

Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Ten problems related to computational complexity, including reductions between problems, proofs of np-completeness, and properties of self-reducible languages. Topics covered include clique, sat, quadratic, np minimization, σp-completeness, factoring, self-reducibility, and nl-completeness.
Typology: Assignments
1 / 3
This page cannot be seen from the preview
Don't miss anything!


Give a Karp reduction from CLIQUE to SAT.
Let Quadratic be the problem of deciding whether a given system of quadratic multivariate polynomial equations with integer coefficients has a solution modulo 2. Prove that Quadratic is NP-Complete.
An NP minimization problem is defined by an objective function Obj : Σ∗^ × Σ∗^ → N for which there is a constant c and an algorithm that for every x, y ∈ { 0 , 1 }∗, computes Obj(x, y) in time O(|x|c). For such an objective function Obj, the corresponding NP minimization problem is: Given x ∈ Σ∗, find a y ∈ Σ∗^ such that Obj(x, y) is minimized. Prove that P = NP if and only if every NP minimization problem has a polynomial-time algorithm.^1
Prove that for each i ∈ N, Σi-SAT is ΣPi - Complete.
Consider the Factoring problem: Given a natural number N , express N as a product of its prime factors. To date no polynomial-time algorithm for Factoring is known, and the conjectured hardness of Factoring has been the basis of several public-key cryptosystems.
A language L is self-reducible if there is a polynomial-time oracle machine M such that (a) M L^ decides L, and (b) on every input x, M only makes queries of length strictly smaller than |x|. For instance, as shown in class, SAT and TQBF are self-reducible. Prove that every self-reducible language is in PSPACE.