Lukas' Notes

computation complexity

Definition

Strong Exponential Time Hypothesis

Simplified

For every constant , SAT cannot be solved in running time, i.e.,

where is the number of variables and denotes Big-O-star notation.

Exhaustive Branching

For SAT, exhaustive branching with running time is essentially optimal; the base cannot be improved by any fixed constant amount, i.e.,

Clause width

For each , let

The strong exponential time hypothesis states that

Equivalently, for every , there is a clause width for which k-SAT has no algorithm. The width may depend on .

SETH forbids smaller linear exponents such as . It therefore also forbids sublinear exponents such as or .

Relation to ETH

ETH says that 3-SAT has no subexponential-time algorithm of the form .

SETH is stronger. It rules out even slightly faster-than-brute-force algorithms for SAT, such as

Thus:

  • ETH forbids improving the exponent all the way to sublinear in ;
  • SETH forbids improving the constant in the exponent below .

Formal variant

A common formal version is stated through k-SAT: for every , there exists a clause width such that -SAT cannot be solved in time .

This avoids claiming that every fixed-width SAT variant has exactly the same exponential constant.