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Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning

Published online by Cambridge University Press:  14 February 2023

J. Goodman
Affiliation:
SUPA Department of Physics, University of Strathclyde, Glasgow, UK
M. King
Affiliation:
SUPA Department of Physics, University of Strathclyde, Glasgow, UK The Cockcroft Institute, Sci-Tech Daresbury, Warrington, UK
E. J. Dolier
Affiliation:
SUPA Department of Physics, University of Strathclyde, Glasgow, UK
R. Wilson
Affiliation:
SUPA Department of Physics, University of Strathclyde, Glasgow, UK
R. J. Gray
Affiliation:
SUPA Department of Physics, University of Strathclyde, Glasgow, UK
P. McKenna*
Affiliation:
SUPA Department of Physics, University of Strathclyde, Glasgow, UK The Cockcroft Institute, Sci-Tech Daresbury, Warrington, UK
*
Correspondence to: P. McKenna, SUPA Department of Physics, University of Strathclyde, Glasgow G4 0NG, UK. Email: paul.mckenna@strath.ac.uk

Abstract

The optimum parameters for the generation of synchrotron radiation in ultraintense laser pulse interactions with planar foils are investigated with the application of Bayesian optimization, via Gaussian process regression, to 2D particle-in-cell simulations. Individual properties of the synchrotron emission, such as the yield, are maximized, and simultaneous mitigation of bremsstrahlung emission is achieved with multi-variate objective functions. The angle-of-incidence of the laser pulse onto the target is shown to strongly influence the synchrotron yield and angular profile, with oblique incidence producing the optimal results. This is further explored in 3D simulations, in which additional control of the spatial profile of synchrotron emission is demonstrated by varying the polarization of the laser light. The results demonstrate the utility of applying a machine learning-based optimization approach and provide new insights into the physics of radiation generation in laser–foil interactions, which will inform the design of experiments in the quantum electrodynamics (QED)-plasma regime.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press in association with Chinese Laser Press
Figure 0

Figure 1 (a) The Bayesian optimization loop and schematic of the simulation setup. The synchrotron photon energy spectrum (${\mathrm{d}N}_{\mathrm{sy}}/ \mathrm{d}\varepsilon$) and angle-resolved yield ($\mathrm{d}\sum {\varepsilon}_{\mathrm{sy}}/ \mathrm{d}\theta$) generated in each simulation are depicted to illustrate several of the objective functions. (b) An example of Bayesian optimization of a noisy 1D function showing the true function (black), the model (red) and the acquisition function (blue) for different numbers of iterations (n).

Figure 1

Figure 2 (a) Percentage transmission of the laser pulse, (b) total electron energy in front of the plasma critical surface and in the laser skin depth averaged over the period of synchrotron emission and (c) laser-to-synchrotron photon energy conversion efficiency, all for varying target thickness and laser intensity. (d)–(f) Laser-to-synchrotron photon energy conversion efficiency for varying pulse duration, focal spot size and defocus, respectively, with target thickness.

Figure 2

Figure 3 Scaling of the laser-to-synchrotron energy conversion efficiency with (a) peak laser intensity, (b) pulse duration and (c) focal spot FWHM, for varying target thickness. Power law fits are shown for the optimum target thicknesses (black) and for the thickest targets used (red; $l = 5\ \unicode{x3bc}\mathrm{m} $ for (a) and $l = 3\ \unicode{x3bc}\mathrm{m} $ for (b) and (c)).

Figure 3

Figure 4 (a) Laser-to-synchrotron photon energy conversion efficiency for varying angle-of-incidence and target thickness. (b) Electron spectra, sampled over the whole simulation space, averaged over the period of synchrotron emission for a 200 nm foil at normal and 45° incidence, and (c) the corresponding time-averaged ${\chi}_{\mathrm{e}}$ spectra.

