The objective of Linguaggi di Programmazione course is to introduce main formal language theory concepts and results as well as their application for programming language classification.
Most relevant approaches for syntactic analysis of programming languages are introduced. Learning how to recognize the structure of a programming language and the implementation techniques for the abrstract machine.
Understanding the Object Oriented paradigm together with other non imperative approaches.

[1] Maurizio Gabbrielli, Simone Martini,Programming Languages - Principles and paradigms, 2/ed. McGraw-Hill, (2011).
[2] Dean Wampler, Alex Payne, Programming Scala: Scalability = Functional Programming + Objects, 2 edizione. O’Reilly Media, (2014).
[3] David Parsons, Foundational Java Key Elements and Practical Programming. Springer- Verlag, (2012).
Course Slides

Field theory. Galois groups and Galois extensions. The Correspondence of Galois. Some applications of the Galois Correspondence: Constructions with ruler and compass, Solubility of polynomial equations.

S. Gabelli, Teoria delle Equazioni e Teoria di Galois. Springer Italia, (2008).

C. Procesi, Elementi di Teoria di Galois. Decibel, Zanichelli, (Seconda ristampa, 1991).
I. Stewart, Galois Theory. Chapman and Hall, (1989).

Field theory. Galois groups and Galois extensions. The Correspondence of Galois. Some applications of the Galois Correspondence: Constructions with ruler and compass, Solubility of polynomial equations.

S. Gabelli, Teoria delle Equazioni e Teoria di Galois. Springer Italia, (2008).

C. Procesi, Elementi di Teoria di Galois. Decibel, Zanichelli, (Seconda ristampa, 1991).
I. Stewart, Galois Theory. Chapman and Hall, (1989).

1. Abstract integration theory
Riemann integration theory. The concept of measurability. Step functions. Elementary properties of measures. Arithmetic in [0,∞]. Integration of positive functions. Integration of complex functions. Importance of sets
with null measure.
2. Positive Borel measures
Vector spaces. Topological preliminaries. Riesz representation theorem. Regularity properties of Borel measures. Lebesgue measure. Continuity properties of measurable functions.
3. L^p spaces
Inequalities and convex functions. L^p spaces. Approximation through continuous functions.
4. Basic theory of Hilbert spaces
Inner products and linear functionals. Dual space of L^2
5. Integration on product spaces
Measurability on cartesian products. Product measure. Fubini theorem.
6. Complex measures
Total variation. Absolute continuity. Radon-Nykodym theorem. Bounded linear functionals on L^p. The Riesz representation theorem.

"Analisi reale e complessa”, W. Rudin. Bollati Boringhieri.

abstract measures and integrations, Banach and Hilbert spaces.

Rudin - Real and Complex analysis

1. Topological classification of curves and compact surfaces. Triangulations, Euler carachetristic.
2. Smooth and regular curves in Euclidean space. Immersions and imbeddings. Arc lenght. Curvature and the Fundamental Theorem of local geometry of plane curves.
3. Regular surfaces in R^3, local coordinates. Inverse image of a regular value. Maps and diffeomorphisms. Tangent plane and derivative of a map. Normal unit vector, orientation
and the Gauss map of a surface in R^3. Orientable surfaces, examples. The Moebius band is non-orientable.
4. Riemannian metric, examples. The shape operator is self-adjoint. Principal and asymptotic directions. The Mean and Gauss curvatures.
5. The geometry of the Gauss map. The sign of the Gauss curvature and position of the tangent plane. Theorems of Meusnieur and Olinde Rodrigues. Geometric properties of compact surfaces, Minimal surfaces and Ruled surfaces.
6. Isometries and local isometries. The Shape operator in isothermal coordinates. Proof of Gauss' Theorema Egregium. Examples, counter-examples and applications.
7. Homeworks.
8. 12 hours of lab for the visualization and computation on curves and surfaces.

Testi consigliati
[1] J.M. Lee, Introduction to topological manifolds. Springer, (2000). - – http://dx.doi.org/10.1007/b98853
[2] E. Sernesi, Geometria 2. Boringhieri, (1994).
[3] M. Do Carmo , Differential Geometry of Curves and Surfaces. Prentice Hall, (1976).

1.Euclidean Geometry; rudiments of history of Greek Mathematics. Ruler and compass constructions. The classical problems. Euclid's Elements.
2. The V Postulate's problem: Posidonius attempt. Equivalent Postulates: Playfair, Wallis, transitivity of parallelism. Saccheri's work. Saccheri's Quadrilaterals. The three hyposes. Saccheri-Lagrange's Theorem and the exclusion of obtuse angle hypothesis. The birth of Non-Euclidean Geometry in Bolyai and Lobatchewaki.
3. Symmetries of the plane: Isometries of the plane and their type. Characterization of an isometry by the image of three points not on a line, Chasles' Theorem. Discrete groups of isometries. Rosettes, Friezes and Wallpaper groups. The Theorem of addiction of the angles. Leonardo's Theorem and the classification of finite groups of isometries. Sketch of the classification of the Frieze groups. Crystallographic restriction's Theorem and the classification of wallpaper groups.
4. Gauss' Geometry; The geometry on the Sphere. Locally euclidean geometries. Uniformly discontinuous groups of isometries. The Torus, Mobius band, Klein bottle. Classification of uniforly discontinuous groups of isometries. Sketch of the proof of the Theorem of classification of locally euclidean geometries
5. Moduli of geometries on the torus and hyperbolic geometry: Similar geometries. Similar geometries on the Torus. The modular figure. Poincaré upper plane model.Lines and distance. What was repugnant to Saccheri and that was not for Aristotle.

R. Trudeau: "La rivoluzione non Euclidea" Bollati Boringhieri
V, Nikulin, I. Shafarevich "Geometries and groups" Springer ed.

The subject integrates with exercises and insights the activities planned by the colleague owner of MC310, with whom the lessons will be coordinated.

John Stillwell, The Four Pillars of Geometry (Undergraduate Texts in Mathematics) 2005th Edition;
notes.

Introduction to cryptography. Classic ciphers. Introduction to cryptanalysis.
Introduction to public-key cryptography.
The RSA cryptosystem.
Primality tests.
Factorization algorithms.
Some attacks on the RSA.
The discrete logarithm problem. Diffie-Hellman key exchange.
Elgamal cryptosystem.
Massey-Omura cryptosystem.
Digital signatures.
Overview of some cryptographic protocols.

Baldoni, Ciliberto, Piacentini: Aritmetica, crittografia e codici
D. Stinson: Cryptography - theory and practice

1) Computability, complexity and representability:

- Introduction to decision problems, algorithmic and non-algorithmic procedures, deterministic computations, discrete procedures, the notion of alphabet, of speech. Decidability and semi-decidability of a set. Deterministic, finitary and discrete computations. Formal algorithms: formal definition of algorithm, configurations of input, output, transition function. Example of formalization of an algorithm. Decidability for finished automata. Representation of the automata by matrices. Free Monoid of words. Formal semi-rings. Non-deterministic finite automata. Regular Languages. Equivalence between deterministic and non-deterministic automata.

- Turing machines: definition, decidability for Turing machine, stopping time, stopping space. Cost of computation. Complexity: worst-case and average case. Independence of decision time from a finite number of input configurations. Complexity functions, complexity classes DTIME and DSPACE (deterministic time and space). Inclusion DTIME (T (n)) ⊂ DSPACE (T (n)) ⊂ DTIME (2 ^ {cT (n)}). Pumping Lemma. Simulation of algorithms, simulation of the half tape Turing machine, simulation of a multi-tape machine. Special Turing machines. Linear Speedup theorem for Turing machines with an extended alphabet. Evaluation of acceleration coefficient in relation to alphabets. Decisions of natural number sets. Independence from representation. Considerations concerning complexity.

- Turing computability: definition of Turing computable function, characteristic functions of Turing decidable sets, the class of Turing computable functions is closed by composition, concatenation, primitive recursion and minimization. Examples of Turing computable functions. Recursive Functions: equivalence between Turing computability and recursive functions. Ackermann function ([1] chapter 1,2,3,4,5 and [4] chapter 1).

- Time-constructible functions. The notion of T-clock. Examples of some time constructible function. Closure by composition.

- Non-deterministic Turing machines: characterization through the decidability of projection sets. Definition of the class of polynomial non-deterministic functions. NP-complete problems.

2) Lambda calculus and functional programming:

- Declarative programming: a historical outline on the lambda calculus, basic definitions, the terms of the lambda calculus, the simple substitution. Relations on the lambda terms. Congruences, transition to the context. α-equivalence. alpha-equivalence passes to the context. The transitive closure of a relationship, owned by Church-Rosser. Listing of lambda-terms concerning alpha-equivalence.

- Definition of beta-reduction and beta-equivalence. Church-Rosser's theorem for beta-reduction. Normal forms for beta-reduction. Beta-reduction strategies. Normalizing strategy: left reduction (left most-outer most). Head reduction. Soluble Terms. Head Normal Forms. Solvability characterization theorem.

- Representation of the recursive functions: lambda definability theorem. Existence of the fixed point for the lambda terms. Church Fixed Point and Curry fixed point.
- Representation of other data types in the lambda-calculus: pairs, lists, trees, the solution of recursive equations on lambda-terms ([2] chapters 1, 2, 5).

[1] DEHORNOY, P., COMPLEXITÈ ET DECIDABILITÈ. SPRINGER-VERLAG, (1993).
[2] KRIVINE, J.-L., LAMBDA CALCULUS: TYPES AND MODELS. ‪ELLIS HORWOOD, (1993).
[3] SIPSER,M., INTRODUCTION TO THE THEORY OF COMPUTATION.THOMSON COURSE TECHNOLOGY, (2006).

Affine Spaces
Zariski topology. Affine closed subsets and radical ideals. Theorem of the zeros of Hilbert. Correspondence between closed subsets and radical ideals. Noetherian topological spaces. Irreducible closed subsets, irreducible components. Regular functions of affine closed subsets. Regular maps, isomorphisms. Principal open subsets. Examples. Projections are open. Finite morphisms.

Varieties
Projective spaces and their Zariski topology. Quasi-projective varieties. Rational and regular maps. Projective hypersurfaces. Birational equivalence. Principal open subsets and affine closed subsets. Affine varieties. Dimension of quasi-projective varieties. Finite and generically finite morphisms. Characterizations of birational equivalence. Characterization of generically finite morphisms. Costructible sets, Chevalley's theorem. Every variety is birational to a hypersurface.

Local geometry
Local ring of a variety in a point. Zariski cotangent space. Zariski tangent space. Singular and non singular points.

L. Caporaso
Introduction to algebraic geometry
Notes of the course

I. Shafarevich
Basic Algebraic geometry
Springer-Verlag, Berlin, 1994

Field theory. Galois groups and Galois extensions. The Correspondence of Galois. Some applications of the Galois Correspondence: Constructions with ruler and compass, Solubility of polynomial equations.

S. Gabelli, Teoria delle Equazioni e Teoria di Galois. Springer Italia, (2008).

C. Procesi, Elementi di Teoria di Galois. Decibel, Zanichelli, (Seconda ristampa, 1991).
I. Stewart, Galois Theory. Chapman and Hall, (1989).

1. Abstract integration theory
Riemann integration theory. The concept of measurability. Step functions. Elementary properties of measures. Arithmetic in [0,∞]. Integration of positive functions. Integration of complex functions. Importance of sets
with null measure.
2. Positive Borel measures
Vector spaces. Topological preliminaries. Riesz representation theorem. Regularity properties of Borel measures. Lebesgue measure. Continuity properties of measurable functions.
3. L^p spaces
Inequalities and convex functions. L^p spaces. Approximation through continuous functions.
4. Basic theory of Hilbert spaces
Inner products and linear functionals. Dual space of L^2
5. Integration on product spaces
Measurability on cartesian products. Product measure. Fubini theorem.
6. Complex measures
Total variation. Absolute continuity. Radon-Nykodym theorem. Bounded linear functionals on L^p. The Riesz representation theorem.

"Analisi reale e complessa”, W. Rudin. Bollati Boringhieri.

1. Topological classification of curves and compact surfaces. Triangulations, Euler carachetristic.
2. Smooth and regular curves in Euclidean space. Immersions and imbeddings. Arc lenght. Curvature and the Fundamental Theorem of local geometry of plane curves.
3. Regular surfaces in R^3, local coordinates. Inverse image of a regular value. Maps and diffeomorphisms. Tangent plane and derivative of a map. Normal unit vector, orientation
and the Gauss map of a surface in R^3. Orientable surfaces, examples. The Moebius band is non-orientable.
4. Riemannian metric, examples. The shape operator is self-adjoint. Principal and asymptotic directions. The Mean and Gauss curvatures.
5. The geometry of the Gauss map. The sign of the Gauss curvature and position of the tangent plane. Theorems of Meusnieur and Olinde Rodrigues. Geometric properties of compact surfaces, Minimal surfaces and Ruled surfaces.
6. Isometries and local isometries. The Shape operator in isothermal coordinates. Proof of Gauss' Theorema Egregium. Examples, counter-examples and applications.
7. Homeworks.
8. 12 hours of lab for the visualization and computation on curves and surfaces.

Testi consigliati
[1] J.M. Lee, Introduction to topological manifolds. Springer, (2000). - – http://dx.doi.org/10.1007/b98853
[2] E. Sernesi, Geometria 2. Boringhieri, (1994).
[3] M. Do Carmo , Differential Geometry of Curves and Surfaces. Prentice Hall, (1976).

Linear Systems
Direst methods: Gaussian elimination. Pivoting strategies. Gaussian elimination as a factorization. Doolittle and Choleshy factorizations. Iterative methods: Jacobi, Gauss-Seidel, SOR, Richardson, and related convergence results. Comparison of direct vs iterative solvers. Stability of algorithms for the solution of linear systems.

Iterative Methods for Scalar Nonlinear Equations
The intermediate zero theorem. The algorithms of bisection, Newton, secants, chords, and related convergence results. (Reference: Chapter 1 excluding Section 1.2.3, and Appendices A.1, A.2)

Approximation of Functions
General approximation strategies. Interpolating polynomial in Lagrange and Newton form. Representation of the interpolation error. Convergence of the interpolating polynomial for analytic functions. Refinement strategies in interpolation: Chebyshev nodes, composite approximations. Error estimates. Hermite polynomial, construction and representation of the error. Least Squares approximations. (Reference: Chapter 5 excluding Section 5.2, and Appendix A.4)

Numerical Integration
General principles of numerical integration. Polya's Theorem on the convergence of interpolatory quadrature formulae. Closed and open Newton-Cotes formulae. Stability results and error estimation. Generalized Newton-Cotes formulae and their convergence. Gaussian quadratures and their convergence. (Reference: Chapter 6)

Laboratory Activity
C language coding of some of the major algorithms, and in particular: Gaussian elimination, iterative methods for linear systems and scalar equations, Lagrange/Newton interpolation with a refinement strategy.

