Second Cycle Degree/Two Year Master in Mathematics

Syllabus - Master Degree

Minimum knowledge required for admission to the Master’s Degree in Mathematics

  • Concepts of limit and continuity for real functions of one or more real variables, and more generally for functions between normed or topological spaces.
  • Ordinary differential equations and solution methods.
  • Taylor polynomial for a real function of one or more variables.
  • Line integrals and surface integrals.
  • Numerical series and the main criteria for convergence and divergence. Power series in real and complex settings; elementary notions of holomorphic functions of a complex variable.
  • Basic elements of functions of a complex variable, analytic functions.
  • Basic knowledge of Lebesgue measure and integral in R and R^n.
  • Basic knowledge of the most important function spaces: C^n, C^∞, L^p, L^∞ on open sets of R or R^n.
  • Abstract Hilbert space. 
  • Fundamentals of classical mechanics, in particular: Energy conservation law. Qualitative analysis of one-dimensional motion. Equilibrium of mechanical systems. Principle of Virtual Work. Two-body problem. The rigid body. 
  • Elements of analytical mechanics (Lagrangian and Hamiltonian), in particular: Euler-Lagrange equations. Hamilton equations. Canonical transformations. Integrable systems. Hamilton-Jacobi method.
  • Basics of thermodynamics, in particular: first and second law, entropy and its probabilistic interpretation. Diffusive motion and random walk.
  • Equivalence relations and order relations.
  • Divisibility among integers: Euclidean algorithm and Bézout's theorem. Prime numbers and the fundamental theorem of arithmetic.
  • Polynomials with real coefficients: division of polynomials and irreducible polynomials; polynomials with complex coefficients and the fundamental theorem of algebra.
  • Elements of group theory; normal subgroups and quotients; homomorphisms.
  • Elements of ring theory; principal ideal domains; Euclidean rings; homomorphisms.
  • Elements of field theory: numerical fields. Characteristic of a field.
  • Vector spaces and linear maps; matrices and linear systems; eigenvalues, eigenvectors, diagonalization of endomorphisms.
  • Affine spaces, subspaces, and affine transformations. Inner product, Euclidean vector spaces.
  • Quadratic forms and their classification by congruence; conics and quadrics: affine and metric classification.
  • Topological spaces and continuous functions, homeomorphisms, product and quotient topology, connected and compact spaces. Real projective spaces.
  • Differentiable curves in the plane and in space; surface theory in E3, geodesics.
  • Axioms of probability calculus; events, independent events, and conditional probability.
  • Random variables and main distributions (binomial, geometric, hypergeometric, Poisson, exponential, gamma, Gaussian, beta).
  • Multinomial distribution and multivariate Gaussian distribution. Stochastic independence and uncorrelation.
  • Bernoulli scheme. Weak law of large numbers. Generating function. Characteristic function.
  • Basic notions of descriptive statistics.
  • Basic elements of numerical calculus: finite arithmetic, numerical linear algebra, data approximation.
  • Principles of programming.