computational complexity

computational complexity presents outstanding research in computational complexity. Its subject is at the interface between mathematics and theoretical computer science, with a clear mathematical profile and strictly mathematical format.

The central topics are:

Models of computation, complexity bounds (with particular emphasis on lower bounds), complexity classes, trade-off results

• for sequential and parallel computation
• for "general" (Boolean) and "structured" computation (e.g. decision trees, arithmetic circuits)
• for deterministic, probabilistic, and nondeterministic computation
• worst case and average case

Specific areas of concentration include:

• Structure of complexity classes (reductions, relativization questions, degrees, derandomization)
• Algebraic complexity (bilinear complexity, computations for polynomials, groups, algebras, and representations)
• Interactive proofs, pseudorandom generation, and randomness extraction

Complexity issues in:

• cryptography
• learning theory
• number theory
• logic (complexity of logical theories, cost of decision procedures)
• combinatorial optimization and approximate solutions
• distributed computing
• property testing

Bibliographic Data
comput. complex.
First published in 1991
1 volume per year, 4 issues per volume
approx. 800 pages per volume
Format: 15.5 x 23.5 cm
ISSN 1016-3328 (print)
ISSN 1420-8954 (electronic)

AMS Mathematical Citation Quotient (MCQ): 0.45 (2017)

• A resource for outstanding research in computational complexity
• Covers models of computation, complexity bounds, complexity classes and more
• Explores the structure of complexity classes, algebraic complexity, the role of randomness, and issues in cryptography, robotics, logic and distributed computing