Publications related to A machine learning architecture for including wave breaking in envelope-type wave models

Soliton gas: Theory, numerics, and experiments

The concept of soliton gas was introduced in 1971 by Zakharov as an infinite collection of weakly interacting solitons in the framework of Korteweg-de Vries (KdV) equation. In this theoretical construction of a diluted (rarefied) soliton gas, solitons with ...

Amer Physical Soc2024

Electric-field-induced second-order nonlinear processes in stoichiometric silicon nitride

Boris Zabelich

Nonlinear optical frequency conversion is one of the driving research areas in photonics. Its quasi instantaneous response and the promise of low power consumption in integrated structures could cover the demand for fast signal processing with minimal ener ...

EPFL2024

Oblique streaming waves observed in multipactor-induced plasma discharge above a dielectric surface

Guang-Yu Sun, Haomin Sun

In a recent discovery (Wen et al 2022 Phys. Rev. Lett. 129 045001), streaming waves were found in multipactor-induced plasma discharges. However, due to the limitations of a 1D simulation setup, these waves displayed only transverse dynamics. In this lette ...

2024

Optothermal shaping of lamb waves with square and spiral phase fronts

Romain Christophe Rémy Fleury, Aleksi Antoine Bossart, Janez Rus

We introduce a Lamb-wave medium with tunable propagation velocities, which are controlled by a two-dimensional heating pattern produced by a laser beam. We utilized it to demonstrate that waves in an appropriately designed medium can propagate in the form ...

2024

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Stochastic particle transport by deep-water irregular breaking waves

Debbie Eeltink

Correct prediction of particle transport by surface waves is crucial in many practical applications such as search and rescue or salvage operations and pollution tracking and clean-up efforts. Recent results by Deike et al. (J. Fluid Mech., vol. 829, 2017, ...

Cambridge University Press2023

Mean flow modeling in high-order nonlinear Schrodinger equations

Debbie Eeltink

The evaluation and consideration of the mean flow in wave evolution equations are necessary for the accurate prediction of fluid particle trajectories under wave groups, with relevant implications in several domains, from the transport of pollutants in the ...

2023

Nonlinear interactions of ion acoustic waves explored using fast imaging decompositions

Fast camera imaging is used to study ion acoustic waves propagating azimuthally in a magnetized plasma column. The high-speed image sequences are analyzed using proper orthogonal decomposition and 2D Fourier transform, allowing to evaluate the assets and d ...

2023

Non-contact robotic manipulation of floating objects: exploiting emergent limit cycles

Nana Obayashi, Josephine Anna Eleanor Hughes

The study of non-contact manipulation in water, and the ability to robotically control floating objects has gained recent attention due to wide-ranging potential applications, including the analysis of plastic pollution in the oceans and the optimization o ...

Frontiers Media Sa2023

Optimization of elastic wave propagation in a reconfigurable medium by genetic algorithms with adaptive mutation probability

Romain Christophe Rémy Fleury, Janez Rus

We introduce a reconfigurable medium for the manipulation of elastic propagation properties of Lamb waves. It is based on a shape memory polymer (SMP) with temperature-dependent Young's modulus. Waves are excited by a laser pulse and detected by a laser vi ...

IOP Publishing Ltd2023

Temporal Prediction of Landslide-Generated Waves Using a Theoretical-Statistical Combined Method

Christophe Ancey, Zhenzhu Meng, Yating Hu

For the prediction of landslide-generated waves, previous studies have developed numerous empirical equations to express the maximums of wave characteristics as functions of slide parameters upon impact. In this study, we built the temporal relationship be ...

MDPI2023

Nonlocally-resonant metamaterials

Aleksi Antoine Bossart

In this thesis, we unveil a third design path to manipulate elastic waves within architected media, distinct from the traditional phononic crystal and locally-resonant metamaterial concepts. The core innovation lies in the concept of nonlocal resonances, d ...

EPFL2023

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

Emilio Maddalena

This thesis is situated at the crossroads between machine learning and control engineering. Our contributions are both theoretical, through proposing a new uncertainty quantification methodology in a kernelized context; and experimental, through investigat ...

EPFL2023

Aiming beyond slight increases in accuracy

Daniel Probst

Owing to the diminishing returns of deep learning and the focus on model accuracy, machine learning for chemistry might become an endeavour exclusive to well-funded institutions and industry. Extending the focus to model efficiency and interpretability wil ...

NATURE PORTFOLIO2023

Natural slicks on Lake Geneva: From small-scale effects to large-scale formation and distribution

Mehrshad Foroughan

Low wind speeds (< 4 m/s) are ubiquitous in many water bodies, yet the physical processes occurring at the air-water interface in this range are poorly understood. A notable example is smooth patches on the water surface, known as natural slicks, formed wh ...

EPFL2023

Dissipative Solitons and Switching Waves in Dispersion-Modulated Kerr Cavities

Rui Ning Wang, Tobias Kippenberg, Miles Henry Anderson, Alexey Tikan, Aleksandr Tusnin, Alisa Davydova

We theoretically and experimentally investigate the formation of dissipative coherent structures in Kerr nonlinear optical microresonators, whose spectrum encompasses an integrated dispersion that exceeds the cavity free-spectral range. We are able to acce ...

American Physical Society2023

A multi-modal pre-training transformer for universal transfer learning in metal-organic frameworks

Berend Smit, Hyunsoo Park

Metal-organic frameworks (MOFs) are a class of crystalline porous materials that exhibit a vast chemical space owing to their tunable molecular building blocks with diverse topologies. An unlimited number of MOFs can, in principle, be synthesized. Machine ...

NATURE PORTFOLIO2023

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

Rita Drissi Daoudi

Laser Powder Bed Fusion (LPBF) is an Additive Manufacturing (AM) process consolidating parts layer by layer, from a metallic powder bed. It allows no limitation in terms of geometry and is therefore of particular interest to various industries. Metallic LP ...

EPFL2023

3D Printed Acoustically Programmable Soft Microactuators

Mahmut Selman Sakar, Murat Kaynak, Amit Yedidia Dolev

The concept of creating all-mechanical soft microrobotic systems has great potential to address outstanding challenges in biomedical applications, and introduce more sustainable and multifunctional products. To this end, magnetic fields and light have been ...

2023

HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration

David Atienza Alonso, William Andrew Simon, Una Pale, Tomas Teijeiro Campo

The HyperDimensional Computing (HDC) Machine Learning (ML) paradigm is highly interesting for applications involving continuous, semi-supervised learning for long-term monitoring. However, its accuracy is not yet on par with other ML approaches, necessitat ...

Association for Computing MachineryNew YorkNYUnited States2022