Title: Excitonic effects in MoSe2 monolayer

Abstract
In the last decade monolayers of transition metal dichalcogenides have drawn much interest due to their electrical and optical properties, which differ from their bulk counterpart and make them suitable for technological applications in quantum computing and optoelectronics. In particular, - due to the different behaviour of the screening in the 2D and in the 3D cases - the optical properties of these low-dimensionality materials are dominated by excitons, which are bound pairs of an electron and a hole. In this talk I am going to present some interesting results regarding the behaviour of excitons in a particular member of this family, i.e. MoSe2, studied within the framework of many-body perturbation theory on top of ab-initio calculations.

Biography
Hi, I am Niccolò and I earned both my bachelor's and my master's degree at the University of Padua. I moved to Trento in order to pursue my PhD in the Materials Theory Group under the guidance of Professor Cudazzo. I am currently studying optical properties of transition metal dichalcogenides, with a particular focus on the exciton-phonon coupling, employing both theoretical and computational methods. 

Title: Functional Residues and Allosteric Pathways of Current and Ancestral Steroid Receptors highlighted using Information Theory

Abstract
Steroid receptors (SR) are nuclear proteins that, upon ligand binding, are able to bind to DNA as a dimer and induce post-translational modification to enhance or suppress sexual development and reproduction. SR evolved in the chordata phylum only, about 400-500 million years ago, with ancient sequences showing great similarities to the current ones. While many tools have been developed in phylogenetics to explore the relations between current and ancient sequences, little work has been done to investigate the allosteric mechanisms of these proteins. Information-theoretical measures, such as mapping entropy and mutual information, have proved to be effective in retrieving those amino acids that are involved in such pathways. Our preliminar results, analyzing an ancestor and six current SR, highlight the involvement of specific protein chains (H3, H4) in the allosteric mechanism. These findings will help understand how SR work and how their function evolved with the sequence. 

Biography
Hello! My name is Alessia Guadagnin Pattaro, I am a 2nd year PhD student in Physics with a Bachelor's in Chemistry and a Master's degree in Quantitative and Computational Biology. I am currently investigating protein dynamics, especially allosteric mechanisms in steroid receptors (the root cause of why your body transforms when you are about 10-12). When I'm not ranting about some error message or about proteins wiggling and vibing in the wrong way, you'll find me reading and writing science fiction stories.

Title: Finding order within disorder: structural modeling of glasses via the Reverse Monte Carlo method

Abstract
The physical properties of a material are determined by its atomic structure. This particularly relevant for disordered systems, as they are extremely widespread in all fields of technology, yet our structural understanding is still very limited.  I will present the first complete study of the structural evolution with temperature of v-GeO2, from the glass up to the liquid. This is done via a mixed approach, combining both experiments and simulations. In particular, neutron diffraction data are acquired at each investigated temperature, then the structure of the system is modeled via Reverse Monte Carlo algorithm, a very versatile and powerful method which allows to produce three-dimensional configurations compatible with experimental data. This way we captured the evolution of both the short- and medium-range structure of the system, and revealed the subtle structural differences between a glass and its parent liquid.

Biography
I completed both my Bachelor's and Master's degrees at the University of Trento, and then started a PhD in the Structure and Dynamics of Complex Systems group. My research focuses mainly on studying the structure of liquids and glasses, both experimentally and through simulations.

Title:  Search for antimatter in 10-30 MeV cosmic rays with the HEPD-02 instrument

Abstract
Monolithic Active Pixel Sensors (MAPS) are silicon-based solid-state detectors used in high-energy physics experiments, such as the Inner Tracking System of the ALICE experiment at CERN, valued for their high granularity and minimal material budget. We present the first application of this technology to a space-borne detector: the High Energy Particle Detector (HEPD-02), launched in June 2025 onboard the China Seismo-Electromagnetic Satellite (CSES-02). The main novelty of HEPD-02 is the first space use of ALTAI MAPS in the tracker system, featuring a digital read-out circuit integrated on the same silicon substrate. The tracker, with 80 Mpixel divided into three layers over a 15 cm × 15 cm area, achieves a 5 μm single-hit resolution. This high granularity allows reconstruction of the annihilation process, enabling antimatter identification and the potential detection of low-energy (10–30 MeV/n) annihilation, a range unexplored by previous experiments.

