Infinitary logics and 0–1 laws

We investigate the infinitary logic L_∞ω^ω, in which sentences may have arbitrary disjunctions and conjunctions, but they involve only finite numbers of distinct variables. We show that various fixpoint logics can be viewed as fragments of L_∞ω^ω, and we describe a game-theoretic characterization of the expressive power of the logic. Finally, we study asymptotic probabilities of properties expressible in L_∞ω^ω on finite structures. We show that the 0–1 law holds for L_∞ω^ω, i.e., the asymptotic probability of every sentence in this logic exists and is equal to either 0 or 1. This result subsumes earlier work on asymptotic probabilities for various fixpoint logics and reveals the boundary of 0–1 laws for infinitary logics.     

The most nonelementary theory

We give a direct proof by generic reduction that testing validity of formulas in a decidable rudimentary theory Ω of finite typed sets (Henkin, Fundamenta Mathematicæ 52 (1963) 323–344) requires space and time exceeding infinitely often(1)where n denotes the length of input. This gives the highest currently known lower bound for a decidable logical theory and affirmatively settles Problem 10.13 from (Compton and Henson, Ann. Pure Applied Logic 48 (1990) 1–79):

Is there a “natural” decidable theory with a lower bound of the form exp_∞(f(n)), where f is not linearly bounded?

The highest previously known lower (and upper) bounds for “natural” decidable theories, like WS1S, S2S, are of the form exp_∞(dn), with just linearly growing stacks of twos.Originally, the lower bound (1) for Ω was settled in (12th Annual IEEE Symposium on Logic in Computer Science (LICS’97), 1997, 294–305) using the powerful uniform lower bounds method due to Compton and Henson, and probably would never be discovered otherwise. Although very concise, the original proof has certain gaps, because the method was pushed out of the limits it was originally designed and intended for, and some hidden assumptions were violated. This results in slightly weaker bounds—the stack of twos in (1) grows subexponentially, but superpolynomially, namely, as for formulas with fixed quantifier prefix, or as 2^cn/log(n) for formulas with varying prefix. The independent direct proof presented in this paper closes the gaps and settles the originally claimed lower bound (1) for the minimally typed, succinct version of Ω.     

Toward a theory of Pollard's rho method

Pollard's “rho” method for integer factorization iterates a simple polynomial map and produces a nontrivial divisor of n when two such iterates agree modulo this divisor. Experience and heuristic arguments suggest that a prime divisor p should be detected in steps, but this has never been proved. Indeed, nothing seems to be have been rigorously proved about the probability of success that would improve the obvious lower bound of 1/p. This paper shows that for fixed k, this probability is at least (₂^k)/p + O(p^−3/2) as p → ∞. This leads to an Ω(log²p)/p estimate of the success probability.     

A Coalgebraic View of Infinite Trees and Iteration

The algebra of infinite trees is, as proved by C. Elgot, completely iterative, i.e., all ideal recursive equations are uniquely solvable. This is proved here to be a general coalgebraic phenomenon: let H be an endofunctor such that for every object X a final coalgebra, TX, of H(_) + X exists. Then TX is an object-part of a monad which is completely iterative. Moreover, a similar contruction of a “completely iterative monoid” is possible in every monoidal category satisfying mild side conditions.     

Lower Bounds for Dynamic Algebraic Problems

We consider dynamic evaluation of algebraic functions (matrix multiplication, determinant, convolution, Fourier transform, etc.) in the model of Reif and Tate; i.e., if f(x₁,…, x_n)=(y₁, …, y_m) is an algebraic problem, we consider serving online requests of the form “change input x_i to value v” or “what is the value of output y_i?” We present techniques for showing lower bounds on the worst case time complexity per operation for such problems. The first gives lower bounds in a wide range of rather powerful models (for instance, history dependent algebraic computation trees over any infinite subset of a field, the integer RAM, and the generalized real RAM model of Ben-Amram and Galil). Using this technique, we show optimal Ω(n) bounds for dynamic matrix–vector product, dynamic matrix multiplication, and dynamic discriminant and an Ω( ) lower bound for dynamic polynomial multiplication (convolution), providing a good match with Reif and Tate's O( ) upper bound. We also show linear lower bounds for dynamic determinant, matrix adjoint, and matrix inverse and an Ω( ) lower bound for the elementary symmetric functions. The second technique is the communication complexity technique of Miltersen, Nisan, Safra, and Wigderson which we apply to the setting of dynamic algebraic problems, obtaining similar lower bounds in the word RAM model. The third technique gives lower bounds in the weaker straight line program model. Using this technique, we show an Ω((log n)²/log log n) lower bound for dynamic discrete Fourier transform. Technical ingredients of our techniques are the incompressibility technique of Ben-Amram and Galil and the lower bound for depth-two superconcentrators of Radhakrishnan and Ta-Shma. The incompressibility technique is extended to arithmetic computation in arbitrary fields.     

