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arXiv:2611.09773 · v1

A proof of the Aaronson-Ambainis conjecture

Aaronson-Ambainis 猜想的证明

首次提交 2026-11-07 01:36
版本更新 2026-11-07 01:36
雷达观测 2026-11-09 13:22
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摘要

Aaronson and Ambainis conjectured that every bounded polynomial of low degree on the discrete cube has an influential variable. They showed that the conjecture implies that the acceptance probability of every quantum algorithm making TT queries can be approximated on most inputs by a classical algorithm making poly(T)\mathrm{poly}(T) queries. We prove their conjecture: every function f ⁣:{−1,1}n→[−1,1]f\colon\{-1,1\}^n\to[-1,1] of degree at most d≥1d\ge1 has a variable of influence at least c Var⁡(f)5/2/d6c\,\operatorname{Var}(f)^{5/2}/d^{6}, where c>0c>0 is an absolute constant. In the original formulation, for polynomials of degree at most dd with values in [0,1][0,1] on {0,1}n\{0,1\}^n and variance at least ε\varepsilon, this gives a variable of influence at least (ε/d)7(\varepsilon/d)^{7}. The proof is elementary, with steps inspired by works of others. Thus, as Aaronson and Ambainis anticipated, superpolynomial quantum speedups in the query model require structure, such as a promise on the inputs.

作者备注:60 pages. Lean formalization and reproducibility materials: https://github.com/physical-superintelligence/aaronson-ambainis

AI 论文解读

基于摘要 · 非全文审阅

作者证明低次有界多项式在离散立方体上必有有影响的变量,从而证实 Aaronson-Ambainis 猜想。

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v1 · 2026-11-07 01:36 · 最新观测版本

A proof of the Aaronson-Ambainis conjecture

Aaronson and Ambainis conjectured that every bounded polynomial of low degree on the discrete cube has an influential variable. They showed that the conjecture implies that the acceptance probability of every quantum algorithm making TT queries can be approximated on most inputs by a classical algorithm making poly(T)\mathrm{poly}(T) queries. We prove their conjecture: every function f ⁣:{−1,1}n→[−1,1]f\colon\{-1,1\}^n\to[-1,1] of degree at most d≥1d\ge1 has a variable of influence at least c Var⁡(f)5/2/d6c\,\operatorname{Var}(f)^{5/2}/d^{6}, where c>0c>0 is an absolute constant. In the original formulation, for polynomials of degree at most dd with values in [0,1][0,1] on {0,1}n\{0,1\}^n and variance at least ε\varepsilon, this gives a variable of influence at least (ε/d)7(\varepsilon/d)^{7}. The proof is elementary, with steps inspired by works of others. Thus, as Aaronson and Ambainis anticipated, superpolynomial quantum speedups in the query model require structure, such as a promise on the inputs.

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