http://compalg.inf.elte.hu/~tony/Kutatas/BinPacking/Johnson-BinPacking-NP-Column-JAlg-2002.pdf

The NP-completeness column: An ongoing guide

Publisher Summary This chapter discusses the concepts needed for defining the complexity classes. A complexity class is a set of problems of related resource-based complexity. A typical complexity class has a definition of the form—the set of problems that can be solved by an abstract machine M using O(f(n)) of resource R , where n is the size of the input. The simpler complexity classes are defined by various factors. The type of computational problem in which the most commonly used problems are decision problems. However, complexity classes can be defined based on function problems, counting problems, optimization problems, promise problems, etc. The most common model of computation is the deterministic Turing machine, but many complexity classes are based on nondeterministic Turing machines, etc.

A catalog of complexity classes

Starting with Cook's pioneering work on NP-completeness in 1970, polynomial complexity theory, the study of polynomial-time com putability, has quickly emerged as the new foundation of algorithms. On the one hand, it bridges the gap between the abstract approach of recursive function theory and the concrete approach of analysis of algorithms. It extends the notions and tools of the theory of computability to provide a solid theoretical foundation for the study of computational complexity of practical problems. In addition, the theoretical studies of the notion of polynomial-time tractability some times also yield interesting new practical algorithms. A typical exam ple is the application of the ellipsoid algorithm to combinatorial op timization problems (see, for example, Lovasz [1986]). On the other hand, it has a strong influence on many different branches of mathe matics, including combinatorial optimization, graph theory, number theory and cryptography. As a consequence, many researchers have begun to re-examine various branches of classical mathematics from the complexity point of view. For a given nonconstructive existence theorem in classical mathematics, one would like to find a construc tive proof which admits a polynomial-time algorithm for the solution. One of the examples is the recent work on algorithmic theory of per mutation groups. In the area of numerical computation, there are also two tradi tionally independent approaches: recursive analysis and numerical analysis."

Complexity theory of real functions

For all known NP-complete problems the number of solutions in instances having solutions may vary over an exponentially large range. Furthermore, most of the well-known ones, such as satisfiability, are parsimoniously interreducible, and these can have any number of solutions between zero and an exponentially large number. It is natural to ask whether the inherent intractability of NP-complete problems is caused by this wide variation. In this paper we give a negative answer to this using randomized reductions. We show that the problems of distinguishing between instances of SAT having zero or one solution, or finding solutions to instances of SAT having unique solutions, are as hard as SAT itself. Several corollaries about the difficulty of specific problems follow. For example if the parity of the number of solutions of SAT can be computed in RP then NP = RP. Some further problems can be shown to be hard for NP or DP via randomized reductions.

NP is as easy as detecting unique solutions

This is the second volume of a systematic two-volume presentation of the various areas of research in the field of structural complexity. The mathematical theory of computation has developed into a broad and rich discipline within which the theory of algorithmic complexity can be approached from several points of view. This volume is addressed to graduate students and researchers and assumes knowledge of the topics treated in the first volume but is otherwise nearly self-contained. Topics covered include vector machines, parallel computation, alternation, uniform circuit complexity, isomorphism, biimmunity and complexity cores, relativization and positive relativization, the low and high hierarchies, Kolmogorov complexity and probability classes. Numerous exercises and references are given.

Structural Complexity II

A general theory of public-key cryptography is developed that is based on the mathematical framework of complexity theory. Two related approaches are taken to the development of this theory, and th...

Complexity measures for public-key cryptosystems

The first part of this paper gives results about promise problems. A "promise problem" is a formulation of a partial decision problem that is useful for describing cracking problems for public-key cryptosystems (PKCS). We prove that every NP-hard promise problem is uniformly NP-hard, and we show that a number of results and a conjecture about promise problems are equivalent to separability assertions that are the natural analogues of well-known results in classical recursion theory. The conjecture, if it is true, implies nonexistence of PKCS having NP-hard cracking problems. The second part of the paper studies more appropriate measures for PKCS. Among the results obtained are the following: One-way functions exist if an only if P /spl ne/ U and one-way functions f such that range f /spl epsiv/ P exist if and only if U /spl cap/ co-U /spl ne/ P. It will allow that there exist PKCS that cannot be cracked in polynomial time (and that satisfy other reasonable assumptions) only if P /spl ne/ U.

Complexity Measures For Public-Key Cryptosystems

We study relationships between ${\bf P}$, $NP$ , and the unambiguous and random time classes, ${\bf U}$, and ${\bf R}$. Questions concerning these relationships are motivated by complexity issues in public-key cryptosystems. We prove that there exists a recursive oracle A such that ${\bf P}^A \ne {\bf U}^A \ne {\bf NP}^A $, and such that the first inequality is “strong,” i.e., there exists a ${\bf P}^A $-immune set in ${\bf U}^A $. Further, we construct a recursive oracle B such that ${\bf U}^B $ contains an ${\bf R}^B $-immune set. As a corollary, we obtain ${\bf P}^B \ne {\bf R}^B \ne {\bf NP}^B $ and both inequalities are strong. By use of the techniques employed in the proof that ${\bf P}^A \ne {\bf U}^A \ne {\bf NP}^A $, we are also able to solve an open problem raised by Book, Long and Selman [Quantitative relativizations of complexity classes, SIAM J. Comput. 13 (1984), pp 461–487].

Joachim Grollmann

Papers

Complexity measures for public-key cryptosystems

Complexity Measures For Public-Key Cryptosystems

Relativizations of unambiguous and random polynomial time classes

A user interface management system for rapid prototyping and generation of dialog managers

On the Software Structure of User Interface Management Systems