10620699 | Computational Biophysics [FIS/03] [ENG] | 1st | 1st | 6 |
Educational objectives GENERAL OBJECTIVES:
This course is designed as an introduction to computational biology and biophysics. It aims to bridge the gap between institutional learning and active research. The course is structured around three main aspects: i) TOPICS (principles, ideas); ii) METHODS (algorithms and computational techniques); iii) PERSPECTIVES of contemporary computational biology. Extensive reference and critical introductions to literature and current texts will be provided as guides for individual study. Efforts will be made to provide a clear framework of bibliographic references for each topic discussed, aiding in preparation for the final exam. At the end of the course, special guests will present original research lines of interest to students in biosystems, materials physics, and theoretical courses. By successfully completing the course, students will be able to navigate the world of computational biophysics at various scales (from molecules to cells) and master the main computation and analysis algorithms used in the field.
SPECIFIC OBJECTIVES:
A - Knowledge and Understanding
SO 1) Gain a historical-critical perspective of modern computational biology/biophysics
SO 2) Understand the fundamentals of modern evolutionary theory
SO 3) Gain practical experience with data analysis models based on Bayesian inference
SO 4) Gain direct experience with major bioinformatics databases (SwissProt, pFam, PDB,…)
B - Applied Skills
SO 7) Translate at least the main computational biophysics simulation and analysis algorithms into pseudo-code
SO 8) Improve programming skills in scripting languages (Python) or compiled languages (C/C++)
SO 9) Execute a molecular dynamics simulation of a small protein on GROMACS
C - Judgment Autonomy
SO 10) Evaluate the quality of a scientific article
D - Communication Skills
SO 11) Report the results of a research project to the class participants
SO 12) Actively participate in classroom discussions (in Italian and/or English)
E - Learning Skills
SO 13) Acquire fluency in consulting specific databases (e.g., PubMed, Google Scholar) to support/refute a research hypothesis
SO 14) Actively participate in the organization of self-learning groups
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10616466 | Computational Statistical Mechanics [FIS/03] [ENG] | 1st | 1st | 6 |
Educational objectives The course of Computational Statistical Mechanics aims to provide the necessary knowledge to understand and implement classical molecular dynamics and Monte Carlo techniques. The methods, that allow us to generate trajectories in phase space for sampling distinct statistical ensembles, will be studied. Some techniques which offer the possibility to calculate the free energy will be also discussed and it will be shown how the use of such results can provide a description of the atoms and molecules phase diagrams. At the end of the course, students will develop the ability of a quantitative reasoning and numerical skills useful for studying, modeling and understanding a large class of atomic and molecular systems as well as supramolecular aggregates. In addition, the student will be able to utilize the most common simulation packages which are available for a numerical study of complex systems, such as colloidal and bio-molecular systems, due to the acquired full knowledge of algorithms and numerical techniques on which these programs are built. Particular emphasis will be given to object-oriented and generic programming in the implementation of a computer simulation code. In particular, the modern C++ programming language will be introduced and discussed in the context of atomistic simulations. It will be also illustrated the use of the Python language, through the NumPy and MatPlotLib libraries, to analyze and visualize the data produced by computer simulations. During the course there will be also hands-on lectures, so that students will be able to put into practice the acquired knowledge through the implementation of their own simulation code. Students will be also stimulated to present the results obtained from the simulations, so as to test their ability to communicate clearly and effectively such results. The development of a numerical simulation code will be an opportunity for the students to design and develop their own project. This way they will be able to show their learning level and ability to apply independently the theoretical concepts acquired in the course.
OBJECTIVES
A - Knowledge and understanding
OF 1) Know common techniques to carry out computer simulations
OF 2) Know object oriented programming for scientific computations.
OF 3) Know common methods for analyzing data obtained from computer simulations.
OF 4) Understand data produced by computer simulations.
B - Application skills
OF 5) Ability to implement a simulation code.
