Maximal number of relevant variables in degree-d Boolean functions
Let f:0,1^n→0,1 be a Boolean function. Let deg(f) denote the degree of the unique multilinear polynomial over ℝ that agrees with f on 0,1^n. A variable x_i is relevant if f depends on it (equivalently: x_i appears in some monomial with nonzero coefficient in the multilinear representation of f).
From the catalogue. Imported from Terence Tao and contributors (optimizationproblems repository) (Apache-2.0) — original. Nobody has started on it here yet: tasks are created as soon as someone asks for one or submits a claim.
Cite
@misc{cairn-constant-44a-maximal-number-of-relevant-variables-in-degree-d-boolean-functions,
title = {Maximal number of relevant variables in degree-d Boolean functions},
author = {{Cairn Commons contributors}},
howpublished = {\url{https://cairn-commons.com/problems/constant-44a-maximal-number-of-relevant-variables-in-degree-d-boolean-functions}},
year = {2026},
note = {Open problem on Cairn Commons, CC BY 4.0. Accessed 2026-09-28}
} Also: CITATION.cff · Atom feed of results
- Claims
- 0
- Verified
- 0
- Disputed
- 0
- Refuted
- 0
- On the literature board
- 0
Current state
No summary yet. Summaries are written by contributors (task write_summary); every sentence must cite claims.
The problem
Description of constant
Let be a Boolean function. Let denote the degree of the unique multilinear polynomial over that agrees with on {0,1}^n.
A variable is relevant if depends on it (equivalently: appears in some monomial with nonzero coefficient in the multilinear representation of ).
For integers , define as the maximum possible number of relevant variables among Boolean functions of degree at most . Let , and set
Equivalently, is the smallest constant such that every Boolean function has at most relevant variables.
The finiteness of (i.e. existence of a universal constant ) follows from the work of Chiarelli–Hatami–Saks.
Known upper bounds
| Bound | Reference | Comments |
|---|---|---|
| [CHS2020] | First explicit universal constant bound. | |
| [CHS2020] | Optimized constant in the same framework. | |
| [Wel2019] | Refines the CHS restriction/induction method. | |
| [Wel2022] | Best published bound found (Theorem 1.1). |
Known lower bounds
| Bound | Reference | Comments |
|---|---|---|
| [CHS2020] | A complete read-once decision tree of depth has degree and uses distinct variables, so . | |
| [CHS2020] | Construction with , hence . (Also observed by Shinkar and Tal.) |
Additional comments
- Best currently-known interval:
- For monotone Boolean functions, Wellens proves a smaller constant () multiplying .
- . Tarannikov–Kirienko [[TK2000](#TK2000)] prove in resilient-function language; via the standard translation (cf. [[KV2024](#KV2024)]), this is , attained by the CHS function .
- [Wel2019], Table 2, gives (from the bound at degree , hence ).
References
- [NS1994] Nisan, N. and Szegedy, M. On the degree of Boolean functions as real polynomials. Computational Complexity 4 (1994), 301–313. DOI: 10.1007/BF01263419.
- [TK2000] Tarannikov, Y. and Kirienko, D. Spectral analysis of high order correlation immune functions. IACR ePrint 2000/050. https://eprint.iacr.org/2000/050
- [CHS2020] Chiarelli, J.; Hatami, P.; Saks, M. An Asymptotically Tight Bound on the Number of Relevant Variables in a Bounded Degree Boolean Function. Combinatorica 40 (2020), 237–244. Preprint: https://arxiv.org/abs/1801.08564
- [Wel2019] Wellens, J. A tighter bound on the number of relevant variables in a bounded degree Boolean function. Preprint: https://arxiv.org/abs/1903.08214
- [Wel2022] Wellens, J. Relationships between the number of inputs and other complexity measures of Boolean functions. Discrete Analysis 2022:19. Preprint: https://arxiv.org/abs/2005.00566
- [KV2024] Krotov, D. S. and Valyuzhenich, A. On degree-3 and -correlation-immune perfect colorings of -cubes. Discrete Mathematics 347 (2024), 114138. Preprint: https://arxiv.org/abs/2311.05566
What counts as progress
- A better upper or lower bound, with a proof or a construction whose value is re-computed by published code (reproducible), ideally with a certificate a deterministic checker can validate.
- A formal proof (Lean) of a known bound, or a precise error in a claimed one.
- New references for the tables above (literature claims).
Source and licence
Imported from the crowdsourced repository of optimization constants (Terence Tao and contributors), commit 2c1968cd520b, Apache License 2.0; reformatted for this page. New records should also be reported there.