Detailed study of Gaussian boson sampling

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

doi:10.1103/physreva.100.032326

Cited by 144 publications

(131 citation statements)

References 56 publications

(96 reference statements)

Supporting

Mentioning

130

Contrasting

Order By: Relevance

“…In analogy with Boson Sampling, one might wonder if there is a matrix function, related to graphs, that is proportional to the FCFs of a given vibronic molecular transition. An important step in answering this question was taken by Hamilton et al 13 and Kruse et al 14 Using phase-space methods, they showed that, for the case of squeezed states (with no displacement) going into a linear optical network and probed with PNRD, the probability (not the amplitude) of given Fock number detection event is proportional to another matrix function called the hafnian. The hafnian counts the number of perfect matchings of an undirected graph without loops.…”

Section: Introductionmentioning

confidence: 99%

Franck-Condon factors by counting perfect matchings of graphs with loops

Quesada

2019

The Journal of Chemical Physics

View full text Add to dashboard Cite

We show that the Franck-Condon Factor (FCF) associated to a transition between initial and final vibrational states in two different potential energy surfaces, having N and M vibrational quanta, respectively, is equivalent to calculating the number of perfect matchings of a weighted graph with loops that has P = N + M vertices. This last quantity is the loop hafnian of the (symmetric) adjacency matrix of the graph which can be calculated in O(P 3 2 P/2 ) steps. In the limit of small numbers of vibrational quanta per normal mode our loop hafnian formula significantly improves the speed at which FCFs can be calculated. Our results more generally apply to the calculation of the matrix elements of a bosonic Gaussian unitary between two multimode Fock states having N and M photons in total and provide a useful link between certain calculations of quantum chemistry, quantum optics and graph theory. arXiv:1811.09597v2 [quant-ph]

show abstract

Section: Introductionmentioning

confidence: 99%

Franck-Condon factors by counting perfect matchings of graphs with loops

Quesada

2019

The Journal of Chemical Physics

View full text Add to dashboard Cite

show abstract

“…Recently, a new protocol called Gaussian boson sampling (GBS) [17,20,21] offers a unique shortcut to enormously enhance the generation efficiency based on parametric down-conversion (PDC). The GBS exploited the full Gaussian nature of the photon sources, while the previous works [4,5,9] relied on probabilistically post-selected singlephoton Fock states from the Gaussian state naturally produced by PDC.…”

Section: Introductionmentioning

confidence: 99%

Experimental Gaussian Boson sampling

Zhong

Peng

et al. 2019

Science Bulletin

View full text Add to dashboard Cite

Gaussian Boson sampling (GBS) provides a highly efficient approach to make use of squeezed states from parametric down-conversion to solve a classically hard-to-solve sampling problem. The GBS protocol not only significantly enhances the photon generation probability, compared to standard boson sampling with single photon Fock states, but also links to potential applications such as dense subgraph problems and molecular vibronic spectra. Here, we report the first experimental demonstration of GBS using squeezed-state sources with simultaneously high photon indistinguishability and collection efficiency. We implement and validate 3-, 4-and 5-photon GBS with high sampling rates of 832 kHz, 163 kHz and 23 kHz, respectively, which is more than 4.4, 12.0, and 29.5 times faster than the previous experiments. Further, we observe a quantum speed-up on a NP-hard optimization problem when comparing with simulated thermal sampler and uniform sampler.

show abstract

“…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: 76%

Information scrambling in a collision model

Jin

2020

Phys. Rev. A

View full text Add to dashboard Cite

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.

show abstract

Detailed study of Gaussian boson sampling

Cited by 144 publications

References 56 publications

Franck-Condon factors by counting perfect matchings of graphs with loops

Franck-Condon factors by counting perfect matchings of graphs with loops

Experimental Gaussian Boson sampling

Information scrambling in a collision model

Contact Info

Product

Resources

About