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This paper delivers a polynomial-time algorithmic solution to Marton's conjecture, directly enabling efficient learning protocols for quantum states with bounded stabilizer extent. By bridging combinatorial theory with practical computation, the work establishes new pathways for agnostic tomography and quadratic Goldreich-Levin problems within quantum information science.
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Marton's conjecture in polynomial time

arXiv1 min read

arXiv:2609.20771v1 Announce Type: cross Abstract: Gowers, Green, Manners, and Tao (Annals '25) recently resolved Marton's polynomial Freiman-Ruzsa conjecture. We give an algorithmic counterpart to their result: given uniform sampling and membership-oracle access to a set $A \subseteq \mathbb{F}_2^n$ with doubling constant at most $K$, our algorithm outputs a subspace of size at most $|A|$ whose $K^{O(1)}$ translates cover $A$. The algorithm runs in $\textsf{poly}(n,K)$ time. As applications, we obtain polynomial-time algorithms for a variety of learning problems, including quadratic Goldreich-Levin, improper agnostic tomography of stabilizer states, and tomography of quantum states with bounded stabilizer extent.

Abstract:Gowers, Green, Manners, and Tao (Annals '25) recently resolved Marton's polynomial Freiman-Ruzsa conjecture. We give an algorithmic counterpart to their result: given uniform sampling and membership-oracle access to a set $A \subseteq \mathbb{F}_2^n$ with doubling constant at most $K$, our algorithm outputs a subspace of size at most $|A|$ whose $K^{O(1)}$ translates cover $A$. The algorithm runs in $\textsf{poly}(n,K)$ time. As applications, we obtain polynomial-time algorithms for a variety of learning problems, including quadratic Goldreich-Levin, improper agnostic tomography of stabilizer states, and tomography of quantum states with bounded stabilizer extent.

Computational Complexity (cs.CC); Combinatorics (math.CO); Quantum Physics (quant-ph)

arXiv:2609.20771 [cs.CC]

(or arXiv:2609.20771v1 [cs.CC] for this version)

https://doi.org/10.48550/arXiv.2609.20771 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 189 words

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