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Proton Beam Imaging Energy Spectrometer (PROBIES) for high repetition rate laser plasma experiments

ORAL

Abstract

High-intensity (>10^18 W/cm2) laser interactions with thin foils have long been known to accelerate high-energy, high-flux proton beams via the target normal sheath acceleration mechanism [1,2]. To spatially and spectrally characterize these beams, radiochromic film (RCF) stacks have been widely employed due to their accuracy and reliability [3,4]. In practice, the size of the target holder and the time required to prepare and scan the films limit the number of films that can be fielded in the stack, and the films must be removed from the vacuum chamber and replaced between shots. These constraints may be eliminated without sacrificing spatial or spectral information with the use of a proton energy step wedge and scintillator combination that allows the same information to be collected on a single camera frame. Building on previous work [5], the step wedge consists of a set of repeating periodic filters so that for each energy, the beam profile is discretely sampled at an array of spatial locations. This array of spatial samples is interpolated to obtain the spatial profile for each energy. An organic scintillator [6] is used to detect MeV protons, and an optical imaging setup collects the emerging light on a CCD, enabling high repetition rate (>1 Hz) data collection with a spectral resolution of 1.2 MeV and spatial imaging resolution of 20 microns. Preliminary results from commissioning experiments at the ALEPH laser facility at CSU will be presented, including cross-calibration with RCF and automated analysis for spatio-spectral proton beam retrieval.

[1] Snavely et al, PRL(2000) [2] Wilks et al, PoP(2001) [3] Hey et al, RSI(2008) [4] Schollmeier et al, RSI(2014) [5] Dover et al, RSI(2017) [6] Buck et al, RSI(2010)

Publication: D. Mariscal et al., Plasma Physics and Controlled Fusion (2021), submitted

Presenters

  • Elizabeth S Grace

    Georgia Institute of Technology

Authors

  • Elizabeth S Grace

    Georgia Institute of Technology

  • Derek Mariscal

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory

  • Ghassan Zeraouli

    Colorado State University

  • Graeme G Scott

    Lawrence Livermore National Laboratory, Lawrence Livermore Natl Lab

  • Raspberry A Simpson

    Massachusetts Institute of Technology MI, Massachusetts Institute of Technology

  • Kelly Swanson

    Lawrence Livermore National Laboratory

  • Blagoje Z Djordjevic

    Lawrence Livermore National Lab, Lawrence Livermore National Laboratory, Lawrence Livermore Natl Lab

  • Huanyu Song

    Colorado State University, Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80521 USA

  • Ryan Nedbaillo

    Colorado State University

  • Jaebum Park

    Colorado State University

  • John Morrison

    Colorado State University

  • Reed C Hollinger

    Colorado State University, Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80521 USA

  • Shoujun Wang

    Colorado State University, Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80521 USA

  • Jorge J Rocca

    Colorado State University, Electrical and Computer Engineering Department, Colorado State University, Fort Collins, CO 80521 USA

  • Tammy Ma

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory