collaborators

7 papers

physics.data-an2025

Maximum Information Extraction Via Clustering and Minimization of Shannon Entropy

Matteo Becchi, Giovanni Maria Pavan

In the analysis of any type of system, granting maximum information extraction from its data is non-trivial. Confidence in successful information extraction typically builds on pri…

cond-mat.mtrl-sci2025

A rigorous data-driven approach to the nucleation of defects in metals exploiting the link between kinetic properties and (dis)order parameters

Mattia Perrone, David D. Girardier, Giovanni M. Pavan +1

Nucleation processes, through which a new structure progressively forms within a pre-existing homogeneous phase, are fundamental in materials science, but are also typically non-tr…

physics.chem-ph2025

Relevant, hidden, and frustrated information in high-dimensional analyses of complex dynamical systems with internal noise

Chiara Lionello, Matteo Becchi, Simone Martino +1

Extracting from trajectory data meaningful information to understand complex molecular systems might be non-trivial. High-dimensional analyses are typically assumed to be desirable…

cond-mat.mtrl-sci2025

Unsupervised Tracking of Local and Collective Defects Dynamics in Metals Under Deformation

Matteo Cioni, Mattia Perrone, Massimo Delle Piane +1

Metals owe their unique mechanical properties to how defects emerge and propagate within their crystal structure under stress. However, the mechanisms leading from the early emergi…

physics.data-an2025

Data-driven assessment of optimal spatiotemporal resolutions for information extraction in noisy time series data

Domiziano Doria, Simone Martino, Matteo Becchi +1

In general, comprehension of any type of complex system depends on the resolution used to examine the phenomena occurring within it. However, identifying a priori, for example, the…

cond-mat.mtrl-sci2024

A data driven approach to classify descriptors based on their efficiency in translating noisy trajectories into physically-relevant information

Simone Martino, Domiziano Doria, Chiara Lionello +2

Reconstructing the physical complexity of many-body dynamical systems can be challenging. Starting from the trajectories of their constitutive units (raw data), typical approaches…