Gaussian Boson Sampling

Hamilton, Craig S.; Kruse, Regina; Sansoni, Linda; Barkhofen, Sonja; Silberhorn, Christine; Jex, Igor

doi:10.1103/physrevlett.119.170501

Cited by 366 publications

(379 citation statements)

References 32 publications

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“…It has been utilized to simulate the Anderson localization [46] and Boson sampling [50][51][52]. In particular, the studies on the Gaussian Boson sampling with linear optics elements from both the theoretical [53][54][55] and experimental [56] perspectives support the experimental realization of our CM.…”

Section: Discussionmentioning

confidence: 77%

Information scrambling in a collision model

Jin

2020

Phys. Rev. A

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The information scrambling in many-body systems is closely related to quantum chaotic dynamics, complexity, and gravity. Here we propose a collision model to simulate the information dynamics in an all-optical system. In our model the information is initially localized in the memory and evolves under the combined actions of many-body interactions and dissipation. We find that the information is scrambled if the memory and environmental particles are alternatively squeezed along two directions which are perpendicular to each other. Moreover, the disorder and imperfection of the interaction strength tend to prevent the information flow away to the environment and lead to the information scrambling in the memory. We analyze the spatial distributions of the correlations in the memory. Our proposal is possible to realize with current experimental techniques.

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Section: Discussionmentioning

confidence: 77%

Information scrambling in a collision model

Jin

2020

Phys. Rev. A

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“…Similar to MIS, SC-MCMC is also case independent. Besides boson sampling, SC-MCMC can be directly used as a general sampling framework for any sampling tasks as long as we can evaluate the probabilities for given events, for example the Gaussian boson sampling [26], IQP circuit sampling [27,28] and random quantum circuit sampling [29,30]. Meanwhile, SC-MCMC is particularly suitable for tasks where a large number of samples are taken.…”

Section: The Sample Caching Methodsmentioning

confidence: 99%

“…Particularly, the SC-MCMC method can be used for quantum-enhanced applications based on boson sampling such as simulating the molecular vibronic spectra [23], finding dense subgraphs [24] or approximate optimization [25]. Moreover, Our method can also be directly applied on other quantum supremacy candidates, such as the Gaussian boson sampling [26], the IQP circuit sampling [27,28] and random quantum circuit (RQC) sampling [29,30], especially when a lot of samples are taken for validating the device [31]. (2) On the quantum side, our results suggest that the hardness of demonstrating quantum supremacy by boson sampling is increasing with the development of classical simulator.…”

Section: Introductionmentioning

confidence: 99%

Sample caching Markov chain Monte Carlo approach to boson sampling simulation

Liu

Xiong

et al. 2020

New J. Phys.

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Boson sampling is a promising candidate for quantum supremacy. It requires to sample from a complicated distribution, and is trusted to be intractable on classical computers. Among the various classical sampling methods, the Markov chain Monte Carlo method is an important approach to the simulation and validation of boson sampling. This method however suffers from the severe sample loss issue caused by the autocorrelation of the sample sequence. Addressing this, we propose the sample caching Markov chain Monte Carlo method that eliminates the correlations among the samples, and prevents the sample loss at the meantime, allowing more efficient simulation of boson sampling. Moreover, our method can be used as a general sampling framework that can benefit a wide range of sampling tasks, and is particularly suitable for applications where a large number of samples are taken.

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“…While part of this is due to fundamental interest, there are many practical applications of squeezed light as well, including computation [6], communication [7], and metrology [8]. In recent years, Gaussian Boson Sampling (GBS) [9,10] has emerged as one of the most actively researched applications [11][12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Degenerate squeezing in waveguides: a unified theoretical approach

Helt

Quesada

2020

J. Phys. Photonics

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We consider pulsed-pump spontaneous parametric downconversion (SPDC) as well as pulsed single-and dual-pump spontaneous four-wave mixing processes in waveguides within a unified Hamiltonian theoretical framework. Working with linear operator equations in k-space, our approach allows inclusion of linear losses, self-and cross-phase modulation, and dispersion to any order. We describe state evolution in terms of second-order moments, for which we develop explicit expressions. We use our approach to calculate the joint spectral amplitude of degenerate squeezing using SPDC analytically in the perturbative limit, benchmark our theory against well-known results in the limit of negligible group velocity dispersion, and study the suitability of recently proposed sources for quantum sampling experiments. arXiv:1910.06873v2 [quant-ph] 23 Oct 2019 [1] R. E. Slusher, L. W. Hollberg, B. Yurke, J. C. Mertz, and J. F. Valley. Observation of squeezed states generated by four-wave mixing in an optical cavity. Phys. Rev. Lett.,

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Gaussian Boson Sampling

Cited by 366 publications

References 32 publications

Information scrambling in a collision model

Information scrambling in a collision model

Sample caching Markov chain Monte Carlo approach to boson sampling simulation

Degenerate squeezing in waveguides: a unified theoretical approach

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