# Gaussian boson sampling using threshold detectors

@article{Quesada2018GaussianBS, title={Gaussian boson sampling using threshold detectors}, author={Nicol{\'a}s Quesada and Juan Miguel Arrazola and Nathan Killoran}, journal={Physical Review A}, year={2018} }

We study what is arguably the most experimentally appealing Boson Sampling architecture: Gaussian states sampled with threshold detectors. We show that in this setting, the probability of observing a given outcome is related to a matrix function that we name the Torontonian, which plays an analogous role to the permanent or the Hafnian in other models. We also prove that, provided that the probability of observing two or more photons in a single output mode is sufficiently small, our model…

## 43 Citations

Training Gaussian boson sampling by quantum machine learning

- Computer Science, PhysicsQuantum Mach. Intell.
- 2021

It is demonstrated that multi-particle events in Gaussian boson sampling can be optimized by a proper design and training of the neural network weights.

Benchmarking of Gaussian boson sampling using two-point correlators

- Physics, Computer SciencePhysical Review A
- 2019

This contribution studies two-point photon-number correlation functions to gain insight into the interference of Gaussian states in optical networks and investigates the characteristic features of statistical signatures which enable us to distinguish classical from quantum interference.

Regimes of Classical Simulability for Noisy Gaussian Boson Sampling.

- Physics, Computer SciencePhysical review letters
- 2020

It is shown that, for most linear-optical architectures, where photon loss increases exponentially with the circuit depth, noisy GBS loses its quantum advantage in the asymptotic limit, and delineate intermediate-sized regimes where GBS devices might considerably outperform classical computers for modest noise levels.

Efficient approximation of experimental Gaussian boson sampling

- Computer Science
- 2021

Two recent landmark experiments have performed Gaussian boson sampling (GBS) with a nonprogrammable linear interferometer and threshold detectors on up to 144 output modes (see Refs. 1 and 2). Here…

Effect of partial distinguishability on quantum supremacy in Gaussian Boson sampling

- Computer Sciencenpj Quantum Information
- 2022

This paper develops a model and algorithm and shows how the boundary of quantum supremacy in GBS can be affected by partial distinguishability, and proposes an efficient classical simulation algorithm which can be used to calculate the probabilities.

Gaussian boson sampling and multi-particle event optimization by machine learning in the quantum phase space

- Computer Science, PhysicsArXiv
- 2021

The layered neural networks are used to represent the characteristic function of many-body Gaussian states in the quantum phase space, and it is demonstrated that multiparticle events in Gaussian boson sampling can be optimized by a proper design and training of the neural network weights.

Point processes with Gaussian boson sampling.

- Computer SciencePhysical review. E
- 2020

It is shown that Gaussian boson sampling can be used to implement a class of point processes based on hard-to-compute matrix functions which, in general, are intractable to simulate classically.

Classical benchmarking of Gaussian Boson Sampling on the Titan supercomputer

- Physics, Computer ScienceQuantum Inf. Process.
- 2020

This work employs a recent exact sampling algorithm for GBS with threshold detectors to perform classical simulations on the Titan supercomputer and indicates that large losses can be tolerated and that the use of threshold detectors is preferable over using photon-number-resolving detectors postselected on collision-free outputs.

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