help us decide where and how to put our efforts into solving We show that MAEXP, the exponential time version of problems in complexity theory. It is still true that virtually the Merlin-Arthur class, does not have polynomial size cir- all of the theorems in computational complexity theory that cuits. This significantly improves the previous known result have reasonable relativizations do relativize (see [For94]). due to Kannan since we furthermore show that our result But we do have a small number of exceptions that arise does not relativize. This is the first separation result in com- from the area of interactive proofs. These results have preplexity theory that does not relativize. As a corollary to our viously always taken the form of collapses such as IP= separation result we also obtain that PEXP, the exponen- PSPACE [LFKN92, Sha92], MIP=NEXP [BFL91] and tial time version of PP is not in P=poly. PCP(O(1);O(logn))=NP [ALM+92]. In this paper we give the first reasonable nonrel-1

We give the first nontrivial model-independent time-space 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 random-access 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 log-space 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 polynomial-time 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...

We construct an oracle A such that P A = \PhiP A and NP A = EXP A : This relativized world has several amazing properties: ffl The oracle A gives the first relativized world where one can solve satisfiability on formulae with at most one assignment yet P 6= NP. ffl The oracle A is the first where P A = UP A 6= NP A = coNP A : ffl The construction gives a much simpler proof than Fenner, Fortnow and Kurtz of a relativized world where all NP-complete sets are polynomial-time isomorphic. It is the first such computable oracle. ffl Relative to A we have a collapse of \PhiEXP A ` ZPP A ` P A /poly. We also create a different relativized world where there exists a set L in NP that is NP- complete under reductions that make one query to L but not under traditional many-one reductions. This contrasts with the result of Buhrman, Spaan and Torenvliet showing that these two completeness notions for NEXP coincide. 1 Introduction Valiant and Vazirani [VV86] show the sur...

We discuss the possibility of using the relatively old technique of diagonalization to separate complexity classes, in particular NL from NP. We show several results in this direction. ffl Any nonconstant level of the polynomial-time hierarchy strictly contains NL. ffl SAT is not simultaneously in NL and deterministic n log j n time for any j. ffl On the negative side, we present a relativized world where P = NP but any nonconstant level of the polynomial-time hierarchy differs from P. 1 Introduction Separating complexity classes remains the most important and difficult of problems in theoretical computer science. Circuit complexity and other techniques on finite functions have seen some exciting early successes (see the survey of Boppana and Sipser [BS90]) but have yet to achieve their promise of separating complexity classes above logarithmic space. Other techniques based on logic and geometry also have given us separations only on very restricted models. We should turn back to...

The complexity of quantum computation remains poorly understood. While physicists attempt to find ways to create quantum computers, we still do not have much evidence one way or the other as to how useful these machines will be. The tools of computational complexity theory should come to bear on these important questions. Quantum Computing

Abstract. In this paper, we formalize two stepwise approaches, based on pseudo-random generators, for proving P � = NP and its arithmetic analog: Permanent requires superpolynomial sized arithmetic circuits. 1

Any proof of P � = NP will have to overcome two barriers: relativization and natural proofs. Yet over the last decade, we have seen circuit lower bounds (for example, that PP does not have linear-size circuits) that overcome both barriers simultaneously. So the question arises of whether there is a third barrier to progress on the central questions in complexity theory. In this paper we present such a barrier, which we call algebraic relativization or algebrization. The idea is that, when we relativize some complexity class inclusion, we should give the simulating machine access not only to an oracle A, but also to a low-degree extension of A over a finite field or ring. We systematically go through basic results and open problems in complexity theory to delineate the power of the new algebrization barrier. First, we show that all known non-relativizing results based on arithmetization—both inclusions such as IP = PSPACE and MIP = NEXP, and separations such as MAEXP � ⊂ P/poly —do indeed algebrize. Second, we show that almost all of the major open problems—including P versus NP, P versus RP, and NEXP versus P/poly—will require non-algebrizing techniques. In some cases algebrization seems to explain exactly why progress stopped where it did: for example, why we have superlinear circuit lower bounds for PromiseMA but not for NP. Our second set of results follows from lower bounds in a new model of algebraic query complexity, which we introduce in this paper and which is interesting in its own right. Some of our lower bounds use direct combinatorial and algebraic arguments, while others stem from a surprising connection between our model and communication complexity. Using this connection, we are also able to give an MA-protocol for the Inner Product function with O ( √ n log n) communication (essentially matching a lower bound of Klauck), as well as a communication complexity conjecture whose truth would imply NL � = NP. 1

Contradictory oracle results have traditionally been interpreted as giving some evidence that resolving a complexity issue is difficult. However, for quite a while, there have been a few known complexity results that do not hold for every oracle, at least in the most obvious way of relativizing the results. In the early 1990’s, a sequence of important non-relativizing results concerning “non-controversially relativizable ” complexity classes has been proved, mainly using algebraic techniques. Although the techniques used to obtain these results seem similar in flavor, it is not clear what common features of complexity they are exploiting. It is also not clear to what extent oracle results should be trusted as a guide to estimating the difficulty of proving complexity statements, in light of these non-relativizing techniques. The results in this paper are intended to shed some light on these issues. First, we give a list of simple axioms based on Cobham’s machineless characterization of P [Cob64]. We show that a complexity statement (provably) holds relative to all oracles if and only if it is a consequence of these axioms. Thus, these axioms in some sense capture the set of techniques that relativize. Oracle results, while not necessarily showing that resolving a complexity conjecture is “beyond current technology ” at least show that the result is

In the past few years, generalized operators (a. k. a. leaf languages) in the context of polynomial -time machines, and gates computing arbitrary groupoidal functions in the context of Boolean circuits have raised some interest. We survey results from both areas, point out connections between them, and present relations to a generalized quantifier concept known from finite model theory. 1 Introduction There is an "amusing and instructive way of looking at [...] diverse complexity classes" [Pap94a, p. 504] that are of current focal interest in computational complexity theory. This way makes instrumental use of characterizations of classes in terms of conditions on computations trees of nondeterministic polynomial-time Turing machines. As an example, let us look at the class NP. By definition, a language A 2 NP is given by a nondeterministic polynomial-time machine (NPTM) M such that for all inputs x, we have that x belongs to A if and only if in the computation tree that M produces wh...

Design of secure systems can often be expressed as ensuring that some property is maintained at every step of a distributed computation among mutually-untrusting parties. Special cases include integrity of programs running on untrusted platforms, various forms of confidentiality and side-channel resilience, and domain-specific invariants. We propose a new approach, proof-carrying data (PCD), which circumnavigates the threat of faults and leakage by reasoning about properties of the output data, independently of the preceding computation. In PCD, the system designer prescribes the desired properties of the computation’s outputs. Corresponding proofs are attached to every message flowing through the system, and are mutually verified by the system’s components. Each such proof attests that the message’s data and all of its history comply with the specified properties. We construct a general protocol compiler that generates, propagates and verifies such proofs of compliance, while preserving the dynamics and efficiency of the original computation. Our main technical tool is the cryptographic construction of short non-interactive arguments (computationally-sound proofs) for statements whose truth depends on “hearsay evidence”: previous arguments about other statements. To this end, we attain a particularly strong proof of knowledge. We realize the above, under standard cryptographic assumptions, in a model where the prover has blackbox access to some simple functionality — essentially, a signature card.