Astrophysics of compact objects

The course will introduce the nature of astrophyisical compact objects and their emission, both from a theoretical and observational point of view. The program of the lectures is:
a) Introduction to compact objects: white dwarfs, neutron stars and black holes.
b) Black holes: general properties. Schwarschild and Kerr metrics
c) Neutron stars. Pulsars: general properties and emission mechanisms.
Pulsars as General Relativity laboratories
 

Evolution of galaxies and AGN at high redshift

Formation and co-evolution of galaxies and AGN. New observations and results. The accretion and star formation history.
The galaxy and AGN luminosity functions.
The super-massive black hole mass function.
Evolution of the black hole mass - bulge scaling relations.
Feedback. The role of radio jets. Merging and interaction.
The large scale structure distribution.

Spectroscopy of Astrophysical Plasmas

Programme:
 
-Spectroscopic Notation, Energy Levels, Transitions: selection rules -Basic Processes, The Ionisation Balance -Line Radiation: Emission -Line Absorption, Dust Extinction, Photoionised Plasmas
 

Introduction to Axion Physic

The program offers a comprehensive introduction to the field of axion physics, covering a range of subjects from particle physics to astrophysics and cosmology, including the principles of axion detection. It caters to a diverse group of students with interests in both theoretical and experimental studies.

• Part 1 (10h): Axion and Particle Physics

The strong CP problem and the QCD vacuum structure
Peccei Quinn mechanism
Axion chiral potential (axion mass and coupling to photons)
Axion effective Lagrangian (Georgi-Kaplan-Randall basis)
Benchmark axion models (KSVZ/DFSZ)

• Part 2 (3h): Axions in Astrophysics:

• Part 3 (3h): Axions in Cosmology (4h)

• Part 4 (2h): Axion detection

 

Statistics and Machine Learning Methods for Climate Data

Program
The objective of the course is to show how modern machine learning and deep learning techniques can be used to analyze large climate datasets and to build predictive and generative models.
After a brief introduction to the specific characteristics of climate data, often complex, noisy and with multiple temporal and spatial scales, real use cases will be presented such as climate forecasting, downscaling and the generation of future scenarios, with practical exercises on real datasets. In this context, it is also planned to test and discuss the use of recent AI models for weather and climate forecasting, such as GraphCast, Aurora and other next-generation models, evaluating their strengths and limitations.
Syllabus
How to analyze geophysical data
Statistical methods for geophysical data
PCA, FFT, wavelet.
Netcdf data and xarray
Machine Learning Methods
Random Forest, XGBOOST, Support Vector Machine
Neural Networks, Convolutional Neural Network,
LSTM: Long-short term memory Neural Networks
GNN: Graph neural networks
How to design a Machine Learning experiment
Indicators, metrics and analysis.
AI models for meteo and climate: Graphcast and Aurora.
 

EXTRASOLAR PLANETOLOGY

Description
The discovery of about 4000 extrasolar planets, gives a new start to the astrobiological research,
allowing to go further the Solar System. Moreover, the physical and orbital characteristics of the
new worlds, very different from those of our Solar System, are critical for the classical theory of the
planetary formation. The course aims to describe the experimental techniques for the search and
characterization of extrasolar planets, the statistical and physical results obtained up to now, the
consequences on the astrobiological studies and the search for life in other worlds than Earth. In
particular, the following points will be discussed:

• The techniques exploited to search for extrasolar planets.
• Observing techniques for the characterization of Exoplanet's atmospheres.
• Hints on the planetary formation and the migration theory. Pro and cons of both the core
  accretion and disk instability theories.
• Main results obtained in the exoplanets research. Known and unknown things (statistic
   properties, metallicity vs formation, orbital properties, mass period and eccentricity
   distributions, etc. etc.)
• Giant planets and Brown dwarfs physics. The hot Jupiters topic will deepen.
• Terrestrial and rocky planets physics. The super-Earths.
• The concept of the habitable zone, its definition in the Sun case and its extension to the other
  stars.
• The search for life as astrophysical problem.

Physics of planetary ices

Ices in the Solar System
Geophysical techniques for planetary ices investigation
Electrical properties of ices
Subsurface radar on planetary and terrestrial ices
Laboratory measurements on planetary ices

 

Space Weather

According to the European Space Agency, Space weather refers to the environmental conditions in Earth’s magnetosphere, ionosphere and thermosphere due to the Sun and the solar wind that can influence the functioning and reliability of spaceborne and ground-based systems and services or endanger property or human health. As the several branches of application, the theme is very alive all over the world and carried out by teams representing different competences, such as physics, engineering, mathematics, chemistry, biology and medicine.
The course offers an overview of the physical mechanisms triggering the extreme events to highlight the space weather complexity and to represent the competences necessary to develop effective mitigation and forecasting strategies. Finally, the proposed course intends to highlight the scientific, technological and societal challenges still unsolved, also providing example of vulnerable technologies in the daily life.

