recently, interference of multi-particle states has raised a strong interest in the scientific community, since it is believed to be at the very heart of post-classical computation. In this context, Boson Sampling [1] devices exploit multi-photon interference effects to provide evidence of a superior quantum computational power with current state-of-the-art technology. Thus, the capability to correctly certify the presence of multi-particle interference and find optimal platforms, becomes a crucial task because is expected to find numerous applications in photonic quantum information as a diagnostic tool for quantum optical devices.We investigate different scenarios, namely, when the consider only a fixed set of input modes, but also for the situation where all input sets can be used. We find that, in certain cases, the best choice for this task consist of Hadamard [2,3] interferometers which we implemented with a novel architecture enabled by the 3D capabilities of femtosecond laser writing. We derive and experimentally demonstrate a novel zero-transmission law based on symmetric interferometers (Fig. 1) and we verifyied the optimality of these platforms by performing further Bayesian analysis and by maximizing the total variation distance between the probability distributions corresponding to indistinguishable and distinguishable particles. The results suggest an immediate application for scattershot Boson Sampling experiments [4], where an exponential advantage in terms of generation rate is obtained with respect to the fixed-input problem. The main advantage of this technique consists in the large fraction of input-output suppressed combinations when these trasformations are injected with indistinguishable photons. In summary, this work represents a further step for quantum interference analysis and it is worth noting that Hadamard matrices naturally appear as the optimal designs for identifying genuine photonic indistinguishability in multimode interferometers and a powerful tool to validate Boson Sampling experiments. We aknowledge QUCHIP and 3D-Quest for funding this work.