Strong Exponential Time Hypothesis
As satisfiability clauses become longer, does the best worst-case running-time exponent approach exhaustive search?
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As satisfiability clauses become longer, does the best worst-case running-time exponent approach exhaustive search?
Does a quantum computer gain verification power when its certificate can be a quantum state rather than a classical string?
Can every polynomial described as a sum of efficiently computable terms itself be computed by a small arithmetic circuit?
Does a yes-or-no rule’s sensitivity to flipped inputs limit how widely its Fourier weight can spread?
Must a bounded low-degree polynomial that varies appreciably have an input bit with noticeable influence?
Can an algorithm reliably construct a prime of any requested bit length in polynomial time without randomness?
Does each additional level of alternating computational choices add power, forever?
How much can the best traveling-salesperson tour cost exceed its standard fractional relaxation in the worst metric instance?
Whenever yes answers have short efficiently checkable certificates, must no answers have them too?
Is it computationally hard to distinguish a graph with a small nearly isolated set from one where every equally small set strongly expands?
Can one efficiently checkable proof system match every other system’s proof lengths within a polynomial factor?
Can a fast algorithm always choose k vertices spanning within a fixed factor of the largest possible number of edges?
Can the winner of every finite parity game be determined in polynomial time?
Can every problem solvable with polynomial memory also be solved in polynomial time?
Several methods correct errors in analog memory calculations. How should they be combined when inputs, noise and conversion costs change?
Can a complete countable theory have an intermediate number of countable models?
Can every synchronizing n-state automaton be reset with at most (n−1)² input symbols?
Can a classical polynomial-time algorithm recognize all minimal hitting sets?
Can ordinary random labeled examples teach a DNF formula in polynomial time under the uniform distribution?
Can an algorithm decide whether one database query always produces each answer no more often than another?
Can an algorithm decide whether an integer sequence defined by a linear recurrence never becomes negative?
Can a deterministic parallel algorithm find a perfect matching in every general graph with polylogarithmic time and polynomially many processors?
Can an algorithm efficiently determine, without random choices, whether an arithmetic circuit computes the zero polynomial?
Can we explicitly construct binary matrices whose linear maps require more than a constant number of XOR gates per input?