• Space weather: science or service?
• Weather and climate in the circumterrestrial space
• The Sun, the solar wind, the magnetosphere and the ionosphere
• Space weather applications: how to predict and mitigate the impact on communication and navigation systems
• Space weather programs and services all over the world

 

Time series analysis

1. We will recall the basic principles of applied and numerical Fourier analysis: Fourier series and transform, energy and power spectrum, mutual and autocorrelation and their numerical computation.
2. Impulse and harmonic response of a system.
3. Filtering of a time series.
4. Time series as sampling of a continuous signal.

Inversion methods in geophysics

This course is an introduction to geophysical inversion methods. The course will deal with both the resolution of linear and nonlinear problems using deterministic approaches such as the least squares method, the SVD, and regularization techniques as well as purely probabilistic approaches such as Markov chain Monte Carlo methods. The theory is illustrated through some examples taken from geophysical problems and their solution is discussed by performing inversion algorithms in the classroom.
References Books:
A. Tarantola, Inverse Problem Theory and Methods for Model Parameter Estimation, Siam
M. Bertero and P. Boccacci, Introduction to Inverse Problems in imaging, IoP
W. Menke: Geophysical Data Analysis: Discrete Inverse Theory. Academic Press


 

Enhanced sampling techniques

The course provides an introduction to the main enhanced sampling techniques used to study molecular systems characterized by metastability and multimodal free energy surfaces. The aim of the course is to provide students with both the theoretical background and the practical tools to estimate free energies and transition pathways from molecular dynamics simulations.
Course contents:

• Metastability and rare events
• Collective Variables
• Umbrella Sampling and free energy reconstruction methods
• Metadynamics

Introduction to Spintronics

1. Spin and charge coupled density diffusion equations.
2. Giant Magnetoresistance Effect (GMR)
3. Spin-orbit coupling in metals and semiconductors (Rashba, Dresselhaus, etc.)
4. Extrinsic Spin Hall Effect.
5. Intrinsic Spin  Hall Effect.
6. Graphene and Topological Insulators.

Experimental Flavour Physics

• Flavour Physics Lectures   (A. Passeri)
  
  Definition of flavour and flavour physics.
  Flavour and Higgs.
  CKM matrix. Unitarity triangles.
  Flavour physics beyond the Standard Model
  Lepton Flavour Violation.
  Introduction to CP violation.
  CP violation in Kaons. Experimental measurement in NA48 and KLOE.
  Cabibbo angle (Vus) measurement fro charged and neutral kaon decays.
  Rare and very rare kaon decays.
  The GIM mechanism and observation of the charm quark.
  Charmed hadrons lifetimes.
  Leptonic and semileptonic charm decays.
  D meson mixing.
  Charmed mesons decay asymmetries.
  Accelerators and experiments for b physics studies.
  B meson mixing and CP violation.
  Measurement of angles and sides of the b unitarity triangle.
  Experimental measurement of Bd and Bs mixing.
  B hadrons lifetimes
  Search for new physics with B and D mesons decays.
  The leptonic flavour in the Standard Model.
  LFV beyond the SM.
  Mu-> e gamma and the MEG experiment.
  Future prospects: Mu2E proposal
  Tau LFV decays at B factories.
  Electrical dipole moments in physics BSM and their measurement.

Experimental High Energy Physics at Colliders

- Accelerator Physics, Detectors (Lecture 1)

- Reconstruction of Objects (Lecture 2) - Cross Section Measurements (Lecture 3) - Cross Section Measurements (Lecture 3,continued)
- Kinematics, Feynman Diagrams (Lecture 4)
- pdf’s
- MC Generators & Geant

- Electro Weak Physics (Lecture 5)

a) Standard Candles (Low Mass Resonances, W Boson, Z Boson)
- QCD Physics & B Physics(Lecture 6)
- Top Physics (Lecture 7)
- Higgs Physics (Lectures 8, 9)
- Susy Physics (Lecture 10)
- Exotic Physics
- Future Accelerators and Perspectives (Lecture 11)

 

Hadron interactions at high energy

Experimental environment: ISR, SppS, Tevatron, RHIC, LHC.
General characteristics of low momentum-transfer interactions.
Inclusive particle production. Elastic, diffractive, total cross section.
Quantum chromodynamics, quark and gluons, colour factors, a_S(Q²).
Deep inelastic lepton scattering, structure functions and Q² evolution.
Parton density functions, Monte Carlo event generators, parton shower.
Drell–Yan, W and Z production.
Hadronic jets, jet-reconstruction algorithms, event-shape variables.
Inclusive jets, jet-pairs, jet-photon, multi-jet production.
Jet fragmentation function.
Measurements of a_S(Q²).
Relativistic nuclei collisions, the quark-gluon plasma.
General characteristics of AA collisions, signals of plasma formation.
 

