Padding argument

In computational complexity theory, the padding argument is a tool to conditionally prove that if some complexity classes are equal, then some other bigger classes are also equal.

Example

The proof that P = NP implies EXP = NEXP uses "padding".

E X P N E X P {\displaystyle \mathrm {EXP} \subseteq \mathrm {NEXP} } by definition, so it suffices to show N E X P E X P {\displaystyle \mathrm {NEXP} \subseteq \mathrm {EXP} } .

Let L be a language in NEXP. Since L is in NEXP, there is a non-deterministic Turing machine M that decides L in time 2 n c {\displaystyle 2^{n^{c}}} for some constant c. Let

L = { x 1 2 | x | c x L } , {\displaystyle L'=\{x1^{2^{|x|^{c}}}\mid x\in L\},}

where '1' is a symbol not occurring in L. First we show that L {\displaystyle L'} is in NP, then we will use the deterministic polynomial time machine given by P = NP to show that L is in EXP.

L {\displaystyle L'} can be decided in non-deterministic polynomial time as follows. Given input x {\displaystyle x'} , verify that it has the form x = x 1 2 | x | c {\displaystyle x'=x1^{2^{|x|^{c}}}} and reject if it does not. If it has the correct form, simulate M(x). The simulation takes non-deterministic 2 | x | c {\displaystyle 2^{|x|^{c}}} time, which is polynomial in the size of the input, x {\displaystyle x'} . So, L {\displaystyle L'} is in NP. By the assumption P = NP, there is also a deterministic machine DM that decides L {\displaystyle L'} in polynomial time. We can then decide L in deterministic exponential time as follows. Given input x {\displaystyle x} , simulate D M ( x 1 2 | x | c ) {\displaystyle DM(x1^{2^{|x|^{c}}})} . This takes only exponential time in the size of the input, x {\displaystyle x} .

The 1 d {\displaystyle 1^{d}} is called the "padding" of the language L. This type of argument is also sometimes used for space complexity classes, alternating classes, and bounded alternating classes.

See also

  • Paddable language

References

  • Arora, Sanjeev; Barak, Boaz (2009), Computational Complexity: A Modern Approach, Cambridge, p. 57, ISBN 978-0-521-42426-4