Fast breakdown (FB), a breakdown process composed of systems of high‐velocity streamers, has been observed to precede lightning leader formation and play a critical role in lightning initiation. Vigorous FB events are responsible for the most powerful natural radio emissions on Earth, known as narrow bipolar events (NBEs). In this paper, an improved version of the Griffiths and Phelps (1976,
We employ two machine learning techniques, i.e., neural networks and genetic-programming-based symbolic regression, to examine the dynamics of the electron-positron pair creation process with full space–time resolution inside the interaction zone of a supercritical electric field pulse. Both algorithms receive multiple sequences of partially dressed electronic and positronic spatial probability densities as training data and exploit their features as a function of the dressing strength in order to predict each particle’s spatial distribution inside the electric field. A linear combination of both predicted densities is then compared with the unambiguous total charge density, which also contains contributions associated with the independent vacuum polarization process. After its subtraction, the good match confirms the validity of the machine learning approach and lends some credibility to the validity of the predicted single-particle densities.
more » « less- Award ID(s):
- 2106585
- NSF-PAR ID:
- 10306365
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Journal of the Optical Society of America B
- Volume:
- 38
- Issue:
- 12
- ISSN:
- 0740-3224; JOBPDE
- Page Range / eLocation ID:
- Article No. 3582
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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