Random circuits satisfy an ergodicity condition for positive-coefficient polynomials, and its deviation can benchmark quantum chip fidelity, recovering and generalizing linear cross-entropy benchmarking.
Gaussian Boson Sampling
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Boson Sampling has emerged as a tool to explore the advantages of quantum over classical computers as it does not require a universal control over the quantum system, which favours current photonic experimental platforms.Here, we introduce Gaussian Boson Sampling, a classically hard-to-solve problem that uses squeezed states as a non-classical resource. We relate the probability to measure specific photon patterns from a general Gaussian state in the Fock basis to a matrix function called the hafnian, which answers the last remaining question of sampling from Gaussian states. Based on this result, we design Gaussian Boson Sampling, a #P hard problem, using squeezed states. This approach leads to a more efficient photonic boson sampler with significant advantages in generation probability and measurement time over currently existing protocols.
citation-role summary
citation-polarity summary
fields
quant-ph 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Generalized Cross-Entropy Benchmarking for Random Circuits with Ergodicity
Random circuits satisfy an ergodicity condition for positive-coefficient polynomials, and its deviation can benchmark quantum chip fidelity, recovering and generalizing linear cross-entropy benchmarking.