Publications associées à Machine de Turing

Optimizing Dynamic Aperture Studies with Active Learning

Tatiana Pieloni, Ekaterina Krymova, Mike Seidel, Davide Di Croce, 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 ...

Iop Publishing Ltd2024

Novel Design and Implementation of a Neuromuscular Controller on a Hip Exoskeleton for Partial Gait Assistance

Auke Ijspeert, Mohamed Bouri, Ali Reza Manzoori, Andrea Di Russo, Sara Messara

Exoskeletons intended for partial assistance of walking should be able to follow the gait pattern of their users, via online adaptive control strategies rather than imposing predefined kinetic or kinematic profiles. NeuroMuscular Controllers (NMCs) are ada ...

2023

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

Frédéric Blanc, Tatiana Pieloni, Davide Di Croce, 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

TimeEvolver: A program for time evolution with improved error bound

Sebastian Zell

We present TimeEvolver, a program for computing time evolution in a generic quantum system. It relies on well-known Krylov subspace techniques to tackle the problem of multiplying the exponential of a large sparse matrix iH, where His the Hamiltonian, with ...

ELSEVIER2022

Gemini: Elastic SNARKs for Diverse Environments

Alessandro Chiesa

We introduce a new class of succinct arguments, that we call elastic. Elastic SNARKs allow the prover to allocate different resources (such as memory and time) depending on the execution environment and the statement to prove. The resulting output is indep ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Leibniz en Créateur. Un regard matériel sur sa machine à calculer

Simon François Dumas Primbault

Between 1671 and 1716, the German mathematician Gottfried Wilhelm Leibniz attempted to design a reckoning machine. Working closely with the Parisian clockmaker Monsieur Ollivier, Leibniz eventually failed at producing a working prototype. After the redisco ...

2022

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

A (2+epsilon)-Approximation Algorithm for Preemptive Weighted Flow Time on a Single Machine

Lars Rohwedder

Weighted flow time is a fundamental and very well-studied objective function in scheduling. In this paper, we study the setting of a single machine with preemptions. ...

ASSOC COMPUTING MACHINERY2021

Magnetization-prepared 2 Rapid Gradient-Echo MRI for B-1 Insensitive 3D T1 Mapping of Hip Cartilage: An Experimental and Clinical Validation

Tobias Kober

Background: Often used for T1 mapping of hip cartilage, three-dimensional (3D) dual-flip-angle (DFA) techniques are highly sensitive to flip angle variations related to B-1 inhomogeneities. The authors hypothesized that 3D magnetization-prepared 2 rapid gr ...

RADIOLOGICAL SOC NORTH AMERICA2021

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