arXiv subjects

Ezio Puppin

Publications and source records attributed to Ezio Puppin.

5 recordsLinked to original sources

arXiv2026

Machine-learning test of the single-ion model for $dd$ excitations in cuprates

We investigate $dd$ excitations in Resonant Inelastic X-ray Scattering spectra of YBa$_2$Cu$_3$O$_6$ and La$_2$CuO$_4$ using the local single-ion model. The data are analyzed by conventional global fitting and by a convolutional neural network trained within the same theoretical framework. For YBa$_2$Cu$_3$O$_6$, the excited state energies obtained with the two methods coincide, leading to the $xy$, $3z^2-r^2$, $xz/yz$ sequence for increasing energy. This result validates the use of machine learning tools for the analysis of RIXS spectra dominated by $dd$ excitations. By contrast, for La$_2$CuO$_4$, the two methods do not converge to a single solution, revealing the limitations of the single-ion model in describing $dd$ excitations in cuprates and pointing to the role of additional contributions beyond a purely local picture in shaping high-energy excitations.

cond-mat.str-el↗

arXiv2026

Rejection-free Glauber Monte Carlo for the 2D Random Field Ising Model via Hierarchical Probabilistic Counters

We present an efficient Monte Carlo algorithm for the simulation of the two-dimensional Random Field Ising Model (RFIM). The method combines the event-driven, rejection-free character of the Bortz Kalos-Lebowitz (BKL) algorithm with Glauber transition probabilities, introducing hierarchical probabilistic counters to perform spin selection in O(log N) operations. This enables efficient sampling of the system's dynamics, especially in the low-temperature and low-disorder regime, where traditional Metropolis updates suffer from critical slowing down. Furthermore, this approach allows a proper dynamical simulation of the Ising system's behavior even in the presence of a Random Field (RF), unlike the BKL method. RFIM simulations with Gaussian field distributions reproduce the expected reduction of the pseudo-critical temperature with increasing disorder. Benchmarking shows speedups exceeding two orders of magnitude compared to the Metropolis algorithm in the low-temperature regime. The proposed method provides an efficient and dynamically faithful tool for studying both equilibrium and non-equilibrium phenomena in disordered spin systems.

cond-mat.stat-mech↗

arXiv2024

VirtualRelativity: An Interactive Simulation of the Special Theory of Relativity in Virtual Reality

The Special Theory of Relativity, introduced by Albert Einstein in the early 20th century, marked a radical shift in our understanding of space and time. Nevertheless, the theory's non-intuitive implications continue to pose conceptual challenges for novice physicists. In this thesis, we propose a virtual reality solution based on the development of a Unity package capable of simulating the effects of relativity in a digital environment. The current implementation includes the representation of space contraction, time dilation and relativistic Doppler effect. The primary focus lies in the accurate representation of relativistic laws, as well as in computational efficiency and in the modeling of a user interface specifically crafted to enhance understanding and interactivity. The package significantly reduces developer workload through a streamlined API, enabling maximum freedom in the development of virtual scenarios. Design goals are validated by a testing phase conducted through dedicated probe scenes. To showcase the potential of this work, we also present the deployment of a VR application built on top of the package, that transports users in experiencing relativistic effects in real-life scenarios. The application is scheduled to be used by Master's students in Physical Engineering at Politecnico di Milano. In the meanwhile, other educational areas of expansion are being considered, suggesting a promising future in the direction of this work.

physics.ed-ph↗

arXiv2024

Dynamic Phase Transition in 2D Ising Systems: Effect of Anisotropy and Defects

We investigate the dynamic phase transition in two-dimensional Ising models whose equilibrium characteristics are influenced by either anisotropic interactions or quenched defects. The presence of anisotropy reduces the dynamical critical temperature, leading to the expected result that the critical temperature approaches zero in the full-anisotropy limit. We show that a comprehensive understanding of the dynamic behavior of systems with quenched defects requires a generalized definition of the dynamic order parameter. By doing so, we demonstrate that the inclusion of quenched defects lowers the dynamic critical temperature as well, with a linear trend across the range of defect fractions considered. We also explore if and how it is possible to predict the dynamic behavior of specific magnetic systems with quenched randomness. Various geometric quantities, such as a defect potential index, the defect dipole moment, and the properties of the defect Delaunay triangulation, prove useful for this purpose.

cond-mat.stat-mech↗

arXiv2021

Temperature-dependent criticality in random 2D Ising models

We consider 2D random Ising ferromagnetic models, where quenched disorder is represented either by random local magnetic fields (Random Field Ising Model) or by a random distribution of interaction couplings (Random Bond Ising Model). In both cases we first perform zero- and finite-temperature Monte-Carlo simulations to determine how the critical temperature depends on the disorder parameter. We then focus on the reversal transition triggered by an external field, and study the associated Barkhausen noise. Our main result is that the critical exponents characterizing the power-law associated with the Barkhausen noise exhibit a temperature dependence in line with existing experimental observations.

cond-mat.dis-nn↗