Scientific Computing

Versión en Español

Objectives

The main objective of this area is to develop and apply models able to predict the behavior of systems in science and engineering.

Reseach lines

  • Parallel processing of models of systems in science and engineering.
  • Numerical methods of partial differential equations.
  • Specific applications for modelling oil deposits for their efficient explotation and flow and transport modelling of underground water.
  • Category theory with applications to languages, programming, and data. Multilevel systems, multigraph. Information systems. Petri nets.
  • Scientific computing with Matematica, Maple, for automating deduction for computing differential forms (differential equations as exterior, ideal, and Cartan systems), in areas such as physics and engineering. Symbolic computing.
  • Quantic computing, quantic algoritms.
  • Multivalued fuzzy logic, rough sets, evidence theory, confidence theory, posibility theory.
  • Algorithmic problems of algebra theory and integer number theory.
  • Symbolic computing for associative algebras and Lie algebras.
  • Quantifications of Lie algebras and their applications in quantic group theory with computational methods.
  • Theory of Galois for associative algebras with computational methods.
  • Free algebras ant their automorphisms with computational methods.
  • Ring theory with computational methods.
  • Computational models and algorithms for fractal structure generation.
  • Computational model of the bi-color DLA.
  • Computational models in natural science.
  • Computational algorithms and multi-thread programming in Windows and Linux.
  • Advanced programming in C++ and its application implementing computational algorithms.
  • Scientific visualization with C++ Builder, OpenGL and other computer packages.

Faculty

¤ Masters and Doctoral

¤ Masters