Theoretical understanding of the physical phenomena.
Thorough general culture in Physics, namely computational algorithms that are used in the different fields of Physics.
Numeric interpolation: Spline and Lagrange interpolation.
Numeric differentiation: rules of 2, 3 and 5 points and Richardson method. Numeric integration: Trapezoid Rule, Simpson’s rule, Romberg and Gaussian Quadrature.
Zeros and extrema of the function of a variable: bisection, secant, regula falsi and the newton-raphson methods.
Linear systems of equations: Gauss-Jordan elimination, LU factorization, Cholesky factorization and QR factorization.
Extrema of the function of various variables: maximum decrease method and conjugated gradients method, genetic algorithms, simulated annealing and search methods in a pattern.
Applications in Physics (molecular geometry, etc.).
Monte Carlo method: integration, radioactive decay, diffusion. Random walks and Metropolis algorithm. Ising Model.
Problems of intrinsic values: diagnolization of Schrödinger equation.
Differential equations: Euler’s method, Runge-Kutta methods and predictor-corrector methods.
The cushioned and forced pendulum. Chaos.
Resolution of the Schrödinger equation by means of the integration of the differential equation: the Numerov’s method.
Laplace and Poisson’s equations.
Quantum Monte Carlo methods: the hydrogen and helium atoms and H2 and H2+ Molecules.
Mathematical Analysis I, II, III.
Linear Algebra and Analytical Geometry.
Computers and Programming.
Quantum Mechanics I.
Generic skills to reach
. Computer Skills for the scope of the study; . Competence to solve problems; . Competence in autonomous learning; . Adaptability to new situations; . Competence in applying theoretical knowledge in practice; . Competence in oral and written communication; . Critical thinking; . Creativity; . Initiative and entrepreneurial spirit; . Quality concerns; (by decreasing order of importance)
Teaching hours per semester
total of teaching hours
assessment implementation in 20102011 Resolution of problems : 100.0%
Bibliography of reference
PRESS, William [et.al.]. Numerical Recipes in F77/F90/C/C++: The Art of Scientific Computing, Cambridge: Cambridge University Press.
HJORTH-JENSEN, M. Computational Physics. http://www.uio.no/studier/emner/matnat/fys/FYS3150/h11/undervisningsmateriale/Lecture%20Notes/lectures2011.pdf
PANG, Tao (2006). An Introduction to Computational Physics. Cambridge: Cambridge University Press. ISBN: 978-0521825696.
ALLEN, M. P. and TILDESLEY, D. J. (1989). Computer Simulation of Liquids. Oxford: Clarendon Press. ISBN: 978-0198556459.
FRENKEL, Daan and SMIT, Berend (2001). Understanding Molecular Simulation: From Algorithms to Applications. New York: Academic Press. ISBN: 978-0122673511 .
The essential objectives of this curricular unit are those marked with the number1 in the Dublin descriptors mentioned above. Especially, students are expected to be able to identify, implement and critically analyse a numeric method (or a set of methods) in order to solve an essential problem of Physics. The adopted strategy comprises the brief theoretical lecturing of a wide number of methods and an assessment system based on the accomplishment of small project assignments and their reports. Students will be advised to carry out 4 assignments: the first two should be done during two weeks (the time given to students to accomplish the assignment, which is counted from the day on which the assignment is delivered by the teacher); the last two should be done during 4 weeks.
These assignments allow students to develop their ability to do research and their ability to work alone in the resolution of advanced problems.