Simulability of Imperfect Gaussian and Superposition Boson Sampling

We study the hardness of classically simulating Gaussian boson sampling at nonzero photon distinguishability. We find that similar to regular boson sampling, distinguishability causes exponential attenuation of the many-photon interference terms in Gaussian boson sampling. Barring an open problem in the theory of matrix permanents, this leads to an efficient classical algorithm to simulate Gaussian boson sampling in the presence of distinguishability. We also study a new form of boson sampling based on photon number superposition states, for which we also show noise sensivity. The fact that such superposition boson sampling is not simulable with out method at zero distinguishability is the first evidence for the computational hardness of this problem

Marginal probabilities in boson samplers with arbitrary input states

With the recent claim of a quantum advantage demonstration in photonics by Zhong et al, the question of the computation of lower-order approximations of boson sampling with arbitrary quantum states at arbitrary distinguishability has come to the fore. In this work, we present results in this direction, building on the results of Clifford and Clifford. In particular, we show: 1) How to compute marginal detection probabilities (i.e. probabilities of the detection of some but not all photons) for arbitrary quantum states. 2) Using the first result, how to generalize the sampling algorithm of Clifford and Clifford to arbitrary photon distinguishabilities and arbitrary input quantum states. 3) How to incorporate truncations of the quantum interference into a sampling algorithm. 4) A remark considering maximum likelihood verification of the recent photonic quantum advantage experiment

Quantum-to-classical transition in many-body bosonic interference

Bosonic many-body systems are prominent candidates for a quantum advantage demonstration, with the most popular approaches being either a quantum simulation beyond the reach of current classical computers, or a demonstration of boson sampling. It is a crucial open problem to understand how resilient such quantum advantage demonstrations are to imperfections such as boson loss and particle distinguishability. We partially solve this problem by showing that imperfect multi-boson interference can be efficiently approximated as ideal interference of groups of smaller number of bosons, where the other particles interfere classically. Crucially, the number of bosons undergoing interference in our approxmation only depends on the level of imperfections, but is independent of the actual number of particles. This allows us to construct a simple but stringent benchmark for comparing many-body bosonic technological platforms

Simulating boson sampling in lossy architectures

Photon losses are among the strongest imperfections affecting multi-photon interference. Despite their importance, little is known about their effect on boson sampling experiments. In this work we show that using classical computers, one can efficiently simulate multi-photon interference in all architectures that suffer from an exponential decay of the transmission with the depth of the circuit, such as integrated photonic circuits or optical fibers. We prove that either the depth of the circuit is large enough that it can be simulated by thermal noise with an algorithm running in polynomial time, or it is shallow enough that a tensor network simulation runs in quasi-polynomial time. This result suggests that in order to implement a quantum advantage experiment with single-photons and linear optics new experimental platforms may be needed

Gaussian Optical Ising Machines

It has recently been shown that optical parametric oscillator (OPO) Ising machines, consisting of coupled optical pulses circulating in a cavity with parametric gain, can be used to probabilistically find low-energy states of Ising spin systems. In this work, we study optical Ising machines that operate under simplified Gaussian dynamics. We show that these dynamics are sufficient for reaching probabilities of success comparable to previous work. Based on this result, we propose modified optical Ising machines with simpler designs that do not use parametric gain yet achieve similar performance, thus suggesting a route to building much larger systems.Comment: 6 page

Classically simulating near-term partially-distinguishable and lossy boson sampling

Boson Sampling is the problem of sampling from the same distribution as indistinguishable single photons at the output of a linear optical interferometer. It is an example of a non-universal quantum computation which is believed to be feasible in the near term and cannot be simulated on a classical machine. Like all purported demonstrations of "quantum supremacy", this motivates optimizing classical simulation schemes for a realistic model of the problem, in this case Boson Sampling when the implementations experience lost or distinguishable photons. Although current simulation schemes for sufficiently imperfect boson sampling are classically efficient, in principle the polynomial runtime can be infeasibly large. In this work, we develop a scheme for classical simulation of Boson Sampling under uniform distinguishability and loss, based on the idea of sampling from distributions where at most k photons are indistinguishable. We show that asymptotically this scheme can provide a polynomial improvement in the runtime compared to classically simulating idealised Boson Sampling. More significantly, we show that in the regime considered experimentally relevant, our approach gives an substantial improvement in runtime over other classical simulation approaches.Comment: 15 pages, 5 figures, comments welcom

Photon distillation schemes with reduced resource costs based on multiphoton Fourier interference

Improving the indistinguishability of single photons is a crucial prerequisite for achieving large-scale photonic quantum computation. Photon distillation uses quantum interference to enhance the quality of single photons, sacrificing multiple photons to generate one photon with enhanced indistinguishability. By studying multiphoton interference in Fourier matrices, we find photon distillation schemes that require fewer photons to achieve the same improvement in indistinguishability, compared to the state of the art. These results may find application as a component in large-scale photonic quantum computers.<br/