PhD Courses

The CM courses are structured in three terms, as detailed below. You can check the weekly schedule along with the seminars here.

The total number of required credits is 34. Attending the lectures of all basic courses of Term 1 is strongly suggested. In order to be admitted to the second year, students must obtain an average mark of 27/30 or better, and a minimum mark of 24/30 in every exam. Students are expected to start their research activity during the Spring of their first year, and a progress report is scheduled in the Fall of the second academic year.

Term 1 (October-December): contains the CM basic courses, split into smaller modules for a larger flexibility. Each of the courses usually requires a series of small standard problems which should be solved by the students enrolled in the course, with a suitable deadline (for instance, mid January): as an alternative, students might opt for an oral final exam for the course. In case a student has already a reasonable knowledge on the material covered in one of the courses, he can ask for an ad-hoc assignment from the course instructor. (Go to the courses)

Term 2 (January-February): is dedicated to guided “hands-on” problem solving: several assignments will be handed out to the students during the Christmas break, which are supposed to give a first-hand experience on some condensed matter problems and a more in-dept view of the basic theory covered in the first term. All the staff members will propose problem assignments, tutoring the students who decide to take that assignment. Each completed assignment is worth 3 credits (or more, if necessary). Students are encouraged to collaborate in small groups (2-3 persons) on the same assignment. It is foreseen that in the time-span of two months, each student might complete 2 assignments (hence at least 6 credits). (Go to the courses)

Term 3 (March-May): contains a number of advanced courses offered to the students, with different number of credits. These courses are supposed to introduce the students to the research they would like to do, getting a more detailed training on a particular field of interest. (Go to the courses)

Advanced Courses

Algorithmic differentiation for electronic simulations
Teachers: Sandro Sorella Credits: 2
Classical and quantum phase transitions: Critical Phenomena and the RG
Teachers: Alessandro Silva Credits: 6
Advanced quantum Monte Carlo techniques for the many electron problem
Teachers: Sandro Sorella Credits: 2
Advanced techniques in Tensor Networks
Teachers: Mario Collura Credits: 4
Scalar and fully relativistic pseudopotential theory
Teachers: Andrea Dal Corso Credits: 4
Introduction to group theory for molecules and solids
Teachers: Andrea Dal Corso Credits: 4
Landau-Fermi liquids without quasiparticles
Teachers: Michele Fabrizio Credits: 4
Introduction to Quantum Computation and Information
Teachers: Giuseppe Santoro, Prof. Rosario Fazio Credits: 5
Nonequilibrium dynamics of quantum systems
Teachers: Alessandro Silva Credits: 4
Strongly Correlated Systems: from the Fermi-liquid theory to DMFT (and beyond)
Teachers: Massimo Capone Credits: 4
Theory and numerical simulation of mass, charge, and heat transport in condensed matter
Teachers: Stefano Baroni Credits: 2
Electronic Structure: from BlackBoard to Source Code
Teachers: Stefano de Gironcoli Credits: 2
Machine Learning for Material Science (a biased introduction)
Teachers: Stefano de Gironcoli Credits: 1
Introduction to Path Integral Monte Carlo in Continuous Space
Teachers: , Saverio Moroni Credits: 1
Lattice gauge theories - and an introduction to topological matter
Teachers: Marcello Dalmonte Credits: TBA