OF 6) Ability to exploit simulations to obtain information about the physical properties of investigated systems.
OF 7) Be able to develop computer codes for analyzing data produced by computer simulations.
C - Autonomy of judgment
OF 8) Be able to critically analyze the results of “numerical experiments”.
OF 9) Be able to integrate autonomously the acquired knowledge in order to face new problems that require additional numeric techniques.
OF 10) Be able to identify the best technique to solve and study a physical problem numerically.
D - Communication skills
OF 11) Know how to communicate clearly to specialists and non-specialists, through manuscripts and presentations, the results obtained.
OF 12) Know how to clearly discuss a scientific topic.
OF 13) Know how to reproduce calculations related to a given scientific topic in a critical and informed manner.
E - Ability to learn
OF 14) Have the ability to learn new algorithms and numerical techniques by exploiting the scientific literature.
OF 15) Be able to conceive and develop their own project consisting of writing a simulation code or implementing a numerical technique.
OF 16) Be able to overcome difficulties and setbacks in the implementation of numerical techniques through original ideas and solutions.
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10616467 | Computational Solid State Physics [FIS/03] [ENG] | 1st | 1st | 6 |
Educational objectives GENERAL OBJECTIVES:
The aim of the course 'Computational Solid State Physics' is to provide both theoretical and practical understanding with the two main numerical approaches currently in use for the solution of the quantum many body problem in condensed matter physics:
a) Density Functional Theory, which allows to obtain predictions from first principles of electronic states, structural energies, and interatomic forces in molecules and solids;
b) Quantum Monte Carlo methods - variational, diffusion, path-integral – which can be applied to the numerical study of various many-body quantum systems (liquid or solid helium, electron gas, electrons in atoms and molecules).
SPECIFIC OBJECTIVES:
A- Knowledge and Understanding:
OF1: To know and understand the fundamentals of Hartree-Fock (H-F) theory.
OF2: To know and understand the fundamentals of Density Functional Theory (DFT).
OF3: To know and understand the fundamentals of Pseudopotential theory (PPT).
OF4: To know and understand the DFT+PPT theory of crystalline systems.
OF5: To know and understand the variational Monte Carlo (MC) method for identical particles.
OF6: To know and understand the "projection MC" method for identical particles.
OF7: To know and understand the path integral Monte Carlo (PIMC) method.
OF8: To know and understand the "sign problem" for systems of many identical fermions.
B- Application Skills:
OF9: To apply DFT+PPT to simple solid-state systems (using software like Quantum Espresso).
OF10: To apply various quantum Monte Carlo methods to simple systems of many identical bosons or fermions (writing simple C codes and using large pre-existing FORTRAN codes).
C- Autonomy of Judgement:
OF11: To be able to assess, for a real quantum solid or fluid, which theories and algorithms presented in the course are suitable for describing and/or predicting which physical properties.
OF12: To be able to evaluate the feasibility, in terms of memory and CPU time, of a numerical project in molecular or solid-state physics.
D- Communication Skills:
OF13: To be able to present the results of a theoretical-numerical project.
OF14: To be able to write concise reports on the results of a theoretical-numerical project.
Ability to Learn:
OF15: To progress autonomously in C programming skills.
OF16: To progress autonomously in the use of existing software and codes.
OF17: To progress in graphical visualization skills of one's own results.
OF18: To progress in the ability to read reviews and research articles.
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10616465 | Object Oriented Programming for Data Processing [FIS/01] [ENG] | 1st | 1st | 6 |
Educational objectives The main goal of Object Oriented Programming for Data Processing is to provide an introduction to the most recent computational methods, used in the context of data analysis in current research.
The course aims to familiarize students with modern techniques programming used in data analysis. In the first part of the course, C++ and object oriented programming will be presented and physics problems will be solved with Strategy and Composition patterns. ROOT will be discussed and used for data analysis and persistent data storage. In the second part of the course, Python will be introduced, along with the NumPy and SciPy packages. The MatPlotLib package will be used for data visualization and animation.