N.B.: References are provided with respect to the course notes.

Roberto Ferretti, "Appunti del corso di Analisi Numerica", available at the address: http://www.mat.uniroma3.it/users/ferretti/corso.pdf

Roberto Ferretti, "Esercizi d'esame di Analisi Numerica", available at the address: http://www.mat.uniroma3.it/users/ferretti/Esercizi.pdf

Slides of the lessons, available from the course page: http://www.mat.uniroma3.it/users/ferretti/bacheca.html

Affine Spaces
Zariski topology. Affine closed subsets and radical ideals. Theorem of the zeros of Hilbert. Correspondence between closed subsets and radical ideals. Noetherian topological spaces. Irreducible closed subsets, irreducible components. Regular functions of affine closed subsets. Regular maps, isomorphisms. Principal open subsets. Examples. Projections are open. Finite morphisms.

Varieties
Projective spaces and their Zariski topology. Quasi-projective varieties. Rational and regular maps. Projective hypersurfaces. Birational equivalence. Principal open subsets and affine closed subsets. Affine varieties. Dimension of quasi-projective varieties. Finite and generically finite morphisms. Characterizations of birational equivalence. Characterization of generically finite morphisms. Costructible sets, Chevalley's theorem. Every variety is birational to a hypersurface.

Local geometry
Local ring of a variety in a point. Zariski cotangent space. Zariski tangent space. Singular and non singular points.

L. Caporaso
Introduction to algebraic geometry
Notes of the course

I. Shafarevich
Basic Algebraic geometry
Springer-Verlag, Berlin, 1994

Quantum mechanics: The crisis of classical physics. Waves and particles. State vectors and operators. Measurements and observables. The position operator. Translations and momentum. Time evolution and the schrodinger equation. Parity. One-dimensional problems. Harmonic oscillator. Symmetries and conservation laws. Time independent perturbation theory. Time dependent perturbation theory.

Lecture notes available on the course website

J.J. Sakurai, Jim Napolitano - Meccanica Quantistica Moderna - Seconda Edizione [Zanichelli, Bologna, 2014]
An english version of the book is also available:
Sakurai J.J., Modern Quantum Mechanics (Revised Edition) [Addison-Wesley, 1994]

1. ATOMIC THEORY AND ATOMIC STRUCTURE. Atoms, molecules, moles; atomic and molecular weight. Atomic models: Rutheford, Bohr. Quantum theory, quantum numbers and energy levels. Polyelectronic atoms; periodic system.
2. CHEMICAL BONDS. Ionic bond. Covalent bond: and bonds. Polyatomic molecules: molecular structure. Hybridization and resonance. Molecular orbital. Metallic bond. Intermolecular forces.
3. NOMENCLATURE AND CHEMICAL REACTIONS. Oxides, hydroxides, acids, salts, ions. Balancing chemical reactions: redox reactions.
4. STATES OF AGGREGATION. Gas state, ideal gas law. Solid state: ionic, covalent, molecular and metallic solids. Conductors, semiconductors, insulators. Liquid and amorphous states. Phase transitions and phase diagrams.
5. THERMODYNAMICS. Matter, energy, heat, first and second principles; enthalpy, entropy, free energy.
6. SOLUTIONS. Concentration, colligative properties; electrolyte solutions.
7. CHEMICAL KINETICS. Reaction speed, speed constant. Influence of the temperature on the reaction speed: Arrhenius equation. Catalysts.
8. CHEMICAL EQUILIBRIUM. Equilibrium constant and free energy. Gas-phase and heterogeneous equilibria. Le Chatelier’s principle. Van’t Hoff equation.
9. EQUILIBRIA IN SOLUTION. Acid-base equilibria: acids and bases, pH, dissociation constant, polyprotic acids, hydrolysis, buffers. Acid-base titrations and pH indicators. Solubility equilibria: solubility product, common ion effect.
10. ELECTROCHEMISTRY. Batteries, electrode potentials, Nernst’s equation. Electrolysis.
Numerical exercises on all the listed subjects.

P.W.Atkins, L. Jones; CHEMISTRY: MOLECULES, MATTER, AND CHANGE

Graphs: basic definitions. Simple and non simple graphs, planarity, connectivity, degree, regularity, incidence and adjacency matrices. Examples of families of graphs. The '' handshaking lemma ''.
Graphs obtained from others: complement, subgraph, cancellation and contraction. Isomorphisms and automorphisms of graphs. Connectivity: paths, cycles. A graph is bipartite if and only if each cycle has equal length.
Connetivity and connected component. Connectivity for sides and vertices. Eulerian and semi-Eulerian graphs.
Euler's theorem: a connected graph is Eulerian if and only if every vertex has an even degree. Hamiltonian graphs. Sufficient conditions to guarantee that a graph is Hamiltonian: the theorems of Ore and Dirac.
the Ore theorem. Trees and forests. The cyclomatic number and the "cutset" rank of a graph.
Fundamental system of cycles and cuts associated with a generating forest. Enumeration of generating forests. The Cayley theorem.
Generating trees: the "greedy" algorithm for the "connector problem". Planar graphs. K3.3 and K5 are not planar. Statement of the theorem of Kuratovski and variations.
Euler's formula for planar graphs. The dual of a planar graph.
Correspondence between cycles and cuts for planar graphs and their dual. Dual abstract. A graph that admits a dual abstract is planar. Colorings: initial considerations and some properties.
Colorings: the 5 colors theorem. Graphs on surfaces: classification of topological surfaces.
Coloring of faces and duality between this problem and the coloring of vertices. Reduction of the proof of the 4-color theorem to the coloring of cubic graph faces. '' The marriage problem ": Hall's theorem.
Hall's theorem in the language of transversals. Criteria of existence of transversal and partial transversivities. Application to the construction of Latin squares. Direct graphs: basic notions and orientability.
The Max-Flow Min-Cut theorem and Menger's theorem.
Complexity of algorithms and applications to the theory of graphs.
Introduction to the theory of matroids: definitions using bases and independent elements. Graphical and cographic matroids, vector matroids and the problem of representability.
Definition of matroid using the cycles and the rank function. Minors of a matroid. Transverse matroids and the Rado Theorem for matroids.
Union of matroids and applications: existence of disjoint bases in a matroid. Duality for matroids and applications to graphic and cographic matroids. Planar matroids and the generalization of Kuratovski's theorem for matroids.
Elements of algebraic graph theory: the incidence matrix and the Laplacian matrix of an oriented graph. The vertex space and the space of edges of a graph. Subspaces of the cycles and subspace of the cuts of a defined oriented graph of the incidence matrix.
Basis for the space of the cycles and for the space of the cuts of a graph. The Riemann-Roch theorem for graphs.
Proof of the "generalized Matrix Tree theorem". The contraction / restriction algorithm for matroids. Examples. The number of acyclical orientations of a graph.
Graph polynomials: the chromatic polynomial, the "reliabiliaty" polynomial. Examples. The polynomial rank of a matroid. Properties and first applications.
Proof of the structure theorem for functions on matroids that satisfy contraction/restriction properties. Their incarnation through the polynomial rank.
Whitey's moves and two isomorphisms for graphs. Isomorphism between graphical matroids implies isomorphism between graphs in case the graphs are 3 connected.
Whitney's Theorem for graphic matroids: sketch of the demonstration. Characterization for minors excluded from binary and regular matroids. The theorem of Seymour.

R. Diestel: Graph theory, Spriger GTM 173.
R. Wilson: Introduction to Graph theory, Prentice Hall.
B. Bollobas: Modern Graph theory, Springer GTM 184.
J. A. Bondy, U.S.R. Murty: Graph theory, Springer GTM 244.
N. Biggs: Algebraic graph theory, Cambridge University Press.
C. D. Godsil, G. Royle: Algebraic Graph theory, Springer GTM 207.
J. G. Oxley: Matroid theory. Oxford graduate texts in mathematics, 3.

The objective of Linguaggi di Programmazione course is to introduce main formal language theory concepts and results as well as their application for programming language classification.
Most relevant approaches for syntactic analysis of programming languages are introduced. Learning how to recognize the structure of a programming language and the implementation techniques for the abrstract machine.
Understanding the Object Oriented paradigm together with other non imperative approaches.

[1] Maurizio Gabbrielli, Simone Martini,Programming Languages - Principles and paradigms, 2/ed. McGraw-Hill, (2011).
[2] Dean Wampler, Alex Payne, Programming Scala: Scalability = Functional Programming + Objects, 2 edizione. O’Reilly Media, (2014).
[3] David Parsons, Foundational Java Key Elements and Practical Programming. Springer- Verlag, (2012).
Course Slides

Introduction to Systems Biology: What Computational Biology is about; the role of mathematical modelling and bioinformatics; what are the aims and the main problems; what are the theoretical tools used.

Introduction to Molecular and Cell Biology; basic knowledge of genetics, proteomics and cellular processes; ecology and evolution; outline of the availability of open access biological data.

Recall of probability theory: discrete and continuous random variables; distributions; entropy; inference; sampling; estimation of probability; the EM algorithm (Expectation Maximisation).

Recall of information theory: Shannon entropy and other measures of entropy; measures of diversity (Shannon-Wiener index, Simpson index).

Introduction to Stochastic Processes: random walks, Markov chains.

Introduction to Machine Learning and Pattern Recognition: supervised and unsupervised learning; Bayesian methods; non-parametric techniques; Neural Networks; stochastic methods; clustering; k-means.

Sequence analysis: alignment algorithms (e.g., BLAST); Hidden Markov Models (HMM); internet services available.

Recall of Graph Theory: notation; types of graphs; representation; algorithms on graphs; statistical properties of the networks; centrality measures; motifs; network clustering.
Biological Networks: networks of signal transduction; gene regulatory networks; protein-protein interaction networks; metabolic networks; internet services available.

Bio-mathematical models; predictions by theoretical models; continuous models; recall of numerical methods for solving systems of ordinary differential equations; discrete models; spin models (Ising models); Cellular Automata; Boolean networks; Agent-based models; data fitting and parameter estimation; available software.

• E.S. Allman, J.A. Rhodes. Mathematical Models in Biology: An Introduction (2004) Cambridge University Press.

• W.J. Ewens, G.R. Grant. Statistical Methods in Bioinformatics, An Introduction (2005) Springer Verlag.

• R. Durbin, S. Eddy, A. Krogh, G. Mitchison. Biological sequence analysis - Probabilistic models of proteins and nucleic acids (1998) Cambridge University Press.

• B.H. Junker, F. Schreiber (eds). Analysis of biological networks (2008) John Wiley & Sons.

• R.O. Duda, P.E. Hart, D.G. Stork. Pattern Classification (2001) John Wiley & Sons.

1.Euclidean Geometry; rudiments of history of Greek Mathematics. Ruler and compass constructions. The classical problems. Euclid's Elements.
2. The V Postulate's problem: Posidonius attempt. Equivalent Postulates: Playfair, Wallis, transitivity of parallelism. Saccheri's work. Saccheri's Quadrilaterals. The three hyposes. Saccheri-Lagrange's Theorem and the exclusion of obtuse angle hypothesis. The birth of Non-Euclidean Geometry in Bolyai and Lobatchewaki.
3. Symmetries of the plane: Isometries of the plane and their type. Characterization of an isometry by the image of three points not on a line, Chasles' Theorem. Discrete groups of isometries. Rosettes, Friezes and Wallpaper groups. The Theorem of addiction of the angles. Leonardo's Theorem and the classification of finite groups of isometries. Sketch of the classification of the Frieze groups. Crystallographic restriction's Theorem and the classification of wallpaper groups.
4. Gauss' Geometry; The geometry on the Sphere. Locally euclidean geometries. Uniformly discontinuous groups of isometries. The Torus, Mobius band, Klein bottle. Classification of uniforly discontinuous groups of isometries. Sketch of the proof of the Theorem of classification of locally euclidean geometries
5. Moduli of geometries on the torus and hyperbolic geometry: Similar geometries. Similar geometries on the Torus. The modular figure. Poincaré upper plane model.Lines and distance. What was repugnant to Saccheri and that was not for Aristotle.

R. Trudeau: "La rivoluzione non Euclidea" Bollati Boringhieri
V, Nikulin, I. Shafarevich "Geometries and groups" Springer ed.

Branching processes, introduction to Sigma-algebras, measure spaces and probability spaces. Contruction of Lebesgue measure. Pi-systems, Dynkin's lemma. Properties of measures, sup and inf limits of events, measurable functions and random variables. Borel-Cantelli lemmas. Law and distribution of a random variable. Concept of independence. Convergence in probability and almost sure convergence. Skorokhod's representation theorem. Kolmogorov's 0-1 law.
Integrals, their properties and related theorems. Expectation of random variables. Markov, Jensen and Hoelder's inequalities. L^p spaces. Weierstrass' Theorem. Product measures, Fubini's theorem and joint laws.
Conditional expectation and its properties. Martingales, predictable processes. Stopping times and stopped processes. Optional stopping theorem, applications to random walks. Theorems about convergence of martingales. Strong law of large numbers.
Doob's inequalities for martingales and sub-martingales, applications. Characteristic functions and inversion theorem. Fourier transform in L^1. Equivalence between convergence in distribution and convergence of characteristic functions. Central limit theorem.

D. Williams, Probability with martingales
R. Durrett, Probability: Theory and examples

1. Random walks and Markov Chains. Sequence of random variables, random walks, Markov chains in discrete and continuous time. Invariant measures, reversibility.
2. Classical examples. Random walks on graphs, Birth and death chains, exclusion process. Markov Chain Monte Carlo: Metropolis and Glauber dynamics for the Ising model, colorings and other interacting particle systems.
3. Convergence to equilibrium I. Variation distance and mixing time. Ergodic theorems and coupling techniques. Strong stationary times. The coupon collector problem and card shuffling.
4. Convergence to equilibrium II. Spectral gap and relaxation times. Cheeger inequality, conductance and canonical paths. Comparison method and spectral gap for the exclusion process. Logarithmic Sobolev inequality.
5. Other topics: Glauber dynamics for the Ising model, phase transition, cutoff phenomenon, perfect simulation.

