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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 22, Iss. 7 — Apr. 7, 2014
  • pp: 8585–8597

Classification of birefringence in mode-locked fiber lasers using machine learning and sparse representation

Xing Fu, Steven L. Brunton, and J. Nathan Kutz  »View Author Affiliations


Optics Express, Vol. 22, Issue 7, pp. 8585-8597 (2014)
http://dx.doi.org/10.1364/OE.22.008585


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Abstract

It has been observed that changes in the birefringence, which are difficult or impossible to directly measure, can significantly affect mode-locking in a fiber laser. In this work we develop techniques to estimate the effective birefringence by comparing a test measurement of a given objective function against a learned library. In particular, a toroidal search algorithm is applied to the laser cavity for various birefringence values by varying the waveplate and polarizer angles at incommensurate angular frequencies, thus producing a time-series of the objective function. The resulting time series, which is converted to a spectrogram and then dimensionally reduced with a singular value decomposition, is then labelled with the corresponding effective birefringence and concatenated into a library of modes. A sparse search algorithm (L1-norm optimization) is then applied to a test measurement in order to classify the birefringence of the fiber laser. Simulations show that the sparse search algorithm performs very well in recognizing cavity birefringence even in the presence of noise and/or noisy measurements. Once classified, the wave plates and polarizers can be adjusted using servo-control motors to the optimal positions obtained from the toroidal search. The result is an efficient, self-tuning laser.

© 2014 Optical Society of America

OCIS Codes
(140.3510) Lasers and laser optics : Lasers, fiber
(140.4050) Lasers and laser optics : Mode-locked lasers
(320.7090) Ultrafast optics : Ultrafast lasers

ToC Category:
Lasers and Laser Optics

History
Original Manuscript: December 18, 2013
Revised Manuscript: March 20, 2014
Manuscript Accepted: March 21, 2014
Published: April 3, 2014

Citation
Xing Fu, Steven L. Brunton, and J. Nathan Kutz, "Classification of birefringence in mode-locked fiber lasers using machine learning and sparse representation," Opt. Express 22, 8585-8597 (2014)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-22-7-8585


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