Learning outcomes

1. Communicate complex information in an effective, clear and concise manner, either orally, in writing or through ICTs, in front of both specialist and general publics.
2. Use critical reasoning, show analytical skills, correctly use technical language and develop logical arguments
3. Work independently, take initiative itself, be able to organize to achieve results and to plan and execute a project.
4. Working in groups, assume shared responsibilities and interact professionally and constructively with others, showing absolute respect for their rights.
5. Describe the most important statistical groups and the assumptions underlying the theory of groups.
6. Correctly apply the theory of ideal systems for groups of distinguishable and indistinguishable particles.
7. Apply statistical physics to interacting particle systems.
8. Deduce classical and quantum statistics and apply them correctly to different systems.
9. Applying the tools of kinetic theory to describe transport processes.
10. Describe the concept of stochastic process and apply their basic techniques to the description of physical systems.
11. Apply the concept of frozen and wake degrees of freedom to predicting the heat capacity of gases.
12. Quantify the contribution of each internal degree of freedom in the heat capacity of a gas in diatomic molecules.
13. Qualitatively and quantitatively predict the macroscopic behaviour of ideal magnetic systems for classical and quantum moments.
14. Reason the temperature dependence of heat capacity for electrons and the crystalline network.
15. Apply Fermi statistics to a degenerate gas of relativistic particles.
16. Describe and quantify Brownian motion.
17. Describe the thermal denaturation of DNA and quantify it for certain simple models.
18. Describe ion transport in passive and active membranes, quantifying it for certain simple models.
19. Determine the fraction of molecules adsorbed on a macromolecule in simple models.
20. Analyse stochastic processes and use them to model physical systems and in other ambits.
21. Determine the magnetic response of a superparamagnetic nanoparticle and the behaviour in a dispersion of these particles.
22. Analyse interacting particle systems through simple models and simulation techniques.
23. Describe and Analyse the Bose-Einstein condensation.
24. Describe the basis of Brownian motors.
25. Apply the kinetic theory of quantum gases and predict the thermal conductivity of metals and insulators.
26. Describe biological systems using techniques of statistical physics.
27. Qualitatively and quantitatively describe the behaviour of system close to critical points and the concept of universality.
28. Analyse biological systems using techniques of statistical physics.
29. Distinguish between mean-field models and those that are not.
30. Use mean-field approaches to describe physical systems.
31. Define characteristic magnitudes to discern the relevance of different mechanisms.
32. Describe and analyse the models of Weiss, Landau and Ising for magnetic systems with interaction.
33. Apply different techniques of simulation for the study of systems with interaction to simple cases: Monte Carlo, molecular dynamics, Brownian dynamics and Langevin dynamics.
34. Analyse random paths and use them to model real systems.
35. Analyse simple stochastic equations.
36. Identify situations in which a change or improvement is needed.
37. Identify the social, economic and environmental implications of academic and professional activities within one's own area of knowledge.