Concept

Machine de Turing universelle

Publications associées (38)

Optimizing Dynamic Aperture Studies with Active Learning

Davide Di Croce, Tatiana Pieloni, Ekaterina Krymova, Massimo Giovannozzi

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

2024

Locked mode detection during error field identification studies

Olivier Sauter

At the beginning of a machine operation, an assessment of the intrinsic error fields, spurious magnetic field perturbations which can affect plasma dynamics, is often carried out by executing the compass scan method [Scoville J.T. et al. Nucl. Fusion 43 25 ...

ELSEVIER SCIENCE SA2023

A Novel Method for Detecting Unidentified Falling Object Loss Patterns in the LHC

Frédéric Blanc, Davide Di Croce, Tatiana Pieloni, Jorg Wenninger, Loïc Thomas Davies Coyle

Understanding and mitigating particle losses in the Large Hadron Collider (LHC) is essential for both machine safety and efficient operation. Abnormal loss distributions are tell- tale signs of abnormal beam behaviour or incorrect machine configuration. By ...

Journals of Accelerator Conferences Website (JACoW) 2022

Asynchrony Increases Efficiency: Time Encoding of Videos and Low-Rank Signals

Martin Vetterli, Adam James Scholefield, Karen Adam

In event-based sensing, many sensors independently and asynchronously emit events when there is a change in their input. Event-based sensing can present significant improvements in power efficiency when compared to traditional sampling, because (1) the out ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Timing is Everything

Karen Adam

In this thesis, timing is everything. In the first part, we mean this literally, as we tackle systems that encode information using timing alone. In the second part, we adopt the standard, metaphoric interpretation of this saying and show the importance of ...

EPFL2022

A Time Encoding Approach to Training Spiking Neural Networks

Karen Adam

While Spiking Neural Networks (SNNs) have been gaining in popularity, it seems that the algorithms used to train them are not powerful enough to solve the same tasks as those tackled by classical Artificial Neural Networks (ANNs).In this paper, we provide ...

IEEE2022

Efficiency Optimisation of Slotless Magnetic Bearing Machines

Yves Perriard, Douglas Martins Araujo, Leopoldo Rossini, Guzmán Borque Gallego

Efficiency is one of the key performance indexes in the design of electric motors. When considering fully active magnetic bearing machines, this aspect gain further relevance due to the necessity of actively controlling all the remaining degrees of freedom ...

2021

How Asynchronous Events Encode Video

Martin Vetterli, Adam James Scholefield, Karen Adam

As event-based sensing gains in popularity, theoretical understanding is needed to harness this technology’s potential. Instead of recording video by capturing frames, event-based cameras have sensors that emit events when their inputs change, thus encodin ...

IEEE2021

What graph neural networks cannot learn: depth vs width

Andreas Loukas

This paper studies the expressive power of graph neural networks falling within the message-passing framework (GNNmp). Two results are presented. First, GNNmp are shown to be Turing universal under sufficient conditions on their depth, width, node attribut ...

2020

Dynamic behaviour of a Francis turbine during voltage regulation in the electrical power system

François Avellan, Elena Vagnoni

Hydroelectric units can be operated in synchronous condenser mode to provide reactive power to the electrical power system (EPS) for voltage regulation. In this operating mode, the hydraulic turbine consumes active power and in case of hydroelectric units ...

2020

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