aiqbench analysis
This research presents a sample- and time-efficient algorithm for learning bosonic Fock states under Gaussian unitaries, directly addressing an open problem in BosonSampling complexity. By leveraging higher moments to define state invariants, the study establishes necessary conditions for state equivalence beyond standard linear optics. The work advances the theoretical understanding of quantum state characterization and its learnability within photonic quantum computing frameworks.
Higher moment theory and learnability of bosonic states
arXiv:2510.01610v2 Announce Type: replace Abstract: We present a sample- and time-efficient algorithm to learn any bosonic Fock state acted upon by an arbitrary Gaussian unitary. As a special case, this algorithm efficiently learns states produced in Fock state BosonSampling, thus resolving an open question put forth by Aaronson and Grewal (Aaronson, Grewal 2023). We further study a hierarchy of classes of states beyond Gaussian states that are specified by a finite number of their higher moments. Using the higher moments, we find a full spectrum of invariants under Gaussian unitaries, thereby providing necessary conditions for two states to be related by an arbitrary (including active, e.g. beyond linear optics) Gaussian unitary.
Abstract:We present a sample- and time-efficient algorithm to learn any bosonic Fock state acted upon by an arbitrary Gaussian unitary. As a special case, this algorithm efficiently learns states produced in Fock state BosonSampling, thus resolving an open question put forth by Aaronson and Grewal (Aaronson, Grewal 2023). We further study a hierarchy of classes of states beyond Gaussian states that are specified by a finite number of their higher moments. Using the higher moments, we find a full spectrum of invariants under Gaussian unitaries, thereby providing necessary conditions for two states to be related by an arbitrary (including active, e.g. beyond linear optics) Gaussian unitary.
9+21 pages, 1 figure. Bounds have been improved for V2
arXiv:2510.01610 [quant-ph]
(or arXiv:2510.01610v2 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2510.01610 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 205 words
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