Università Cattolica del Sacro Cuore

Research projects started in 2021

Machine learning applications to physics research

Student: Cassio Cristani

Background and motivation

This research project lays in the flourishing intersection between Computer Science and Physics. In last years it has been observed that machine learning is coming to hold a crucial position in fields of physical science ranging from particle physics to cosmology, quantum many-body physics, quantum computing, and chemical and material physics [1].
Examples of successful applications of machine learning techniques to physics research include, among others: discovering gravitational lenses [2], constructing effective variational many-body wavefunctions in interacting systems with long-range entanglement [3], identifying phase transitions from entanglement spectra [4], characterizing dynamical phases in closed quantum systems where statistical mechanics is not applicable [5], etc. 
On the other hand, machine learning development can benefit from physics research, in particular for the understanding of internal operations. In fact, one of the major open problems in machine learning is related to explainability, in particular with deep neural networks: these algorithms can perform very well in some tasks (e.g., classification) but it’s difficult to understand exactly why, both in theory and in practice.  Examples of how machine learning theoretical development can exploit physical research are the recent proposal of an explanation for the performance of deep learning based on renormalization group theory [6], and an approach to clustering based on statistical physics [7].
The goals of the present project are: exploring the connections between physics and computer science, developing ad hoc machine learning models for physics research, and proposing new techniques for explainable machine learning.

Supervisors

Dr Enrico Barbierato, UCSC, Italy, enrico.barbierato@unicatt.it
Prof. Yi-Ting Hsu, ND, USA, yhsu2@nd.edu

Large scale ozone risk assessment for vegetation, from past years to the end of the century under different climate change scenarios

Student: 

Background and motivation

Ozone (O3) is a secondary pollutant that can cause visible injuries to vegetation in general, but also relative growth reductions in forest plants and crop yield losses in agricultural species1. The phytotoxic ozone dose (POD) index seems the best suited for the estimation of the impact of stomatal ozone deposition under future climate. The project will be focused on modeling activities aimed at defining an integrated procedure based on meteo-chemical data, spatialization techniques and deposition models to produce regional scale maps for the ozone risk assessment for vegetation in Europe.

The main goals of the project are:

  • the calibration and validation of a model for the estimation of the phytotoxic ozone dose absorbed by vegetation (wheat and poplar will be used as reference receptors for crop and forest species, respectively) at 1km2 resolution in non-complex terrain;
  • the production of O3 risk assessment maps for vegetation based on future climate change scenarios in order to outline possible mitigation strategies for the O3 impacts.

The candidate is expected to acquire the knowledge in the fields of environmental data elaboration, atmospheric pollutants deposition, plant physiology and soil water dynamics modelling, risk assessment.

Supervisors

Prof. Giacomo Gerosa, UCSC, Italy, giacomo.gerosa@unicatt.it
Prof. Paola Crippa, ND, USA, pcrippa@nd.edu
Dr. Riccardo Marzuoli, UCSC, Italy, riccardo.marzuoli@unicatt.it

 

Study of Cooperative Optical Phenomena in Artificial Solids of Nanocrystalline Metal Halides

Student: Umberto Filippi

Background and motivation

Light-emitting nanocrystals of metal halides provide an opportunity to engineer artificial solids with a cooperative emission. Such solids, known as colloidal nanocrystal superlattices, are a promising platform for applications in quantum photonics and information science. The project will address two important aspects of colloidal nanocrystal superlattices and light emission from them.
First, there is a need to discover single- and multi-component nanocrystal solids made of recent generations of colloidal nanocrystals that include (but are not limited to) lead halide perovskites, lead-free double perovskites, and lead chalcohalides. Despite rapid progress in synthesis and optimization of such nanocrystals, little is known about the diversity of colloidal superlattices that they can form.
Second, there is a need to investigate the cooperative response of such superlattices upon interaction with optical excitation. For example, there are preliminary indications that pulsed laser excitation of cesium lead bromide nanocrystals produces intensity-dependent oscillations and acceleration of radiative decay. Such response could be indicative of cooperative effects, whether that is the case is not well understood.
In the present project we will combine state-of-the-art facilities in the partner institutions. The synthesis and characterization of the colloidal superlattices will be carried out at the Italian Institute of Technology (IIT) in Genova (supervisors: prof. Liberato Manna and Dr. Dmitry Baranov). The investigation of collective and cooperative phenomena in colloidal superlattices will be carried out in collaboration with the group of prof. Claudio Giannetti at Università Cattolica (UCSC) in Brescia and in collaboration with the group of prof. Masaru Kuno at Notre Dame University (ND). A specific multidimensional optical spectroscopy setup will be developed @UCSC to investigate the decoherence dynamics of optical excitons and hunt for evidence of changes in the ultrafast decoherence driven by cooperative phenomena.

The main goals of the project are:

  • Synthesis and characterization of novel colloidal superlattices
  • Investigation of collective and cooperative phenomena in colloidal superlattices excited by tunable ultrafast light pulses in the weak and strong excitation regimes to manage cooperative absorption and emission on ultrafast timescales.  

Supervisors

Prof. Liberato Manna (IIT) Italy, liberato.manna@iit.it
Dr. Dmitry Baranov (IIT) Italy, dmitry.baranov@iit.it
Prof. Masaru Kuno (ND) USA, mkuno@nd.edu
Prof. Claudio Giannetti (UCSC) Italy, claudio.giannetti@unicatt.it