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[Editor's Pick] Current Optics and Photonics Vol. 9 no. 1 (2025 February)

사무국 hit 236 date 2025-02-25

Recent Theoretical and Experimental Progress on Boson Sampling

Changhun Oh*

 

Current Optics and Photonics  Vol. 9 No. 1 (2025 Februrary), pp. 1-18
DOI: https://doi.org/10.3807/COPP.2025.9.1.1 

Transverse cross section of the proposed photonic crystal fiber (PCF) design, and the extended view of the slotted porous core.

Fig. 1  Setup for Fock-state boson sampling. N indistingui shable photons pass through an M-mode interferometer, and then are measured at the output modes on the Fock basis. Reprinted from R. Garcia-Patron et al. Quantum 2019; 3; 169. Copyright © 2019, R. Garcia-Patron et al. [35].

 
Keywords: Boson sampling, Quantum advantage, Quantum computer, Quantum optics
OCIS codes: (270.0270) Quantum optics; (270.5585) Quantum information and processing; (270.6570) Squeezed states


Abstract
Boson sampling is a restricted model of quantum computation, designed to achieve quantum advantage using nonuniversal quantum systems. By harnessing the quantum interference of indistinguishable bosons (typically photons), it becomes possible to sample from a probability distribution, which is intractable for classical computers. This paper reviews the theoretical foundations of boson sampling and its variations, including Fock-state, scattershot, and Gaussian boson sampling, along with significant experimental progress, from early small-scale demonstrations to large-scale quantum supremacy claims. We further explore classical algorithms for simulating boson sampling, which are crucial for benchmarking the performance of experimental results. Finally we examine potential applications of boson sampling in various fields, including simulation of molecular vibronic spectra in quantum chemistry, and solution of graph-based problems in optimization. These applications demonstrate the wide-ranging impact that boson sampling could have on industries that rely on complex computational models, making it a promising quantum technology for near-term applications.