Publications associées à Emergent coherent modes in nonlinear magnonic waveguides detected at ultrahigh frequency resolution

Publications associées (17)

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

Ramin Mohammadi, Nikolaos Stergiopoulos, Georgios Rovas, Lydia Aslanidou, Sokratis Anagnostopoulos

Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

2025

Pulsed Magnetophononics in Gapped Quantum Magnets

Baptiste Paul Eloi Demazure

One route to the control of quantum magnetism at ultrafast timescales is magnetophononics, the modulation of magnetic interactions by coherently driven lattice excitations. Theoretical studies of a gapped quantum magnet subject to continuous, single-freque ...

AMER PHYSICAL SOC2025

On the added value of sequential deep learning for the upscaling of evapotranspiration

Devis Tuia

Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

2025

Enhancing skin lesion classification: a CNN approach with human baseline comparison

Zaffar Ahmed Shaikh

This study presents an augmented hybrid approach for improving the diagnosis of malignant skin lesions by combining convolutional neural network (CNN) predictions with selective human interventions based on prediction confidence. The algorithm retains high ...

PeerJ2025

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Su Yeon Chang

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approach produces similar outcomes with respect to previous models but with fewer ...

IOP Publishing Ltd2025

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Michael Lehning, Devis Tuia, Yael Frischholz

To retrieve Surface Solar Radiation (SSR) from satellite images, a baseline reflectance of the observed ground in clear-sky conditions, also called background reflectance, is necessary to distinguish atmospheric absorption and scattering effects from surfa ...

2025

Visualizing hot carrier dynamics by nonlinear optical spectroscopy at the atomic length scale

Klaus Kern

Probing and manipulating the spatiotemporal dynamics of hot carriers in nanoscale metals is crucial to a plethora of applications ranging from nonlinear nanophotonics to single-molecule photochemistry. The direct investigation of these highly non-equilibri ...

Springer Science and Business Media LLC2025

Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

Alfio Quarteroni

Scientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problems. Physics-based models rely on the physical understanding of the problem at ...

2025

Neural Garment Modeling

Ren Li

The digitization of 3D deformable objects remains a significant challenge in computer graphics and vision, particularly in the accurate modeling of garments. Garments exhibit complex shape variability, non-rigid deformations, and frequent self-occlusion, m ...

EPFL2025

Accurate Implementation of Rotating Magneto-Hydrodynamics in a Channel Geometry Using an Influence Matrix Method

Tobias Schneider

We numerically study wall-bounded convectively driven magneto-hydrodynamic (MHD) flows subject to rotation in a Cartesian periodic channel. For the accurate treatment of the rotating MHD equations, we develop a pseudo-spectral simulation code with accurate ...

MDPI AG2025

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Jérôme Chenal, Baraka Jean-Claude Munyaka

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

AIP Publishing2025

Compact Superconducting Vacuum-gap Capacitors with Low Microwave Loss and High Mechanical Coherence for Scalable Quantum Circuits

Tobias Kippenberg, Marco Scigliuzzo, Amir Youssefi, Mahdi Chegnizadeh

Vacuum-gap capacitors have recently attracted significant interest in superconducting circuit platforms due to their compact design and exceptionally low dielectric losses in the microwave regime. Their intrinsic ability to support mechanical vibrational m ...

American Physical Society (APS)2025

Decoupling Optical and Thermal Dynamics in Dielectric Metasurfaces for Self-Encoded Photonic Control

Giulia Tagliabue, Alan Richard Bowman, Elif Nur Dayi, Gopal Narmada Naidu, Omer Can Karaman

Thermo-optical nonlinearities (TONL) in metasurfaces enable dynamic control of optical properties—such as transmitted power, phase, and polarization—through external stimuli like laser irradiation or temperature. Due to the inherently slow thermal dynamics ...

2025

Towards microwave-to-optical quantum transduction with barium titanate/strontium titanate integrated photonics

Annina Irina Riedhauser

The faithful bidirectional quantum coherent conversion of microwave (5 GHz) and optical (193.5 THz) quantum states will become essential for future quantum networks. Due to their low transition frequency, qubit states are quickly destroyed at room temperat ...

EPFL2025

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Anne-Clémence Corminboeuf, Friedrich Eisenbrand, Rubén Laplaza Solanas, Puck Elisabeth van Gerwen, Ksenia Briling, Jan Weinreich, Matthieu Nicolas Haeberle

Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

IOP Publishing Ltd2025

MetaCap: Meta-learning Priors from Multi-view Imagery for Sparse-View Human Performance Capture and Rendering

Pascal Fua

Faithful human performance capture and free-view rendering from sparse RGB observations is a long-standing problem in Vision and Graphics. The main challenges are the lack of observations and the inherent ambiguities of the setting, e.g. occlusions and dep ...

Springer Science and Business Media Deutschland GmbH2025

XLSR-Transducer: Streaming ASR for Self-Supervised Pretrained Models

Juan Pablo Zuluaga Gomez

Self-supervised pretrained models exhibit competitive performance in automatic speech recognition (ASR) on finetuning, even with limited in-domain supervised data. However, popular pretrained models are not suitable for streaming ASR because they are train ...

Institute of Electrical and Electronics Engineers2025