Specific Objectives
A. Knowledge and understanding
1. Knowing object-oriented programming
2. Understanding polymorphism and its applications in physics problems
3. Using ROOT libraries for data analysis
4. Knowing the basic ingredients to simulate physical processes numerically 5. Understandint the main features of Python for data analysis
B. Application skills
7. Implementint polymorphic classes for notions of physics
8. Carrying out numerical simulations through the use of polymorphic classes and objects
9. Performing data analysis with ROOT and using classes to plot and interpolate data in C++
10. Using Jupyter Notebook and the SciPy, Numpy and Matplotlib packages for numerical simulations and data analysis with Python
C. Autonomy of judgment
11. Being able to apply the knowledge acquired in data analysis and numerical simulations also in other fields of physics and in commercial and industrial contexts
12. Being able to apply Machine Learning techniques in Python to physics problems
D. Communication skills
13. Being able to illustrate the concept of polymorphism with examples applied in physics
E. Ability to learn
14. Being able to study more advanced aspects of object-oriented programming independently
15. Being able to carry out numerical simulations for more complex physical processes such as those covered in the courses of Physics Laboratory
16. Being able to perform data analysis and numerical interpolations in the courses of Physics Laboratory
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10616468 | Advanced Mathematical Methods for Physics [FIS/02] [ENG] | 1st | 1st | 6 |
Educational objectives GENERAL OBJECTIVES:
The main objective of Advanced Mathematical Methods for Physics is that of providing an introduction to up-to-date computational methods that are used in research areas of current interest. Three different courses are offered.
The goal of the third course is to provide the students with the theoretical background of perturbative and asymptotic analysis used in many fields of theoretical physics:
a) Definition and properties of the perturbative and asymptotic exapansions used in theoretical physics;
b) Introduction to some asymptiotic methods --- Boundary Layers, WKB, Multiple Scale, Renormalization Group --- and analisys of their filds of applicability.
SPECIFIC OBJECTIVES:
A - Knowledge and understanding
OF 1) To know and understand the foundations of the perturbative methods
OF 2) To know and understand the foundations asymptotic analysis
OF 3) To know and understand the Boundary Layer Theory
OF 4) To know and understand the WKB method
OF 5) To know and understand the Multiple Scale method
OF 6) To know and understand the Renormalization Group and it connections with asymptotica analysis.
B - Application skills
OF 7) Application of the asymptotic analysis to the solution of comlex problems
OF 8) Application of the Boundary Layer Theory, WKB method and Multiple Scale method to the study of simple problems.
OF 9) Application of the Renormalization Group method to the asymptotic analysis of the solution of simple ordinary differential equations.
C - Autonomy of judgment
OF 10) Ability to analize a simple perturbative problem.
OF 11) Ability to evaluate the structure of a simple perturbative problem and use the more appropriate method to its study.
D - Communication skills
OF 12) Ability to create an effective presentation of the results of a theoretical project
OF 13) Ability to present the basis of the asymptotic analysis and some of its methods.
E - Ability to learn
OF 14) Autonomous improvement in the study of perturbation method
OF 15) Autonomous improvement in the use of asymptotic analysis in more comlex problems
OF 16) Autonomous improvement in reading and understanding research articles and reviews
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10621020 | FUNDAMENTALS OF QUANTUM OPTICS [FIS/03] [ENG] | 1st | 1st | 6 |
Educational objectives The student will acquire knowledge of the fundamental principles of light-matter interaction studied via semi-classical and quantum approaches. Moreover, the student will study different aspects related to the quantum mechanical nature of light and its characterization according to photon statistics. During the course, the student will also deal with non-linear optics and will study some practical applications of quantum optics.
A - Knowledge and understanding
OF 1) To understand the fundamentals of quantum optics and non linear optics.
OF 3) To understand phenomena related to light-matter interaction, using both semi-classical and quantum approaches.
