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The Aaronson–Ambainis conjecture

Show that every bounded low-degree polynomial on the Boolean cube with non-negligible variance has a variable of polynomially large influence.

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The Aaronson–Ambainis conjecture

The acceptance probability of a quantum algorithm that makes TT queries to an NN-bit input is a polynomial of degree at most 2T2T in the input bits, taking values in [0,1][0,1]. Aaronson and Ambainis conjectured that every such bounded low-degree polynomial that is not nearly constant has a variable with large influence. If true, every quantum query algorithm could be simulated on most inputs by a classical one with only polynomially more queries, so large quantum speedups would need structure, such as a promise on the input.

Problem

Let p:RN→Rp:\mathbb{R}^N\to\mathbb{R} be a real polynomial of degree at most dd with

0≤p(X)≤1for all X∈{0,1}N.0\le p(X)\le 1\qquad\text{for all } X\in\{0,1\}^N .

For XX uniform on {0,1}N\{0,1\}^N, let Var[p]=E[(p(X)−E[p])2]\mathrm{Var}[p]=\mathbb{E}\big[(p(X)-\mathbb{E}[p])^2\big], and define the influence of the ii-th variable as

Infi[p]=E[(p(X)−p(Xi))2],\mathrm{Inf}_i[p]=\mathbb{E}\big[(p(X)-p(X^{i}))^2\big],

where XiX^{i} is XX with its ii-th bit flipped.

Conjecture. There is a universal constant CC such that whenever Var[p]≥ε\mathrm{Var}[p]\ge\varepsilon, some variable has Infi[p]≥(ε/d)C\mathrm{Inf}_i[p]\ge(\varepsilon/d)^{C}, independently of NN.

Background

For total Boolean functions, quantum and classical query complexities are polynomially related, while for problems with a promise on the input the quantum advantage can be enormous [1]. Aaronson and Ambainis posed the conjecture, as "bounded polynomials have influential variables", in a paper first circulated in 2009 and published in 2014 [1]. They showed that it implies a folklore conjecture known since about 1999: for every TT-query quantum algorithm and every ε,δ>0\varepsilon,\delta>0, a deterministic classical algorithm making poly(T,1/ε,1/δ)\mathrm{poly}(T,1/\varepsilon,1/\delta) queries approximates its acceptance probability to within ε\varepsilon on all but a δ\delta fraction of inputs. It would also mean that one essentially cannot hope to prove P≠BQP\mathsf{P}\ne\mathsf{BQP} relative to a random oracle [1].

What is known

  • A theorem of Dinur, Friedgut, Kindler and O'Donnell implies the weaker bound Infi[p]≥ε3/2O(d)\mathrm{Inf}_i[p]\ge\varepsilon^3/2^{O(d)}, so every TT-query algorithm can be simulated on most inputs with 2O(T)2^{O(T)} classical queries [1]. The conjecture is known when pp is Boolean-valued [3].
  • In 2019 Keller and Klein posted a proof, then withdrew it after a flaw was found in a key lemma [2].
  • Bansal, Sinha and de Wolf proved the conjecture for completely bounded block-multilinear forms with constant variance, giving efficient classical simulation on most inputs for a class of quantum algorithms that includes kk-fold Forrelation [3].
  • Bhattacharya showed that the conclusion holds for a non-negligible fraction of random restrictions of pp, provided its variance is not too small [4].
  • Blanc, Docter, Strassle and Tan proved the simulation statement for parallel algorithms: a tt-query, dd-round quantum algorithm can be simulated on most inputs with tO(d2)t^{O(d^2)} classical queries (FOCS 2026) [5].
  • Girish, Mittal, Nehoran and Raz showed in September 2026 that analogues for biased product distributions and for slices of the cube are equivalent to the original [6].

What would count as progress

  • A proof for a class larger than that of [3], for example all polynomials that arise as acceptance probabilities of quantum query algorithms, the case behind the simulation consequence [1, 3].
  • A classical simulation with poly(t)\mathrm{poly}(t) queries for quantum algorithms whose number of rounds grows with the input, improving the tO(d2)t^{O(d^2)} bound of [5].
  • A counterexample: explicit degree-dd polynomials bounded in [0,1][0,1] on the cube, with variance at least ε\varepsilon and all influences (ε/d)ω(1)(\varepsilon/d)^{\omega(1)}. For small NN these properties can be checked exhaustively.

References

  1. S. Aaronson and A. Ambainis, "The need for structure in quantum speedups", Theory of Computing 10, 133–166 (2014). doi:10.4086/toc.2014.v010a006
  2. N. Keller and O. Klein, "Quantum speedups need structure", preprint (2019), withdrawn. arXiv:1911.03748
  3. N. Bansal, M. Sinha and R. de Wolf, "Influence in completely bounded block-multilinear forms and classical simulation of quantum algorithms", in 37th Computational Complexity Conference (CCC 2022), LIPIcs 234, 28 (2022). doi:10.4230/LIPIcs.CCC.2022.28
  4. S. K. Bhattacharya, "Random restrictions of bounded low degree polynomials are juntas", in 16th Innovations in Theoretical Computer Science Conference (ITCS 2025), LIPIcs 325, 17 (2025). doi:10.4230/LIPIcs.ITCS.2025.17
  5. G. Blanc, J. Docter, C. Strassle and L.-Y. Tan, "Quantum speedups require structure or depth", preprint (2026), FOCS 2026. arXiv:2608.19158
  6. U. Girish, K. Mittal, B. Nehoran and R. Raz, "Distributional variants of the Aaronson–Ambainis conjecture", preprint (2026). arXiv:2609.35327

Source

Imported from QIQCOP Zoo op_a11fdfadc84e4379, curated by Bikun Li, Qicheng Tang, Changhao Li, Chengkai Zhu, Minbo Gao, Zhong-Xia Shang, Bin Cheng and Naixu Guo. Open according to the source as of 2026-10-20. The statement above is written in our own words; see the source for the original wording, history and discussion.