University of Torino

Graduate Program in Physics

Course proposal (2021-2022)

Title 01-  Introduction to Supersymmetry
Prof. Igor Pesando,
Period Every Tuesday and Wednesday  from 16 November to mid December, h 11:15-12:45, Aula Fubini
Programme *Chiral multiplet in 4D,Coleman-Mandula theorem, R symmetry, susy action for chiral superfield, non renormalization theorem and holomorphy
*  Vector multiplet in 4D Wess-Zumino gauge, susy action for vector multiplet
*  Susy breaking: O' Raifeartaigh model, Fayet-Iliopoulos model, soft breaking
*  Basic of MSSM the action and  unwanted symmetries
*  Moduli space of the vacua and IR effective description


Students who are willing to attend this course are **REQUESTED** to register by sending an email to the teacher


Title 02-Introduction to the large-N limit
Prof. Marco Panero,
CFU 5, 20 hrs
Period 24 January-4 February 2022, h 16-18
delivered by distance learning via Webex
(online synchronous lessons)
Programme 1 - Introduction
2 - The large-N limit in O(N) vector models
3 - QCD with many colors: The 't Hooft limit and its phenomenological
4 - The role of the large-N limit in the gauge/gravity correspondence

Students wishing to take this course must register with the teacher via email



Title 03-Many-body techniques for nuclear theory
Prof. Andrea Beraudo,
Marzia Nardi,
CFU 5, 20 hrs
Period Mid March 2022
Programme - Symmetries and Thermodynamics of QCD;
- Weak-coupling calculations in thermal field-theory;
- Effective Lagrangians for hadronic and quark matter
- Relativistic calculations of nuclear and neutron matter

- Inter-nucleon forces
 -Ab initio techniques for the nuclear many-body problem
a. Exact methods
b. Correlation-expansion methods
c. Symmetry-breaking methods
-Equation of state of nuclear matter and neutron stars


Students wishing to take this course must register with the teacher via email


Title 04-Dark Matter physics
Prof. Marco Regis,
Period First week (10h): February 7-11, 2022, 11am-1pm.
Second week (6h): February 21-23, 11am-1pm.
Third week (4h): March 7-8, 11am-1pm.
Programme - Cosmological and astrophysical evidences for dark matter
- Dark matter candidates: WIMPs, Axions, Sterile neutrinos, Primordial black holes
- Direct, indirect and collider searches 
- Hands-on learning

Understanding the nature of dark matter is one of the defining scientific problems of our age.
The first week of the course will be devoted to an overview of the observational evidences for dark matter and to the methods that have been proposed to unveil its fundamental properties, focusing, in particular, on the mostly studied candidates, such as WIMPs, axions, sterile neutrinos and primordial black holes.
During the second and the third week, we will discuss together some current open issues in the dark matter field.

Students wishing to take this course must register with the teacher via email

Title 05-  Effective field theory techniques for New Physics searches
Prof. Martin Jung,
CFU 5, 20 hrs
Period April-May 2022
Effective field theories (EFTs) constitute an essential technique in physics, allowing for the systematic separation of largely different scales in a problem, i.e. for exploiting hierarchies.
Such hierarchies occur everywhere in physics; in the Standard Model (SM) examples are the hierarchy between the masses of the massive gauge bosons and the top quark compared to those of all other fermions, or the mass of the bottom quark compared to typical hadronic scales. Importantly, the absence of indications for new states beyond the SM ones indicates that such states might be very heavy. As a consequence, their impact on low-energy observables can be treated in an EFT framework; precision measurements at much lower energies can then be used to constrain New Physics models strongly, even if the corresponding states cannot be produced at existing colliders.

The plan of the course is to introduce EFT techniques in general, discussing their applicability and restrictions. The developed methods are then applied to specific classes of observables relevant to the discourse of NP, in order to explicitly demonstrate how constraints on NP scenarios are obtained.

Students wishing to take this course must register with the teacher via email

Title 06-  Introduction to on-shell amplitudes
Prof. Simon Badger,
CFU 6, 24 hrs
Period March-April 2022
Programme Scattering amplitudes can be seen as fundamental building blocks for Gauge, Gravity and String theories. The study of their mathematical structure has led to many new insights into connections between seemingly unrelated topics as well as enabling new computations unfeasible with conventional techniques. In this course I will cover some of the new methods that are now being used to provide efficient and precise predictions for higher order corrections at colliders.

1) Spinor-helicity methods for massless and massive particles.

2) Tree-level techniques: on-shell and off-shell recursion.