Fast algorithms for long transportation problems

The paper deals with large transportation problems in which the number of destinations (n) is much larger than the number of origins (m), and in which some or many of the paths from origins to destinations may be inadmissible. Using a new approach, with certain auxilary lists, it is proved that the ordinary simplex algorithm (“Most Negative Rule”) can be performed in O(m²+ m log n) computer operations per iteration, as against O(mn) in the usual approach. A search-in-a-row simplex algorithm (“Row Most Negative Rule”), for which the total number of iterations is probably only somewhat larger, is shown to require just O(m + σm log n) operations per iteration, where σ is the density of the cost matrix (i.e. the proportion of admissible paths). For these rigorous results one needs computer storage which is not considerably larger than that required for storing the cost matrix. For smaller memory an efficient algorithm is also proposed. A general tentative rule for die amount of scanning per iteration is introduced and applied. Computer experiments are reported, confirming theoretical estimates.     

Universal stabilization of a class of nonlinear systems with homogeneous vector fields

Under relative-degree-one and minimum-phase assumptions, it is well known that the class of finite-dimensional, linear, single-input (u), single-output (y) systems (A,b,c) is universally stabilized by the feedback strategy u = Λ(λ)y, λ = y², where Λ is a function of Nussbaum type (the terminology “universal stabilization” being used in the sense of rendering /s(0/s) a global attractor for each member of the underlying class whilst assuring boundedness of the function λ(·)). A natural generalization of this result to a class ^k of nonlinear control systems (a,b,c), with positively homogeneous (of degree k 1) drift vector field a, is described. Specifically, under the relative-degree-one (cb ≠ 0) and minimum-phase hypotheses (the latter being interpreted as that of asymptotic stability of the equilibrium of the “zero dynamics”), it is shown that the strategy u = Λ(λ)/vby/vb^k−1y, assures ^k-universal stabilization. More generally, the strategy u = Λ(λ)exp(/vby/vb)y, assures -universal stabilization, where = _{k 1} ^k.     

The unification problem for confluent right-ground term rewriting systems

The unification problem for term rewriting systems (TRSs) is the problem of deciding, for a given TRS R and two terms M and N, whether there exists a substitution θ such that Mθ and Nθ are congruent modulo R (i.e., Mθ↔_R^*Nθ). In this paper, the unification problem for confluent right-ground TRSs is shown to be decidable. To show this, the notion of minimal terms is introduced and a new unification algorithm for obtaining a substitution whose range consists of minimal terms is proposed. Our result extends the decidability of unification for canonical (i.e., terminating and confluent) right-ground TRSs given by Hullot [Proceedings of the 5th Conference on Automated Deduction, LNCS, vol. 87, 1980, p. 318] in the sense that the termination condition can be omitted.     

H optimization problem with sign-indefinite quadratic form

This paper presents the solution to min-max control problem arising when the matrix C₁^TC₁ of the cost function in the standard H^∞ control problem (Doyle et al., 1989) is replaced by an arbitrary matrix Q 0. This difference is proved to be sufficient for results obtained in (Doyle et al., 1989) not to cover such the case. Their derivations essentially base on the cost function being H^∞ norm and can not be adjusted to deal with sign-indefinite quadratic form. With some sort of strict frequency condition assumed, state space technique is fruitful to obtain the necessary and sufficient conditions of the solvability of the problem. The solution is given by two Riccati equations and has some difference when compared to that of (Doyle et al., 1989).     

Languages Defined with Modular Counting Quantifiers

We prove that a regular language defined by a boolean combination of generalized Σ₁-sentences built using modular counting quantifiers can be defined by a boolean combination of Σ₁-sentences in which only regular numerical predicates appear. The same statement, with “Σ₁” replaced by “first-order,” is equivalent to the conjecture that the nonuniform circuit complexity class ACC is strictly contained in NC¹. The argument introduces some new techniques, based on a combination of semigroup theory and Ramsey theory, which may shed some light on the general case.     

