Recherche

Afficher tous les résultats pour

Accueil

Publication

Meandering particle bunches and a link between averages of time series of particle counts and higher-order moments

Publications associées (28)

À propos
Confidentialité
Mentions légales

Graph Chatbot

Performance of the MALTA telescope

Edoardo Charbon, Francesco Piro, Abhishek Sharma

MALTA is part of the Depleted Monolithic Active Pixel sensors designed in Tower 180 nm CMOS imaging technology. A custom telescope with six MALTA planes has been developed for test beam campaigns at SPS, CERN, with the ability to host several devices under ...

SPRINGER2023

Development of the self-modulation instability of a relativistic proton bunch in plasma

Ambrogio Fasoli, Ivo Furno, Patrick Blanchard, Yanis Andrebe, Riccardo Agnello, Christine Stollberg, Sun Hee Kim, Ana Francisca Leal Silva Soares, Alban Sublet, Samuel Rey-Mermet

Self-modulation is a beam-plasma instability that is useful to drive large-amplitude wakefields with bunches much longer than the plasma skin depth. We present experimental results showing that, when increasing the ratio between the initial transverse size ...

2023

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

Electromagnetic forces in the time domain

Olivier Martin, Karim Achouri, Andrei Kiselev

We look beyond the standard time-average approach and investigate optical forces in the time domain. The formalism is developed for both the Abraham and Minkowski momenta, which appear to converge in the time domain. We unveil an extremely rich - and by fa ...

Optica Publishing Group2022

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Andrea Zanoni

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

EPFL2022

Design, prototyping, and thermo-mechanical modelling of a neutron spallation target impacted by high-energy proton-beam pulses in the n_TOF facility at CERN

Raffaele Esposito

This manuscript describes the design work and the R&D activities carried out for the third-generation neutron production target in the neutron Time-Of-Flight (n_TOF) facility at the European Laboratory for Particle Physics (CERN). The facility is composed ...

EPFL2022

Modelling electronic transport in monocrystalline metal oxide gas sensors: from the surface kinetics to the experimental response

Roberto Guarino, Gianluca Piccinini

Gas sensing systems and devices based on metal oxides are widely spreading due to their high performance in terms of sensor response and relatively low costs. Despite several experimental studies, as well as molecular simulations, are available in the lite ...

2022

The exploration process of critical Boltzmann planar maps decorated by a triangular O(n) loop model

Aleksandra Korzhenkova

In this paper we investigate pointed (q, g, n)-Boltzmann loop-decorated maps with loops traversing only inner triangular faces. Using peeling exploration Budd (2018) modified to this setting we show that its law in the non-generic critical phase can be cod ...

IMPA2022

Design of the 590 MeV proton beamline for the proposed TATTOOS isotope production target at PSI

Mike Seidel, Hong Zhang

IMPACT (Isotope and Muon Production with Advanced Cyclotron and Target Technologies) is a proposed initiative envisaged for the high-intensity proton accelerator facility (HIPA) at the Paul Scherrer Institute (PSI). As part of IMPACT, a radioisotope target ...

IOP Publishing2022

Sparsely Observed Functional Time Series: Theory and Applications

Tomas Rubin

Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...

EPFL2021

Page 2 sur 3

Design, prototyping, and thermo-mechanical modelling of a neutron spallation target impacted by high-energy proton-beam pulses in the n_TOF facility at CERN

Raffaele Esposito

EPFL2022

Modelling electronic transport in monocrystalline metal oxide gas sensors: from the surface kinetics to the experimental response

Roberto Guarino, Gianluca Piccinini

2022

Design of the 590 MeV proton beamline for the proposed TATTOOS isotope production target at PSI

Mike Seidel, Hong Zhang

IOP Publishing2022

Sparsely Observed Functional Time Series: Theory and Applications

Tomas Rubin

EPFL2021