D. Levine, Y. Peres, E. Wilmer, Markov chains and mixing times.. AMS bookstore, (2009).

The purpose of this course is to give a brief introduction to the Finite Elements Method (FEM), a gold standard for the numerical solution of PDEs systems. Oddly enough, the widespread use of the FEM is not accompanied by an adequate knowledge of the mathematical framework underlying the method.
This course, starting from the weak formulation of balance equations, will give an overview of the techniques used to reduce a differential problem into an algebraic one. During the course, some selected problems in mechanics and physics will be solved, covering the three main types of equations: elliptic, parabolic and hyperbolic.
The course will cover the following topics: - Applied Linear Algebra.
- Boundary Value Problems.
- Initial Value Problems
Moreover, the students will be introduced to the use COMSOL Multiphysics, a scientific software for numerical simulations based on the Finite Element Method.

1) Integral Form at a Glance,
note a cura del docente

2) When functions have no value(s): Delta functions and distributions
Steven G. Johnson, MIT course 18.303 notes, 2011

3) Understanding and Implementing the Finite Elements Method
Mark S. Gockenbach, SIAM, 2006 Cap. 1 Some model PDE’s
Cap. 2 The weak formo of a BVP Cap. 3 The Galerkin method
Cap. 4 Piecewise polynomials and the finite element method (sections 4.1, 4.2) Cap. 5 Convergence of the finite element method (sections 5.1 ~ 5.4)

Introduction to cryptography. Classic ciphers. Introduction to cryptanalysis.
Introduction to public-key cryptography.
The RSA cryptosystem.
Primality tests.
Factorization algorithms.
Some attacks on the RSA.
The discrete logarithm problem. Diffie-Hellman key exchange.
Elgamal cryptosystem.
Massey-Omura cryptosystem.
Digital signatures.
Overview of some cryptographic protocols.

Baldoni, Ciliberto, Piacentini: Aritmetica, crittografia e codici
D. Stinson: Cryptography - theory and practice

The environment of celestial bodies; the Solar System; the shape and size of the Earth; the main motions of the Earth (rotation and revolution); the long-term movements of the Earth; the Earth-Moon system.
Orientation; time and its measure; the representation of the earth's surface; the geographical coordinates (latitude and longitude), the reading of topographic maps.
The shapes of the relief and the modeling of the terrestrial relief; the marine hydrosphere, the continental hydrosphere, the cryosphere; the atmosphere; the climate.
The materials of the Earth: the minerals, the lithogenetic processes, the lithogenetic cycle.
The evolution of the Earth

Capire la Terra
J.P. Grotzinger, T-H Jordan
(Terza edizione italiana condotta sulla settima edizione americana)

Il Globo Terrestre e la sua evoluzione
E. L. Palmieri e M. Parotto
Sesta Edizione (2008)

Educational material distributed during the course

1) Computability, complexity and representability:

- Introduction to decision problems, algorithmic and non-algorithmic procedures, deterministic computations, discrete procedures, the notion of alphabet, of speech. Decidability and semi-decidability of a set. Deterministic, finitary and discrete computations. Formal algorithms: formal definition of algorithm, configurations of input, output, transition function. Example of formalization of an algorithm. Decidability for finished automata. Representation of the automata by matrices. Free Monoid of words. Formal semi-rings. Non-deterministic finite automata. Regular Languages. Equivalence between deterministic and non-deterministic automata.

- Turing machines: definition, decidability for Turing machine, stopping time, stopping space. Cost of computation. Complexity: worst-case and average case. Independence of decision time from a finite number of input configurations. Complexity functions, complexity classes DTIME and DSPACE (deterministic time and space). Inclusion DTIME (T (n)) ⊂ DSPACE (T (n)) ⊂ DTIME (2 ^ {cT (n)}). Pumping Lemma. Simulation of algorithms, simulation of the half tape Turing machine, simulation of a multi-tape machine. Special Turing machines. Linear Speedup theorem for Turing machines with an extended alphabet. Evaluation of acceleration coefficient in relation to alphabets. Decisions of natural number sets. Independence from representation. Considerations concerning complexity.

- Turing computability: definition of Turing computable function, characteristic functions of Turing decidable sets, the class of Turing computable functions is closed by composition, concatenation, primitive recursion and minimization. Examples of Turing computable functions. Recursive Functions: equivalence between Turing computability and recursive functions. Ackermann function ([1] chapter 1,2,3,4,5 and [4] chapter 1).

- Time-constructible functions. The notion of T-clock. Examples of some time constructible function. Closure by composition.

- Non-deterministic Turing machines: characterization through the decidability of projection sets. Definition of the class of polynomial non-deterministic functions. NP-complete problems.

2) Lambda calculus and functional programming:

- Declarative programming: a historical outline on the lambda calculus, basic definitions, the terms of the lambda calculus, the simple substitution. Relations on the lambda terms. Congruences, transition to the context. α-equivalence. alpha-equivalence passes to the context. The transitive closure of a relationship, owned by Church-Rosser. Listing of lambda-terms concerning alpha-equivalence.

- Definition of beta-reduction and beta-equivalence. Church-Rosser's theorem for beta-reduction. Normal forms for beta-reduction. Beta-reduction strategies. Normalizing strategy: left reduction (left most-outer most). Head reduction. Soluble Terms. Head Normal Forms. Solvability characterization theorem.

- Representation of the recursive functions: lambda definability theorem. Existence of the fixed point for the lambda terms. Church Fixed Point and Curry fixed point.
- Representation of other data types in the lambda-calculus: pairs, lists, trees, the solution of recursive equations on lambda-terms ([2] chapters 1, 2, 5).

[1] DEHORNOY, P., COMPLEXITÈ ET DECIDABILITÈ. SPRINGER-VERLAG, (1993).
[2] KRIVINE, J.-L., LAMBDA CALCULUS: TYPES AND MODELS. ‪ELLIS HORWOOD, (1993).
[3] SIPSER,M., INTRODUCTION TO THE THEORY OF COMPUTATION.THOMSON COURSE TECHNOLOGY, (2006).

1. Classic Cryptography

- Basic cryptosystems: encryption by substitution, by translation, by permutation, affine cryptosystem, by Vigenère, by Hill. Stream encryption (synchronous and asynchronous), Linear feedback shift registers (LFSR) on finite fields, Autokey cypher. Product cyphers. Basic cryptanalysis: classification of attacks; cryptoanalysis for affine cyphers, for substitution cypher (frequency analysis), for Vigenere cypher: Kasiski test, coincidence index; cryptoanalysis of Hill's cypher and LFSR: algebraic attacks, cube attack.

2. Application of Shannon theory to cryptography

- Security of cyphers: computational security, provable security, unconditional security. Basics of probability: discrete random variables, joint probability, conditional probability, independent random variables, Bayes' theorem. Random variables associated with cryptosystems. Perfect secrecy for encryption systems. Vernam cryptosystem. Entropy. Huffman codes. Spurious Keys and Unicity distance.

3. Block cyphers

- iterative encryption schemes; Substitution-Permutation Networks (SPN); Linear cryptanalysis for SPN: Piling-Up Lemma, linear approximation of S-boxes, linear attacks on S-boxes; Differential cryptanalysis for SPN; Feistel cyphers; DES: description and analysis; AES: description; Notes on finite fields: operations on finite fields, Euclid's generalized algorithm for the computation of the GCD and inverse; Operating modes for block cyphers.

4. Hash functions and codes for message authentication

- Hash functions and data integrity. Safe hash functions: resistance to the pre-image, resistance to the second pre-image, collision resistance. The random oracle model: ideal hash functions, properties of independence. Randomized algorithms, collision on the problem of the second pre-image, collision on the problem of the pre-image. Iterated hash functions; the construction of Merkle-Damgard. Safe Hash Algorithm (SHA-1). Authentication Codes (MAC): nested authentication codes (HMAC).

[1] Antoine Joux, Algorithmic Cryptanalysis, (2010) CRC Press.
[2] Douglas Stinson, Cryptography: Theory and Practice, 3rd edition, (2006) Chapman and Hall/CRC.
[3] Delfs H., Knebl H., Introduction to Cryptography, (2007) Springer Verlag.

Notes on graph theory: graph, directed graph, tree, free and rooted tree, connection, strong connection, acyclicality; isomorphisms between graphs, planarity, Kuratowski's theorem, Euler's formula; coloring of graphs, Eulerian paths, Hamiltonian circuits.
Review of algorithm theory and computational complexity: complexity classes, the class of NP, NP-complete, NP-hard problems. Problems of decision, search, enumeration and optimization; problems of nonlinear programming, convex programming, linear programming and integer linear programming; combinatorial optimization problems. Recalls on the elements of combinatorics.
Optimization problems on graphs: visit of graphs, verification of fundamental properties, connection, presence of cycles, strongly connected components, topological ordering of a graph. Minimum spanning tree (Prim and Kruskal algorithms). Paths of minimum cost (Dijkstra and Bellman-Ford algorithms, dynamic programming technique, Floyd-Warshall algorithm, computation of the transitive closure of a graph). Networks and calculation of the maximum flow on a network, maximum flow / minimum cut theorem, Ford-Fulkerson algorithm, Edmonds-Karp algorithm, preflow algorithms, "push-relabel" algorithms.
Partitioning problems of graphs, trees and paths into connected components, objective functions and algorithmic techniques.
Stable marriage problem, generalizations and applications of the problem, Gale and Shapley algorithm.
Huffman codes.
Programming laboratory for the implementation of algorithms in Python language and with the help of Mathematica software.

T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, "Introduction to algorithms"

Lecture notes and other teaching material in Italian provided by the teacher and made available on the course website (http://www.mat.uniroma3.it/users/liverani/IN440) and on the Microsoft Teams platform

Complex numbers; some complex maps; the Riemann sphere; fractional-linear transformations; they preserve the cross ratio and the set of circles and straight lines. The apollonius circles. Integral of a complex function along a curve; length of a curve; properties of the integral; indicator function; formal sum of curves. Cauchy's theorem on rectangles and on all curves; Caucgy's formula. Liouville's principle. The identity principle for holomorphic functions; removable singularities; almost uniform convergence and its properties. Morera's lemma; mean value theorem and maximum principle; harmonic functions locally are the real part of holomorphic functions. Hadamard's three circles theorem. Euler's product for the sine. Harmonic functions and the electric potential; mean value theorem for harmonic functions, maximum principle and uniqueness for the Dirichlet problem. Dirichlet's kernel; the functions with the mean value property are harmonic. Schwarz's reflection principle. Laurent series; residues and residue calculus. The argument principle and Rouche's theorem. Holomorphic maps are open; a variant of the argument principle and Lagrange's inversion formula; the almost uniform limit of univalent functions is either univalent or constant. Schwarz's lemma; automorphisms of the disc; hyperbolic metric on the disc and its geodesics; the automorphisms of the disc preserve the hyperbolic metric. Analytic extension and monodromy theorem; some examples of Riemann surfaces. The Riemann mapping theorem; Picard's small theorem.

W. Rudin, Real and complex Analysis.

J. B. Conway, Functions of one complex variable.

Ordinary Differential Equations
Finite difference approximation for ordinary differential equations: Euler's method. Consistency, stability, absolute stability. Second order Runge-Kutta methods.
Single step implicit methods: backward Euler and Crank-Nicolson methods. Convergence of single step methods. Multi-step methods: general structure, complexity, absolute stability. Stability and consistency of multi-step methods. Adams methods, BDF methods, Predictor-Corrector methods. (Reference: Chapter 7 of curse notes "Appunti del corso di Analisi Numerica")

Partial Differential Equations
Finite difference approximation for partial differential equations. Semi-discrete approximations and convergence. The Lax-Richtmeyer theorem. Transport equation: the method of characteristics. The "Upwind" (semi-discrete and fully-discrete) scheme, consistency and stability. Heat equation: Fourier approximation. Finite difference scheme, consistency and stability. Poisson equation: Fourier approximation. Finite difference scheme, convergence. (Reference: notes by R. LeVeque, "Finite Difference methods for differential equations", selected chapters 1, 2, 3, 12, 13)

Roberto Ferretti, "Appunti del corso di Analisi Numerica", in pdf at http://www.mat.uniroma3.it/users/ferretti/corso.pdf

Roberto Ferretti, "Esercizi d'esame di Analisi Numerica", in pdf at http://www.mat.uniroma3.it/users/ferretti/Esercizi.pdf

Lecture slides in pdf at http://www.mat.uniroma3.it/users/ferretti/bacheca.html

Additional notes given by the teacher

Fundamentals of the approximation of Ordinary Differential Equations systems. One-step methods of forward/backward Euler type and their convergence.
Convergence of numerical methods for time-dependent Partial Differential Equations, Lax-Richtmyer theorem.
Advection equation: analytical aspects. Representation formula via characteristics. Monotone methods for the advection equation: Upwind, Lax-Friedrichs.
Hyperbolic scalar conservation laws in one dimension: analytical aspects, basics on entropic solutions, Rankine-Hougoniot condition. Fundamentals on convergence theory for finite-volume approximations. Monotone finite-volume methods: Godunov, Lax-Friedrichs, Rusanov.
Linear and nonlinear hyperbolic systems: analytical aspects, characteristic decomposition. Central schemes for hyperbolic systems.
The Shallow Water Equations in one and two space dimensions. Central scheme approximation, basics on boundary conditions.
The heat equation: analytical aspects, domain of dependence, regularity. Explicit and implicit approximation in one and two space dimensions via centered second differences and Euler time discretization.
Modelling of incompressible fluids: the Navier-Stokes Equations. Approximate formulations (Euler, Stokes), derivation of the Shallow Water Equations. Finite difference numerical methods based on the Vorticity-Streamfunction formulation.

R. J. LeVeque, Finite Volume Methods for Hyperbolic Problems, Cambridge University Press

Additional material provided by the teacher.

Small bibliography of related texts:
O. Foster 'Lecture on Riemann Surfaces', (Editore Springer)
S. Lang 'Introduction to algebraic and abelian surfaces', (Editore Addison-Wesley)
R. Miranda 'Algebraic Curves and Riemann Surfaces' (Editore AMS)
G. Springer 'Introduction to Riemann Surfaces' (Editore AMS)

Physical quantities. Intensive and extensive physical quantities. Direct and indirect measurements.
Basic and derived quantities.
Units of measurement. Units of measurement systems. Change of units. Dimensions,
physical principle of homogeneity and dimensional analysis.
Measurement tools. Analogical and Digital Instruments.
Characteristics of the instruments: Range, Threshold, Resolution, Linearity and Sensitivity. Accuracy and Precision.
Uncertainty in measurements. Definition of measurement error. Random errors and
systematic errors. Concept of measurement uncertainty. Causes of uncertainties. Uncertainties of Type
A and Type B.
Graphical analysis of data. Usage of tables and graphs for representation and preliminary analysis
of data without the use of statistical tools. Linear, semi-logarithmic graphs,
Double-logarithmic. Histograms.
Propagation of uncertainties. Uncertainty in indirect measurements. Propagation
of uncertainties for independent quantities. Correlated random variables. Definition of
correlation coefficient. Propagation of uncertainties for correlated quantities.


