DocumentCode :
2345703
Title :
Making hard problems harder
Author :
Buresh-Oppenheim, Joshua ; Santhanam, Rahul
Author_Institution :
Simon Fraser Univ., Burnaby, BC
fYear :
0
fDate :
0-0 0
Lastpage :
87
Abstract :
We consider a general approach to the hoary problem of (im)proving circuit lower bounds. We define notions of hardness condensing and hardness extraction, in analogy to the corresponding notions from the computational theory of randomness. A hardness condenser is a procedure that takes in a Boolean function as input, as well as an advice string, and outputs a Boolean function on a smaller number of bits which has greater hardness when measured in terms of input length. A hardness extractor takes in a Boolean function as input, as well as an advice string, and outputs a Boolean function defined on a smaller number of bits which has close to maximum hardness. We prove several positive and negative results about these objects. First, we observe that hardness-based pseudo-random generators can be used to extract deterministic hardness from non-deterministic hardness. We derive several consequences of this observation. Among other results, we show that if E/O(n) has exponential non-deterministic hardness, then E/O{n) has deterministic hardness 2n/n, which is close to the maximum possible. We demonstrate a rare downward closure result: E with sub-exponential advice is contained in non-uniform space 2deltan for all delta > 0 if and only if there is k > 0 such that P with quadratic advice can be approximated in non-uniform space nk . Next, we consider limitations on natural models of hardness condensing and extraction. We show lower bounds on the advice length required for hardness condensing in a very general model of "relativizing" condensers. We show that non-trivial black-box extraction of deterministic hardness from deterministic hardness is essentially impossible. Finally, we prove positive results on hardness condensing in certain special cases. We show how to condense hardness from a biased function without advice using a hashing technique. We also give a hardness condenser without advice from average-case hardness to worst-- - case hardness. Our technique uses a connection between hardness condensing and explicit constructions of covering codes
Keywords :
Boolean functions; computational complexity; Boolean function; computational theory of randomness; deterministic hardness; exponential nondeterministic hardness; hard problems; hardness condenser; hardness extraction; hardness-based pseudorandom generators; nontrivial black-box extraction; Boolean functions; Circuit simulation; Circuit testing; Complexity theory; Computational complexity; Error correction codes; Length measurement; Polynomials; Signal generators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Complexity, 2006. CCC 2006. Twenty-First Annual IEEE Conference on
Conference_Location :
Prague
ISSN :
1093-0159
Print_ISBN :
0-7695-2596-2
Type :
conf
DOI :
10.1109/CCC.2006.26
Filename :
1663727
Link To Document :
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