3) Loop amplitude techniques: unitarity, integrand reductions, IBPs and finite fields, differential equations and special functions.

4) New methods for gravity amplitudes: the double-copy and applications to gravitational waves.
Note(s) Students wishing to take this course must register with the teacher via email

Title 07-Introduction to non-perturbative solutions in field theory
Prof. Marco Billo',
Period January 2022, 31-February 2022, 3: h 10-12, Aula Fubini

``Topological'' classical configurations of fields: kinks, vortices, monopoles and instantons.
Instantons as tunneling solutions in Quantum Mechanics, then in Yang-Mills.

NOTES Students wishing to take this course must register with the teacher via email

Title 08-Experiment design in particle physics
Prof. Linda Finco,
Period TBD
Prerequisites Basic knowledge of particle detectors, interactions of particles and radiation with matter, physics at colliders
Goals The student will learn in an interactive way how particle physics experiments are designed, according to the processes they have to measure and the precision they want to achieve.
  • Select a physical process:
  • Why this physical process is of interest?
  • Previous measurements – if any – and their precision
  • Identify which type of accelerator machine is best for producing it
  • Analyze signal properties and topology of the final states
  • Identify the possible background contributions
  • Design an experimental apparatus to measure the process under study:
    • Analyze what kind of detectors are needed (vertex detectors, caloremeters, muon chambers...)
  • Choose their characteristics according to the precision we want to achieve 
  • Develop a strategy to select signal events (trigger and analysis procedure)
  • Identify the main systematic uncertainties due to detector effects
  • Determine the needed statistics
Notes Students wishing to take this course must register with the teacher via email

Title 09-Data Analysis Techniques
Prof. Livio Bianchi
Period TBD
Prerequisites Basics on statistics and probability theory
Basic programming skills in c/c++
Programme Reminder of basic probability theory
Monte Carlo methods (basic)
Statistical methods for:
- Parameter estimation (confidence intervals)
- Hypothesis testing (general, goodness-of-fit)
Bibliography See last year's course webpage

Students wishing to take this course must register with the teacher via email

Students wishing to take this course must register with the teacher via email

Students wishing to take this course must register with the teacher via email

Title 10-Hands on fitting and statistical tools for data analysis
Prof. Giacomo Ortona,
Period TBD
Prerequisites Make sure before the classes to have an account on the local machines, or bring your laptop with a ROOT/RooFit installation
Programme The class will have an exercise oriented approach, with quick reminders of the statistical theory and a large fraction of time dedicated to practical examples.

Fitting Tools
      Usage of the RooFit library:
      Signal and background modelling, fitting and plotting
      Treatment of extended Fits, Conditional Probability Density Functions, Toy Monte-Carlo generation

Statistics Tools
     Usage of the RooStats library:
     Hypothesis testing
     Determination of Upper Limits
     Determination of confidence intervals in likelihood ratio and Feldman-Cousins approaches
     Determination of probability intervals in Bayesian approaches
     Bayesian numerical calculators vs Markov-Chains MC approach 

Students wishing to take this course must register with the teacher via email

Title 11-  Big Data Science and Machine Learning
Prof. F. Legger,
Period  TBD
Prerequisites  Basic knowledge of python


Data science is one of the fastest growing fields of information technology, with wide applications in key sectors such as research, industry, public administration. The course will cover the definition of big data and the basic techniques to store, handle and process them. Machine Learning (ML) and Deep Learning (DL) algorithms will be briefly introduced. We will focus on the technical implementation of different ML algorithms, focusing on the parallelisation aspects and the deployment on distributed resources  and different architectures (CPUs, FPGAs, GPUs). A basic introduction to the current computer architecture will be given, with a focus on parallel computing paradigms aimed at the exploitation of the full potential of parallel architectures. An overview of the fundamental OpenMP and MPI coding patterns is covered during hands-on sessions.


- Introduction to big data science
- The big data pipeline: state-of-the-art tools and technologies
- ML and DL methods: supervised and unsupervised training,   neural network models
- Introduction to computer architecture and parallel computing patterns
- Initiation to OpenMP and MPI
- Parallelisation of ML algorithms on distributed resources
- Beyond CPUs: ML applications on distributed architectures, GPUs, FPGAs


Chen, M., Mao, S. & Liu, Y. Mobile Netw Appl (2014) 19: 171.