Laboratory program
- Measurements of fundamental quantities: mass, length, time
- Determination of measurement uncertainty: sensitivity of the instrument,
- Standard deviation in repeated measurements, propagation of uncertainties
- Uncertainty on the average in repeated measurements and dependence on sample size
- Study of the pendulum: verification of the independence of the period from the mass, study of the dependence of the period on the length, measurement of g
- Study of the motion of a cart on the inclined plane, effect of friction, measurement of g
- Static and dynamic study of the elastic constant of a spring
- Measurement of resistances with voltamperometric method, study of a resistive voltage divider
- Study of diffraction, verification of Snell's law

notes distributed during the classes

Notes on graph theory: graph, directed graph, tree, free and rooted tree, connection, strong connection, acyclicality; isomorphisms between graphs, planarity, Kuratowski's theorem, Euler's formula; coloring of graphs, Eulerian paths, Hamiltonian circuits.
Review of algorithm theory and computational complexity: complexity classes, the class of NP, NP-complete, NP-hard problems. Problems of decision, search, enumeration and optimization; problems of nonlinear programming, convex programming, linear programming and integer linear programming; combinatorial optimization problems. Recalls on the elements of combinatorics.
Optimization problems on graphs: visit of graphs, verification of fundamental properties, connection, presence of cycles, strongly connected components, topological ordering of a graph. Minimum spanning tree (Prim and Kruskal algorithms). Paths of minimum cost (Dijkstra and Bellman-Ford algorithms, dynamic programming technique, Floyd-Warshall algorithm, computation of the transitive closure of a graph). Networks and calculation of the maximum flow on a network, maximum flow / minimum cut theorem, Ford-Fulkerson algorithm, Edmonds-Karp algorithm, preflow algorithms, "push-relabel" algorithms.
Partitioning problems of graphs, trees and paths into connected components, objective functions and algorithmic techniques.
Stable marriage problem, generalizations and applications of the problem, Gale and Shapley algorithm.
Huffman codes.
Programming laboratory for the implementation of algorithms in Python language and with the help of Mathematica software.

T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, "Introduction to algorithms"

Lecture notes and other teaching material in Italian provided by the teacher and made available on the course website (http://www.mat.uniroma3.it/users/liverani/IN440) and on the Microsoft Teams platform

Banach and Hilbert spaces, general properties, projections in Hilbert spaces, orthonormal systems.
Hahn-Banach theorem, analytic and geometric form, consequences.
First and second category spaces, Baire's Theorem, Banach-Steinhaus Theorem, open map and closed graph theorem, applications.
Weak topologies, closed and convex sets, Banach-Alaoglu theorem, separability and reflexivity.
Sobolev spaces in dimensione one, immersion theorems, Poincaré inequality, application to variational problems.
Spectral theory, Fredholm alternative, spectral theorem for compact and self-adjoint operators, application to variational problems.

H. Brezis - Analisi Funzionale - Liguori (1986)
H. Brezis - Functional Analysis, Sobolev Spaces and Partial Differential Equations - Springer (2010)
W. Rudin - Functional Analysis - McGraw-Hill (1991)

Classification of Partial differential equations and reduction to canonical form; Wave, Heat, Laplace equations; introduction to Schrodinger equation

A. N. Tikhonov, A. A. Samarskii - Equations of Mathematical Physics

the course touches on basic algebraic topics:
divisibility, Euclid's algorithm,
continuous fractions, Fibonacci numbers,
combinatorics, straightedge and compass construction, cardinality, lattices and Boole Algebras.

testi consigliati (non da acquistare)
Baldoni, Ciliberto, Piacentini: Aritmetica, crittografia e codici
Papick, Algebra Connections
Materiale e dispense online

CONTENTS OF THE LECTURES: the numbers in round brackets refer to the chapter and section of the textbook adopted.
Kinetic theory of gases. Boltzmann equation and H theorem. (1, Par.2.1,2.2,2.3,2.4)
Maxwell-Boltzmann distribution. (1, Par. 2.5)
Phase space and Liouville theorem. (1, Par. 3.1,3.2)
Gibbs ensembles. Micro canonical ensemble. Definition of entropy. (1, Par. 3.3,3.4)
The ideal gas in the micro canonical ensemble. (1, Par. 3.6)
The equipartition theorem. (1, Par. 3.5)
The canonical ensemble. (1, Par.4.1).
The partition function and the free energy. Fluctuations of energy in the canonical ensemble. (1 Par. 4.4)
The grand canonical ensemble. The grand potential. The ideal gas in the grand canonical ensemble. (1 Par. 4.3).
Fluctuations of the particle number. (1 Par. 4.4)
Classical theory of the linear response and fluctuation-dissipation theorem. (1, Par. 8.4).
Einstein and Langevin theories of the Brownian motion. (Par. 1 par. 11.1,11.2).
Johnson-Nyqvist theory of thermal noise. (1 Par. 11.3).
Quantum statistical mechanics and the density matrix. (1, Par. 6.2,6.3,6.4)
Fermi-Dirac and Bose-einstein quantum statistics. ( 1, Par. 7.1)
The Fermi gas. The Sommerfeld expansion and the electron specific heat. (1, Par. 7.2)
The Bose gas. The Bose-Einstein condensation. (1, Par. 7.3)
Quantum theory of black-body radiation. (1, Par. 7.5)

e-Learning Moodle Platform with Supplementary Material

Suggested textbook:
1) C. Di Castro and R. Raimondi, Statistical Mechanics and Applications in Condensed Matter, Cambridge University Press, 2015.

Further reading:
2) K. Huang, Meccanica Statistica, Zanichelli, 1997.
3) L. Peliti, Appunti di Meccanica Statistica, Bollati Boringhieri, 2003.
4) Joel L. Lebowitz, Statistical mechanics: A selective review of two central issues, Reviews of Modern Physics, 71, S346 (1999).

The materials of the Earth: minerals, the lithogenetic processes, the lithogenetic cycle, the magmatic rocks, the sedimentary rocks, the metamorphic rocks, the bedding and the deformation of the rocks.
Volcanic phenomena: magma and volcanic activity, the main types of eruptions, shape of volcanic buildings, products of volcanic activity, the geographic distribution of volcanoes, volcanoes and man (the volcanic risk).
Seismic phenomena: the theory of elastic rebound, the seismic cycle, types of seismic waves and their propagation and registration, the force of an earthquake (scales of intensity and magnitude), the geographic distribution of earthquakes, the seismic activity and the man (seismic risk)
Plate tectonics: the internal structure of the Earth, the structure of the crust, the Earth's magnetic field, Earth’s internal heat, the convective mantle, from the hypothesis of the drift of the continents to the formulation of the theory of plate tectonics.
The Earth as an integrated system: interaction between the different systems of the planet (biosphere, atmosphere, hydrosphere, lithosphere, cryosphere), the earth's atmosphere, climate and meteorological phenomena, renewable and non-renewable natural resources.
Field trip in Caffarella Valley
Field trip in the city of Rome

Capire la Terra
J.P. Grotzinger, T-H Jordan
(Terza edizione italiana condotta sulla settima edizione americana)

Il Globo Terrestre e la sua evoluzione
E. L. Palmieri e M. Parotto
Sesta Edizione (2008)

Educational material distributed during the course

The course is aimed at introducing students to the teaching of mathematics in 6th to 12th grades.
Contents include a historical, epistemological approach to the basic concepts in elementary mathematics (numbers, geometry, algebra, probability and functions); a discussion of the origins and present situations of mathematical education in compulsory education and secondary education; and examples regarding the mathematical biography of pupils from preschool, the mathematical anxiety and difficulties in understanding and appropriation of mathematical concepts and vision (intuition, error, deduction and argumentation, math draws, math conversation, meaning and the role of history), and the main elements of a good didactical approach in the classroom.

GIORGIO ISRAEL, ANA MILLÁN GASCA, Pensare in matematica, Zanichelli, 2012.
FEDERIGO ENRIQUES 1921, “Insegnamento dinamico”, Periodico di Matematiche, s. IV, 1, pp. 6-16.
http://www.mat.uniroma2.it/mep/Articoli/Enri/Enri.html
Further materials will be suggested during the course.

Module 1. From common knowledge to scientific knowledge. The indicators of scientific knowledge; the contribution of formal education to the image of science; scientific communication.
Module 2. Physics education, a research fieldOrigin and development of research in physics education in Italy; the constructivist paradigm; concepts and misconceptions; research on mental representations; conceptual change models; the conceptual nuclei of Physics.
Module 3. Scientific teaching in secondary school Design the curriculum of Physics in the different orders and in the various study addresses; the teaching / learning process; orientation teaching and laboratory teaching as a didactic methodological approach; from content to programming by skills; training orientation.
Module 4. The role of the "laboratory" in learning Physics Integration between theory and experimental verification; from observation of the phenomenon to the construction of the model; the different ways of "doing laboratory"; design of work units identifying the most appropriate experimental activities (demonstration; in the classroom with poor materials, in the instrumental laboratory, simulated through multimedia aids); implementation of laboratory operational skills for experiment management.
Module 5. Flexible and modular design of content / knowledge, teaching methodologies and learning environments Core foundations of Physics; analysis and planning of didactic courses that respond to verticality criteria (evolution of concepts coherent and appropriate to students' cognitive development) and transversality (integration of Physics with other disciplines); simulations of teaching methodologies such as: dialogue lesson, microteaching, co-planning, peer-to-peer evaluation, cooperative learning activities, group work.
Module 6. Learning evaluation of learning Modes and tools used in the various stages of monitoring, measurement, verification, evaluation and self-evaluation of learning; identification of learning contexts capable of developing and detecting skills; the National Evaluation System (SNV).
Module 7. Modern and Contemporary Physics The role of modern and contemporary Physics in school curricula: what content / paths to propose that guarantee students a real understanding of them. The new State Exam and the role of Physics in the second written test in scientific high schools. Instrumental laboratory. Five instrumental laboratories of three hours each in the months of March, April and May.

Students can take advantage of the following teaching material on the Platform of the Department of Mathematics and Physics: Power-pointrelative presentations to the contents of the lessons, research articles, work material (texts to be analyzed taken from textbooks, articles of scientific dissemination, original memories , “tutorial” cards, videos, applets, cards for group work, grids for assessing learning, web-sites).

ESSENTIAL BIBLIOGRAFY
Arons Arnold B. 1992, Guida all'insegnamento della fisica, Zanichelli•P. Guidoni, M. Arcà 2000 –Guardare per sistemi e guardare per variabili –l’educazione scientifica di base -AIF Editore•Vicentini M., Mayer M. (a cura di) (1999). Didattica della Fisica, Loescher Editore.•Grimellini Tomasini N., Segré G. (a cura di) (1991). Conoscenze scientifiche: le rappresentazioni mentali degli studenti, La Nuova Italia, Firenze.•La fisica secondo il PSSC, 25 film del Physical Science Study-Zanichelli•F. Bocci, Manuale per il laboratorio di fisica: introduzione all’analisi dei dati sperimentali -Zanichell

Complex numbers; some complex maps; the Riemann sphere; fractional-linear transformations; they preserve the cross ratio and the set of circles and straight lines. The apollonius circles. Integral of a complex function along a curve; length of a curve; properties of the integral; indicator function; formal sum of curves. Cauchy's theorem on rectangles and on all curves; Caucgy's formula. Liouville's principle. The identity principle for holomorphic functions; removable singularities; almost uniform convergence and its properties. Morera's lemma; mean value theorem and maximum principle; harmonic functions locally are the real part of holomorphic functions. Hadamard's three circles theorem. Euler's product for the sine. Harmonic functions and the electric potential; mean value theorem for harmonic functions, maximum principle and uniqueness for the Dirichlet problem. Dirichlet's kernel; the functions with the mean value property are harmonic. Schwarz's reflection principle. Laurent series; residues and residue calculus. The argument principle and Rouche's theorem. Holomorphic maps are open; a variant of the argument principle and Lagrange's inversion formula; the almost uniform limit of univalent functions is either univalent or constant. Schwarz's lemma; automorphisms of the disc; hyperbolic metric on the disc and its geodesics; the automorphisms of the disc preserve the hyperbolic metric. Analytic extension and monodromy theorem; some examples of Riemann surfaces. The Riemann mapping theorem; Picard's small theorem.

W. Rudin, Real and complex Analysis.

J. B. Conway, Functions of one complex variable.

The objective of Linguaggi di Programmazione course is to introduce main formal language theory concepts and results as well as their application for programming language classification.
Most relevant approaches for syntactic analysis of programming languages are introduced. Learning how to recognize the structure of a programming language and the implementation techniques for the abrstract machine.
Understanding the Object Oriented paradigm together with other non imperative approaches.

[1] Maurizio Gabbrielli, Simone Martini,Programming Languages - Principles and paradigms, 2/ed. McGraw-Hill, (2011).
[2] Dean Wampler, Alex Payne, Programming Scala: Scalability = Functional Programming + Objects, 2 edizione. O’Reilly Media, (2014).
[3] David Parsons, Foundational Java Key Elements and Practical Programming. Springer- Verlag, (2012).
Course Slides

Field theory. Galois groups and Galois extensions. The Correspondence of Galois. Some applications of the Galois Correspondence: Constructions with ruler and compass, Solubility of polynomial equations.

S. Gabelli, Teoria delle Equazioni e Teoria di Galois. Springer Italia, (2008).

C. Procesi, Elementi di Teoria di Galois. Decibel, Zanichelli, (Seconda ristampa, 1991).
I. Stewart, Galois Theory. Chapman and Hall, (1989).

1. Abstract integration theory
Riemann integration theory. The concept of measurability. Step functions. Elementary properties of measures. Arithmetic in [0,∞]. Integration of positive functions. Integration of complex functions. Importance of sets
with null measure.
2. Positive Borel measures
Vector spaces. Topological preliminaries. Riesz representation theorem. Regularity properties of Borel measures. Lebesgue measure. Continuity properties of measurable functions.
3. L^p spaces
Inequalities and convex functions. L^p spaces. Approximation through continuous functions.
4. Basic theory of Hilbert spaces
Inner products and linear functionals. Dual space of L^2
5. Integration on product spaces
Measurability on cartesian products. Product measure. Fubini theorem.
6. Complex measures
Total variation. Absolute continuity. Radon-Nykodym theorem. Bounded linear functionals on L^p. The Riesz representation theorem.

