Publications related to Stochastic fluctuations and the detectability limit of network communities

Related publications (27)

The effect of plasma shaping on high density H-mode SOL profiles and fluctuations in TCV

Nicola Vianello, Benoît Labit, Holger Reimerdes, Christian Gabriel Theiler, Cedric Kar-Wai Tsui, Umar Sheikh, Guang-Yu Sun, Claudia Colandrea, Sophie Danielle Angelica Gorno, Luke Simons

The impact of plasma shaping on the properties of high density H-mode scrape-off layer (SOL) profiles and transport at the outer midplane has been investigated on Tokamaka configuration variable. The experimental dataset has been acquired by evolving the u ...

IOP Publishing Ltd2024

Role of Minimum Adhesive Wear Particle Size in Third-Body Layer Properties

Jean-François Molinari, Son-Jonathan Pham-Ba

We employ a novel discrete element method (DEM) force formulation to simulate adhesive wear and assess the effects of material and loading parameters on the properties of the third-body layer (TBL) formed during sliding motion. The study emphasizes the rol ...

2023

Design and Development of a Diagnostic System for a Non-Intercepting Direct Measure of the SPIDER Ion Source Beamlet Current

Basile Marie Jacques Pouradier Duteil

Stable and uniform beams with low divergence are required in particle accelerators; therefore, beyond the accelerated current, measuring the beam current spatial uniformity and stability over time is necessary to assess the beam performance, since these pa ...

MDPI2023

Beam homogeneity of caesium seeded SPIDER using a direct beamlet current measurement

Basile Marie Jacques Pouradier Duteil

The ITER Heating Neutral Beam (HNB) source prototype SPIDER (Source for the Production of Ions of Deuterium Extracted from a Radio frequency plasma), hosted at the Neutral Beam Test Facility (NBTF) in Padova, Italy, has recently started operating with evap ...

ELSEVIER SCIENCE SA2023

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Victor Panaretos, Leonardo Vincenzo Santoro, Neda Mohammadi Jouzdani

We consider the problem of nonparametric estimation of the drift and diffusion coefficients of a Stochastic Differential Equation (SDE), based on n independent replicates {Xi(t) : t is an element of [0 , 1]}13 d B(t), where alpha is an element of {0 , 1} a ...

Elsevier2024

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Wiley2023

Unsupervised Electrofacies Clustering Based on Parameterization of Petrophysical Properties: A Dynamic Programming Approach

François Fleuret

Electrofacies using well logs play a vital role in reservoir characterization. Often, they are sorted into clusters according to the self-similarity of input logs and do not capture the known underlying physical process. In this paper, we propose an unsupe ...

SOC PETROPHYSICISTS & WELL LOG ANALYSTS-SPWLA2023

Incremental Learning in Diagonal Linear Networks

Raphaël Jean Berthier

Diagonal linear networks (DLNs) are a toy simplification of artificial neural networks; they consist in a quadratic reparametrization of linear regression inducing a sparse implicit regularization. In this paper, we describe the trajectory of the gradient ...

Microtome Publishing2023

Role of stochastic noise and generalization error in the time propagation of neural-network quantum states

Giuseppe Carleo

Neural-network quantum states (NQS) have been shown to be a suitable variational ansatz to simulate out-of-equilibrium dynamics in two-dimensional systems using timedependent variational Monte Carlo (t-VMC). In particular, stable and accurate time propagat ...

SCIPOST FOUNDATION2022

Latent Space Slicing for Enhanced Entropy Modeling in Learning-Based Point Cloud Geometry Compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

The growing adoption of point clouds as an imaging modality has stimulated the search for efficient solutions for compression. Learning-based algorithms have been reporting increasingly better performance and are drawing the attention from the research com ...

IEEE2022

EMC Impact of Disturbances Generated by Multiple Sources

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

In this paper, the impact of an increasing number of arbitrary electrical/electronic devices on the overall radiated emissions is investigated. Understanding and quantifying such an impact are prerequisites to the proper evaluation of electromagnetic compa ...

2022

Hybrid Flock - Formation Control Algorithms

Alcherio Martinoli, Cyrill Silvan Baumann

Two prominent categories for achieving coordinated multirobot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. While typic ...

Springer Nature Switzerland2022

Evaluation Criterion of Proton Exchange Membrane (ECPEM) fuel cells considering inserted porous media inside the gas flow channel

Jan Van Herle, Hossein Pourrahmani

The focus of this study is to evaluate the effects of porous media inside the gas flow channel of Proton Exchange Membrane Fuel Cells (PEMFC) on four different output parameters of voltage, power density, pressure drop, and Nusselt number (Nu) considering ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Step Change Detection for Improved ROCOF Evaluation of Power System Waveforms

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandra Cameron Karpilow

In the analysis of power grid waveforms, the presence of amplitude or phase steps can disrupt the estimation of frequency and rate-of-change-of-frequency (ROCOF). Standard methods based on phasor-models fail in the extraction of signal parameters during th ...

IEEE2022

Bootstrapping for Approximate Homomorphic Encryption with Negligible Failure-Probability by Using Sparse-Secret Encapsulation

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Léonard Bossuat

Bootstrapping parameters for the approximate homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17), are usually instantiated using sparse secrets to be efficient. However, using sparse secrets constrains the range of practical parameters withi ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

The aging brain as a model to understand motor skill acquisition in humans and its restoration using non-invasive brain stimulation

Pablo Maceira Elvira

Motor skill acquisition is essential to our survival, as it enables an efficient interaction with the changing world around us. The acquisition of novel sequential tasks, of particular relevance due to their pervasiveness in everyday life activities, can b ...

EPFL2022

First operations with caesium of the negative ion source SPIDER

Riccardo Agnello, Basile Marie Jacques Pouradier Duteil

The negative-ion based neutral beam injector for heating and current drive of the ITER plasma (ITER HNB) is under development, at present focusing on the optimization of the full-scale plasma source in the SPIDER test stand. The production of H- or D- ions ...

IOP Publishing Ltd2022

Practical Byzantine-resilient Stochastic Gradient Descent

Sébastien Louis Alexandre Rouault

Algorithms are everywhere. The recipe for the frangipane cake is an algorithm. If all the listed ingredients are available and the cook is sufficiently deft, after a finite number of small, well-defined steps a delicious dessert will exit the oven. Now, wh ...

EPFL2022

Optimization Method for Extracting Stabilizer Geometry and Properties of REBCO Tapes

Bertrand Dutoit, Bertrand Dutoit, Francesco Grilli, Nicolo' Riva, Arooj Akbar

A good knowledge of material properties is a critical aspect for modeling high-temperature superconductor (HTS) devices. However, the electrical resistivity of coated conductors above the critical current is limited. The major challenge in characterizing t ...

2021

Averages of b-hadron, c-hadron, and tau-lepton properties as of 2018 Heavy Flavor Averaging Group (HFLAV)

Olivier Schneider, Ho Ling Li, Tara Nanut

This paper reports world averages of measurements of b-hadron, c-hadron, and tau-lepton properties obtained by the Heavy Flavour Averaging Group using results available through September 2018. In rare cases, significant results obtained several months late ...

SPRINGER2021