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79
Randomness is Linear in Space
 Journal of Computer and System Sciences
, 1993
"... We show that any randomized algorithm that runs in space S and time T and uses poly(S) random bits can be simulated using only O(S) random bits in space S and time T poly(S). A deterministic simulation in space S follows. Of independent interest is our main technical tool: a procedure which extracts ..."
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Cited by 229 (20 self)
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We show that any randomized algorithm that runs in space S and time T and uses poly(S) random bits can be simulated using only O(S) random bits in space S and time T poly(S). A deterministic simulation in space S follows. Of independent interest is our main technical tool: a procedure which extracts randomness from a defective random source using a small additional number of truly random bits. 1
Graph Nonisomorphism Has Subexponential Size Proofs Unless The PolynomialTime Hierarchy Collapses
 SIAM Journal on Computing
, 1998
"... We establish hardness versus randomness tradeoffs for a broad class of randomized procedures. In particular, we create efficient nondeterministic simulations of bounded round ArthurMerlin games using a language in exponential time that cannot be decided by polynomial size oracle circuits with acce ..."
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Cited by 108 (6 self)
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We establish hardness versus randomness tradeoffs for a broad class of randomized procedures. In particular, we create efficient nondeterministic simulations of bounded round ArthurMerlin games using a language in exponential time that cannot be decided by polynomial size oracle circuits with access to satisfiability. We show that every language with a bounded round ArthurMerlin game has subexponential size membership proofs for infinitely many input lengths unless exponential time coincides with the third level of the polynomialtime hierarchy (and hence the polynomialtime hierarchy collapses). This provides the first strong evidence that graph nonisomorphism has subexponential size proofs. We set up a general framework for derandomization which encompasses more than the traditional model of randomized computation. For a randomized procedure to fit within this framework, we only require that for any fixed input the complexity of checking whether the procedure succeeds on a given ...
Representing Boolean Functions As Polynomials Modulo Composite Numbers
 Computational Complexity
, 1994
"... . Define the MODm degree of a boolean function F to be the smallest degree of any polynomial P , over the ring of integers modulo m, such that for all 01 assignments ~x, F (~x) = 0 iff P (~x) = 0. We obtain the unexpected result that the MODm degree of the OR of N variables is O( r p N ), wher ..."
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Cited by 56 (6 self)
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. Define the MODm degree of a boolean function F to be the smallest degree of any polynomial P , over the ring of integers modulo m, such that for all 01 assignments ~x, F (~x) = 0 iff P (~x) = 0. We obtain the unexpected result that the MODm degree of the OR of N variables is O( r p N ), where r is the number of distinct prime factors of m. This is optimal in the case of representation by symmetric polynomials. The MOD n function is 0 if the number of input ones is a multiple of n and is one otherwise. We show that the MODm degree of both the MOD n and :MOD n functions is N\Omega\Gamma1/ exactly when there is a prime dividing n but not m. The MODm degree of the MODm function is 1; we show that the MODm degree of :MODm is N\Omega\Gamma30 if m is not a power of a prime, O(1) otherwise. A corollary is that there exists an oracle relative to which the MODmP classes (such as \PhiP) have this structure: MODmP is closed under complementation and union iff m is a prime power, and...
TimeSpace Tradeoffs for Branching Programs
, 1999
"... We obtain the first nontrivial timespace tradeoff lower bound for functions f : {0, 1}^n → {0, 1} on general branching programs by exhibiting a Boolean function f that requires exponential size to be computed by any branching program of length (1 + ε)n, for some constant ε > 0 ..."
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Cited by 44 (2 self)
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We obtain the first nontrivial timespace tradeoff lower bound for functions f : {0, 1}^n → {0, 1} on general branching programs by exhibiting a Boolean function f that requires exponential size to be computed by any branching program of length (1 + ε)n, for some constant ε > 0. We also give the first separation result between the syntactic and semantic readk models [BRS93] for k > 1 by showing that polynomialsize semantic readtwice branching programs can compute functions that require exponential size on any syntactic readk branching program. We also show...
Synthesizers and Their Application to the Parallel Construction of PseudoRandom Functions
, 1995
"... A pseudorandom function is a fundamental cryptographic primitive that is essential for encryption, identification and authentication. We present a new cryptographic primitive called pseudorandom synthesizer and show how to use it in order to get a parallel construction of a pseudorandom function. ..."
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Cited by 42 (10 self)
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A pseudorandom function is a fundamental cryptographic primitive that is essential for encryption, identification and authentication. We present a new cryptographic primitive called pseudorandom synthesizer and show how to use it in order to get a parallel construction of a pseudorandom function. We show several NC¹ implementations of synthesizers based on concrete intractability assumptions as factoring and the DiffieHellman assumption. This yields the first parallel pseudorandom functions (based on standard intractability assumptions) and the only alternative to the original construction of Goldreich, Goldwasser and Micali. In addition, we show parallel constructions of synthesizers based on other primitives such as weak pseudorandom functions or trapdoor oneway permutations. The security of all our constructions is similar to the security of the underlying assumptions. The connection with problems in Computational Learning Theory is discussed.
Pseudorandom bits for polynomials
 In 48th Annual Symposium on Foundations of Computer Science. IEEE
, 2007
"... We present a new approach to constructing pseudorandom generators that fool lowdegree polynomials over finite fields, based on the Gowers norm. Using this approach, we obtain the following main constructions of explicitly computable generators G: F s → F n that fool polynomials over a prime field F: ..."
