Apprendimento profondo disaggregato tramite calcolo in-fisico a radiofrequenza
Dispositivi edge moderni, come le fotocamere, droni, e nodi dell'Internet delle cose, fare affidamento sul deep learning per abilitare un’ampia gamma di applicazioni intelligenti, compreso il riconoscimento degli oggetti, percezione dell'ambiente, and autonomous navigation. Tuttavia, deploying deep learning models directly on the often resource-constrained edge devices...
Sulle equazioni differenziali canoniche per Feynman multiscala di Calabi-Yau integrali
Generalizziamo un metodo recentemente introdotto in letteratura, that derives canonical differential equations, to multi-scale Feynman integrals with an underlying Calabi-Yau geometry. We start by recomputing a canonical form for the sunrise integral with all unequal masses. Inoltre, we compute for...
Sul grado di automatizzazione delle dimostrazioni della somma dei quadrati
The Sum-of-Squares (SoS) hierarchy, also known as Lasserre hierarchy, has emerged as a promising tool in optimization. Tuttavia, it remains unclear whether fixed-degree SoS proofs can be automated [O’Donnell (2017)]. Indeed, there are examples of polynomial systems with bounded coefficients that admit...
First study of neutrino angle reconstruction using quasielastic-like interactions in MicroBooNE
We investigate the expected precision of the reconstructed neutrino direction using a {\non}{\In}-argon quasielastic-like event topology with one muon and one proton in the final state and the reconstruction capabilities of the MicroBooNE liquid argon time projection chamber. This direction is of...
Bringing light into the Landau-Lifshitz-Gilbert equation: Consequences of its fractal non-Markovian memory kernel for optically induced magnetic inertia and magnons
The Landau-Lisfhitz-Gilbert (LLG) equation has been the cornerstone of modeling the dynamics of localized spins, viewed as classical vectors of fixed length, within nonequilibrium magnets. When light is employed as the nonequilibrium drive, the LLG equation must be supplemented with additional terms...
Zeptosecond free-electron compression through temporal lensing
The pursuit of ever-shorter time scales is a frontier in modern physics, exemplified by the synthesis of attosecond light pulses — an achievement made possible by coherently superimposing a broad range of photon energies, as required by the uncertainty principle. Tuttavia, extending...
Adattamento delle metriche degli alberi e degli ultrametrici nei flussi di dati
Fitting distances to tree metrics and ultrametrics are two widely used methods in hierarchical clustering, primarily explored within the context of numerical taxonomy. Given a positive distance function $D:\binom{V}{2}\rightarrow\mathbb{R}_{>0}$, the goal is to find a tree (or ultrametric) $T$ including all elements...
Polarizzazione flessoelettrica in cristalli liquidi chirali: elettrostatico Autointerazioni di difetti topologici
The presence of topological defects in apolar chiral liquid crystals cause orientational distortions, portando a una tensione non uniforme. This non-uniform strain generates an electric polarization response due to the flexoelectric effect, che induce un campo elettrico interno. Associated to this electric field is...
Riproduci per ricordare: Conservare la conoscenza del dominio nel linguaggio di streaming Modelli
Apprendimento continuo in grandi modelli linguistici (LLM) typically encounters the critical challenge of catastrophic forgetting, where previously acquired knowledge deteriorates upon exposure to new data. While techniques like replay buffers and parameter-efficient tuning (per esempio., Adattamento di basso rango o LoRA) have been proposed, few...
Token-Shuffle: Verso la generazione di immagini ad alta risoluzione con Modelli autoregressivi
Autoregressivo (AR) modelli, a lungo dominante nella generazione del linguaggio, are increasingly applied to image synthesis but are often considered less competitive than Diffusion-based models. A primary limitation is the substantial number of image tokens required for AR models, which constrains both training and...