"Analisi reale e complessa”, W. Rudin. Bollati Boringhieri.

1. Topological classification of curves and compact surfaces. Triangulations, Euler carachetristic.
2. Smooth and regular curves in Euclidean space. Immersions and imbeddings. Arc lenght. Curvature and the Fundamental Theorem of local geometry of plane curves.
3. Regular surfaces in R^3, local coordinates. Inverse image of a regular value. Maps and diffeomorphisms. Tangent plane and derivative of a map. Normal unit vector, orientation
and the Gauss map of a surface in R^3. Orientable surfaces, examples. The Moebius band is non-orientable.
4. Riemannian metric, examples. The shape operator is self-adjoint. Principal and asymptotic directions. The Mean and Gauss curvatures.
5. The geometry of the Gauss map. The sign of the Gauss curvature and position of the tangent plane. Theorems of Meusnieur and Olinde Rodrigues. Geometric properties of compact surfaces, Minimal surfaces and Ruled surfaces.
6. Isometries and local isometries. The Shape operator in isothermal coordinates. Proof of Gauss' Theorema Egregium. Examples, counter-examples and applications.
7. Homeworks.
8. 12 hours of lab for the visualization and computation on curves and surfaces.

Testi consigliati
[1] J.M. Lee, Introduction to topological manifolds. Springer, (2000). - – http://dx.doi.org/10.1007/b98853
[2] E. Sernesi, Geometria 2. Boringhieri, (1994).
[3] M. Do Carmo , Differential Geometry of Curves and Surfaces. Prentice Hall, (1976).

1.Euclidean Geometry; rudiments of history of Greek Mathematics. Ruler and compass constructions. The classical problems. Euclid's Elements.
2. The V Postulate's problem: Posidonius attempt. Equivalent Postulates: Playfair, Wallis, transitivity of parallelism. Saccheri's work. Saccheri's Quadrilaterals. The three hyposes. Saccheri-Lagrange's Theorem and the exclusion of obtuse angle hypothesis. The birth of Non-Euclidean Geometry in Bolyai and Lobatchewaki.
3. Symmetries of the plane: Isometries of the plane and their type. Characterization of an isometry by the image of three points not on a line, Chasles' Theorem. Discrete groups of isometries. Rosettes, Friezes and Wallpaper groups. The Theorem of addiction of the angles. Leonardo's Theorem and the classification of finite groups of isometries. Sketch of the classification of the Frieze groups. Crystallographic restriction's Theorem and the classification of wallpaper groups.
4. Gauss' Geometry; The geometry on the Sphere. Locally euclidean geometries. Uniformly discontinuous groups of isometries. The Torus, Mobius band, Klein bottle. Classification of uniforly discontinuous groups of isometries. Sketch of the proof of the Theorem of classification of locally euclidean geometries
5. Moduli of geometries on the torus and hyperbolic geometry: Similar geometries. Similar geometries on the Torus. The modular figure. Poincaré upper plane model.Lines and distance. What was repugnant to Saccheri and that was not for Aristotle.

R. Trudeau: "La rivoluzione non Euclidea" Bollati Boringhieri
V, Nikulin, I. Shafarevich "Geometries and groups" Springer ed.

Introduction to cryptography. Classic ciphers. Introduction to cryptanalysis.
Introduction to public-key cryptography.
The RSA cryptosystem.
Primality tests.
Factorization algorithms.
Some attacks on the RSA.
The discrete logarithm problem. Diffie-Hellman key exchange.
Elgamal cryptosystem.
Massey-Omura cryptosystem.
Digital signatures.
Overview of some cryptographic protocols.

Baldoni, Ciliberto, Piacentini: Aritmetica, crittografia e codici
D. Stinson: Cryptography - theory and practice

1) Computability, complexity and representability:

- Introduction to decision problems, algorithmic and non-algorithmic procedures, deterministic computations, discrete procedures, the notion of alphabet, of speech. Decidability and semi-decidability of a set. Deterministic, finitary and discrete computations. Formal algorithms: formal definition of algorithm, configurations of input, output, transition function. Example of formalization of an algorithm. Decidability for finished automata. Representation of the automata by matrices. Free Monoid of words. Formal semi-rings. Non-deterministic finite automata. Regular Languages. Equivalence between deterministic and non-deterministic automata.

- Turing machines: definition, decidability for Turing machine, stopping time, stopping space. Cost of computation. Complexity: worst-case and average case. Independence of decision time from a finite number of input configurations. Complexity functions, complexity classes DTIME and DSPACE (deterministic time and space). Inclusion DTIME (T (n)) ⊂ DSPACE (T (n)) ⊂ DTIME (2 ^ {cT (n)}). Pumping Lemma. Simulation of algorithms, simulation of the half tape Turing machine, simulation of a multi-tape machine. Special Turing machines. Linear Speedup theorem for Turing machines with an extended alphabet. Evaluation of acceleration coefficient in relation to alphabets. Decisions of natural number sets. Independence from representation. Considerations concerning complexity.

- Turing computability: definition of Turing computable function, characteristic functions of Turing decidable sets, the class of Turing computable functions is closed by composition, concatenation, primitive recursion and minimization. Examples of Turing computable functions. Recursive Functions: equivalence between Turing computability and recursive functions. Ackermann function ([1] chapter 1,2,3,4,5 and [4] chapter 1).

- Time-constructible functions. The notion of T-clock. Examples of some time constructible function. Closure by composition.

- Non-deterministic Turing machines: characterization through the decidability of projection sets. Definition of the class of polynomial non-deterministic functions. NP-complete problems.

2) Lambda calculus and functional programming:

- Declarative programming: a historical outline on the lambda calculus, basic definitions, the terms of the lambda calculus, the simple substitution. Relations on the lambda terms. Congruences, transition to the context. α-equivalence. alpha-equivalence passes to the context. The transitive closure of a relationship, owned by Church-Rosser. Listing of lambda-terms concerning alpha-equivalence.

- Definition of beta-reduction and beta-equivalence. Church-Rosser's theorem for beta-reduction. Normal forms for beta-reduction. Beta-reduction strategies. Normalizing strategy: left reduction (left most-outer most). Head reduction. Soluble Terms. Head Normal Forms. Solvability characterization theorem.

- Representation of the recursive functions: lambda definability theorem. Existence of the fixed point for the lambda terms. Church Fixed Point and Curry fixed point.
- Representation of other data types in the lambda-calculus: pairs, lists, trees, the solution of recursive equations on lambda-terms ([2] chapters 1, 2, 5).

[1] DEHORNOY, P., COMPLEXITÈ ET DECIDABILITÈ. SPRINGER-VERLAG, (1993).
[2] KRIVINE, J.-L., LAMBDA CALCULUS: TYPES AND MODELS. ‪ELLIS HORWOOD, (1993).
[3] SIPSER,M., INTRODUCTION TO THE THEORY OF COMPUTATION.THOMSON COURSE TECHNOLOGY, (2006).

Affine Spaces
Zariski topology. Affine closed subsets and radical ideals. Theorem of the zeros of Hilbert. Correspondence between closed subsets and radical ideals. Noetherian topological spaces. Irreducible closed subsets, irreducible components. Regular functions of affine closed subsets. Regular maps, isomorphisms. Principal open subsets. Examples. Projections are open. Finite morphisms.

Varieties
Projective spaces and their Zariski topology. Quasi-projective varieties. Rational and regular maps. Projective hypersurfaces. Birational equivalence. Principal open subsets and affine closed subsets. Affine varieties. Dimension of quasi-projective varieties. Finite and generically finite morphisms. Characterizations of birational equivalence. Characterization of generically finite morphisms. Costructible sets, Chevalley's theorem. Every variety is birational to a hypersurface.

Local geometry
Local ring of a variety in a point. Zariski cotangent space. Zariski tangent space. Singular and non singular points.

L. Caporaso
Introduction to algebraic geometry
Notes of the course

I. Shafarevich
Basic Algebraic geometry
Springer-Verlag, Berlin, 1994

Linear Systems
Direct methods: Gaussian elimination. Pivoting strategies. Gaussian elimination as a factorization. Doolittle and Choleshy factorizations. Iterative methods: Jacobi, Gauss-Seidel, SOR, Richardson, and related convergence results. Comparison of direct vs iterative solvers. Stability of algorithms for the solution of linear systems.

Iterative Methods for Scalar Nonlinear Equations
The intermediate zero theorem. The algorithms of bisection, Newton, secants, chords, and related convergence results. (Reference: Chapter 1 excluding Section 1.2.3, and Appendices A.1, A.2)

Approximation of Functions
General approximation strategies. Interpolating polynomial in Lagrange and Newton form. Representation of the interpolation error. Convergence of the interpolating polynomial for analytic functions. Refinement strategies in interpolation: Chebyshev nodes, composite approximations. Error estimates. Hermite polynomial, construction and representation of the error. Least Squares approximations. (Reference: Chapter 5 excluding Section 5.2, and Appendix A.4)

Numerical Integration
General principles of numerical integration. Polya's Theorem on the convergence of interpolatory quadrature formulae. Closed and open Newton-Cotes formulae. Stability results and error estimation. Generalized Newton-Cotes formulae and their convergence. Gaussian quadratures and their convergence. (Reference: Chapter 6)

Laboratory Activity
C language coding of some of the major algorithms, and in particular: Gaussian elimination, iterative methods for linear systems and scalar equations, Lagrange/Newton interpolation with a refinement strategy.

N.B.: References are provided with respect to the course notes.

Roberto Ferretti, "Appunti del corso di Analisi Numerica", available at the address: http://www.mat.uniroma3.it/users/ferretti/corso.pdf

Roberto Ferretti, "Esercizi d'esame di Analisi Numerica", available at the address: http://www.mat.uniroma3.it/users/ferretti/Esercizi.pdf

Slides of the lessons, available from the course page: http://www.mat.uniroma3.it/users/ferretti/bacheca.html

Field theory. Galois groups and Galois extensions. The Correspondence of Galois. Some applications of the Galois Correspondence: Constructions with ruler and compass, Solubility of polynomial equations.

S. Gabelli, Teoria delle Equazioni e Teoria di Galois. Springer Italia, (2008).

C. Procesi, Elementi di Teoria di Galois. Decibel, Zanichelli, (Seconda ristampa, 1991).
I. Stewart, Galois Theory. Chapman and Hall, (1989).

1. Abstract integration theory
Riemann integration theory. The concept of measurability. Step functions. Elementary properties of measures. Arithmetic in [0,∞]. Integration of positive functions. Integration of complex functions. Importance of sets
with null measure.
2. Positive Borel measures
Vector spaces. Topological preliminaries. Riesz representation theorem. Regularity properties of Borel measures. Lebesgue measure. Continuity properties of measurable functions.
3. L^p spaces
Inequalities and convex functions. L^p spaces. Approximation through continuous functions.
4. Basic theory of Hilbert spaces
Inner products and linear functionals. Dual space of L^2
5. Integration on product spaces
Measurability on cartesian products. Product measure. Fubini theorem.
6. Complex measures
Total variation. Absolute continuity. Radon-Nykodym theorem. Bounded linear functionals on L^p. The Riesz representation theorem.

"Analisi reale e complessa”, W. Rudin. Bollati Boringhieri.

1. Topological classification of curves and compact surfaces. Triangulations, Euler carachetristic.
2. Smooth and regular curves in Euclidean space. Immersions and imbeddings. Arc lenght. Curvature and the Fundamental Theorem of local geometry of plane curves.
3. Regular surfaces in R^3, local coordinates. Inverse image of a regular value. Maps and diffeomorphisms. Tangent plane and derivative of a map. Normal unit vector, orientation
and the Gauss map of a surface in R^3. Orientable surfaces, examples. The Moebius band is non-orientable.
4. Riemannian metric, examples. The shape operator is self-adjoint. Principal and asymptotic directions. The Mean and Gauss curvatures.
5. The geometry of the Gauss map. The sign of the Gauss curvature and position of the tangent plane. Theorems of Meusnieur and Olinde Rodrigues. Geometric properties of compact surfaces, Minimal surfaces and Ruled surfaces.
6. Isometries and local isometries. The Shape operator in isothermal coordinates. Proof of Gauss' Theorema Egregium. Examples, counter-examples and applications.
7. Homeworks.
8. 12 hours of lab for the visualization and computation on curves and surfaces.

Testi consigliati
[1] J.M. Lee, Introduction to topological manifolds. Springer, (2000). - – http://dx.doi.org/10.1007/b98853
[2] E. Sernesi, Geometria 2. Boringhieri, (1994).
[3] M. Do Carmo , Differential Geometry of Curves and Surfaces. Prentice Hall, (1976).

Linear Systems
Direst methods: Gaussian elimination. Pivoting strategies. Gaussian elimination as a factorization. Doolittle and Choleshy factorizations. Iterative methods: Jacobi, Gauss-Seidel, SOR, Richardson, and related convergence results. Comparison of direct vs iterative solvers. Stability of algorithms for the solution of linear systems.

Iterative Methods for Scalar Nonlinear Equations
The intermediate zero theorem. The algorithms of bisection, Newton, secants, chords, and related convergence results. (Reference: Chapter 1 excluding Section 1.2.3, and Appendices A.1, A.2)

Approximation of Functions
General approximation strategies. Interpolating polynomial in Lagrange and Newton form. Representation of the interpolation error. Convergence of the interpolating polynomial for analytic functions. Refinement strategies in interpolation: Chebyshev nodes, composite approximations. Error estimates. Hermite polynomial, construction and representation of the error. Least Squares approximations. (Reference: Chapter 5 excluding Section 5.2, and Appendix A.4)

Numerical Integration
General principles of numerical integration. Polya's Theorem on the convergence of interpolatory quadrature formulae. Closed and open Newton-Cotes formulae. Stability results and error estimation. Generalized Newton-Cotes formulae and their convergence. Gaussian quadratures and their convergence. (Reference: Chapter 6)

Laboratory Activity
C language coding of some of the major algorithms, and in particular: Gaussian elimination, iterative methods for linear systems and scalar equations, Lagrange/Newton interpolation with a refinement strategy.

N.B.: References are provided with respect to the course notes.

Roberto Ferretti, "Appunti del corso di Analisi Numerica", available at the address: http://www.mat.uniroma3.it/users/ferretti/corso.pdf

Roberto Ferretti, "Esercizi d'esame di Analisi Numerica", available at the address: http://www.mat.uniroma3.it/users/ferretti/Esercizi.pdf

Slides of the lessons, available from the course page: http://www.mat.uniroma3.it/users/ferretti/bacheca.html

Affine Spaces
Zariski topology. Affine closed subsets and radical ideals. Theorem of the zeros of Hilbert. Correspondence between closed subsets and radical ideals. Noetherian topological spaces. Irreducible closed subsets, irreducible components. Regular functions of affine closed subsets. Regular maps, isomorphisms. Principal open subsets. Examples. Projections are open. Finite morphisms.

