Employing machine learning for theory validation and identification of experimental conditions in laser-plasma physics

@article{Gonoskov2019EmployingML,
  title={Employing machine learning for theory validation and identification of experimental conditions in laser-plasma physics},
  author={A. Gonoskov and E. Wallin and A. Polovinkin and I. Meyerov},
  journal={Scientific Reports},
  year={2019},
  volume={9}
}
  • A. Gonoskov, E. Wallin, +1 author I. Meyerov
  • Published 2019
  • Computer Science, Physics, Medicine
  • Scientific Reports
  • The validation of a theory is commonly based on appealing to clearly distinguishable and describable features in properly reduced experimental data, while the use of ab-initio simulation for interpreting experimental data typically requires complete knowledge about initial conditions and parameters. We here apply the methodology of using machine learning for overcoming these natural limitations. We outline some basic universal ideas and show how we can use them to resolve long-standing… CONTINUE READING
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