Upload
apollo
View
24
Download
0
Embed Size (px)
DESCRIPTION
The Padding Argument. Motivation: Scaling-Up Complexity Claims. We have:. can be simulated by…. space. space. + non-determinism. + determinism. We want:. can be simulated by…. space. space. + non-determinism. + determinism. Formally. s i (n) can be computed with space s i (n). - PowerPoint PPT Presentation
Citation preview
Complexity1
The Padding Argument
Complexity2
Motivation: Scaling-Up Complexity Claims
space
+ non-determinism
We have:
space
+ determinism
can be simulated by…
We want:
space
+ non-determinism
space
+ determinism
can be simulated by…
Complexity3
Formally
NSPACE(s1(n)) SPACE(s2(n))
NSPACE(s1(f(n))) SPACE(s2(f(n)))
Claim: For any two space constructible functions s1(n),s2(n)logn, f(n)n:
si(n) can be computed with space si(n)
simulation overhead
E.g NSPACE(n)SPACE(n2) NSPACE(n2)SPACE(n4)
Complexity4
Idea
NTM...
n
space: O(s1(f(n)))
.
.
.
.
.
.
.
.
.
.
f(n)
space: s1(.) in the size of its
input
DTMspace: O(s2(f(n)))0
0
.
.
.n
Complexity5
Padding argument
• Let LNPSPACE(s1(f(n)))
• There is a 3-Tape-NTM ML:
babba������������������������
���������������������������
Input
Work
|x|
O(s1(f(|x|)))
Complexity6
Padding argument• Let L’ = { x0f(|x|)-|x| | xL }
• We’ll show a NTM ML’ which decides L’ in the same number of cells as ML.
babba00000000000000000000000000000000���
���������������������������
Input
Work
f(|x|)
O(s1(f(|x|))
Complexity7
Padding argument – ML’
1. Count backwards the number of 0’s and check there are f(|x|)-|x| such.
2. Run ML on x.
babba00000000000000000000000000000000���
���������������������������
Input
Work
f(|x|)
O(s1(f(|x|)))
In O(log(f(|x|)) space
in O(s1(f(|x|))) space
Complexity8
Padding argument
babba00000000000000000000000000000000���
���������������������������
Input
Work
f(|x|)
O(s1(f(|x|)))
Total space: O(s1(f(|x|)))
Complexity9
Padding Argument
• We started with LNSPACE(s1(f(n)))
• We showed: L’NSPACE(s1(n))
• Thus, L’SPACE(s2(n))
• Using the DTM for L’ we’ll construct a DTM for L, which will work in O(s2(f(n))) space.
Complexity10
Padding Argument
• The DTM for L’ will simulate the DTM for L when working on its input concatenated with zeros
babba���
00000000000000000000000
Input
Complexity11
Padding Argument
• When the input head leaves the input part, just pretend it encounters 0s.
• keeping track after the simulated position takes O(log(f(|x|))) space.
• Thus our machine uses O(s2(f(|x|))) space.
NSPACE(s1(f(n)))SPACE(s2(f(n)))
Complexity12
Savitch: Generalized Version
Theorem (Savitch):S(n) ≥ log(n)
NSPACE(S(n)) SPACE(S(n)2)
Proof: We proved NLSPACE(log2n). The theorem follows from the padding argument.
Complexity13
Corollary
Corollary: PSPACE = NPSPACE
Proof: Clearly, PSPACENPSPACE. By Savitch’s theorem,
NPSPACEPSPACE.