Educational objectives General targets: To acquire advanced knowledge in the theory of dynamical systems.
Knowledge and understanding: Students who have passed the exam will have acquired rigorous and advanced theoretical knowledge in the field of dynamical systems theory, with focus on hyperbolic systems and applications in mechanics, like stability theory. Moreover, they will learn part of the general theory of hyperbolic invariant sets, with applications to homoclinic intersections, chaotic motion, and ergodic theory, in the framework of concrete mechanical systems.
Applying knowledge and understanding: Students who have passed the exam will be able to: i) study equilibrium stability problems both when this is recognized by the linear part and by the methods of Liapunov's theory; iii) analyze planar systems that exhibit self-oscillation phenomena; iv) formalize in concrete problems the concepts of intersection of stable and unstable manifolds and the related chaotic phenomena; v) apply the basic techniques of ergodic theory to concrete problems.
Making judgements: Students who have passed the exam will be able to use the acquired knowledge in the analysis of nonlinear evolutionary models arising in Applied Sciences.
Communication skills: Students who have passed the exam will have gained the ability to communicate and expose concepts, ideas and methodologies of the theory of dynamic systems.
Learning skills: The acquired knowledge will allow students who have passed the exam to deepen, in an individual and autonomous way, techniques and methodologies of the theory of dynamical systems.
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Educational objectives General objectives: to acquire basic knowledge in stochastic process theory and in stochastic modeling of real phenomena.
Specific objectives:
Knowledge and understanding: at the end of the course the student will have acquired the basic notions and results concerning stochastic processes in discrete and continuous time, on discrete structures such as graphs or on continuous spaces.
Apply knowledge and understanding: at the end of the course the student will be able to model the temporal evolution of various real phenomena through stochastic processes, to analyze the stationarity and / or temporal reversibility of stochastic processes, to calculate probabilities of absorption and expected absorption times, to simulate stochastic processes and to estimate the rate of convergence at equilibrium.
Critical and judgmental skills: the student will have the basis to study stochastic dynamic systems and acquire the ability to evaluate the goodness of a model compared to others in the modeling of real phenomena.
Communication skills: having to take an oral theory test, students will develop the communication skills necessary to expose the mathematical theory and the various models considered in the course.
Learning skills: the acquired knowledge will allow a more in-depth study of stochastic processes both on discrete and continuous spaces, helping the student to study other courses such as stochastic calculus.
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Educational objectives General targets:
acquire basic knowledge on a rigorous approach to statistical equilibrium mechanics.
Applying knowledge and understanding:
knowledge of statistical ensembles, Gibbs measures and thermodynamic functionals; understanding of phase transitions for paradigmatic lattice particle models.
Making judgements:
ability to describe mechanical and thermodynamic behavior of large systems of particles.
Communication skills:
ability to identify the main points of the theory, to be able to illustrate the most interesting elements by using appropriate examples, and to discuss the mathematic details for simple models.
Learning skills:
the acquired knowledge will allow to face advanced studies, i.e. at PhD level, related to equilibrium and non-equilibrium statistical mechanics, and to use the basic tools of statistical mechanics in other contexts.
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Educational objectives General targets:
acquire basic knowledge on a rigorous approach to statistical equilibrium mechanics.
Applying knowledge and understanding:
knowledge of statistical ensembles, Gibbs measures and thermodynamic functionals; understanding of phase transitions for paradigmatic lattice particle models.
Making judgements:
ability to describe mechanical and thermodynamic behavior of large systems of particles.
Communication skills:
ability to identify the main points of the theory, to be able to illustrate the most interesting elements by using appropriate examples, and to discuss the mathematic details for simple models.
Learning skills:
the acquired knowledge will allow to face advanced studies, i.e. at PhD level, related to equilibrium and non-equilibrium statistical mechanics, and to use the basic tools of statistical mechanics in other contexts.
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Educational objectives General targets:
acquire basic knowledge on a rigorous approach to statistical equilibrium mechanics.
Applying knowledge and understanding:
knowledge of statistical ensembles, Gibbs measures and thermodynamic functionals; understanding of phase transitions for paradigmatic lattice particle models.
Making judgements:
ability to describe mechanical and thermodynamic behavior of large systems of particles.
Communication skills:
ability to identify the main points of the theory, to be able to illustrate the most interesting elements by using appropriate examples, and to discuss the mathematic details for simple models.
Learning skills:
the acquired knowledge will allow to face advanced studies, i.e. at PhD level, related to equilibrium and non-equilibrium statistical mechanics, and to use the basic tools of statistical mechanics in other contexts.
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Educational objectives General skills
The course aims to transmit to students a deep knowledge of the mathematical structure of Quantum Mechanics, of the historical and conceptual path leading to its formulation, and of its relations with other mathematical subjects (as e.g. functional analysis, operator theory, theory of Lie groups and their unitary representations).
Specific skills
A) Knowledge and understanding
After the conclusion of the course, successful students will know and understand the fundamental concepts of Fourier theory, the mathematical analogy between classical mechanics and geometric optics, the historical and conceptual path which led to overcome Classical Mechanics in favour of the more general Quantum Mechanics, and the mathematical structure of Quantum Theory, with a particular emphasis on dynamical aspects (time evolution) and on the analysis of the symmetries of a quantum system (representation of the symmetry group).
B) Applying knowledge and understanding
The general knowledge will be complemented by the application of general concepts to some specific models, and by the ability to analyze symmetries and dynamics of simple quantum systems. Specific simple systems will be analyzed in detail, including the case of a quantum particle in a linear potential, in a harmonic potential, in a uniform magnetic field, and in a Kepler potential (hydrogenoid atom). Successful students will be potentially able to apply the general concepts also to other more complex systems, including non-hydrogenoid atoms, molecules and crystalline solids.
C) Making judgements
The analysis of the historical and conceptual path which led to overcome Classical Mechanics in favour of the more general Quantum Mechanics will make successful students able to autonomously judge the epistemological foundations of a physical theory, and hence to understand its natural range of application and validity. This critical judgement will lead students to privilege an epistemological apophantic approach, with respect to an apodictic one.
Moreover, successful students will be able to autonomously judge the validity of a mathematical statement, through a critical analysis of the hypotheses and of the deductive steps leading to the proof of the statement itself, and to autonomously formulate counterexamples to mathematical statements whenever one of the hypotheses is denied.
D) Communication skills
Successful students will acquire the ability to communicate what has been learned through written themes and oral exams, and to formulate a logically structured speech, with a clear distinction between hypotheses, deduction and thesis.
E) Learning skills
Successful students will acquire the ability to identify the most relevant topics in a subject and to make the logical connections between the topics covered.
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Educational objectives Knowledge and understanding:Successful students will learn various characterizations of Brownianan motion, the fundamental properties of diffusion processes and the main results of stochastic calculus, including the Ito formula.Skills and attributes:Successful students will be able to apply stochastic calculus in various applications, from mathematical finance to physics and biology.
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