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Research PaperResearchia:202608.20077

Non-Local Search-to-Decision Reduction over F2

Prabhanjan Ananth

Abstract

Non-local search-to-decision asks whether two noncommunicating parties, given the two shares of a bipartite encoding of a uniformly random string $x\in \mathbb{F}_2^n$, can both predict the same random parity $\langle r,x\rangle$ without there also being local measurements with which both parties recover $x$. We prove that if their optimal probability of both recovering $x$ by local measurements is $p$, then their probability of both answering a common parity challenge correctly is at most $\min...

Submitted: August 20, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

Non-local search-to-decision asks whether two noncommunicating parties, given the two shares of a bipartite encoding of a uniformly random string x∈F2nx\in \mathbb{F}_2^n, can both predict the same random parity ⟨r,x⟩\langle r,x\rangle without there also being local measurements with which both parties recover xx. We prove that if their optimal probability of both recovering xx by local measurements is pp, then their probability of both answering a common parity challenge correctly is at most min⁑{1,12+5p1/22}\min\{1,\frac{1}{2}+5p^{1/22}\}. The result is motivated by applications to unclonable encryption and quantum copy-protection. The proof is information-theoretic and does not provide an efficient extractor. The proof and the exposition were developed with assistance from ChatGPT using GPT-5.6 Sol Pro and Codex in the Ultra reasoning mode.


Source: arXiv:2608.19091v1 - http://arxiv.org/abs/2608.19091v1 PDF: https://arxiv.org/pdf/2608.19091v1 Original Link: http://arxiv.org/abs/2608.19091v1

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Date:
Aug 20, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
Comments:
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