1,686+ open-access research outputs.
This paper investigates the asymptotic behavior of high-order vector rogue wave (RW) solutions of the coupled nonlinear Schr\"odinger (CNLS) equation in the presence of multiple large internal paramet…
Context. Convolutional neural networks (CNNs) are widely used for automated galaxy morphological classification in large surveys. However, projection effects, image artefacts, and intrinsic degeneraci…
The core instrument of the SVOM Gamma-ray burst mission launched in June 2024 is the 4-150 keV 2-D coded mask camera ECLAIRs responsible for the autonomous trigger and localization of transient events…
We present a Python spectrophotometry extraction tool tailored for fast-moving point sources detected in the SPHEREx mission, and use it to construct a set of 0.75-5.0 {\mu}m low-resolution ({\lambda}…
We address a fundamental question: under which conditions do the dynamics and thermodynamics of open chemical reaction networks (CRNs), grounded on the notion of idealized chemostats that exchange sel…
Precise on-chip dispersion control is essential for advanced integrated photonic technologies, enabling applications ranging from high-speed communications and sensing to signal processing and biomedi…
Understanding dynamical facilitation in nonequilibrium glass-forming systems driven by active forces remains an open challenge. In particular, it is unclear whether facilitation survives in active gla…
We use deep learning under Bayesian perspective to quantitatively extract the in-medium heavy quark (HQ) potential from bottomonium nuclear modification factors ($R_{AA}$) measured across multiple hea…
We report on the high-pressure synthesis of a CrS$_2$ phase in the form of single-crystalline nanorods. A structural refinement of Precession Electron Diffraction Tomography data confirms the nominal …
Photometric missions such as Kepler and TESS have generated millions of light curves covering almost the entire sky, offering unprecedented opportunities to study stellar variability and advance our u…
We present an end-to-end, iterative pipeline for efficient identification of strong galaxy--galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalogues, we reject point…
Friction forces are conventionally modeled via semiclassical theories that associate energy dissipation with newtonian motion on corrugated interface potentials. This consolidated approach is challeng…
Entanglement is a key quantity for characterizing quantum correlations in particle scattering processes, but its direct evaluation is computationally demanding on quantum hardware. In this work, we in…
Shared mobility systems (e.g., shared cars and ride-hailing services) generate persistent spatial imbalances as vehicles concentrate at popular destinations, leaving trip origins depleted of supply. O…
We present a new class of quantum neural networks (QNNs) whose states are solutions of $p$-adic Schr\"{o}dinger equations with a non-local potential that controls the interaction between the neurons. …
Lightcone observations are the natural data format of galaxy surveys, but their evolving geometry breaks the translational symmetry assumed by standard convolutional neural networks (CNNs). In particu…
In scientific computing, the formulation of numerical discretisations of partial differential equations (PDEs) as untrained convolutional layers within Convolutional Neural Networks (CNNs), referred t…
Chemical imaging enabled by Raman processes is crucial to investigating biological and chemical samples in a label-free manner. Stimulated Raman spectroscopy (SRS) overcomes the key limitation associa…
Advances in the study of relativistic quantum phase space have established the set of Linear Canonical Transformations (LCTs) as a candidate for the fundamental symmetry group associated with relativi…
This review examines multiscale modelling approaches for cellulose nanocrystals (CNCs) and lignocellulosic plant cell walls, with a focus on hemicellulose and lignin interactions in aqueous environmen…
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