1.

Record Nr.

UNINA9910986280903321

Autore

Ouellet, Marc <cardinale> <1944-   >

Titolo

Parola, sacramento, carisma : Chiesa sinodale, rischi, opportunità / Marc Ouellet

Pubbl/distr/stampa

Siena, : Cantagalli, 2024

ISBN

9791259625175

Descrizione fisica

303 p. ; 21 cm

Locazione

FSPBC

Collocazione

STREL 28

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910908381503321

Autore

Hagedorn Melinda

Titolo

Minimization Problems for the Witness Beam in Relativistic Plasma Cavities / / by Melinda Hagedorn

Pubbl/distr/stampa

Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Spektrum, , 2024

ISBN

9783658462260

9783658462253

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (81 pages)

Collana

BestMasters, , 2625-3615

Disciplina

539.73

Soggetti

Particle accelerators

Plasma (Ionized gases)

Plasma accelerators

Mathematical optimization

Accelerator Physics

Plasma Physics

Plasma-based Accelerators

Optimization

Lingua di pubblicazione

Inglese



Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Introduction -- Preparation -- Wakefield acceleration -- Discussion of some Optimization Algorithms -- Numerical Simulations -- Conclusion and Outlook.

Sommario/riassunto

This thesis deals with an optimization problem from the field of theoretical plasma physics. Specifically, it deals with the question of how the accelerated electrons are spatially arranged in a plasma wave generated by a laser pulse. An internal structure of this so-called witness beam is of interest for the radiation characteristics of such electron beams, in particular with regard to the coherence of the generated radiation. The resulting internal structure of the electron beam is a result of the interaction of the electrons with each other and the electric fields of the wakefield, therefore it is determined by solving a minimization problem. The thesis builds on previous results in this field and aims to find suggestions for improved algorithms to determine the minimum sought. About the Author Melinda Hagedorn is a PhD student in Mathematical Optimization, research associate and teaching assistant at Heinrich Heine University in Düsseldorf. She holds master's degrees in mathematics and physics. In her research, she focuses in particular on variants of the stochastic gradient method applied to convex optimization problems.