On the Construction of Classes of Suffix Trees for Square Matrices: Algorithms and Applications

We provide a uniform framework for the study of index data structures for a two-dimensional matrixTEXT[1:n, 1:n] whose entries are drawn from an ordered alphabetΣ. An index forTEXTcan be informally seen as the two-dimensional analog of the suffix tree for a string. It allows on-line searches and statistics to be performed onTEXTby representing compactly theΘ(n³) square submatrices ofTEXTin optimalO(n²) space. We identify 4ⁿ⁻¹families of indices forTEXT, each containing ∏ⁿ_i=1 (2i−1)! isomorphic data structures. We also develop techniques leading to a single algorithm that efficiently builds any index in any family inO(n² log n) time andO(n²) space. Such an algorithm improves in various respects the algorithms for the construction of the PAT tree and the Lsuffix tree. The framework and the algorithm easily generalize tod>2 dimensions. Moreover, as part of our algorithm, we provide new algorithmic tools that yield a space-efficient implementation of the “naming scheme” of R. Karpet al.(in“Proceedings, Fourth Symposium on Theory of Computing,” pp. 125–136) for strings and matrices.     

Fully Scalable Fault-Tolerant Simulations for BSP and CGM

In this paper we consider general simulations of algorithms designed for fully operational BSP and CGM machines on machines with faulty processors. The BSP (or CGM) machine is a parallel multicomputer consisting of p processors for which a memory of n words is evenly distributed and each processor can send and receive at most h messages in a superstep. The faults are deterministic (i.e., worst-case distributions of faults are considered) and static (i.e., they do not change in the course of computation). We assume that a constant fraction of processors are faulty.  We present two fault-tolerant simulation techniques for BSP and CGM:  1. A deterministic simulation that achieves O(1) slowdown for local computations and O((log_h p)²) slowdown for communications per superstep, provided that a preprocessing is done that requires O((log_h p)²) supersteps and linear (in h) computation per processor in each superstep.  2. A randomized simulation that achieves O(1) slowdown for local computations and O(log_h p) slowdown for communications per superstep with high probability, after the same (deterministic) preprocessing as above.  Our results are fully scalable over all values of p from Θ(1) to Θ(n). Furthermore, our results imply that if pn for 0<<1 and h=Θ((n/p)^δ) for 0<δ1 (which hold in almost all practical BSP and CGM computations), algorithms can be made resilient to a constant fraction of processor faults without any asymptotic slowdown.     

A logic for reasoning about probabilities

We consider a language for reasoning about probability which allows us to make statements such as “the probability of E₁ is less than ” and “the probability of E₁ is at least twice the probability of E₂,” where E₁ and E₂ are arbitrary events. We consider the case where all events are measurable (i.e., represent measurable sets) and the more general case, which is also of interest in practice, where they may not be measurable. The measurable case is essentially a formalization of (the propositional fragment of) Nilsson's probabilistic logic. As we show elsewhere, the general (nonmeasurable) case corresponds precisely to replacing probability measures by Dempster-Shafer belief functions. In both cases, we provide a complete axiomatization and show that the problem of deciding satisfiability is NP-complete, no worse than that of propositional logic. As a tool for proving our complete axiomatizations, we give a complete axiomatization for reasoning about Boolean combinations of linear inequalities, which is of independent interest. This proof and others make crucial use of results from the theory of linear programming. We then extend the language to allow reasoning about conditional probability and show that the resulting logic is decidable and completely axiomatizable, by making use of the theory of real closed fields.     

Collecting Statistics over Runtime Executions

By collecting statistics over runtime executions of a program we can answer complex queries, such as “what is the average number of packet retransmissions” in a communication protocol, or “how often does process P₁ enter the critical section while process P₂ waits” in a mutual exclusion algorithm. We present an extension to linear-time temporal logic that combines the temporal specification with the collection of statistical data. By translating formulas of this language to alternating automata we obtain a simple and efficient query evaluation algorithm. We illustrate our approach with examples and experimental results.     

