Students of the past Physics studies will give next Thursday 21st, December 2023, a series of presentations for all students.
Thursday 21st December 2023, Aula 5 (Palazzina di fisica)
Program
09.15-09.30 – Presentation
09.30-11.00 – Quantum computing (Edoardo Ballini, Stefano Scali)
11.00-11.15 – Coffee break
11.15-12.45 – Complex networks (Edoardo Maggioni, Luigi Palmieri)
12.45-14.00 – Lunch
14.00-14.45 – Computational neuroscience (Teo Fantacci)
14.45-15.30 – Astrophysics (Bartolomeo Trefoloni)
15.30-15.45 – Coffee break
15.45-16.30 – Panel discussion
Abstracts
● Quantum computing, le potenzialità di un vantaggio esponenziale – Edoardo Ballini,
Stefano Scali
In this first lesson we will see what quantum computing means and what the
reasons to do so. We will compare classical and quantum algorithms and see how to use a
quantum computer to simulate physical systems. Finally, we will discover what doing research means
in this context in the specific case of quantum topological data analysis.
● Complex networks, un approccio sistematico alla complessità – Edoardo Maggioni,
Luigi Palmieri
In this lesson, network theory will be introduced, starting from what networks are,
how we can measure them and the main models for generating random networks. In the
second part an application of this theory in the case of systems will be presented
distributed, giving as an example a diffusion dynamic on networks and its analogies
with that of heat.
● Computational neuroscience, statistical mechanics and learning – Teo Fantacci
In this lesson an application of statistical mechanics in the field of
computational neuroscience. In particular we will see how it is possible to simulate a network
artificial neural system based on local learning through a modification of the models used
in the physics of matter. To conclude, I will share the challenges and benefits of moving
in different research fields, such as neuroscience, with a background in physics.
● Astrophysics, il fit lineare di un insieme di dati: niente di più semplice, giusto? –
Bartolomeo Trefoloni
In this lesson we will introduce some useful concepts for testing linear correlation
within a data set and quantify the parameters that describe it. They will come too
briefly examined some methods for evaluating uncertainties on these parameters and how
assumptions about data uncertainties influence the best-fit parameters.
● Panel discussion
In this session we will talk about experiences, possible study paths and possible difficulties
found in the years immediately following the triennial. What are the prospects after the three-year period?
What does it mean to study abroad? Dos and donts. A set of questions and topics for
demystify the three-year post. If you have any questions, we will try to give you answers!