B - Application skills
OF 4) To be able to use semi-classical and quantum approaches to understand phenomena related to the interaction of light with matter.
OF 5) To be able to apply the basic principles of quantum optics to solve simple problems related to the knowledge acquired during the course.
C - Autonomy of judgment
OF 6) To be able to evaluate which optical phenomena require a classical or quantum treatment of the electromagnetic field to be explained.
OF 7) To develop quantitative reasoning abilities and problem-solving skills, which represent the basis to study, model and understand quantum phenomena related to light-matter interaction.
D - Communication skills
OF 8) To know how to communicate the knowledge acquired during the course via presentation of a scientific work related to one particular topic discussed during the lecture.
E - Ability to learn
OF 9) Have the ability to consult scientific papers in the field of quantum optics.
OF 10) Have the ability to understand practical applications that use the basic principles of quantum optics.
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10592732 | SOFT AND BIOLOGICAL MATTER [FIS/03] [ENG] | 1st | 1st | 6 |
Educational objectives GENERAL OBJECTIVES: The "Soft and Biological Matter" course aims to provide the necessary knowledge to understand the structure of soft and biological matter, in the relevant scales of
length and time. Important arguments include the origins of the effective forces between macromolecules, the aggregation processes which result in the formation of vesicles, micelles, membranes, the formation of gel phases, structural and dynamic properties of synthetic and biological (nucleic acids and proteins) polymers. At the end of the course, students will develop quantitative reasoning and analytical skills useful for studying, modelling and understanding phenomena related to the dynamic and structural properties of soft and biological matter.
SPECIFIC OBJECTIVES:
A - Knowledge and understanding
OF 1) To understand the physics of soft and biological matter
OF 2) To understand energetic and entropic forces
OF 3) To understand molecular aggregation
OF 4) To understand thermodynamic stability and critical phenomena in soft matter
B - Application skills
OF5) To be able to apply learned methods/techniques to novel problems
C - Autonomy of judgment
OF 6) To be able to apply the topic discussed in the course to the general context of soft and biological matter.
D - Communication skills
E - Ability to learn
OF 7) To be able to understand a scientific publication and deepen her/his own understanding of the arguments discussed in the course.
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1055354 | NUCLEAR PHYSICS [FIS/04] [ENG] | 1st | 1st | 6 |
Educational objectives Aim of the Course is to provide the basic knowledge of Nuclear Physics at the present stage, recalling the strong interplay with other fields of Physics , both at the frontier of the research in the subnuclear Physics (e.g., stellar evolution, search of signals of new Physics) and on the side of applications , like in medical, environmental and cultural-heritage fields. As a part of the final examination, besides the oral one, students will be asked to give a short presentation, at most 20 slides, of a topic chosen among the ones proposed and according to their interests in the field.
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10620727 | PLASMA PHYSICS AND FUSION ENERGY [ING-IND/18] [ENG] | 1st | 1st | 6 |
Educational objectives The objective of the course is to present the fundamental ideas underlying the behavior of fully ionized plasmas, and to provide a quantitative understanding of the physical principles at the basis of the magnetic confinement of high-temperature plasmas, focusing on the peculiarities of the tokamak device.
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10611918 | ADVANCED MACHINE LEARNING FOR PHYSICS [FIS/01] [ENG] | 1st | 2nd | 6 |
Educational objectives GENERAL OBJECTIVES:
Acquire familiarity with advanced deep learning techniques based on differentiable neural network models with supervised, unsupervised and reinforced learning paradigms; acquire skills in modelling complex problems through deep learning techniques, and be able to apply them to different application contexts in the fields of physics and basic and applied scientific research.
Discussed topics include: general machine learning concepts, differentiable neural networks, regularization techniques. Convolutional neural network, neural network for sequence analysis (RNN, LSTM / GRU, Transformers). Advanced learning techniques: transfer learning, domain adaptation, adversarial learning, self-supervised and contrastive learning, model distillation.
