7–12 May 2023
Venice, Italy
Europe/Zurich timezone

Machine learning-based reconstruction of electron radiation spectra

SUPM085
7 May 2023, 14:00
4h
Sala Mosaici 2

Sala Mosaici 2

Poster Presentation Student Poster Session

Speaker

Monika Yadav (The University of Liverpool)

Description

The photon flux resulting from a high energy electron beam's interaction with a target, such as in the upcoming FACET-II experiments at SLAC National Accelerator Laboratory, should yield, through its spectral and angular characteristics, information about the electron beam's underlying dynamics at the interaction point.
This project utilizes data from simulated plasma wakefield acceleration-derived betatron radiation experiments and high-field laser-electron-based radiation production to determine which methods could most reliably reconstruct these key properties. The data from these two cases provide a large range of photon energies; this variation of photon characteristics increases confidence in each analysis method. This work aims to compare several reconstruction methods and determine which best predicts original energy distributions based on simulated spectra.

Funding Agency

This work was performed with the US Department of Energy, Division of High Energy Physics, under Contract No. DE-SC0009914, and the STFC LIV.DAT under grant agreement ST/P006752/1.

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Primary author

Monika Yadav (The University of Liverpool)

Co-authors

Brian Naranjo (University of California, Los Angeles) Prof. Carsten Welsch (The University of Liverpool) Gerard Andonian (University of California, Los Angeles) James Rosenzweig (University of California, Los Angeles) Maanas Oruganti (University of California, Los Angeles) Oznur Apsimon (The University of Liverpool) Sarah Zhang (University of California, Los Angeles)

Presentation materials

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