Un efficiente metodo di posizionamento del sensore offline per la stima del flusso
We present an efficient method to optimize sensor placement for flow estimation using sensors with time-delay embedding in advection-dominated flows. Our solution allows identifying promising candidates for sensor positions using solely preliminary flow field measurements with non-time-resolved Particle Image Velocimetry (PIV), without...
Sistemi binari supermassicci nei solitoni di materia oscura ultraleggera
Ultraleggero (o sfocato) materia oscura (ULDM) is an alternative to cold dark matter. A key feature of ULDM is the presence of solitonic cores at the centers of collapsed halos. These would potentially increase the drag experienced by supermassive black hole (SMBH)...
Property-Preserving Hashing for $\ell_1$-Distance Predicates: Applicazioni per contrastare gli attacchi di input contraddittori
Perceptual hashing is used to detect whether an input image is similar to a reference image with a variety of security applications. Recentemente, they have been shown to succumb to adversarial input attacks which make small imperceptible changes to the input image...
Stati stazionari esatti e rilassamento indotto dalla frammentazione nel processo di esclusione semplice asimmetrico senza passaggio
We introduce a multi-species generalization of the asymmetric simple exclusion process (ASEP) con a “Divieto di passaggio” vincolo, forbidding overtaking, su una catena aperta unidimensionale. This no-passing rule fragments the Hilbert space into an exponential number of disjoint sectors labeled by the particle sequence,...
Quantizzazione hamiltoniana della teoria complessa di Chern-Simons al livello-$k$
This paper develops a framework for the Hamiltonian quantization of complex Chern-Simons theory with gauge group $\mathrm{SL}(2,\mathbb{C})$ at an even level $k\in\mathbb{Z}_+$. Our approach follows the procedure of combinatorial quantization to construct the operator algebras of quantum holonomies on 2-surfaces and develop...
Rivisitazione dell'allineamento della telecamera radar mediante l'apprendimento contrastivo per oggetti 3D Rilevamento
Recentemente, 3D object detection algorithms based on radar and camera fusion have shown excellent performance, setting the stage for their application in autonomous driving perception tasks. Existing methods have focused on dealing with feature misalignment caused by the domain gap between radar...
MPC neurale adattivo online veloce tramite meta-apprendimento
Controllo predittivo del modello basato sui dati (MPC) has demonstrated significant potential for improving robot control performance in the presence of model uncertainties. Tuttavia, existing approaches often require extensive offline data collection and computationally intensive training, limiting their ability to adapt online. To address these...
L'OCCHIO: Un framework a bassa latenza basato su intenti soggettivi per più Previsione della traiettoria congiunta dei partecipanti al traffico
Trajectory prediction is a fundamental technology for advanced autonomous driving systems and represents one of the most challenging problems in the field of cognitive intelligence. Accurately predicting the future trajectories of each traffic participant is a prerequisite for building high safety and...
PINN-MEP: Rappresentazioni neurali continue per il percorso a energia minima Scoperta nei sistemi molecolari
Characterizing conformational transitions in physical systems remains a fundamental challenge in the computational sciences. Traditional sampling methods like molecular dynamics (MD) or MCMC often struggle with the high-dimensional nature of molecular systems and the high energy barriers of transitions between stable states....
Algoritmi MPC completamente scalabili per il k-Center euclideo
The $k$-center problem is a fundamental optimization problem with numerous applications in machine learning, data analysis, data mining, and communication networks. The $k$-center problem has been extensively studied in the classical sequential setting for several decades, and more recently there have been...