### Abstract

Original language | English |
---|---|

Title of host publication | Maximum Entropy and Bayesian Methods Garching, Germany 1998 |

Editors | Wolfgang von der Linden, Volker Dose, Rainer Fischer, Roland Preuss |

Publisher | Springer Netherlands |

Pages | 99-106 |

Number of pages | 8 |

ISBN (Print) | 978-94-010-5982-4 978-94-011-4710-1 |

Publication status | Published - 1999 |

### Publication series

Name | Fundamental Theories of Physics |
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Publisher | Springer Netherlands |

### Fingerprint

### Keywords

- Adaptive Kernels, Artificial Intelligence (incl. Robotics), Coding and Information Theory, Discrete Mathematics in Computer Science, Electron Energy Distribution, Inverse Problem, Low-Pressure Plasma, Occam’s Razor, Over-Fitting, Probability Theory and Stochastic Processes, Statistics, general

### Cite this

*Maximum Entropy and Bayesian Methods Garching, Germany 1998*(pp. 99-106). (Fundamental Theories of Physics). Springer Netherlands.

**Bayesian Reconstruction of Electron Energy Distributions from Emission Line Intensities.** / Fischer, R.; Jacob, W.; Linden, W. Von Der; Dose, V.

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution › Research

*Maximum Entropy and Bayesian Methods Garching, Germany 1998.*Fundamental Theories of Physics, Springer Netherlands, pp. 99-106.

}

TY - CHAP

T1 - Bayesian Reconstruction of Electron Energy Distributions from Emission Line Intensities

AU - Fischer, R.

AU - Jacob, W.

AU - Linden, W. Von Der

AU - Dose, V.

N1 - DOI: 10.1007/978-94-011-4710-110

PY - 1999

Y1 - 1999

N2 - Low-pressure plasmas are nowadays widely used for technical applications of plasma-surface interactions, such as plasma etching, material deposition, sputtering, etc. For a thorough understanding of individual processes in plasma processing the electron energy distribution (EED) function in the bulk plasma is of great importance. The EED determines the rates of all electron induced reactions as ionization, excitation or dissociation of molecules. The ubiquitous assumption of a Maxwellian EED becomes progressively worse for hot and low-density plasmas. Measurements of the EED with probes penetrating the plasma result in deteriorating effects on the plasma and the probe, thus measurements without plasma contact are of great interest. A non-destructive measurement is the detection of radiation emitted by the plasma. The form-free reconstruction of the EED from a small number of measured emission intensities results in an ill-posed inversion problem. In order to avoid spurious features due to overfitting of the data (ringing) we apply Bayesian probability theory along with the adaptive-kernel method. The Bayesian approach will be applied to emission lines of helium, since in this case the relevant atomic input quantities are best known.

AB - Low-pressure plasmas are nowadays widely used for technical applications of plasma-surface interactions, such as plasma etching, material deposition, sputtering, etc. For a thorough understanding of individual processes in plasma processing the electron energy distribution (EED) function in the bulk plasma is of great importance. The EED determines the rates of all electron induced reactions as ionization, excitation or dissociation of molecules. The ubiquitous assumption of a Maxwellian EED becomes progressively worse for hot and low-density plasmas. Measurements of the EED with probes penetrating the plasma result in deteriorating effects on the plasma and the probe, thus measurements without plasma contact are of great interest. A non-destructive measurement is the detection of radiation emitted by the plasma. The form-free reconstruction of the EED from a small number of measured emission intensities results in an ill-posed inversion problem. In order to avoid spurious features due to overfitting of the data (ringing) we apply Bayesian probability theory along with the adaptive-kernel method. The Bayesian approach will be applied to emission lines of helium, since in this case the relevant atomic input quantities are best known.

KW - Adaptive Kernels, Artificial Intelligence (incl. Robotics), Coding and Information Theory, Discrete Mathematics in Computer Science, Electron Energy Distribution, Inverse Problem, Low-Pressure Plasma, Occam’s Razor, Over-Fitting, Probability Theory and St

M3 - Other chapter contribution

SN - 978-94-010-5982-4 978-94-011-4710-1

T3 - Fundamental Theories of Physics

SP - 99

EP - 106

BT - Maximum Entropy and Bayesian Methods Garching, Germany 1998

A2 - Linden, Wolfgang von der

A2 - Dose, Volker

A2 - Fischer, Rainer

A2 - Preuss, Roland

PB - Springer Netherlands

ER -