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arXiv:1705.05299 · Physical Review A

Boson sampling with Gaussian measurements

Levon Chakhmakhchyan, Nicolas J. Cerf

Published Sep 14, 2017• 53 citations
arXivHTMLPDF

Abstract

We develop an alternative boson sampling model operating on single-photon states followed by linear interferometry and Gaussian measurements. The hardness proof for simulating such continuous-variable measurements is established in two main steps, making use of the symmetry of quantum evolution under time reversal. Namely, we first construct a twofold version of scattershot boson sampling in which, as opposed to the original proposal, both legs of a collection of two-mode squeezed vacuum states undergo parallel linear-optical transformations. This twofold scattershot model yields, as a corollary, an instance of boson sampling from Gaussian states where photon counting is hard to simulate. Then, a time-reversed setup is used to exhibit a boson sampling model in which the simulation of Gaussian measurements---namely the outcome of eight-port homodyne detection---is proven to be computationally hard. These results illustrate how the symmetry of quantum evolution under time reversal may serve as a tool for analyzing the computational complexity of novel physically motivated computational problems.

DOI
10.1103/physreva.96.032326

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A universal quantum computer of moderate scale is not available yet, however intermediate models of quantum computation would still permit demonstrations of a quantum computational advantage over classical computing and could challenge the Extended Church-Turing Thesis. One of these models based on single photons interacting via linear optics is called Boson Sampling. Although Boson Sampling was demonstrated and the threshold to claim quantum computational advantage was achieved, the question on how to scale up Boson Sampling experiments remains. To make progress with this problem, here we present a practically achievable pathway to scale Boson Sampling experiments with current technologies by combining continuous-variables quantum information and temporal encoding. We propose the use of switchable dual-homodyne and single-photon detections, the temporal loop technique and scattershot based Boson Sampling. This proposal gives details as to what the required assumptions are and a pathway for scaling Boson Sampling experiments. Furthermore, this particular combination of techniques permits a single efficient implementation of Boson Sampling and efficient certification in a single experimental setup.
A universal quantum computer of moderate scale is not available yet, however intermediate models of quantum computation would still permit demonstrations of a quantum computational advantage over classical computing and could challenge the Extended Church-Turing Thesis. One of these models based on single photons interacting via linear optics is called Boson Sampling. Proof-of-principle Boson Sampling has been demonstrated, but the number of photons used for these demonstrations is below the level required to claim quantum computational advantage. To make progress with this problem, here we conclude that the most practically achievable pathway to scale Boson Sampling experiments with current technologies is by combining continuous-variables quantum information and temporal encoding. We propose the use of switchable dual-homodyne and single-photon detections, the temporal loop technique and scattershot based Boson Sampling. This proposal gives details as to what the required assumptions are and a pathway for a quantum optical demonstration of quantum computational advantage. Furthermore, this particular combination of techniques permits a single efficient implementation of Boson Sampling and efficient verification in a single experimental setup.
Gaussian boson sampling (GBS) seeks quantum advantage by sampling photon-number patterns generated with squeezed inputs and passive linear optics. Many proposed GBS applications instead target function computation by applying functions to mode-resolved photon-number outcomes---a natural form of experimental postprocessing that produces classical outputs. Sampling hardness alone, however, does not determine the complexity of these tasks. By analyzing the irreducible decomposition of fixed-photon-number operator spaces, we prove that the expectation value of every such function in the average case over passive linear-optical networks can be classically evaluated for inputs with finite squeezing strength. We also provide a classical algorithm that estimates this value to inverse-polynomial additive error. The result provides new theoretical tools for analyzing linear-optical quantum systems, helps clarify the origin of current GBS hardness evidence, and inspires new applications of GBS with genuine quantum advantages.
A universal quantum computer of moderate scale is not available yet, however intermediate models of quantum computation would still permit demonstrations of a quantum computational advantage over classical computing and could challenge the Extended Church-Turing Thesis. One of these models based on single photons interacting via linear optics is called Boson Sampling. Proof-of-principle Boson Sampling has been demonstrated, but the number of photons used for these demonstrations is below the level required to claim quantum computational advantage. To make progress with this problem, here we conclude that the most practically achievable pathway to scale Boson Sampling experiments with current technologies is by combining continuous-variables quantum information and temporal encoding. We propose the use of switchable dual-homodyne and single-photon detections, the temporal loop technique and scattershot based Boson Sampling. This proposal gives details as to what the required assumptions are and a pathway for a quantum optical demonstration of quantum computational advantage. Furthermore, this particular combination of techniques permits a single efficient implementation of Boson Sampling and efficient verification in a single experimental setup.
Boson sampling is a quantum mechanical task involving Fock basis state preparation and detection and evolution using only linear interactions. A classical algorithm for producing samples from this quantum task cannot be efficient unless the polynomial hierarchy of complexity classes collapses, a situation believed to be highly implausible. We present a method for constructing a device which uses Fock state preparations, linear interactions, and Gaussian continuous-variable measurements for which one can show that exact sampling would be hard for a classical algorithm in the same way as boson sampling. The detection events used from this arrangement do not allow a similar conclusion to be drawn for the classical hardness of approximate sampling. We discuss the details of this result outlining some specific properties required by approximate sampling hardness.