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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 20, Iss. 14 — Jul. 2, 2012
  • pp: 15569–15579

Predictive modeling techniques for nanosecond-laser damage growth in fused silica optics

Zhi M. Liao, Ghaleb M. Abdulla, Raluca A. Negres, David A. Cross, and Christopher W. Carr  »View Author Affiliations

Optics Express, Vol. 20, Issue 14, pp. 15569-15579 (2012)

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Empirical numerical descriptions of the growth of laser-induced damage have been previously developed. In this work, Monte-Carlo techniques use these descriptions to model the evolution of a population of damage sites. The accuracy of the model is compared against laser damage growth observations. In addition, a machine learning (classification) technique independently predicts site evolution from patterns extracted directly from the data. The results show that both the Monte-Carlo simulation and machine learning classification algorithm can accurately reproduce the growth of a population of damage sites for at least 10 shots, which is extremely valuable for modeling optics lifetime in operating high-energy laser systems. Furthermore, we have also found that machine learning can be used as an important tool to explore and increase our understanding of the growth process.

© 2012 OSA

OCIS Codes
(140.3330) Lasers and laser optics : Laser damage
(160.4670) Materials : Optical materials

ToC Category:
Lasers and Laser Optics

Original Manuscript: April 18, 2012
Revised Manuscript: June 7, 2012
Manuscript Accepted: June 8, 2012
Published: June 26, 2012

Zhi M. Liao, Ghaleb M. Abdulla, Raluca A. Negres, David A. Cross, and Christopher W. Carr, "Predictive modeling techniques for nanosecond-laser damage growth in fused silica optics," Opt. Express 20, 15569-15579 (2012)

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