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Artificial Neural Network Trained to Predict High-Harmonic Flux [post]

Ana Maria Mihaela Gherman, Katalin Kovács, Mircea Vasile Cristea, Valer Tosa
2018 unpublished

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In this work we present the results obtained with an artificial neural network (ANN) which we trained to predict the expected output of high-order harmonic generation (HHG) process, while exploring a multi-dimensional parameter space. We argue on the utility and efficiency of the ANN model and demonstrate its ability to predict the outcome of HHG simulations. In this case study we present the results for a loose focusing HHG beamline, where the changing parameters are: the laser pulse energy,
more » ... s pressure, gas cell position relative to focus and gas cell length. The physical quantity which we predict here using ANN is directly related to the total harmonic yield in a specified spectral domain (20-40 eV). We discuss the versatility and adaptability of the presented method.
doi:10.20944/preprints201809.0563.v1 fatcat:dmash72vhjhvnjuuz4ryj6oxca
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Ana Maria Mihaela Gherman, Katalin Kovács, Mircea Vasile Cristea, Valer Tosa. "Artificial Neural Network Trained to Predict High-Harmonic Flux." (2018)