Deep learning for laser beam imprinting

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61389021%3A_____%2F23%3A00583382" target="_blank" >RIV/61389021:_____/23:00583382 - isvavai.cz</a>

Alternative codes found

RIV/68378271:_____/23:00573225 RIV/68407700:21230/23:00366750 RIV/00216208:11320/23:10468368

Result on the web

<a href="https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-12-19703&id=531063" target="_blank" >https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-12-19703&id=531063</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1364/OE.481776" target="_blank" >10.1364/OE.481776</a>

Result language

angličtina

Original language name

Deep learning for laser beam imprinting

Original language description

Methods of ablation imprints in solid targets are widely used to characterize focused X-ray laser beams due to a remarkable dynamic range and resolving power. A detailed description of intense beam profiles is especially important in high-energy-density physics aiming at nonlinear phenomena. Complex interaction experiments require an enormous number of imprints to be created under all desired conditions making the analysis demanding and requiring a huge amount of human work. Here, for the first time, we present ablation imprinting methods assisted by deep learning approaches. Employing a multi-layer convolutional neural network (U-Net) trained on thousands of manually annotated ablation imprints in poly(methyl methacrylate), we characterize a focused beam of beamline FL24/FLASH2 at the Free-electron laser in Hamburg. The performance of the neural network is subject to a thorough benchmark test and comparison with experienced human analysts. Methods presented in this Paper pave the way towards a virtual analyst automatically processing experimental data from start to end.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10306 - Optics (including laser optics and quantum optics)

Project

<a href="/en/project/GA20-08452S" target="_blank" >GA20-08452S: Towards AbloCAM: fundamental approaches to automated ablation-desorption imprinting of focused X-ray laser beams</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Optics Express

ISSN

1094-4087

e-ISSN

—

Volume of the periodical

31

Issue of the periodical within the volume

12

Country of publishing house

US - UNITED STATES

Number of pages

19

Pages from-to

19703-19721

UT code for WoS article

001026189200003

EID of the result in the Scopus database

2-s2.0-85163592913