Efficiently simulating the work distribution of multiple identical bosons with boson sampling

• URL: http://arxiv.org/abs/2201.01562v4
• Date: Thu, 9 Nov 2023 13:06:01 GMT
• Title: Efficiently simulating the work distribution of multiple identical bosons with boson sampling
• Authors: Wen-Qiang Liu and Zhang-qi Yin
• Abstract summary: Boson sampling has been theoretically proposed and experimentally demonstrated to show quantum computational advantages. We propose that boson sampling can be used to efficiently simulate the work distribution of multiple identical bosons.
• Score: 2.0564677229048987
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Boson sampling has been theoretically proposed and experimentally demonstrated to show quantum computational advantages. However, it still lacks the deep understanding of the practical applications of boson sampling. Here we propose that boson sampling can be used to efficiently simulate the work distribution of multiple identical bosons. We link the work distribution to boson sampling and numerically calculate the transition amplitude matrix between the single-boson eigenstates in a one-dimensional quantum piston system, and then map the matrix to a linear optical network of boson sampling. The work distribution can be efficiently simulated by the output probabilities of boson sampling using the method of the grouped probability estimation. The scheme requires at most a polynomial number of the samples and the optical elements. Our work opens up a new path towards the calculation of complex quantum work distribution using only photons and linear optics.

Related papers

• Iterated Denoising Energy Matching for Sampling from Boltzmann Densities [109.23137009609519]
  Iterated Denoising Energy Matching (iDEM) iDEM alternates between (I) sampling regions of high model density from a diffusion-based sampler and (II) using these samples in our matching objective. We show that the proposed approach achieves state-of-the-art performance on all metrics and trains $2-5times$ faster.
  arXiv  Detail & Related papers  (2024-02-09T01:11:23Z)
• Transition of Anticoncentration in Gaussian Boson Sampling [0.0]
  We develop a graph-theoretic framework for analyzing the moments of the Gaussian Boson Sampling distribution. We show that when the number of initially squeezed modes scales sufficiently slowly with the number of photons, there is a lack of anticoncentration.
  arXiv  Detail & Related papers  (2023-12-13T19:00:00Z)
• Simulating Gaussian boson sampling quantum computers [68.8204255655161]
  We briefly review recent theoretical methods to simulate experimental Gaussian boson sampling networks. We focus mostly on methods that use phase-space representations of quantum mechanics. A brief overview of the theory of GBS, recent experiments and other types of methods are also presented.
  arXiv  Detail & Related papers  (2023-08-02T02:03:31Z)
• Photonic quantum signatures of chaos and boson sampling [0.0]
  In a typical boson sampling experiment, the scattering amplitude is determined by the permanent of a submatrix of a unitary drawn from an ensemble of random matrices. We show that the unitary dynamics of a Floquet system may be exploited to perform sampling tasks with identical particles using single-mode phase shifters and multiport beamsplitters.
  arXiv  Detail & Related papers  (2023-07-25T01:38:57Z)
• Unsupervised Learning of Sampling Distributions for Particle Filters [80.6716888175925]
  We put forward four methods for learning sampling distributions from observed measurements. Experiments demonstrate that learned sampling distributions exhibit better performance than designed, minimum-degeneracy sampling distributions.
  arXiv  Detail & Related papers  (2023-02-02T15:50:21Z)
• Importance sampling for stochastic quantum simulations [68.8204255655161]
  We introduce the qDrift protocol, which builds random product formulas by sampling from the Hamiltonian according to the coefficients. We show that the simulation cost can be reduced while achieving the same accuracy, by considering the individual simulation cost during the sampling stage. Results are confirmed by numerical simulations performed on a lattice nuclear effective field theory.
  arXiv  Detail & Related papers  (2022-12-12T15:06:32Z)
• Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models [65.52639709094963]
  Methods such as beam search and Gumbel top-k sampling can guarantee a different output for each element of the beam, but are not easy to parallelize. We present a framework for sampling according to an arithmetic code book implicitly defined by a large language model.
  arXiv  Detail & Related papers  (2022-10-18T22:19:41Z)
• Certification of Gaussian Boson Sampling via graph theory [4.063872661554895]
  We exploit a connection between photon counting of a genuine Gaussian Boson Sampling device and the number of perfect matchings in a graph. Within this framework, two approaches that exploit the distributions of graph feature vectors and graph kernels are presented.
  arXiv  Detail & Related papers  (2022-02-15T20:22:28Z)
• Bosonic field digitization for quantum computers [62.997667081978825]
  We address the representation of lattice bosonic fields in a discretized field amplitude basis. We develop methods to predict error scaling and present efficient qubit implementation strategies.
  arXiv  Detail & Related papers  (2021-08-24T15:30:04Z)
• Boson Sampling with Gaussian input states: toward efficient scaling and certification [0.0]
  We present a practically achievable pathway to scale Boson Sampling experiments. We propose the combination of switchable dual-homodyne and single-photon detections, the temporal loop technique, and scattershot-based Boson Sampling.
  arXiv  Detail & Related papers  (2018-12-21T07:15:03Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.