ArticleScience advances2022
The boundary for quantum advantage in Gaussian boson sampling.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Training the parametric interactions in an analog bosonic quantum neural network with Fock basis measurement.Scientific reports · 2026Article
- Noise-induced shallow circuits and the absence of barren plateaus.Nature physics · 2026Article
- Noise-tolerant LiDAR approaching the standard quantum-limited precision.Light, science & applications · 2025Article
- A complexity transition in displaced Gaussian Boson sampling.NPJ quantum information · 2025Article
- Hybrid Boson Sampling.Entropy (Basel, Switzerland) · 2024Article
- Speeding up the classical simulation of Gaussian boson sampling with limited connectivity.Scientific reports · 2024Article
- Quantum computing on nucleic acid research: Approaching towards next-generation computing.Molecular therapy. Nucleic acids · 2023Article
- Generation of Pseudo-Random Quantum States on Actual Quantum Processors.Entropy (Basel, Switzerland) · 2023Article
- Classical Modelling of a Bosonic Sampler with Photon Collisions.Entropy (Basel, Switzerland) · 2023Article
- Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying the boundary beyond which quantum machines provide a computational advantage over their classical counterparts is a crucial step in charting their usefulness. Gaussian boson sampling (GBS), in which photons are measured from a highly entangled Gaussian state, is a leading approach in pursuing quantum advantage. State-of-the-art GBS experiments that run in minutes would require 600 million years to simulate using the best preexisting classical algorithms. Here, we present faster classical GBS simulation methods, including speed and accuracy improvements to the calculation of loop hafnians. We test these on a ∼100,000-core supercomputer to emulate GBS experiments with up to 100 modes and up to 92 photons. This reduces the simulation time for state-of-the-art GBS experiments to several months, a nine-orders of magnitude improvement over previous estimates. Last, we introduce a distribution that is efficient to sample from classically and that passes a variety of GBS validation methods.
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Registered trials
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