Graph Neural Networks (static and dynamic) and application to structured models for physics: dynamic models, simulation of complex fluids, GNN Hamiltonians and Lagrangians. Generative and variational models: variational mean-field theory, expectation maximization, energy based and maximum entropy models (Hopfield networks, Boltzman machines and RBM), AutoEncoders, Variational AutoEncoders, GANs, Autoregressive flow models, invertible networks, generative models based on GNN. Quantum Neural Networks.
SPECIFIC OBJECTIVES:
A - Knowledge and understanding
OF 1) Knowledge of the functioning of neural networks and their mathematical interpretation as universal approximators
OF 2) Understanding of the limits and potential of advanced machine learning models
OF 3) Understanding of the limits and potential of DL in solving physics problems
B - Application skills
OF 4) Design, implementation, commissioning and analysis of deep learning architectures to solve complex problems in physics and scientific research.
C - Autonomy of judgment
OF 5) To be able to evaluate the performance of different architectures, and to evaluate the generalization capacity of the same
D - Communication skills
OF 6) Being able to clearly communicate the formulation of an advanced learning problem and its implementation, its applicability in realistic contexts
OF 7) Being able to motivate and to evaluate the generalization capacity of a DL model
E - Ability to learn
OF 8) Being able to learn alternative and more complex techniques
OF 9) Being able to implement existing techniques in an efficient, robust and reliable manner
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10620703 | Computer Architecture for Physics [FIS/01] [ENG] | 1st | 2nd | 6 |
Educational objectives A - Knowledge and understanding
OF 1) To know the elements of the computer hardware and software architecture and to understand their interactions.
OF 2) To know the techniques needed to develop optimized code for a given computer architecture.
OF 3) To know the fundamentals of logic design of digital circuits using hardware description languages (VHDL).
B - Application skills
OF 4) To be able to evaluate the execution performance of code on a given computer architecture.
OF 5) To be able to develop scientific code optimized for a given computer architecture.
OF 6) To be able to select the computer architecture best suited for a given application.
OF 7) To be able to implement a circuit through VHDL coding and to simulate its behaviour.
C - Autonomy of judgment
OF 8) To be able to integrate the knowledge acquired in order to apply them for the processing needs in the experimental or theoretical Physics.
D - Communication skills
E - Ability to learn
OF 9) Have the ability to follow up the development in computer architectures.
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10620701 | Nonlinear Waves and Solitons [FIS/03] [ENG] | 1st | 2nd | 6 |
Educational objectives Formative targets:
The objectives of the course are to bring the student to a deep knowledge and understanding of the basic mathematical properties i) of the nonlinear wave propagation with or without dispersion or dissipation; ii) of the construction of nonlinear mathematical models of physical interest, through the multiscale method, like the soliton equations, and of the mathematical techniques to solve them, arriving to the introduction of current research topics in the theory of solitons and anomalous waves. At the end of the course the student must be able i) to apply the acquired methods to problems in nonlinear physics even different from those studied in the course, in fluid dynamics, nonlinear optics, theory of gravitation, etc .., solving typical problems of the nonlinear dynamics; ii) to integrate in autonomy the acquired knowledges through the suggested literature, to solve also problems of interest for him/her, and not investigated in the course. The student will have the ability to consult supplementary material, interesting scientific papers, having acquired the right knowledges and critical skill to evaluate their content and their potential benefits to his/her scientific interests. At last the student must be able to conceive and develop a research project in autonomy. In order to achieve these goals, we plan to involve the student, during the theoretical lectures and exercises, through general and specific questions related to the subject; or through the presentation in depth of some specific subject agreed with the teacher.
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10592576 | DETECTORS AND ACCELERATORS IN PARTICLE PHYSICS [FIS/01] [ENG] | 1st | 2nd | 6 |
Educational objectives GENERAL OBJECTIVES:
The course will cover the physics of particle detectors and particle accelerators. It will introduce the experimental techniques used in nuclear, particle physics and photon science, and describe the layout and functionality of modern experiments. History, operating principles of modern particle accelerators and applications in nuclear, sub-nuclear and medical physics will be treated as well.