Advanced course on the Standard Model

- Part I - Prof. Bonvini (Infn Roma 1)

1 Fundamentals of QCD
         - The Standard Model and the QCD lagrangian
         - Local, global and approximate symmetries of QCD
           - The QCD vacuum and the strong CP problem
 2 Perturbative QCD
        - The running of the strong coupling
        - Variable flavour number (renormalization) scheme
        - Infrared divergences in QCD
        - Collinear factorization and parton distribution functions
        - DGLAP evolution
        - Variable flavour number (factorization) scheme
        - PDF determination
        - All-order resummations
        - Divergence of perturbative expansions and Borel summation

- Part II: Flavor Physics and Lattice QCD - Prof.  V. Lubicz 6 hour (Roma Tre)

   1) Flavor Physics and its motivations
    -  Open questions in the Standard Model
    -  The flavor sector
    -  Flavor Physics and New Physics searches

    2) Introduction to Lattice QCD
    -  The lattice regularization
    -  The QCD action on the lattice
    -  Monte Carlo simulations and importance sampling
    -  Correlation functions
    -  Systematic Errors

     3) Flavor Physics on the lattice
    - QED corrections and isospin breaking effects
    - Quark masses and the hadronic spectrum
    - The Cabibbo angle and the unitarity test
    - QED corrections and isospin breaking effects in hadronic processes

- Part III Electroweak physics - Prof. G. Degrassi 6 hour (Roma Tre)

   Standard Model Review
    - Definition of the Fermi constant
    - The rho parameter
    - The custodial symmetry
    - Gaugeless limit of the Standard Model

   Renormalization of the Standard Model
    - The  Delta r and Delta kappa parameters
    - The Ms bar and On-Shell renormalization schemes
  
   Precision Physics
    - g-2
    - Indirect determination of the top and Higgs masses
    - Theoretical constraints on the Higgs mass
    - Higgs decays and production
 

Elements of Group Theory and GUT

- Grand Unified Theories: SU(5) and SO(10)
- Models of neutrino masses and mixing

Communicating Science

• You can’t not communicate (1st law of communication).  But at the same time, communicating efficiently is an ability that needs to be learned and constantly improved.  This is always a must, but most of all in the field of science, where convincing the public (and investors) of the importance of your research is becoming everyday more important.
  This didactic module is an introduction to communication for future researchers, engineers, technicians and any other profession related to science.  We do not intend to train professional communicators but to provide to a PhD student some communicating skills he will need sooner or later in his future work, like talking to an audience, presenting the results of his work to an investor, collaborating with press offices, managing interviews by journalists, writing articles for different media, making a website to spread his results, organizing fund raising activities.
  The module is based on hands-on activities and laboratories , starting from the analysis of science communication Case Studies that will be presented and discussed in italian and/or in english (depending on the content) .
   

Communicating science: public speaking (Module B of the course "Communicating Science")

Physics Education

The course will present the founding ideas and main results of research in Physics Education, which, over the past decades, has developed a set of methods, knowledge and applications useful for those who want to try their hand at teaching physics.  
Some of the fundamental aspects of teaching and learning physics will be addressed: the difficulties and common understandings of students, the role of experiments, models and analogies, the educational reconstruction of content, learning paths, teachers' professional development.   
Teaching aims to promote doctoral students' reflection on how to adapt physics content to a specific teaching context, be it University or School.   
Teaching activities will be carried out through interactive lecturing, demonstrating, classroom discussion.

 

Statistical Methods

Infrastructure and best practice for using high-performance computing systems

Motivations and objectives of the course: Modern physics research
requires an intensive use of computing operations that require computing
resources that are not available on personal devices but are available
on advanced and shared computing systems such as Cloud, GRID and
Cluster. The course is aimed at young researchers interested in
accessing computing resources on advanced architectures. In this course
we will explain high-performance shared computing infrastructures and
architectures and techniques for efficiently using multi-core systems
and advanced data storage systems. The course will be carried out
through the use of slides for the theoretical part and for the practical
part the resources of the Department's computing cluster and the INFN
section will be made available

Plan:
·       Introduction to advanced computing systems
·       Introduction to scheduling systems and batch systems.
·       Data storage systems: local, network and parallel file system
architectures.
·       Porting  of applications to HPC systems.
·       Best practice for measuring and optimizing performance on HPC
systems.

 

Inotroduction to Data Analysis and Machine Learning with Python

Acquisire competenze per l'implementazione al calcolatore di programmi ad alto livello nel linguaggio interpretato
Python. Conoscere i costrutti fondamentali di Python e la sua applicazione a casi d'uso legati al calcolo scientifico e
all'elaborazione dei dati.