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1986
A function of boolean arguments is symmetric if its value depends solely on the number of l's among its arguments. In the first part of this paper we partially characterize those symmetric functions that can be computed by constant-depth polynomial-size sequences of boolean circuits, and discuss the complete characterization. (We treat both uniform and non-uniform sequences of circuits.) Our results imply that these circuits can compute functions that are not definable in first-order logic. In the second part of the paper we generalize from circuits computing symmetric functions to circuits recognizing first-order structures. By imposing fairly natural restrictions we develop a circuit model with precisely the power of first-order logic: a class of structures is first-order definable if and only if it can be recognized by a constant-depth polynomial-time sequence of such circuits. © 1986 Academic Press, Inc.
Information and Control, 1984
Consider a family of boolean circuits C~, C2,..., C,,..., constructed by some uniform, effective procedure operating on input n. Such a procedure provides a concise representation of a family of parallel algorithms for computing boolean values. A formula of first-order logic may also be viewed as a concise representation of a family of parallel algorithms for evaluating boolean functions. The parallelism is implicit in the quantification (a formula gx q~(x) is true if and only if each of the formulas q~(a) is true, and all these formulas can be checked simultaneously), and universes of different sizes give rise to boolean functions with different numbers of inputs (the boolean values of the formula's predicates on various combinations of elements of the universe). This note presents an extended first-order logic designed to be exactly equivalent in expressiveness to polynomialsize, constant-depth, unbounded-fan-in circuits constructed by Turing machines of bounded computational complexity.
Theoretical Computer Science, 1985
Let ~:= {f~,f2 .... } be a family of symmetric Boolean functions, where fn has n Boolean variables, for each n I> 1. Let/~(n) be the minimum number of variables offn that each have to be set to constant values so that the resulting function is a constant function. We show that the growth rate of/~(n) completely determines whether or not the family ~: is 'good', that is, can be realized by a family of constant-depth, polynomial-size circuits (with unbounded fan-in). Furthermore, if ~(n)<~ (log n) k for some k, then the family ~: is good. However, if ~(n) ~> n" for some e > 0, then the family is not good.
Theory of Computing Systems / Mathematical Systems Theory, 2007
Any Boolean function can be defined by a Boolean circuit, provided we may use sufficiently strong functions in its gates. On the other hand, what Boolean functions can be defined depends on these gate functions: Each set B of gate functions defines the class of Boolean functions that can be defined by circuits over B. Although these classes have been known since the 1920s, their computational complexity was never investigated. In this paper we will study how difficult it is to decide for a Boolean function f and a class B, whether f is in B. Moreover, we will provide such a decision algorithm with additional information: How difficult is it to decide whether or not f is in B, provided we already know a circuit for f, but with gates from another class A? Given such a circuit, we know that f is in A. Is the problem harder if we do not have a concrete representation for f, but still know that it is from A? For nearly all possible combinations, we show that this is not the case, and that the problem is either in P or coNP-complete.
Theoretical Computer Science, 2010
The expressive power of existentially quantified Boolean formulas ∃CNF with free variables is investigated. We introduce a hierarchy of subclasses ∃MU * (k) of ∃CNF formulas based on the maximum deficiency k of minimal unsatisfiable subformulas of the bound part of the formulas. We will establish an upper bound of the size of minimally equivalent circuits. It will be shown, that there are constants a and b, such that for every formula in ∃MU * (k) of length m of the bound part and length l of the free part of the formula there is an equivalent circuit of size less than l + a • m b(log 2 (m)+k) 2 .
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014
We study algorithms for the satisfiability problem for quantified Boolean formulas (QBFs), and consequences of faster algorithms for circuit complexity. • We show that satisfiability of quantified 3-CNFs with m clauses, n variables, and two quantifier blocks (one existential block and one universal) can be solved deterministically in time 2 n−Ω(√ n) • poly(m). For the case of multiple quantifier blocks (alternations), we show that satisfiability of quantified CNFs of size poly(n) on n variables with q quantifier blocks can be solved in 2 n−n 1/(q+1) • poly(n) time by a zero-error randomized algorithm. These are the first provable improvements over brute force search in the general case, even for quantified polynomial-sized CNFs with two quantifier blocks. A second zero-error randomized algorithm solves QBF on circuits of size s in 2 n−Ω(q) • poly(s) time when the number of quantifier blocks is q. • We complement these algorithms by showing that improvements on them would imply new circuit complexity lower bounds. For example, if satisfiability of quantified CNF formulas with n variables, poly(n) size and at most q quantifier blocks can be solved in time 2 n−n ωq (1/q) , then the complexity class NEXP does not have O(log n) depth circuits of polynomial size. Furthermore, solving satisfiability of quantified CNF formulas with n variables, poly(n) size and O(log n) quantifier blocks in time 2 n−ω(log(n)) time would imply the same circuit complexity lower bound. The proofs of these results proceed by establishing strong relationships between the time complexity of QBF satisfiability over CNF formulas and the time complexity of QBF satisfiability over arbitrary Boolean formulas.