Through classroom lectures, dedicated seminars held by experts and hands-on exercise sessions, the Detectors and Accelerators in Particle Physics course proposes:
- to deepen the knowledge of the interactions of elementary particles with matter;
- to analyze the functioning of the various detectors used for the detection of elementary particles in nuclear and subnuclear physics;
- to examine some current experiments of greater interest;
- to provide an introduction to the physics of particle accelerators by also presenting future projects;
- to teach how to design and simulate simple experimental using the Geant4 software library.
At the end of the course, students will be familiar with modern detection and particle acceleration methods in particle and applied physics. They will have the basis to understand the motivations and the functioning of the various parts of an experiment in high energy physics or instrumentation for the control of the beams in medical physics laboratories. This will include the ability to size and select detectors suitable for the purposes of the experiments to be examined or to be designed.
They will know how to describe measurements of ionization, position, energy, and momentum of particles, as well as particle identification and timing measurements. They will develop competence in quickly and critically acquiring information from publications other then textbooks.
SPECIFIC OBJECTIVES:
A - Knowledge and understanding
OF 1) To know the fundamentals of particle detectors
OF 2) To know the fundamentals of particle accelerators
OF 3) To understand the language of the physics of particle detectors and accelerators
B - Application skills
OF 4) Ability to design, dimension and choose suitable detectors for a specific particle physics experiment
OF 5) Ability to implement a simple simulation setup with Geant4 for a particle detector
C - Autonomy of judgment
OF 6) To be able to analyze and evaluate the performance of a particle physics detectors
OF 7) To be able to analyze and evaluate the performance of a particle accelerator
D - Communication skills
OF 8) Being able to clearly communicate the operation and properties of a particle detector and of a particle accelerator, and their applicability in realistic contexts
OF 9) Being able to motivate the architectural choices behind a specific particle detector or accelerator design
E - Ability to learn
OF 8) Being able to learn alternative and more complex techniques
OF 9) Being able to implement existing techniques in an efficient, robust and reliable manner
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1042011 | ACCELERATOR PHYSICS AND RELATIVISTIC ELECTRODYNAMICS [FIS/01] [ENG] | 1st | 2nd | 6 |
Educational objectives KNOWLEDGE AND UNDERSTANDING
Upon completion of the course, the student will know the principles of special relativity, with particular reference to the link with classical mechanics, electromagnetism, the transformations of fields between inertial reference systems, the principles on which modern particle accelerators are based, the relativistic motion of charges in electric and magnetic fields and the functioning of linear accelerators, cyclotrons and synchrotrons
APPLICATION CAPABILITIES:
The student will be able to schematically design some devices used in accelerators, such as quadrupoles, and discuss the motion of the charges in these devices.
AUTONOMY OF JUDGMENT
The student will be able to determine the operating principles of a circular accelerator thanks to the acquired concepts of betatron and synchrotron motion and to independently use the simulation code ASTRA (A Space Charge Tracking Algorithm).
COMMUNICATION SKILLS
The student will be able to deal with topics related to particle accelerators using terms and concepts typical of this sector
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10621390 | NUCLEAR REACTOR THEORY [ING-IND/19] [ENG] | 1st | 2nd | 6 |
Educational objectives The objective of the course is to provide a general comprehension of the
physical phenomena underlying the slowing-down and diffusion/transport of
neutrons in media without and with nuclear fuel, and to illustrate the
mathematical tools necessary to carry out criticality calculations.
As a learning outcome, the student is expected to be able to perform and
interpret analytical calculations relative to the neutronic design of a
nuclear reactor, both in static and dynamic conditions.
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1052082 | RADIATION PROTECTION [ING-IND/20] [ENG] | 1st | 2nd | 6 |
Educational objectives The course provides in-depth knowledge of the interaction of ionizing radiation with biological systems, of the physical quantities used to quantify it and of the technical and regulatory measures applied for the health of workers and the population.
