High Power Laser Science and Engineering, Volume. 12, Issue 1, 01000e12(2024)

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

J. Goodman*, M. King, E. J. Dolier, R. Wilson, R. J. Gray, and P. McKenna
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Due to an isolated error in the 3D simulation parameters, the laser energy and intensity (calculated using the energy) values were incorrectly stated as 10.9 J and 3×1022 W cm−2, respectively, in Sections 3.3, 7 and 8. The correct values are 39.8 J and 1.1×1023 W cm−2. Similarly, the values stated for the higher energy case, 109 J and 3×1023 W cm−2 in Section 7, should be 398 J and 1.1×1024 W cm−2, respectively.

The conversion efficiencies (which are calculated using the laser energy) shown in Figures 9(d)–9(f) are corrected by multiplying by a constant factor of 0.273. With corrected energies, the synchrotron conversion efficiencies in Section 3.3 now become 4.32%, 4.50% and 1.67% for xf = 0, zR and −zR, respectively, corresponding to changes of +4% and −61% for the positive and negative defocus, respectively.

This error does not affect the conclusions of the article.

[1] J. Goodman, M. King, E. J. Dolier, R. Wilson, R. J. Gray, P. McKenna. Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning. High Power Laser Science and Engineering, 11(2023).

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J. Goodman, M. King, E. J. Dolier, R. Wilson, R. J. Gray, P. McKenna. Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning – CORRIGENDUM[J]. High Power Laser Science and Engineering, 2024, 12(1): 01000e12

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Published Online: Feb. 19, 2024

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DOI:10.1017/hpl.2023.95

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