Yao, Yuanshun & Xiao, Zhujun & Wang, Bolun & Viswanath, Bimal & Zheng, Haitao & Y. Zhao, Ben. (2017). Complexity vs. performance: empirical analysis of machine learning as a service. 384-397. 10.1145/3131365.3131372

NOTES Students wishing to take this course must register with the teacher via email

Title 12- Bayesan inference
Prof. Stefano Camera,
Period TBD
Students wishing to take this course must register with the teacher via email

Title 13-Search and characterization for extrasolar planets
Prof. Alessandro Sozzetti,
Period TBD
Programme -Elements of theory: planetary formation, internal structure and atmosphere, dynamic evolution;
- Detection techniques, instrument limitations and astrophysics;
- Observation of extrasolar planetary systems: statistical, structural and environmental properties
- Observation of extrasolar planetary systems: the next 15 years.

Students wishing to take this course must register with the teacher via email

Title 14-Chemo-dynamical evolution of the Milky Way
Prof. Alessandro Spagna(
Period TBD

Structure, kinematics, and chemical properties of the Galactic stellar populations (disks, bulge, halo)
Non axi-symmetric components: bar, spiral arms, flare, warp
The hierarchical CDM galactic formation scenario
Elements of Galactic dynamics and cosmological simulations of Milky Way-like disk galaxies
Wide field stellar surveys (Gaia, RAVE, APOGEE, GES)
Local cosmology: chemo-dynamical signatures of the Galactic formation processes

Binney & Merrifield, Galactic Astronomy


Students wishing to take this course must register with the teacher via email

Title 15-  Quantum communication
Prof.  Ivo Degiovanni
CFU 5- 20 hours
Period TBD
Programme a)    Introduction to quantum information
The qubit concept
Qubit practical realisations
No-cloning theorem
Quantum state tomography

b) Quantum Cryptography with single photons
      Quantum key distribution
      Experimental implementations
      Von Neumann Entropy vs. Shannon Entropy
      Eavesdropping strategy and security criteria

c) Quantum entanglement
      Entangled states and their properties
      Practical realisations
      Bell’s inequality

d) Quantum Cryptography by entangled states
Experimental implementations

e) Quantum protocols
Teleportation of qubits
Teleportation of entanglement: entanglement swapping
Quantum dense coding
Experimental implementations of Bell’s state analysis

f) Generalized evolution of quantum systems
       Quantum operations
       Tomography of quantum operations

Title 16- Experimental implementation of quantum devices
Prof. Jacopo Forneris,
CFU 2, 8 hrs
Period TBD
Goals Luminescent defects in wide band gap materials are promising candidates for technological applications based on photonics and provide a viable path towards the practical realization of quantum devices. This course provides an introduction to the current trends in experimental quantum
optics and material science, based on the fabrication and exploitation of single-photon sources for quantum information processing and quantum sensing.
Programme 1. Introduction to solid state quantum computing
   Qubits and block sphere
   quantum gates
   errors and decoherence
   Practical systems

2.Single-photon sources based on solid state defects
   Ideal single-photon sources
   Single-photon sources in wide band-gap materials
   Experimental methods for sources characterization: confocal microscopy
and quantumness quantifiers
   Case studies and practical examples

3. Fabrication of of single-photon sources
   Motivation and challenges of deterministic implantation
   Techniques for high-resolution source placement
   Individual ion delivery and detection
   Formation yield

4. Technological applications of single-photon sources
   Integrated quantum devices
   Electrical control of single-photon sources
   Quantum sensing with individual spins in diamond
   Applications and examples

Students wishing to take this course must register with the teacher via email

Title 17-Neutron Imaging and Neutron Diffraction

Prof. Francesco Grazzi,


Spring 2022 (april-june)


Learning the basic principles of neutron-matter interaction, and how to exploit them to study matter.
Learn the principles of neutron imaging (radiography and tomography and be able to evaluate the possible use of this technique to characterize materials
Learn the principle of time of flight neutron diffraction and the Rietveld method for quantitative phase analysis, residual stress analysis and microstructural characterization of crystalline materials.


                Thermal and cold neutron-matter interaction, elastic scattering law, cross section. (1 hr)

                Principles of neutron production, concept of neutron beamlines (1 hr)

                Neutron imaging, Lambert beer law, attenuation law, neutron geometry and optics, example of beamlines, data analysis (radiography and tomography) (3 hrs)

                Neutron diffraction, Bragg law, scattering law, basics of crystallography, neutron instrument geometry and parameters, data analysis (Rietveld refinement using GSAS code) (3 hrs)

                Tutorial on the use of imaging and diffraction software. (2 hrs)

                Practical exercise on data analysis. (2 hrs)


Course material and references will be distributed throughout the course


Lessons are given in open seminar form.

Students wishing to take this course must register with the teacher via email