Abstract
Gaussian boson sampling is gaining relevance among the multiple technologies currently implementing quantum computing. The problem of sampling out of a boson distribution across multiple modes has a strong mathematical connection with combinatorics problems, with multiple practical applications that would classically be unfeasible to solve within reasonable time. The software stack that accompanies this GBS approach, and that takes the application from its high-level description to the hardware implementation, is the main focus of this paper. The general compilation process of Gaussian boson samplers is described in detail. The specifics of the Strawberry Fields (Xanadu) compilation and simulation framework are discussed, along with its time profiling, and time implications on computationally significant problem sizes. Last, a compilation step to reduce the hardware description complexity is presented, demonstrating a linear reduction on the overall number of operators when the number of Gaussian operators increases.
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References
Lund A, Laing A, Rahimi-Keshari S, Rudolph T, O’Brien J, Ralph T (2014) Boson sampling from a gaussian state. Phys Rev Lett. https://doi.org/10.1103/PhysRevLett.113.100502
Gard BT, Motes KR, Olson JP, Rohde PP, Dowling JP (2015) An introduction to boson-sampling, From Atomic to Mesoscale, pp 167–192. https://doi.org/10.1142/97898146787040008
Aaronson S, Arkhipov A (2013) The computational complexity of linear optics. Theory Comput 9:143–252. https://doi.org/10.4086/toc.2013.v009a004
Zhong H-S, Wang H, Deng Y-H, Chen M-C, Peng L-C, Luo Y-H, Qin J, Wu D, Ding X, Huet Y (2020) Quantum computational advantage using photons. Science 370(6523):1460–1463
Madsen LS, Laudenbach F, Askarani MF, Rortais F, Vincent T, Bulmer JFF, Miatto FM, Neuhaus L, Helt LG, Collins MJ, Lita AE, Gerrits T, Nam SW, Vaidya VD, Menotti M, Dhand I, Vernon Z, Quesada N, Lavoie J (2022) Quantum computational advantage with a programmable photonic processor. Nature 606:75–981
Killoran N, Izaac J, Weedbrook C et al (2019) Strawberry fields: a software platform for photonic quantum computing. Quantum 3:129
Bromley TR, Arrazola JM, Jahangiri S, Izaac J, Quesada N, Gran AD, Schuld M, Swinarton J, Zabaneh Z, Killoran N (2020) Applications of near-term photonic quantum computers: software and algorithms. Quantum Sci Technol 5:034010
Xanadu, “Strawberry Fields” Available: https://strawberryfields.ai/
Xanadu AI. Available: “https://www.xanadu.ai/”
Ye H, Gao J, Ding Y (2007) A generalized Gronwall inequality and its application to a fractional differential equation. J Math Anal Appl 328:1075–1081
Timjan K, Nicolas Q (2021) Exact and approximate continuous-variable gate decompositions. Open J Quantum Sci. https://doi.org/10.22331/q-2021-02-08-394
Craig SH, Regina K, Linda S, Sonja B, Christine S, Igor J (2017) Gaussian Boson Sampling. Phys Rev Lett 119:170501
Grier D, Brod DJ, Arrazola JM, de Andrade Alonso MB, Quesada N (2022) The complexity of bipartite Gaussian boson sampling. Quantum 6:863
Deshpande A, Mehta A, Vincent T, Quesada N, Hinsche M, Ioannou M, Madsen L, Lavoie J, Qi H, Eisert J, Hangleiter D (2022) Quantum computational advantage via high-dimensional Gaussian boson sampling. Sci Adv 8(1):eabi7894
Lopez Alarcon S, Haverly A (2021) A comparison of quantum algorithms for the maximum clique problem. Available: https://medium.com/xanaduai/a-comparison-of-quantum-algorithms-for-the-maximum-clique-problem-4cd8984cea59
Lopez Alarcon S, Haverly A (2022) Quantum programming paradigms: boson sampling versus qubit gates. In: SPIE photonics for quantum
Weedbrrok C, Pirandola S, Garcia-Patron R, Cerf NC, Ralf TC, Shapiro JH, Lloyd S (2012) Gaussian quantum information. Rev Modern Phys 84:621
“Executing programs on X8 devices” Available: https://strawberryfields.ai/photonics/demos/tutorial_X8.html
Arrazola JM et al (2021) Quantum circuits with many photons on a programmable nanophotonic chip. Nature 591(7848):54–60
Xanadu, “CV Quantum Gate Visualizations”. Available: https://strawberryfields.ai/photonics/demos/run gatevisualization.html
Chakhmakhchyan L, Cerf NJ (2018) Simulating arbitrary Gaussian circuits with linear optics. Phys Rev A 98(6):062314
Clements WR, Humphreys PC, Metcalf BJ, Steven Kolthammer W, Walmsley IA (2016) Optimal design for universal multiport interferometers. Optica 3:1460–1465
Grier D, Brod DJ, Arrazola JM, de Andrade Alonso MB, Quesada N (2022) The complexity of bipartite Gaussian boson sampling. Quantum 6:863
Acknowledgements
We acknowledge the computational resources and support provided by Xanadu, through their Quantum Sandbox program, and Nicolas Quesada for his invaluable help.
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Lopez Alarcon, S., Rueda, F. Compilation of Gaussian boson samplers for quantum computing. J Supercomput 79, 10533–10554 (2023). https://doi.org/10.1007/s11227-023-05075-9
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DOI: https://doi.org/10.1007/s11227-023-05075-9