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Artificial Neural Network Trained to Predict High-Harmonic Flux
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,doi:10.20944/preprints201809.0563.v1 fatcat:dmash72vhjhvnjuuz4ryj6oxca