Latest papers
Solar Energetic Particles from suprathermal (few keV) up to relativistic (few GeV) energies constitute an important contributor to the characterization of the space environment. Emitted from the Sun they are associated with solar flares and…
Code search in large-scale ecosystems is often hindered by the lexical gap between user queries and implementation details, alongside the trade-off between the low latency of traditional Information Retrieval (IR) and the precision of Deep…
Background/Objectives: Dermoscopic skin lesion classifiers often lose accuracy under domain shift across imaging devices, illumination, and capture artifacts. We study how data augmentation improves the robustness of a binary…
Semantic communication (SemCom) promises to reduce transmitted payloads by conveying task-relevant meaning instead of raw bits. However, practical SemCom also incurs semantic metadata, control signaling, feedback, model or knowledge-base…
Dataset distillation compresses large-scale datasets into compact synthetic sets while preserving their training utility, enabling efficient 3D point cloud training. Current point cloud dataset distillation methods only tackle geometric and…
When it comes to generating vector representations of words, current language models are achieving high-quality results. However, what is not known is the extent to which knowledge about semantic relations is represented in the geometry of…
This thesis explores the role of modes, states, and symmetries in quantum optics, within the context of quantum information and quantum metrology. It proposes a unified framework to analyze how the modal structure of photonic fields, the…
Recent advances in AI agents have increasingly internalized native capabilities into their underlying foundation models, giving rise to multimodal foundation models and large reasoning models. However, agent memory is still primarily…
Compactly Supported Radial Basis Functions (CS-RBFs) are a fundamental tool in multivariate approximation theory. However, their use in statistics and probability modeling remains underexplored, having been used mainly to express covariance…
Anisotropic flow in ultra-relativistic light-ion collisions is sensitive to the initial geometry of the colliding nuclei. We investigate whether elliptic flow measurements can constrain the parameters of the proposed $\alpha$-clustered…
We show how signals of heavy neutrinos with displaced decays can be detected at the Large Hadron Collider in two theoretical setups, both exploiting extended gauge sectors as portals to such new physics, the Left-Right Symmetric Model and…
Randomized compiling (RC) is the standard technique for converting coherent (systematic) gate errors into stochastic noise. The prevailing view is that the twirl destroys coherent-error information. An exact Fisher-information conservation…
In this paper, we revisit the Poincar\'e polynomials, Betti numbers, and Euler characteristics of the Deligne-Mumford moduli spaces $\overline{\mathcal M}_{0,n}$ of stable $n$-pointed rational curves. We give elementary derivations of two…
Recent game world models can generate visually realistic and interactive environments conditioned on player actions. However, games are not defined by pixels alone; they are governed by explicit mechanics, namely state-dependent rules that…
We propose a reconstructed cosmological model in the framework of $f(Q,T)$ gravity, that provides a unified description of the early- and late-time evolution of the Universe. The model exhibits a non-singular asymmetric bounce, smoothly…
Medical world models aim to learn a latent state of patient or organ physiology and a transition function that forecasts how that state evolves under interventions, supporting downstream tasks from imaging-based diagnosis to digital-twin…
State-of-the-art intracortical brain-to-text systems pair a neural-sequence phone decoder with an external language model. Two design axes remain underexplored: whether selective state-space models (Mamba) improve on recurrent decoders, and…
We study the effect of surfactant adsorption kinetics on water electrolysis performance using Surfynol 465, an ultrafast-kinetics surfactant. High-speed optical diagnostics reveal that Surfynol 465 reduces bubble residence time by an order…
We introduce a new approach to the reconstruction of hidden structures from incomplete data, unifying techniques from geometric integration and topological analysis within the frameworks of Vaisman and Neifeld. Our method employs a refined…
We study a Cucker--Smale type system with bonding forces on complete Riemannian manifolds with uniformly bounded curvature. On general manifolds, the time variation of parallel transport between moving agents produces curvature-dependent…