Varieties
Projective spaces and their Zariski topology. Quasi-projective varieties. Rational and regular maps. Projective hypersurfaces. Birational equivalence. Principal open subsets and affine closed subsets. Affine varieties. Dimension of quasi-projective varieties. Finite and generically finite morphisms. Characterizations of birational equivalence. Characterization of generically finite morphisms. Costructible sets, Chevalley's theorem. Every variety is birational to a hypersurface.

Local geometry
Local ring of a variety in a point. Zariski cotangent space. Zariski tangent space. Singular and non singular points.

L. Caporaso
Introduction to algebraic geometry
Notes of the course

I. Shafarevich
Basic Algebraic geometry
Springer-Verlag, Berlin, 1994

Quantum mechanics: The crisis of classical physics. Waves and particles. State vectors and operators. Measurements and observables. The position operator. Translations and momentum. Time evolution and the schrodinger equation. Parity. One-dimensional problems. Harmonic oscillator. Symmetries and conservation laws. Time independent perturbation theory. Time dependent perturbation theory.

Lecture notes available on the course website

J.J. Sakurai, Jim Napolitano - Meccanica Quantistica Moderna - Seconda Edizione [Zanichelli, Bologna, 2014]
An english version of the book is also available:
Sakurai J.J., Modern Quantum Mechanics (Revised Edition) [Addison-Wesley, 1994]

1. ATOMIC THEORY AND ATOMIC STRUCTURE. Atoms, molecules, moles; atomic and molecular weight. Atomic models: Rutheford, Bohr. Quantum theory, quantum numbers and energy levels. Polyelectronic atoms; periodic system.
2. CHEMICAL BONDS. Ionic bond. Covalent bond: and bonds. Polyatomic molecules: molecular structure. Hybridization and resonance. Molecular orbital. Metallic bond. Intermolecular forces.
3. NOMENCLATURE AND CHEMICAL REACTIONS. Oxides, hydroxides, acids, salts, ions. Balancing chemical reactions: redox reactions.
4. STATES OF AGGREGATION. Gas state, ideal gas law. Solid state: ionic, covalent, molecular and metallic solids. Conductors, semiconductors, insulators. Liquid and amorphous states. Phase transitions and phase diagrams.
5. THERMODYNAMICS. Matter, energy, heat, first and second principles; enthalpy, entropy, free energy.
6. SOLUTIONS. Concentration, colligative properties; electrolyte solutions.
7. CHEMICAL KINETICS. Reaction speed, speed constant. Influence of the temperature on the reaction speed: Arrhenius equation. Catalysts.
8. CHEMICAL EQUILIBRIUM. Equilibrium constant and free energy. Gas-phase and heterogeneous equilibria. Le Chatelier’s principle. Van’t Hoff equation.
9. EQUILIBRIA IN SOLUTION. Acid-base equilibria: acids and bases, pH, dissociation constant, polyprotic acids, hydrolysis, buffers. Acid-base titrations and pH indicators. Solubility equilibria: solubility product, common ion effect.
10. ELECTROCHEMISTRY. Batteries, electrode potentials, Nernst’s equation. Electrolysis.
Numerical exercises on all the listed subjects.

P.W.Atkins, L. Jones; CHEMISTRY: MOLECULES, MATTER, AND CHANGE

Graphs: basic definitions. Simple and non simple graphs, planarity, connectivity, degree, regularity, incidence and adjacency matrices. Examples of families of graphs. The '' handshaking lemma ''.
Graphs obtained from others: complement, subgraph, cancellation and contraction. Isomorphisms and automorphisms of graphs. Connectivity: paths, cycles. A graph is bipartite if and only if each cycle has equal length.
Connetivity and connected component. Connectivity for sides and vertices. Eulerian and semi-Eulerian graphs.
Euler's theorem: a connected graph is Eulerian if and only if every vertex has an even degree. Hamiltonian graphs. Sufficient conditions to guarantee that a graph is Hamiltonian: the theorems of Ore and Dirac.
the Ore theorem. Trees and forests. The cyclomatic number and the "cutset" rank of a graph.
Fundamental system of cycles and cuts associated with a generating forest. Enumeration of generating forests. The Cayley theorem.
Generating trees: the "greedy" algorithm for the "connector problem". Planar graphs. K3.3 and K5 are not planar. Statement of the theorem of Kuratovski and variations.
Euler's formula for planar graphs. The dual of a planar graph.
Correspondence between cycles and cuts for planar graphs and their dual. Dual abstract. A graph that admits a dual abstract is planar. Colorings: initial considerations and some properties.
Colorings: the 5 colors theorem. Graphs on surfaces: classification of topological surfaces.
Coloring of faces and duality between this problem and the coloring of vertices. Reduction of the proof of the 4-color theorem to the coloring of cubic graph faces. '' The marriage problem ": Hall's theorem.
Hall's theorem in the language of transversals. Criteria of existence of transversal and partial transversivities. Application to the construction of Latin squares. Direct graphs: basic notions and orientability.
The Max-Flow Min-Cut theorem and Menger's theorem.
Complexity of algorithms and applications to the theory of graphs.
Introduction to the theory of matroids: definitions using bases and independent elements. Graphical and cographic matroids, vector matroids and the problem of representability.
Definition of matroid using the cycles and the rank function. Minors of a matroid. Transverse matroids and the Rado Theorem for matroids.
Union of matroids and applications: existence of disjoint bases in a matroid. Duality for matroids and applications to graphic and cographic matroids. Planar matroids and the generalization of Kuratovski's theorem for matroids.
Elements of algebraic graph theory: the incidence matrix and the Laplacian matrix of an oriented graph. The vertex space and the space of edges of a graph. Subspaces of the cycles and subspace of the cuts of a defined oriented graph of the incidence matrix.
Basis for the space of the cycles and for the space of the cuts of a graph. The Riemann-Roch theorem for graphs.
Proof of the "generalized Matrix Tree theorem". The contraction / restriction algorithm for matroids. Examples. The number of acyclical orientations of a graph.
Graph polynomials: the chromatic polynomial, the "reliabiliaty" polynomial. Examples. The polynomial rank of a matroid. Properties and first applications.
Proof of the structure theorem for functions on matroids that satisfy contraction/restriction properties. Their incarnation through the polynomial rank.
Whitey's moves and two isomorphisms for graphs. Isomorphism between graphical matroids implies isomorphism between graphs in case the graphs are 3 connected.
Whitney's Theorem for graphic matroids: sketch of the demonstration. Characterization for minors excluded from binary and regular matroids. The theorem of Seymour.

R. Diestel: Graph theory, Spriger GTM 173.
R. Wilson: Introduction to Graph theory, Prentice Hall.
B. Bollobas: Modern Graph theory, Springer GTM 184.
J. A. Bondy, U.S.R. Murty: Graph theory, Springer GTM 244.
N. Biggs: Algebraic graph theory, Cambridge University Press.
C. D. Godsil, G. Royle: Algebraic Graph theory, Springer GTM 207.
J. G. Oxley: Matroid theory. Oxford graduate texts in mathematics, 3.

The objective of Linguaggi di Programmazione course is to introduce main formal language theory concepts and results as well as their application for programming language classification.
Most relevant approaches for syntactic analysis of programming languages are introduced. Learning how to recognize the structure of a programming language and the implementation techniques for the abrstract machine.
Understanding the Object Oriented paradigm together with other non imperative approaches.

[1] Maurizio Gabbrielli, Simone Martini,Programming Languages - Principles and paradigms, 2/ed. McGraw-Hill, (2011).
[2] Dean Wampler, Alex Payne, Programming Scala: Scalability = Functional Programming + Objects, 2 edizione. O’Reilly Media, (2014).
[3] David Parsons, Foundational Java Key Elements and Practical Programming. Springer- Verlag, (2012).
Course Slides

Introduction to Systems Biology: What Computational Biology is about; the role of mathematical modelling and bioinformatics; what are the aims and the main problems; what are the theoretical tools used.

Introduction to Molecular and Cell Biology; basic knowledge of genetics, proteomics and cellular processes; ecology and evolution; outline of the availability of open access biological data.

Recall of probability theory: discrete and continuous random variables; distributions; entropy; inference; sampling; estimation of probability; the EM algorithm (Expectation Maximisation).

Recall of information theory: Shannon entropy and other measures of entropy; measures of diversity (Shannon-Wiener index, Simpson index).

Introduction to Stochastic Processes: random walks, Markov chains.

Introduction to Machine Learning and Pattern Recognition: supervised and unsupervised learning; Bayesian methods; non-parametric techniques; Neural Networks; stochastic methods; clustering; k-means.

Sequence analysis: alignment algorithms (e.g., BLAST); Hidden Markov Models (HMM); internet services available.

Recall of Graph Theory: notation; types of graphs; representation; algorithms on graphs; statistical properties of the networks; centrality measures; motifs; network clustering.
Biological Networks: networks of signal transduction; gene regulatory networks; protein-protein interaction networks; metabolic networks; internet services available.

Bio-mathematical models; predictions by theoretical models; continuous models; recall of numerical methods for solving systems of ordinary differential equations; discrete models; spin models (Ising models); Cellular Automata; Boolean networks; Agent-based models; data fitting and parameter estimation; available software.

• E.S. Allman, J.A. Rhodes. Mathematical Models in Biology: An Introduction (2004) Cambridge University Press.

• W.J. Ewens, G.R. Grant. Statistical Methods in Bioinformatics, An Introduction (2005) Springer Verlag.

• R. Durbin, S. Eddy, A. Krogh, G. Mitchison. Biological sequence analysis - Probabilistic models of proteins and nucleic acids (1998) Cambridge University Press.

• B.H. Junker, F. Schreiber (eds). Analysis of biological networks (2008) John Wiley & Sons.

• R.O. Duda, P.E. Hart, D.G. Stork. Pattern Classification (2001) John Wiley & Sons.

1.Euclidean Geometry; rudiments of history of Greek Mathematics. Ruler and compass constructions. The classical problems. Euclid's Elements.
2. The V Postulate's problem: Posidonius attempt. Equivalent Postulates: Playfair, Wallis, transitivity of parallelism. Saccheri's work. Saccheri's Quadrilaterals. The three hyposes. Saccheri-Lagrange's Theorem and the exclusion of obtuse angle hypothesis. The birth of Non-Euclidean Geometry in Bolyai and Lobatchewaki.
3. Symmetries of the plane: Isometries of the plane and their type. Characterization of an isometry by the image of three points not on a line, Chasles' Theorem. Discrete groups of isometries. Rosettes, Friezes and Wallpaper groups. The Theorem of addiction of the angles. Leonardo's Theorem and the classification of finite groups of isometries. Sketch of the classification of the Frieze groups. Crystallographic restriction's Theorem and the classification of wallpaper groups.
4. Gauss' Geometry; The geometry on the Sphere. Locally euclidean geometries. Uniformly discontinuous groups of isometries. The Torus, Mobius band, Klein bottle. Classification of uniforly discontinuous groups of isometries. Sketch of the proof of the Theorem of classification of locally euclidean geometries
5. Moduli of geometries on the torus and hyperbolic geometry: Similar geometries. Similar geometries on the Torus. The modular figure. Poincaré upper plane model.Lines and distance. What was repugnant to Saccheri and that was not for Aristotle.

R. Trudeau: "La rivoluzione non Euclidea" Bollati Boringhieri
V, Nikulin, I. Shafarevich "Geometries and groups" Springer ed.

Branching processes, introduction to Sigma-algebras, measure spaces and probability spaces. Contruction of Lebesgue measure. Pi-systems, Dynkin's lemma. Properties of measures, sup and inf limits of events, measurable functions and random variables. Borel-Cantelli lemmas. Law and distribution of a random variable. Concept of independence. Convergence in probability and almost sure convergence. Skorokhod's representation theorem. Kolmogorov's 0-1 law.
Integrals, their properties and related theorems. Expectation of random variables. Markov, Jensen and Hoelder's inequalities. L^p spaces. Weierstrass' Theorem. Product measures, Fubini's theorem and joint laws.
Conditional expectation and its properties. Martingales, predictable processes. Stopping times and stopped processes. Optional stopping theorem, applications to random walks. Theorems about convergence of martingales. Strong law of large numbers.
Doob's inequalities for martingales and sub-martingales, applications. Characteristic functions and inversion theorem. Fourier transform in L^1. Equivalence between convergence in distribution and convergence of characteristic functions. Central limit theorem.

D. Williams, Probability with martingales
R. Durrett, Probability: Theory and examples

1. Random walks and Markov Chains. Sequence of random variables, random walks, Markov chains in discrete and continuous time. Invariant measures, reversibility.
2. Classical examples. Random walks on graphs, Birth and death chains, exclusion process. Markov Chain Monte Carlo: Metropolis and Glauber dynamics for the Ising model, colorings and other interacting particle systems.
3. Convergence to equilibrium I. Variation distance and mixing time. Ergodic theorems and coupling techniques. Strong stationary times. The coupon collector problem and card shuffling.
4. Convergence to equilibrium II. Spectral gap and relaxation times. Cheeger inequality, conductance and canonical paths. Comparison method and spectral gap for the exclusion process. Logarithmic Sobolev inequality.
5. Other topics: Glauber dynamics for the Ising model, phase transition, cutoff phenomenon, perfect simulation.

D. Levine, Y. Peres, E. Wilmer, Markov chains and mixing times.. AMS bookstore, (2009).

The purpose of this course is to give a brief introduction to the Finite Elements Method (FEM), a gold standard for the numerical solution of PDEs systems. Oddly enough, the widespread use of the FEM is not accompanied by an adequate knowledge of the mathematical framework underlying the method.
This course, starting from the weak formulation of balance equations, will give an overview of the techniques used to reduce a differential problem into an algebraic one. During the course, some selected problems in mechanics and physics will be solved, covering the three main types of equations: elliptic, parabolic and hyperbolic.
The course will cover the following topics: - Applied Linear Algebra.
- Boundary Value Problems.
- Initial Value Problems
Moreover, the students will be introduced to the use COMSOL Multiphysics, a scientific software for numerical simulations based on the Finite Element Method.