Biography
I was born and raised in Rome, where my passion for Physics began. After completing my B.Sc. at “La Sapienza” University of Rome, I started my M.Sc. in Bologna, focusing on Cosmic Ray Astrophysics. For my thesis, I developed a novel technique to predict the astrophysical background of antideuterons in Cosmic Rays using a state-of-the-art coalescence model, in collaboration with the ALICE (CosmicAntiNuclei) and AMS groups. Now in Trento, as part of the LIMADOU collaboration, I study the expected performance of HEPD-02 for antimatter searches.
Moreover, I'm member of the SPaRKLE collaboration as project manager and scientist. When I’m not doing Physics, you’ll probably find me spiking volleyballs—indoors or on the beach.

Title: SMART a SMall pArticle acceleRaTor on chip

Abstract
Dielectric Laser Accelerators (DLA) promise to revolutionize particle acceleration by sustaining ultra-high, GeV/m-scale gradients in microstructures powered by commercial lasers, enabling compact "on-chip" devices. This presentation briefly reviews the fundamental principles and the successful demonstration of DLAs for electrons (e-DLA), which provide the technological foundation for this work. The core of this presentation introduces a novel concept and design for a proton DLA (pDLA). We discuss the unique challenges posed by accelerating non-relativistic heavy particles, including phase stability and integrated focusing. We will present the preliminary design and simulation results (e.g., C++) used to validate this new pDLA scheme, analyzing its potential performance. This research explores a pathway toward compact proton sources for future applications, such as hadron therapy.

Biography
I was born in Livorno, Italy, in 1999. Although I was born there, I have always lived in Sardinia, specifically in Cagliari, where I completed both my undergraduate and master's degrees. I earned my Master of Science in Physics, specializing in Fundamental Interactions. My Master's thesis was on the Vertex and Muon Spectrometer of the NA60+ experiment.

Title: Transformer-Based Encoding of Jet and Track Features for Jet Flavour Tagging

Abstract
This work presents the development of machine learning algorithms for jet flavour tagging within the ATLAS experiment at CERN. Flavour tagging aims to identify the type of quark that initiated a particle jet by exploiting information from reconstructed tracks and detector objects, useful in both Standard Model measurements and searches for new physics. A transformer-based encoder is designed to capture complex correlations among tracks, with a self-supervised pretraining phase using contrastive learning to build effective track representations. The pretrained model is then fine-tuned in a supervised setting to perform jet flavour classification, achieving a flexible and data-driven approach to jet tagging.

Biography
I come from Brianza, Lombardy, a small agricultural and industrial region between Milan and Lecco. I studied Physics at the University of Milan, specializing in Theoretical Particle Physics. I now work mainly on applications of machine learning techniques for particle data analysis, with a focus on jet flavour tagging.

Title: False Vacuum Decay in a Ferromagnetic Superfluid

Abstract
In our lab, we use a superfluid spin mixture of ultracold sodium atoms as a platform to simulate quantum field theories. By engineering metastable configurations of the effective field, we prepare a false vacuum state and study its decay. Our recent work explores the role of temperature in the relaxation dynamics and the expansion of the relaxed region. These experiments demonstrate the versatility of cold atom systems for investigating non-equilibrium quantum dynamics.

Biography
I am a PhD student in the Department of Physics at the University of Trento, where I work on experimental ultracold gases. My research uses superfluid spin mixtures of ultracold sodium atoms to simulate quantum field theories and study false vacuum decay and non-equilibrium quantum dynamics. I completed my bachelor’s degree in Physics at the University of Padova and my master’s at the University of Trento, where I carried out my thesis in the same group where I am now pursuing my PhD. Outside the lab, I enjoy climbing, trail running, and ski mountaineering.

Title: Comparison of Three Photonic Neural Networks for Chromatic Dispersion Equalization

Abstract
Photonic neural networks (PNNs) process information directly in the optical domain, enabling reduced energy consumption and enhanced processing speed in telecommunication systems.

These architectures are particularly promising for mitigating signal distortions accumulated over long fiber transmissions.

However, distortions due to chromatic dispersion remain a major obstacle to effective signal equalization. In this talk, we present an algebraic, numerical, and experimental comparison of three PNN architectures acting as signal equalizers for low-power 10G PAM-2 1550 nm signals after transmission through up to 300 km of fiber. Results show that all architectures achieve comparable performance at a given signal-to-noise ratio, with differences in optical power losses.

Biography
I am Stefano, a second-year PhD student at the University of Trento, working in the Nanoscience Laboratory.
I completed both my Bachelor's and Master's degrees at the same university, and my current research focuses on two main areas.
First, I experimentally and theoretically investigate the performance of all-optical photonic neural networks for tasks such as signal equalization after fiber distortion.
Second, I study nonlinear photonic complex systems, primarily using linearization, stability analysis, and bifurcation theory to gain a deeper understanding of their dynamics. These systems are possible building blocks of future, more complex neural networks.