Structure in Complexity Theory Conference, 1992
Utilizing the connection between uniform constant-depth circuits and first-order logic with numerical predicates, the author provides a purely logical characterization of uniformity based on the intrinsic properties of these predicates. By requiring a numerical predicate R to satisfy a natural extensibility condition-that it can be translated to a polynomially magnified domain based on tuple constructions-he shows that R must already
2016
The automation of reasoning has been an aim of research for a long time. Already in 17th century, the famous mathematician Leibniz invented a mechanical calculator capable of performing all four basic arithmetic operators. Although automatic reasoning can be done in different fields, many of the procedures for automated reasoning handles formulas of first-order logic. Examples of use cases includes hardware verification, program analysis and knowledge representation.One of the fundamental challenges in first-order logic is handling quantifiers and the equality predicate. On the one hand, SMT-solvers (Satisfiability Modulo Theories) are quite efficient at dealing with theory reasoning, on the other hand they have limited support for complete and efficient reasoning with quantifiers. Sequent, tableau and resolution calculi are methods which are used to construct proofs for first-order formulas and can use more efficient techniques to handle quantifiers. Unfortunately, in contrast to S...
Theoretical Computer Science, 1992
Frandsen and C. Sturtivant, An arithmetic model of computation equivalent to threshold circuits. Theoretical Computer Science 93 (1992) 303-319. We define a new structured and general model of computation: circuits using arbitrary fan-in arithmetic gates over the characteristic-two finite fields (F,:,). These circuits have only one input and one output. We show how they correspond naturally to boolean computations with n inputs and n outputs. We show that if circuit sizes are polynomially related, then the arithmetic circuit depth and the threshold circuit depth to compute a given function differ by at most a constant factor. We use threshold functions with arbitrary weights; however, we show that when compared to the usual threshold model. the depth measure of this generalised model differs only by at most a constant factor (at polynomial size). The fan-in of our arithmetic model is also unbounded in the most generous sense: circuit size is measured as the number of Z-and U-gates: there is no bound on the number of "wires". We show that these results are provable for any reasonable correspondence between strings of n-bits and elements of F,,,. And we find two such distinct characterizations. Thus, we show that arbitrary fan-in arithmetic computations over F,. constitute a precise abstraction of Boolean threshold computations with the pleasant property that various algebraic laws have been recovered.
The paper presents a family of new expansions of Boolean functions called Function-driven Linearly Independent (fLI) expansions. On the basis of this expansion a new kind of a canonical representation of Boolean functions is constructed: Function-driven Linearly Independent Binary Decision Diagrams (fLIBDDs). They generalize both Function-driven Shannon Binary Decision Diagrams (fShBDDs) and Linearly Independent Binary Decision Diagram (LIBDDs). The diagrams introduced in the paper, can provide significantly smaller representations of Boolean functions than standard Ordered Binary Decision Diagrams (OBDDs), Ordered Functional Decision Diagrams (OFDDs) and Ordered (Pseudo-) Kronecker Functional Decision Diagrams (OKFDDs) and can be applied to synthesis of reversible circuits.
In circuit complexity, the polynomial method is a general approach to proving circuit lower bounds in restricted settings. One shows that functions computed by sufficiently restricted circuits are "correlated" in some way with a low-complexity polynomial, where complexity may be measured by the degree of the polynomial or the number of monomials. Then, results limiting the capabilities of low-complexity polynomials are extended to the restricted circuits. Old theorems proved by this method have recently found interesting applications to the design of algorithms for basic problems in the theory of computing. This paper surveys some of these applications, and gives a few new ones.
We study Boolean circuits as a representation of Boolean functions and consider different equivalence, audit, and enumeration problems. For a number of restricted sets of gate types (bases) we obtain efficient algorithms, while for all other gate types we show these problems are at least NP-hard.
Information Processing Letters, 1996
Discrete Mathematics & Theoretical Computer Science
Any attempt to find connections between mathematical properties and complexity has a strong relevance to the field of Complexity Theory. This is due to the lack of mathematical techniques to prove lower bounds for general models of computation.\par This work represents a step in this direction: we define a combinatorial property that makes Boolean functions ''\emphhard'' to compute in constant depth and show how the harmonic analysis on the hypercube can be applied to derive new lower bounds on the size complexity of previously unclassified Boolean functions.
