Certificate (complexity) explained

In computational complexity theory, a certificate (also called a witness) is a string that certifies the answer to a computation, or certifies the membership of some string in a language. A certificate is often thought of as a solution path within a verification process, which is used to check whether a problem gives the answer "Yes" or "No".

In the decision tree model of computation, certificate complexity is the minimum number of the

input variables of a decision tree that need to be assigned a value in order to definitely establish the value of the Boolean function .

Use in definitions

is semi-decidable if there is a two-place predicate relation such that is computable, and such that for all : x ∈ L ⇔ there exists y such that R(x, y)

Certificates also give definitions for some complexity classes which can alternatively be characterised in terms of nondeterministic Turing machines. A language

is in NP if and only if there exists a polynomial and a polynomial-time bounded Turing machine such that every word is in the language precisely if there exists a certificate of length at most such that accepts the pair .^[2] The class co-NP has a similar definition, except that there are certificates for the words not in the language.

The class NL has a certificate definition: a problem in the language has a certificate of polynomial length, which can be verified by a deterministic logarithmic-space bounded Turing machine that can read each bit of the certificate once only.^[3] Alternatively, the deterministic logarithmic-space Turing machine in the statement above can be replaced by a bounded-error probabilistic constant-space Turing machine that is allowed to use only a constant number of random bits.^[4]

Examples

The problem of determining, for a given graph

and number , if the graph contains an independent set of size is in NP. Given a pair in the language, a certificate is a set of vertices which are pairwise not adjacent (and hence are an independent set of size ).^[5]

A more general example, for the problem of determining if a given Turing machine accepts an input in a certain number of steps, is as follows: L = Show L ∈ NP. verifier: gets string c = , x, w such that |c| <= P(|w|) check if c is an accepting computation of M on x with at most |w| steps |c| <= O(|w|³) if we have a computation of a TM with k steps the total size of the computation string is k² Thus, <, x, w> ∈ L ⇔ there exists c <= a|w|³ such that <, x, w, c> ∈ V ∈ P

See also

• Witness (mathematics), an analogous concept in mathematical logic

External links

• .
• Computational Complexity: a Modern Approach by Sanjeev Arora and Boaz Barak

Notes and References

1. Web site: Cook. Stephen. Computability and Noncomputability. 7 February 2013.
2. Book: Arora . Sanjeev . Barak . Boaz . Complexity Theory: A Modern Approach . Cambridge University Press . 2009 . 978-0-521-42426-4 . Definition 2.1.
3. Book: Arora . Sanjeev . Barak . Boaz . Complexity Theory: A Modern Approach . Cambridge University Press . 2009 . 978-0-521-42426-4 . Definition 4.19.
4. A. C. Cem Say, Abuzer Yakaryılmaz, "Finite state verifiers with constant randomness," Logical Methods in Computer Science, Vol. 10(3:6)2014, pp. 1-17.
5. Book: Arora . Sanjeev . Barak . Boaz . Complexity Theory: A Modern Approach . Cambridge University Press . 2009 . 978-0-521-42426-4 . Example 2.2.