Table of Contents
Fetching ...

On Extremal Properties of k-CNF: Capturing Threshold Functions

Mohit Gurumukhani, Marvin Künnemann, Ramamohan Paturi

TL;DR

This work analyzes how well $k$-CNF formulas can represent threshold functions by studying the extremal quantity $S(n,t,k)$, the maximum number of weight-$t$ assignments a $t$-admissible $k$-CNF can accept. It reveals deep connections to classical combinatorial problems: for $t=n-k$ the problem is equivalent to Turán-type questions, while in the large-width regime it aligns with Steiner systems, and for the linear-threshold regime it admits an adaptive block construction with a proven optimality for $k=2$. The results yield exact bounds in several regimes and imply circuit lower bounds via $F(n,t,k)$, highlighting a rich interface between CNF representations of threshold functions and extremal combinatorics. The findings advance understanding of the combinatorial structure of $k$-CNF solution spaces and their implications for depth-$3$ circuit complexity.

Abstract

We consider a basic question on the expressiveness of $k$-CNF formulas: How well can $k$-CNF formulas capture threshold functions? Specifically, what is the largest number of assignments (of Hamming weight $t$) accepted by a $k$-CNF formula that only accepts assignments of weight at least $t$? Among others, we provide the following results: - While an optimal solution is known for $t \leq n/k$, the problem remains open for $t > n/k$. We formulate a (monotone) version of the problem as an extremal hypergraph problem and show that for $t = n-k$, the problem is exactly the Turán problem. - For $t = αn$ with constant $α$, we provide a construction and show its optimality for $2$-CNF. Optimality of the construction for $k>2$ would give improved lower bounds for depth-$3$ circuits.

On Extremal Properties of k-CNF: Capturing Threshold Functions

TL;DR

This work analyzes how well -CNF formulas can represent threshold functions by studying the extremal quantity , the maximum number of weight- assignments a -admissible -CNF can accept. It reveals deep connections to classical combinatorial problems: for the problem is equivalent to Turán-type questions, while in the large-width regime it aligns with Steiner systems, and for the linear-threshold regime it admits an adaptive block construction with a proven optimality for . The results yield exact bounds in several regimes and imply circuit lower bounds via , highlighting a rich interface between CNF representations of threshold functions and extremal combinatorics. The findings advance understanding of the combinatorial structure of -CNF solution spaces and their implications for depth- circuit complexity.

Abstract

We consider a basic question on the expressiveness of -CNF formulas: How well can -CNF formulas capture threshold functions? Specifically, what is the largest number of assignments (of Hamming weight ) accepted by a -CNF formula that only accepts assignments of weight at least ? Among others, we provide the following results: - While an optimal solution is known for , the problem remains open for . We formulate a (monotone) version of the problem as an extremal hypergraph problem and show that for , the problem is exactly the Turán problem. - For with constant , we provide a construction and show its optimality for -CNF. Optimality of the construction for would give improved lower bounds for depth- circuits.
Paper Structure (9 sections, 17 theorems, 13 equations, 1 figure)

This paper contains 9 sections, 17 theorems, 13 equations, 1 figure.

Key Result

Theorem 1

For any $n\ge k \ge 2$, we have that $S(n,n-k,k)= \binom{n}{k} - T(n,k+1,k)$.

Figures (1)

  • Figure 1: Illustrates the implication graph of $F$ in the proof of \ref{['lem:k2-monotone']}. In the transformation from $F$ to $F'$, the black dashed edge is deleted and the yellow dashed edges are added.

Theorems & Definitions (20)

  • Theorem 1
  • Conjecture 2
  • Theorem 3: Optimality for $k=2$, Informal Version
  • Lemma 6: MacWilliamsSloane_1977
  • Lemma 7: Putting the block together
  • Theorem 8: Small Thresholds
  • Lemma 9
  • Theorem 10: Intermediate Thresholds
  • Proposition 11: Optimality Implies Circuit Lower Bounds
  • Theorem 12: Tight Bound for 2-CNFs
  • ...and 10 more