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Mathematics
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E1: Mathematics and Computer Science
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E1: Mathematics and Computer Science

A section of Mathematics (ISSN 2227-7390).

Section Information

The “Mathematics and Computer Science” section of Mathematics combines mathematical reasoning and computing. On the one hand, mathematics can be seen as a fundamental tool in computing. On the other hand, computing is increasingly being used in mathematical problem solving. We seek papers that bring mathematical rigor into computing. Topics of interest for the “Mathematics and Computers Science” section include the following:

  • abstract machines;
  • algebraic language theory;
  • algorithmic game theory;
  • approximation algorithms;
  • automated reasoning;
  • coding theory;
  • combinatorics;
  • computability;
  • computational complexity;
  • computational geometry;
  • concurrency;
  • constructive mathematics;
  • cryptography;
  • data structures design and analysis;
  • description logics;
  • equational logic and rewriting;
  • error-correcting codes;
  • formal languages and automata theory;
  • formal methods and theory of security;
  • grammars and context-free languages;
  • graph theory;
  • higher-order logic;
  • Hoare logic;
  • information complexity;
  • interactive computations;
  • lambda calculus;
  • linear logic;
  • logic and verification;
  • machine learning theory;
  • mathematical optimization;
  • mathematical software;
  • mathematics of computing;
  • modal and temporal logic;
  • model checking;
  • models of computations;
  • network protocols;
  • operations research;
  • probabilistic algorithms;
  • probabilistic inference problems;
  • probabilistic reasoning algorithms;
  • probabilistic representations;
  • programming logic;
  • proof theory;
  • random network models;
  • random search heuristics;
  • regular languages;
  • representation of mathematical objects;
  • rewrite systems;
  • semantics and reasoning;
  • simulation theory;
  • statistical paradigms;
  • symbolic and algebraic manipulation;
  • quantum computation theory;
  • timed and hybrid models;
  • theory and algorithms for application domains;
  • tree languages;
  • Turing machines;
  • type theory

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