Iterated Function Systems and Control Languages

Valuations—morphisms from (Σ*, ·, e) to ((0, ∞), ·, 1)—are a generalization of Bernoulli morphisms introduced by Eilenberg [“Automata, Languages, and Machines”, Academic Press, New York, 1974]. Here, we show how to generalize the notion of entropy (of a language) in order to obtain new formulas to determine the Hausdorff dimension of fractal sets (also in Euclidean spaces), especially defined via regular (ω-)languages. By doing this, we can sharpen and generalize earlier results in two ways: first, we treat the case where the underlying basic iterated function system contains noncontractive mappings and, second, we obtain results valid for nonregular languages as well.     

A Calculus of Terms for Coalgebras of Polynomial Functors

A syntax and semantics of types, terms and formulas for coalgebras of polynomial functors is developed, extending earlier work [4] on monomial coalgebras to include functors constructed using coproducts. A modified ultrapower construction for polynomial coalgebras is introduced, adapting the conventional ultrapower to retain only those states that evaluate observable terms in a standard way.A special role is played by terms that take observable values and are “rigid”: their free variables do not occur in any state-valued subterm. The following “co-Birkhoff” theorem is proved: a class of polynomial coalgebras is definable by Boolean combinations of equations between rigid terms iff the class is closed under disjoint unions, images of bisimulations, and observable ultrapowers.     

Error-Free and Best-Fit Extensions of Partially Defined Boolean Functions

In this paper, we address a fundamental problem related to the induction of Boolean logic: Given a set of data, represented as a set of binary “truen-vectors” (or “positive examples”) and a set of “falsen-vectors” (or “negative examples”), we establish a Boolean function (or an extension)f, so thatfis true (resp., false) in every given true (resp., false) vector. We shall further require that such an extension belongs to a certain specified class of functions, e.g., class of positive functions, class of Horn functions, and so on. The class of functions represents our a priori knowledge or hypothesis about the extensionf, which may be obtained from experience or from the analysis of mechanisms that may or may not cause the phenomena under consideration. The real-world data may contain errors, e.g., measurement and classification errors might come in when obtaining data, or there may be some other influential factors not represented as variables in the vectors. In such situations, we have to give up the goal of establishing an extension that is perfectly consistent with the given data, and we are satisfied with an extensionfhaving the minimum number of misclassifications. Both problems, i.e., the problem of finding an extension within a specified class of Boolean functions and the problem of finding a minimum error extension in that class, will be extensively studied in this paper. For certain classes we shall provide polynomial algorithms, and for other cases we prove their NP-hardness.     

The prism machine: An alternative to the pyramid

The prism machine is a stack of n cellular arrays, each of size 2ⁿ × 2ⁿ. Cell (i, j) on level k is connected to cells (i, j), (i + 2^k, j), and (i, j + 2^k) on level k + 1, 1 ≤ k < n, where the sums are modulo 2ⁿ. Such a machine can perform various operations (e.g., “Gaussian” convolutions or least-squares polynomial fits) on image neighborhoods of power-of-2 sizes in every position in O(n) time, unlike a pyramid machine which can do this only in sampled positions. It can also compute the discrete Fourier transform in O(n) time. It consists of n · 4ⁿ cells, while a pyramid consists of fewer than 4ⁿ⁺¹/3 cells; but in practice n would be at most 10, so that a prism would be at most about seven times as large as a pyramid.     

Nonlinear eigenvalue problems for quasilinear systems

The paper deals with the existence of positive solutions for the quasilinear system (Φ(u'))' + λh(t)f(u) = 0,0 < t < 1 with the boundary condition u(0) = u(1) = 0. The vector-valued function Φ is defined by Φ(u) = (q(t)(p(t)u₁), …, q(t)(p(t)u_n)), where u = (u₁, …, u_n), andcovers the two important cases (u) = u and (u) = up > 1, h(t) = diag[h₁(t), …, h_n(t)] and f(u) = (f¹(u), …, fⁿ (u)). Assume that fⁱ and h_i are nonnegative continuous. For u = (u₁, …, u_n), let

, f₀ = maxf¹₀, …, fⁿ₀ and f_∞ = maxf¹_∞, …, fⁿ_∞. We prove that the boundary value problem has a positive solution, for certain finite intervals of λ, if one of f₀ and f_∞ is large enough and the other one is small enough. Our methods employ fixed-point theorem in a cone.