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10621387 | nuclear systems design [ING-IND/19] [ENG] | 1st | 2nd | 6 |
Educational objectives The course provides in-depth knowledge of nuclear operating principles, systems and components, particularly regarding nuclear safety requirements for the whole plant.
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10592565 | PHOTONICS [FIS/03] [ENG] | 1st | 2nd | 6 |
Educational objectives GENERAL OBJECTIVES:
Provide fundamental notions of: ultrashort pulses generation and propagation in linear and non-linear media, characterization of time and frequency, spatial and polarization profiles. Pinpoint selected examples of ultrafast processes in physics, chemistry and biology (molecular switches, photoreceptors isomerization, photoinduced processes in
hemeproteins). Highlight novel approaches to non linear imaging and
related instrumentation. Hands on laboratory tutorials.
SPECIFIC OBJECTIVES:
A - Knowledge and understanding
OF 1) To know photonics foundations and its most common application
OF 2) To understand non linear processes relevant for propagation of light pulses in materials
OF 3) Understand principles of non-linear spectroscopy illustrated by Feynman diagrams
B - Application skills
OF 4) Learn how to apply equations for linear and non linear propagation to real cases such as short pulses in optical fibers.
OF 5) Solve problems related to evaluation of cross sections for linear and non linear spectroscopies
OF 6) To be able to apply numerical techniques for the evaluation of radiation – matter interaction
C - Autonomy of judgment
OF 7) To be able to apply in the future the acquired skills to complex problems in photochemistry and photobiology
D - Communication skills
OF 8) To know how to communicate the critical steps necessary to solve elementary problems dealing with spectroscopy and light matter interaction in non linear regime
E - Ability to learn
OF 10) Have the ability to autonomously consult scientific articles to expand the knowledge developed in the course
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1055684 | SPECTROSCOPY METHODS AND NANOPHOTONICS [FIS/03] [ENG] | 1st | 2nd | 6 |
Educational objectives GENERAL OBJECTIVES:
Nanophotonics and Spectroscopic Methods" course aims to provide the necessary knowledge on spectroscopic and nanophotonics techniques in condensed matter to understand the characteristics of materials from the point of view of electronic, reticular and vibrational degrees of freedom both at equilibrium and out of equilibrium. Different spectroscopic techniques: neutron scattering, scattering and absorption of electromagnetic radiation, will be studied within the formalism of the scattering matrix S and the linear response theorem. It will be understood how from these techniques it is possible to study the spectrum of fundamental excitations in condensed matter such as the phonon spectrum, the electronic absorption of free particles, the effects of the superconductive transition in electromagnetic properties, the vibrational transitions in liquids and biophysical systems. At the end of the course, students will develop quantitative reasoning skills and analytical resolution skills useful for studying, modeling and understanding phenomena related to the electronic and vibrational properties of condensed m
SPECIFIC OBJECTIVES:
A - Knowledge and understanding
OF 1) Know the fundamentals of the different spectroscopies in the linear response
OF 2) To understand how to obtain the spectrum of the relevant excitations of dense and diliut liquids and crystalline solides.
OF 3) Understanding the principles of the interaction between radiation and matter neutrons matter
B - Application skills
OF 4) Learn how to choose the most advantageous spectroscopic technique for the study of specific condensed matter problems
OF 5) Understanding the complementarity between spectroscopic techniques
OF 6) Be able to understand the potential and experimental limitations of the various techniques considered
C - Autonomy of judgment
OF 7) To be able to apply in the future the acquired skills to the more general context of condensed matter physics
D - Communication skills
OF 8) Knowing how to communicate the basic concepts of the different spectroscopic techniques and the results potentially obtainable in the various fields.
E - Ability to learn
OF 10) Have the ability to autonomously consult basic textbooks and in some cases scientific articles to expand the knowledge developed in the course
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