Information Processing Letters, 2010
In this note, we present improved upper bounds on the circuit complexity of symmetric Boolean functions. In particular, we describe circuits of size 4.5n + o(n) for any symmetric function of n variables, as well as circuits of size 3n for MOD n 3 function.
Theoretical Computer Science, 2001
Recent results of Bucciarelli show that the semilattice of degrees of parallelism of firstorder boolean functions in PCF has both infinite chains and infinite antichains. By considering a simple subclass of Sieber's sequentiality relations, we identify levels in the semilattice and derive inexpressibility results concerning functions on different levels. This allows us to further explore the structure of the semilattice of degrees of parallelism: we identify semilattices characterized by simple level properties, and show the existence of new infinite hierarchies which are in a certain sense natural with respect to the levels.
Proceedings of the 33rd Annual ACM/IEEE Symposium on Logic in Computer Science, 2018
Satisfiability of Boolean circuits is among the most known and important problems in theoretical computer science. This problem is NP-complete in general but becomes polynomial time when restricted either to monotone gates or linear gates. We go outside Boolean realm and consider circuits built of any fixed set of gates on an arbitrary large finite domain. From the complexity point of view this is strictly connected with the problems of solving equations (or systems of equations) over finite algebras. The research reported in this work was motivated by a desire to know for which finite algebras A there is a polynomial time algorithm that decides if an equation over A has a solution. We are also looking for polynomial time algorithms that decide if two circuits over a finite algebra compute the same function. Although we have not managed to solve these problems in the most general setting we have obtained such a characterization for a very broad class of algebras from congruence modular varieties. This class includes most known and well-studied algebras such as groups, rings, modules (and their generalizations like quasigroups, loops, near-rings, nonassociative rings, Lie algebras), lattices (and their extensions like Boolean algebras, Heyting algebras or other algebras connected with multi-valued logics including MV-algebras). This paper seems to be the first systematic study of the computational complexity of satisfiability of non-Boolean circuits and solving equations over finite algebras. The characterization results provided by the paper is given in terms of nice structural properties of algebras for which the problems are solvable in polynomial time.
2020
Boolean functional synthesis concerns synthesizing out1 puts as Boolean functions of inputs such that a rela2 tional specification between inputs and outputs is sat3 isfied. This has several applications, including design 4 of safe controllers for autonomous systems, certified 5 QBF solving, cryptanalysis etc. Despite complexity6 theoretic hardness results, several algorithms proposed 7 in the literature are known to work well in practice. 8 This motivates the investigation of whether there exist 9 representations of input specifications that permit and 10 also characterize efficient synthesis. 11 In this paper, we present a normal form called SAUNF 12 that precisely characterizes tractable synthesis in the 13 following sense: a specification is polynomial time syn14 thesizable iff it can be compiled to SAUNF in poly15 nomial time. Additionally, a specification admits a 16 polynomial-sized functional solution iff there exists a 17 semantically equivalent polynomial-sized SAUNF rep18...
Electron. Colloquium Comput. Complex., 2018
A polynomial threshold function (PTF) is defined as the sign of a polynomial p : {0, 1} → R. A PTF circuit is a Boolean circuit whose gates are PTFs. We study the problems of exact and (promise) approximate counting for PTF circuits of constant depth. Satisfiability (#SAT). We give the first zero-error randomized algorithm faster than exhaustive search that counts the number of satisfying assignments of a given constant-depth circuit with a super-linear number of wires whose gates are s-sparse PTFs, for s almost quadratic in the input size of the circuit; here a PTF is called s-sparse if its underlying polynomial has at most s monomials. More specifically, we show that, for any large enough constant c, given a depth-d circuit with (n2−1/c)-sparse PTF gates that has at most n1+εd wires, where εd depends only on c and d, the number of satisfying assignments of the circuit can be computed in randomized time 2n−nε with zero error. This generalizes the result by Chen, Santhanam and Srini...
2021
In this thesis, we study the descriptive complexity of counting classes based on Boolean circuits. In descriptive complexity, the complexity of problems is studied in terms of logics required to describe them. The focus of research in this area is on identifying logics that can express exactly the problems in specific complexity classes. For example, problems are definable in ESO, existential second-order logic, if and only if they are in NP, the class of problems decidable in nondeterministic polynomial time. In the computation model of Boolean circuits, individual circuits have a fixed number of inputs. Circuit families are used to allow for an arbitrary number of input bits. A priori, the circuits in a family are not uniformly described, but one can impose this as an additional condition, e.g., requiring that there is an algorithm constructing them. For any circuit there is a function counting witnesses (or proofs) for the circuit producing the output 1. Consequently, any class o...
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