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Cited by 40 (10 self)
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We present a new approach to constructing pseudorandom generators that fool lowdegree polynomials over finite fields, based on the Gowers norm. Using this approach, we obtain the following main constructions of explicitly computable generators G: F s → F n that fool polynomials over a prime field F: 1. a generator that fools degree2 (i.e., quadratic) polynomials to within error 1/n, with seed length s = O(log n), 2. a generator that fools degree3 (i.e., cubic) polynomials to within error ɛ, with seed length s = O(log F  n) + f(ɛ, F) where f depends only on ɛ and F (not on n), 3. assuming the “Gowers inverse conjecture, ” for every d a generator that fools degreed polynomials to within error ɛ, with seed length s = O(d · log F  n) + f(d, ɛ, F) where f depends only on d, ɛ, and F (not on n). We stress that the results in (1) and (2) are unconditional, i.e. do not rely on any unproven assumption. Moreover, the results in (3) rely on a special case of the conjecture which may be easier to prove. Our generator for degreed polynomials is the componentwise sum of d generators for degree1 polynomials (on independent seeds). Prior to our work, generators with logarithmic seed length were only known for degree1 (i.e., linear) polynomials (Naor and Naor; SIAM J. Comput., 1993). In fact, over small fields such as F2 = {0, 1}, our results constitute the first progress on these problems since the longstanding generator by Luby, Veličković and Wigderson (ISTCS 1993), whose seed length is much bigger: s = exp � Ω � √ log n � � , even for the case of degree2 polynomials over F2.
Separating AC 0 from depth2 majority circuits
 In Proc. of the 39th Symposium on Theory of Computing (STOC
, 2007
"... Abstract. We construct a function in AC 0 that cannot be computed by a depth2 majority circuit of size less than exp(Θ(n 1/5)). This solves an open problem due to Krause and Pudlák (1994) and matches Allender’s classic result (1989) that AC 0 can be efficiently simulated by depth3 majority circuit ..."
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Cited by 36 (17 self)
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Abstract. We construct a function in AC 0 that cannot be computed by a depth2 majority circuit of size less than exp(Θ(n 1/5)). This solves an open problem due to Krause and Pudlák (1994) and matches Allender’s classic result (1989) that AC 0 can be efficiently simulated by depth3 majority circuits. To obtain our result, we develop a novel technique for proving lower bounds on communication complexity. This technique, the Degree/Discrepancy Theorem, is of independent interest. It translates lower bounds on the threshold degree of a Boolean function into upper bounds on the discrepancy of a related function. Upper bounds on the discrepancy, in turn, immediately imply lower bounds on communication and circuit size. In particular, our work yields the first known function in AC 0 with exponentially small discrepancy, exp(−Ω(n 1/5)). Key words. Majority circuits, constantdepth AND/OR/NOT circuits, communication complexity, discrepancy, threshold degree of Boolean functions. AMS subject classifications. 03D15, 68Q15, 68Q17
TimeSpace Tradeoffs for Satisfiability
 Journal of Computer and System Sciences
, 1997
"... We give the first nontrivial modelindependent timespace tradeoffs for satisfiability. Namely, we show that SAT cannot be solved simultaneously in n 1+o(1) time and n 1\Gammaffl space for any ffl ? 0 on general randomaccess nondeterministic Turing machines. In particular, SAT cannot be solved ..."
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Cited by 29 (1 self)
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We give the first nontrivial modelindependent timespace tradeoffs for satisfiability. Namely, we show that SAT cannot be solved simultaneously in n 1+o(1) time and n 1\Gammaffl space for any ffl ? 0 on general randomaccess nondeterministic Turing machines. In particular, SAT cannot be solved deterministically by a Turing machine using quasilinear time and p n space. We also give lower bounds for logspace uniform NC 1 circuits and branching programs. Our proof uses two basic ideas. First we show that if SAT can be solved nondeterministically with a small amount of time then we can collapse a nonconstant number of levels of the polynomialtime hierarchy. We combine this work with a result of Nepomnjascii that shows that a nondeterministic computation of super linear time and sublinear space can be simulated in alternating linear time. A simple diagonalization yields our main result. We discuss how these bounds lead to a new approach to separating the complexity classes NL a...
Hypergraphs, QuasiRandomness, and Conditions for Regularity
 J. COMBIN. THEORY SER. A
, 2002
"... Haviland and Thomason and Chung and Graham were the rst to investigate systematically some properties of quasirandom hypergraphs. In particular, in a series of articles, Chung and Graham considered several quite disparate properties of randomlike hypergraphs of density 1=2 and proved that they are ..."
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Cited by 28 (8 self)
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Haviland and Thomason and Chung and Graham were the rst to investigate systematically some properties of quasirandom hypergraphs. In particular, in a series of articles, Chung and Graham considered several quite disparate properties of randomlike hypergraphs of density 1=2 and proved that they are in fact equivalent. The central concept in their work turned out to be the so called deviation of a hypergraph. They proved that having small deviation is equivalent to a variety of other properties that describe quasirandomness. In this paper, we consider the concept of discrepancy for kuniform hypergraphs with an arbitrary constant density d (0 < d < 1) and prove that the condition of having asymptotically vanishing discrepancy is equivalent to several other quasirandom properties of H, similar to the ones introduced by Chung and Graham. In particular, we prove that the correct `spectrum' of the svertex subhypergraphs is equivalent to quasirandomness for any s 2k. Our work may be viewed as a continuation of the work of Chung and Graham, although our proof techniques are dierent in certain important parts.
TimeSpace Tradeoff Lower Bounds for Randomized Computation of Decision Problems
 In Proc. of 41st FOCS
, 2000
"... We prove the first timespace lower bound tradeoffs for randomized computation of decision problems. ..."
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Cited by 28 (2 self)
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We prove the first timespace lower bound tradeoffs for randomized computation of decision problems.