Figure 4

Figure 5 (a) Laser-to-bremsstrahlung radiation energy conversion efficiency for varying laser intensity and target thickness. (b) Energy spectra for bremsstrahlung photons (solid) and synchrotron photons (dotted) for different target thicknesses. (c) The rate of energy conversion to bremsstrahlung radiation.

Figure 5

Table 1 The objective functions maximized with Bayesian optimization and the parameters of the found optimum for each.

Figure 6

Figure 6 Synchrotron and bremsstrahlung radiation for the objective function optima in Table 1, for which ${I}_{\mathrm{L}} = 3\times {10}^{22}(30\kern0.1em$fs$/{\tau}_{\mathrm{L}})(1\kern0.22em \unicode{x3bc}$m$/{\phi}_{\mathrm{L}})\kern0.1em$W cm−2. (a) Synchrotron photon energy spectra, (b) bremsstrahlung photon energy spectra and (c) angular profiles of total emitted synchrotron photon energy.

Figure 7

Table 2 The objective functions used for optimization with laser intensity of $3\times {10}^{23}(30\kern0.1em$fs$/{\tau}_{\mathrm{L}}\left)\right(1\kern0.22em \unicode{x3bc}$m$/{\phi}_{\mathrm{L}})\kern0.1em$W cm−2, and the parameters of the found optima.

Figure 8

Figure 7 Synchrotron and bremsstrahlung radiation for the objective function optima in Table 2, for which ${I}_{\mathrm{L}} = 3\times {10}^{23}(30\kern0.1em$fs$/{\tau}_{\mathrm{L}})(1\kern0.22em \mu$m$/{\phi}_{\mathrm{L}})\kern0.1em$W cm−2. (a) Synchrotron photon energy spectra, (b) bremsstrahlung photon energy spectra and (c) angular profiles of total emitted synchrotron photon energy.

Figure 9

Figure 8 (a) Maximum value of $\mathrm{d}\sum {\varepsilon}_{\mathrm{sy}}/ \mathrm{d}\theta$ as a function of the angle-of-incidence for synchrotron photons emitted in angular ranges ${\theta}_{90,0}$ (black) and ${\theta}_{0,-90}$ (blue), where $l = 3\kern0.22em \unicode{x3bc}$m, ${I}_{\mathrm{L}} = 3\times {10}^{22}\kern0.1em$ W cm−2, ${\phi}_{\mathrm{L}} = 1\kern0.22em \unicode{x3bc}$m, ${\tau}_{\mathrm{L}} = 30\kern0.1em$fs and ${x}_{\mathrm{f}} = 0$. The optima in Figure 6 are also shown (diamonds). (b) Total energy in electrons more than 10 MeV in a local intensity more than 1021 W cm−2 propagating with angle ${\theta}_{\mathrm{e}}$ in the ranges ${\theta}_{90,0}$ (dashed) and ${\theta}_{0,-90}$ (solid) averaged over the period of synchrotron emission. (c) Energy-weighted mean angle between the electron trajectory and the propagation direction of the local electromagnetic field (left-hand axis) and mean electron quantum parameter (right-hand axis) for each group of electrons in (b). (d)–(f) The electron density for ${\theta}_{\mathrm{i}} = 0{}^{\circ}$, 22.5° and 60°, respectively, where the total momentum of fast electrons (arrows) and the $I = {10}^{21}$ W cm−2 contour (red) are also shown.

Figure 10

Figure 9 3D simulation results for synchrotron photon emission for different laser light polarization states. Peak angle-resolved synchrotron energy emitted in each direction for (a) p-polarization, (b) s-polarization and (c) left-hand and right-hand circular polarization. (d)–(f) Conversion efficiency to synchrotron radiation for p-, s- and both left-hand and right-hand circular polarization, respectively.

Figure 11

Figure 10 Angular profiles of the total energy of synchrotron emission in the forward direction ($\mid \theta \mid <90{}^{\circ}$) in 3D simulations for different laser light polarization states and angles-of-incidence.

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