1) Integral Form at a Glance,
note a cura del docente

2) When functions have no value(s): Delta functions and distributions
Steven G. Johnson, MIT course 18.303 notes, 2011

3) Understanding and Implementing the Finite Elements Method
Mark S. Gockenbach, SIAM, 2006 Cap. 1 Some model PDE’s
Cap. 2 The weak formo of a BVP Cap. 3 The Galerkin method
Cap. 4 Piecewise polynomials and the finite element method (sections 4.1, 4.2) Cap. 5 Convergence of the finite element method (sections 5.1 ~ 5.4)

Introduction to cryptography. Classic ciphers. Introduction to cryptanalysis.
Introduction to public-key cryptography.
The RSA cryptosystem.
Primality tests.
Factorization algorithms.
Some attacks on the RSA.
The discrete logarithm problem. Diffie-Hellman key exchange.
Elgamal cryptosystem.
Massey-Omura cryptosystem.
Digital signatures.
Overview of some cryptographic protocols.

Baldoni, Ciliberto, Piacentini: Aritmetica, crittografia e codici
D. Stinson: Cryptography - theory and practice

The environment of celestial bodies; the Solar System; the shape and size of the Earth; the main motions of the Earth (rotation and revolution); the long-term movements of the Earth; the Earth-Moon system.
Orientation; time and its measure; the representation of the earth's surface; the geographical coordinates (latitude and longitude), the reading of topographic maps.
The shapes of the relief and the modeling of the terrestrial relief; the marine hydrosphere, the continental hydrosphere, the cryosphere; the atmosphere; the climate.
The materials of the Earth: the minerals, the lithogenetic processes, the lithogenetic cycle.
The evolution of the Earth

Capire la Terra
J.P. Grotzinger, T-H Jordan
(Terza edizione italiana condotta sulla settima edizione americana)

Il Globo Terrestre e la sua evoluzione
E. L. Palmieri e M. Parotto
Sesta Edizione (2008)

Educational material distributed during the course

1) Computability, complexity and representability:

- Introduction to decision problems, algorithmic and non-algorithmic procedures, deterministic computations, discrete procedures, the notion of alphabet, of speech. Decidability and semi-decidability of a set. Deterministic, finitary and discrete computations. Formal algorithms: formal definition of algorithm, configurations of input, output, transition function. Example of formalization of an algorithm. Decidability for finished automata. Representation of the automata by matrices. Free Monoid of words. Formal semi-rings. Non-deterministic finite automata. Regular Languages. Equivalence between deterministic and non-deterministic automata.

- Turing machines: definition, decidability for Turing machine, stopping time, stopping space. Cost of computation. Complexity: worst-case and average case. Independence of decision time from a finite number of input configurations. Complexity functions, complexity classes DTIME and DSPACE (deterministic time and space). Inclusion DTIME (T (n)) ⊂ DSPACE (T (n)) ⊂ DTIME (2 ^ {cT (n)}). Pumping Lemma. Simulation of algorithms, simulation of the half tape Turing machine, simulation of a multi-tape machine. Special Turing machines. Linear Speedup theorem for Turing machines with an extended alphabet. Evaluation of acceleration coefficient in relation to alphabets. Decisions of natural number sets. Independence from representation. Considerations concerning complexity.

- Turing computability: definition of Turing computable function, characteristic functions of Turing decidable sets, the class of Turing computable functions is closed by composition, concatenation, primitive recursion and minimization. Examples of Turing computable functions. Recursive Functions: equivalence between Turing computability and recursive functions. Ackermann function ([1] chapter 1,2,3,4,5 and [4] chapter 1).

- Time-constructible functions. The notion of T-clock. Examples of some time constructible function. Closure by composition.

- Non-deterministic Turing machines: characterization through the decidability of projection sets. Definition of the class of polynomial non-deterministic functions. NP-complete problems.

2) Lambda calculus and functional programming:

- Declarative programming: a historical outline on the lambda calculus, basic definitions, the terms of the lambda calculus, the simple substitution. Relations on the lambda terms. Congruences, transition to the context. α-equivalence. alpha-equivalence passes to the context. The transitive closure of a relationship, owned by Church-Rosser. Listing of lambda-terms concerning alpha-equivalence.

- Definition of beta-reduction and beta-equivalence. Church-Rosser's theorem for beta-reduction. Normal forms for beta-reduction. Beta-reduction strategies. Normalizing strategy: left reduction (left most-outer most). Head reduction. Soluble Terms. Head Normal Forms. Solvability characterization theorem.

- Representation of the recursive functions: lambda definability theorem. Existence of the fixed point for the lambda terms. Church Fixed Point and Curry fixed point.
- Representation of other data types in the lambda-calculus: pairs, lists, trees, the solution of recursive equations on lambda-terms ([2] chapters 1, 2, 5).

[1] DEHORNOY, P., COMPLEXITÈ ET DECIDABILITÈ. SPRINGER-VERLAG, (1993).
[2] KRIVINE, J.-L., LAMBDA CALCULUS: TYPES AND MODELS. ‪ELLIS HORWOOD, (1993).
[3] SIPSER,M., INTRODUCTION TO THE THEORY OF COMPUTATION.THOMSON COURSE TECHNOLOGY, (2006).

1. Classic Cryptography

- Basic cryptosystems: encryption by substitution, by translation, by permutation, affine cryptosystem, by Vigenère, by Hill. Stream encryption (synchronous and asynchronous), Linear feedback shift registers (LFSR) on finite fields, Autokey cypher. Product cyphers. Basic cryptanalysis: classification of attacks; cryptoanalysis for affine cyphers, for substitution cypher (frequency analysis), for Vigenere cypher: Kasiski test, coincidence index; cryptoanalysis of Hill's cypher and LFSR: algebraic attacks, cube attack.

2. Application of Shannon theory to cryptography

- Security of cyphers: computational security, provable security, unconditional security. Basics of probability: discrete random variables, joint probability, conditional probability, independent random variables, Bayes' theorem. Random variables associated with cryptosystems. Perfect secrecy for encryption systems. Vernam cryptosystem. Entropy. Huffman codes. Spurious Keys and Unicity distance.

3. Block cyphers

- iterative encryption schemes; Substitution-Permutation Networks (SPN); Linear cryptanalysis for SPN: Piling-Up Lemma, linear approximation of S-boxes, linear attacks on S-boxes; Differential cryptanalysis for SPN; Feistel cyphers; DES: description and analysis; AES: description; Notes on finite fields: operations on finite fields, Euclid's generalized algorithm for the computation of the GCD and inverse; Operating modes for block cyphers.

4. Hash functions and codes for message authentication

- Hash functions and data integrity. Safe hash functions: resistance to the pre-image, resistance to the second pre-image, collision resistance. The random oracle model: ideal hash functions, properties of independence. Randomized algorithms, collision on the problem of the second pre-image, collision on the problem of the pre-image. Iterated hash functions; the construction of Merkle-Damgard. Safe Hash Algorithm (SHA-1). Authentication Codes (MAC): nested authentication codes (HMAC).

[1] Antoine Joux, Algorithmic Cryptanalysis, (2010) CRC Press.
[2] Douglas Stinson, Cryptography: Theory and Practice, 3rd edition, (2006) Chapman and Hall/CRC.
[3] Delfs H., Knebl H., Introduction to Cryptography, (2007) Springer Verlag.

Notes on graph theory: graph, directed graph, tree, free and rooted tree, connection, strong connection, acyclicality; isomorphisms between graphs, planarity, Kuratowski's theorem, Euler's formula; coloring of graphs, Eulerian paths, Hamiltonian circuits.
Review of algorithm theory and computational complexity: complexity classes, the class of NP, NP-complete, NP-hard problems. Problems of decision, search, enumeration and optimization; problems of nonlinear programming, convex programming, linear programming and integer linear programming; combinatorial optimization problems. Recalls on the elements of combinatorics.
Optimization problems on graphs: visit of graphs, verification of fundamental properties, connection, presence of cycles, strongly connected components, topological ordering of a graph. Minimum spanning tree (Prim and Kruskal algorithms). Paths of minimum cost (Dijkstra and Bellman-Ford algorithms, dynamic programming technique, Floyd-Warshall algorithm, computation of the transitive closure of a graph). Networks and calculation of the maximum flow on a network, maximum flow / minimum cut theorem, Ford-Fulkerson algorithm, Edmonds-Karp algorithm, preflow algorithms, "push-relabel" algorithms.
Partitioning problems of graphs, trees and paths into connected components, objective functions and algorithmic techniques.
Stable marriage problem, generalizations and applications of the problem, Gale and Shapley algorithm.
Huffman codes.
Programming laboratory for the implementation of algorithms in Python language and with the help of Mathematica software.

T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, "Introduction to algorithms"

Lecture notes and other teaching material in Italian provided by the teacher and made available on the course website (http://www.mat.uniroma3.it/users/liverani/IN440) and on the Microsoft Teams platform

Complex numbers; some complex maps; the Riemann sphere; fractional-linear transformations; they preserve the cross ratio and the set of circles and straight lines. The apollonius circles. Integral of a complex function along a curve; length of a curve; properties of the integral; indicator function; formal sum of curves. Cauchy's theorem on rectangles and on all curves; Caucgy's formula. Liouville's principle. The identity principle for holomorphic functions; removable singularities; almost uniform convergence and its properties. Morera's lemma; mean value theorem and maximum principle; harmonic functions locally are the real part of holomorphic functions. Hadamard's three circles theorem. Euler's product for the sine. Harmonic functions and the electric potential; mean value theorem for harmonic functions, maximum principle and uniqueness for the Dirichlet problem. Dirichlet's kernel; the functions with the mean value property are harmonic. Schwarz's reflection principle. Laurent series; residues and residue calculus. The argument principle and Rouche's theorem. Holomorphic maps are open; a variant of the argument principle and Lagrange's inversion formula; the almost uniform limit of univalent functions is either univalent or constant. Schwarz's lemma; automorphisms of the disc; hyperbolic metric on the disc and its geodesics; the automorphisms of the disc preserve the hyperbolic metric. Analytic extension and monodromy theorem; some examples of Riemann surfaces. The Riemann mapping theorem; Picard's small theorem.

W. Rudin, Real and complex Analysis.

J. B. Conway, Functions of one complex variable.

Classification of Partial differential equations and reduction to canonical form; Wave, Heat, Laplace equations; introduction to Schrodinger equation

A. N. Tikhonov, A. A. Samarskii - Equations of Mathematical Physics

Ordinary Differential Equations
Finite difference approximation for ordinary differential equations: Euler's method. Consistency, stability, absolute stability. Second order Runge-Kutta methods.
Single step implicit methods: backward Euler and Crank-Nicolson methods. Convergence of single step methods. Multi-step methods: general structure, complexity, absolute stability. Stability and consistency of multi-step methods. Adams methods, BDF methods, Predictor-Corrector methods. (Reference: Chapter 7 of curse notes "Appunti del corso di Analisi Numerica")

Partial Differential Equations
Finite difference approximation for partial differential equations. Semi-discrete approximations and convergence. The Lax-Richtmeyer theorem. Transport equation: the method of characteristics. The "Upwind" (semi-discrete and fully-discrete) scheme, consistency and stability. Heat equation: Fourier approximation. Finite difference scheme, consistency and stability. Poisson equation: Fourier approximation. Finite difference scheme, convergence. (Reference: notes by R. LeVeque, "Finite Difference methods for differential equations", selected chapters 1, 2, 3, 12, 13)

Roberto Ferretti, "Appunti del corso di Analisi Numerica", in pdf at http://www.mat.uniroma3.it/users/ferretti/corso.pdf

Roberto Ferretti, "Esercizi d'esame di Analisi Numerica", in pdf at http://www.mat.uniroma3.it/users/ferretti/Esercizi.pdf

Lecture slides in pdf at http://www.mat.uniroma3.it/users/ferretti/bacheca.html

Additional notes given by the teacher

Fundamentals of the approximation of Ordinary Differential Equations systems. One-step methods of forward/backward Euler type and their convergence.
Convergence of numerical methods for time-dependent Partial Differential Equations, Lax-Richtmyer theorem.
Advection equation: analytical aspects. Representation formula via characteristics. Monotone methods for the advection equation: Upwind, Lax-Friedrichs.
Hyperbolic scalar conservation laws in one dimension: analytical aspects, basics on entropic solutions, Rankine-Hougoniot condition. Fundamentals on convergence theory for finite-volume approximations. Monotone finite-volume methods: Godunov, Lax-Friedrichs, Rusanov.
Linear and nonlinear hyperbolic systems: analytical aspects, characteristic decomposition. Central schemes for hyperbolic systems.
The Shallow Water Equations in one and two space dimensions. Central scheme approximation, basics on boundary conditions.
The heat equation: analytical aspects, domain of dependence, regularity. Explicit and implicit approximation in one and two space dimensions via centered second differences and Euler time discretization.
Modelling of incompressible fluids: the Navier-Stokes Equations. Approximate formulations (Euler, Stokes), derivation of the Shallow Water Equations. Finite difference numerical methods based on the Vorticity-Streamfunction formulation.

R. J. LeVeque, Finite Volume Methods for Hyperbolic Problems, Cambridge University Press

Additional material provided by the teacher.

Ordinary Differential Equations
Finite difference approximation for ordinary differential equations: Euler's method. Consistency, stability, absolute stability. Second order Runge-Kutta methods.
Single step implicit methods: backward Euler and Crank-Nicolson methods. Convergence of single step methods. Multi-step methods: general structure, complexity, absolute stability. Stability and consistency of multi-step methods. Adams methods, BDF methods, Predictor-Corrector methods. (Reference: Chapter 7 of curse notes "Appunti del corso di Analisi Numerica")

Partial Differential Equations
Finite difference approximation for partial differential equations. Semi-discrete approximations and convergence. The Lax-Richtmeyer theorem. Transport equation: the method of characteristics. The "Upwind" (semi-discrete and fully-discrete) scheme, consistency and stability. Heat equation: Fourier approximation. Finite difference scheme, consistency and stability. Poisson equation: Fourier approximation. Finite difference scheme, convergence. (Reference: notes by R. LeVeque, "Finite Difference methods for differential equations", selected chapters 1, 2, 3, 12, 13)

Roberto Ferretti, "Appunti del corso di Analisi Numerica", in pdf at http://www.mat.uniroma3.it/users/ferretti/corso.pdf

Roberto Ferretti, "Esercizi d'esame di Analisi Numerica", in pdf at http://www.mat.uniroma3.it/users/ferretti/Esercizi.pdf

Lecture slides in pdf at http://www.mat.uniroma3.it/users/ferretti/bacheca.html

Additional notes given by the teacher

Fundamentals of the approximation of Ordinary Differential Equations systems. One-step methods of forward/backward Euler type and their convergence.
Convergence of numerical methods for time-dependent Partial Differential Equations, Lax-Richtmyer theorem.
Advection equation: analytical aspects. Representation formula via characteristics. Monotone methods for the advection equation: Upwind, Lax-Friedrichs.
Hyperbolic scalar conservation laws in one dimension: analytical aspects, basics on entropic solutions, Rankine-Hougoniot condition. Fundamentals on convergence theory for finite-volume approximations. Monotone finite-volume methods: Godunov, Lax-Friedrichs, Rusanov.
Linear and nonlinear hyperbolic systems: analytical aspects, characteristic decomposition. Central schemes for hyperbolic systems.
The Shallow Water Equations in one and two space dimensions. Central scheme approximation, basics on boundary conditions.
The heat equation: analytical aspects, domain of dependence, regularity. Explicit and implicit approximation in one and two space dimensions via centered second differences and Euler time discretization.
Modelling of incompressible fluids: the Navier-Stokes Equations. Approximate formulations (Euler, Stokes), derivation of the Shallow Water Equations. Finite difference numerical methods based on the Vorticity-Streamfunction formulation.

R. J. LeVeque, Finite Volume Methods for Hyperbolic Problems, Cambridge University Press

Additional material provided by the teacher.

Small bibliography of related texts:
O. Foster 'Lecture on Riemann Surfaces', (Editore Springer)
S. Lang 'Introduction to algebraic and abelian surfaces', (Editore Addison-Wesley)
R. Miranda 'Algebraic Curves and Riemann Surfaces' (Editore AMS)
G. Springer 'Introduction to Riemann Surfaces' (Editore AMS)

Physical quantities. Intensive and extensive physical quantities. Direct and indirect measurements.
Basic and derived quantities.
Units of measurement. Units of measurement systems. Change of units. Dimensions,
physical principle of homogeneity and dimensional analysis.
Measurement tools. Analogical and Digital Instruments.
Characteristics of the instruments: Range, Threshold, Resolution, Linearity and Sensitivity. Accuracy and Precision.
Uncertainty in measurements. Definition of measurement error. Random errors and
systematic errors. Concept of measurement uncertainty. Causes of uncertainties. Uncertainties of Type
A and Type B.
Graphical analysis of data. Usage of tables and graphs for representation and preliminary analysis
of data without the use of statistical tools. Linear, semi-logarithmic graphs,
Double-logarithmic. Histograms.
Propagation of uncertainties. Uncertainty in indirect measurements. Propagation
of uncertainties for independent quantities. Correlated random variables. Definition of
correlation coefficient. Propagation of uncertainties for correlated quantities.


Laboratory program
- Measurements of fundamental quantities: mass, length, time
- Determination of measurement uncertainty: sensitivity of the instrument,
- Standard deviation in repeated measurements, propagation of uncertainties
- Uncertainty on the average in repeated measurements and dependence on sample size
- Study of the pendulum: verification of the independence of the period from the mass, study of the dependence of the period on the length, measurement of g
- Study of the motion of a cart on the inclined plane, effect of friction, measurement of g
- Static and dynamic study of the elastic constant of a spring
- Measurement of resistances with voltamperometric method, study of a resistive voltage divider
- Study of diffraction, verification of Snell's law

notes distributed during the classes

Notes on graph theory: graph, directed graph, tree, free and rooted tree, connection, strong connection, acyclicality; isomorphisms between graphs, planarity, Kuratowski's theorem, Euler's formula; coloring of graphs, Eulerian paths, Hamiltonian circuits.
Review of algorithm theory and computational complexity: complexity classes, the class of NP, NP-complete, NP-hard problems. Problems of decision, search, enumeration and optimization; problems of nonlinear programming, convex programming, linear programming and integer linear programming; combinatorial optimization problems. Recalls on the elements of combinatorics.
Optimization problems on graphs: visit of graphs, verification of fundamental properties, connection, presence of cycles, strongly connected components, topological ordering of a graph. Minimum spanning tree (Prim and Kruskal algorithms). Paths of minimum cost (Dijkstra and Bellman-Ford algorithms, dynamic programming technique, Floyd-Warshall algorithm, computation of the transitive closure of a graph). Networks and calculation of the maximum flow on a network, maximum flow / minimum cut theorem, Ford-Fulkerson algorithm, Edmonds-Karp algorithm, preflow algorithms, "push-relabel" algorithms.
Partitioning problems of graphs, trees and paths into connected components, objective functions and algorithmic techniques.
Stable marriage problem, generalizations and applications of the problem, Gale and Shapley algorithm.
Huffman codes.
Programming laboratory for the implementation of algorithms in Python language and with the help of Mathematica software.

T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein, "Introduction to algorithms"

Lecture notes and other teaching material in Italian provided by the teacher and made available on the course website (http://www.mat.uniroma3.it/users/liverani/IN440) and on the Microsoft Teams platform

Banach and Hilbert spaces, general properties, projections in Hilbert spaces, orthonormal systems.
Hahn-Banach theorem, analytic and geometric form, consequences.
First and second category spaces, Baire's Theorem, Banach-Steinhaus Theorem, open map and closed graph theorem, applications.
Weak topologies, closed and convex sets, Banach-Alaoglu theorem, separability and reflexivity.
Sobolev spaces in dimensione one, immersion theorems, Poincaré inequality, application to variational problems.
Spectral theory, Fredholm alternative, spectral theorem for compact and self-adjoint operators, application to variational problems.

H. Brezis - Analisi Funzionale - Liguori (1986)
H. Brezis - Functional Analysis, Sobolev Spaces and Partial Differential Equations - Springer (2010)
W. Rudin - Functional Analysis - McGraw-Hill (1991)

the course touches on basic algebraic topics:
divisibility, Euclid's algorithm,
continuous fractions, Fibonacci numbers,
combinatorics, straightedge and compass construction, cardinality, lattices and Boole Algebras.

testi consigliati (non da acquistare)
Baldoni, Ciliberto, Piacentini: Aritmetica, crittografia e codici
Papick, Algebra Connections
Materiale e dispense online

CONTENTS OF THE LECTURES: the numbers in round brackets refer to the chapter and section of the textbook adopted.
Kinetic theory of gases. Boltzmann equation and H theorem. (1, Par.2.1,2.2,2.3,2.4)
Maxwell-Boltzmann distribution. (1, Par. 2.5)
Phase space and Liouville theorem. (1, Par. 3.1,3.2)
Gibbs ensembles. Micro canonical ensemble. Definition of entropy. (1, Par. 3.3,3.4)
The ideal gas in the micro canonical ensemble. (1, Par. 3.6)
The equipartition theorem. (1, Par. 3.5)
The canonical ensemble. (1, Par.4.1).
The partition function and the free energy. Fluctuations of energy in the canonical ensemble. (1 Par. 4.4)
The grand canonical ensemble. The grand potential. The ideal gas in the grand canonical ensemble. (1 Par. 4.3).
Fluctuations of the particle number. (1 Par. 4.4)
Classical theory of the linear response and fluctuation-dissipation theorem. (1, Par. 8.4).
Einstein and Langevin theories of the Brownian motion. (Par. 1 par. 11.1,11.2).
Johnson-Nyqvist theory of thermal noise. (1 Par. 11.3).
Quantum statistical mechanics and the density matrix. (1, Par. 6.2,6.3,6.4)
Fermi-Dirac and Bose-einstein quantum statistics. ( 1, Par. 7.1)
The Fermi gas. The Sommerfeld expansion and the electron specific heat. (1, Par. 7.2)
The Bose gas. The Bose-Einstein condensation. (1, Par. 7.3)
Quantum theory of black-body radiation. (1, Par. 7.5)

e-Learning Moodle Platform with Supplementary Material

Suggested textbook:
1) C. Di Castro and R. Raimondi, Statistical Mechanics and Applications in Condensed Matter, Cambridge University Press, 2015.

Further reading:
2) K. Huang, Meccanica Statistica, Zanichelli, 1997.
3) L. Peliti, Appunti di Meccanica Statistica, Bollati Boringhieri, 2003.
4) Joel L. Lebowitz, Statistical mechanics: A selective review of two central issues, Reviews of Modern Physics, 71, S346 (1999).

The materials of the Earth: minerals, the lithogenetic processes, the lithogenetic cycle, the magmatic rocks, the sedimentary rocks, the metamorphic rocks, the bedding and the deformation of the rocks.
Volcanic phenomena: magma and volcanic activity, the main types of eruptions, shape of volcanic buildings, products of volcanic activity, the geographic distribution of volcanoes, volcanoes and man (the volcanic risk).
Seismic phenomena: the theory of elastic rebound, the seismic cycle, types of seismic waves and their propagation and registration, the force of an earthquake (scales of intensity and magnitude), the geographic distribution of earthquakes, the seismic activity and the man (seismic risk)
Plate tectonics: the internal structure of the Earth, the structure of the crust, the Earth's magnetic field, Earth’s internal heat, the convective mantle, from the hypothesis of the drift of the continents to the formulation of the theory of plate tectonics.
The Earth as an integrated system: interaction between the different systems of the planet (biosphere, atmosphere, hydrosphere, lithosphere, cryosphere), the earth's atmosphere, climate and meteorological phenomena, renewable and non-renewable natural resources.
Field trip in Caffarella Valley
Field trip in the city of Rome

Capire la Terra
J.P. Grotzinger, T-H Jordan
(Terza edizione italiana condotta sulla settima edizione americana)

Il Globo Terrestre e la sua evoluzione
E. L. Palmieri e M. Parotto
Sesta Edizione (2008)

Educational material distributed during the course

The course is aimed at introducing students to the teaching of mathematics in 6th to 12th grades.
Contents include a historical, epistemological approach to the basic concepts in elementary mathematics (numbers, geometry, algebra, probability and functions); a discussion of the origins and present situations of mathematical education in compulsory education and secondary education; and examples regarding the mathematical biography of pupils from preschool, the mathematical anxiety and difficulties in understanding and appropriation of mathematical concepts and vision (intuition, error, deduction and argumentation, math draws, math conversation, meaning and the role of history), and the main elements of a good didactical approach in the classroom.

GIORGIO ISRAEL, ANA MILLÁN GASCA, Pensare in matematica, Zanichelli, 2012.
FEDERIGO ENRIQUES 1921, “Insegnamento dinamico”, Periodico di Matematiche, s. IV, 1, pp. 6-16.
http://www.mat.uniroma2.it/mep/Articoli/Enri/Enri.html
Further materials will be suggested during the course.

Module 1. From common knowledge to scientific knowledge. The indicators of scientific knowledge; the contribution of formal education to the image of science; scientific communication.
Module 2. Physics education, a research fieldOrigin and development of research in physics education in Italy; the constructivist paradigm; concepts and misconceptions; research on mental representations; conceptual change models; the conceptual nuclei of Physics.
Module 3. Scientific teaching in secondary school Design the curriculum of Physics in the different orders and in the various study addresses; the teaching / learning process; orientation teaching and laboratory teaching as a didactic methodological approach; from content to programming by skills; training orientation.
Module 4. The role of the "laboratory" in learning Physics Integration between theory and experimental verification; from observation of the phenomenon to the construction of the model; the different ways of "doing laboratory"; design of work units identifying the most appropriate experimental activities (demonstration; in the classroom with poor materials, in the instrumental laboratory, simulated through multimedia aids); implementation of laboratory operational skills for experiment management.
Module 5. Flexible and modular design of content / knowledge, teaching methodologies and learning environments Core foundations of Physics; analysis and planning of didactic courses that respond to verticality criteria (evolution of concepts coherent and appropriate to students' cognitive development) and transversality (integration of Physics with other disciplines); simulations of teaching methodologies such as: dialogue lesson, microteaching, co-planning, peer-to-peer evaluation, cooperative learning activities, group work.
Module 6. Learning evaluation of learning Modes and tools used in the various stages of monitoring, measurement, verification, evaluation and self-evaluation of learning; identification of learning contexts capable of developing and detecting skills; the National Evaluation System (SNV).
Module 7. Modern and Contemporary Physics The role of modern and contemporary Physics in school curricula: what content / paths to propose that guarantee students a real understanding of them. The new State Exam and the role of Physics in the second written test in scientific high schools. Instrumental laboratory. Five instrumental laboratories of three hours each in the months of March, April and May.

Students can take advantage of the following teaching material on the Platform of the Department of Mathematics and Physics: Power-pointrelative presentations to the contents of the lessons, research articles, work material (texts to be analyzed taken from textbooks, articles of scientific dissemination, original memories , “tutorial” cards, videos, applets, cards for group work, grids for assessing learning, web-sites).

ESSENTIAL BIBLIOGRAFY
Arons Arnold B. 1992, Guida all'insegnamento della fisica, Zanichelli•P. Guidoni, M. Arcà 2000 –Guardare per sistemi e guardare per variabili –l’educazione scientifica di base -AIF Editore•Vicentini M., Mayer M. (a cura di) (1999). Didattica della Fisica, Loescher Editore.•Grimellini Tomasini N., Segré G. (a cura di) (1991). Conoscenze scientifiche: le rappresentazioni mentali degli studenti, La Nuova Italia, Firenze.•La fisica secondo il PSSC, 25 film del Physical Science Study-Zanichelli•F. Bocci, Manuale per il laboratorio di fisica: introduzione all’analisi dei dati sperimentali -Zanichell

Complex numbers; some complex maps; the Riemann sphere; fractional-linear transformations; they preserve the cross ratio and the set of circles and straight lines. The apollonius circles. Integral of a complex function along a curve; length of a curve; properties of the integral; indicator function; formal sum of curves. Cauchy's theorem on rectangles and on all curves; Caucgy's formula. Liouville's principle. The identity principle for holomorphic functions; removable singularities; almost uniform convergence and its properties. Morera's lemma; mean value theorem and maximum principle; harmonic functions locally are the real part of holomorphic functions. Hadamard's three circles theorem. Euler's product for the sine. Harmonic functions and the electric potential; mean value theorem for harmonic functions, maximum principle and uniqueness for the Dirichlet problem. Dirichlet's kernel; the functions with the mean value property are harmonic. Schwarz's reflection principle. Laurent series; residues and residue calculus. The argument principle and Rouche's theorem. Holomorphic maps are open; a variant of the argument principle and Lagrange's inversion formula; the almost uniform limit of univalent functions is either univalent or constant. Schwarz's lemma; automorphisms of the disc; hyperbolic metric on the disc and its geodesics; the automorphisms of the disc preserve the hyperbolic metric. Analytic extension and monodromy theorem; some examples of Riemann surfaces. The Riemann mapping theorem; Picard's small theorem.

W. Rudin, Real and complex Analysis.

J. B. Conway, Functions of one complex variable.