scholarly journals Bifurcation Study of a Semiconductor Laser with Saturable Absorber and Delayed Optical Feedback

2012 ◽  
pp. 161-181 ◽  
Author(s):  
Bernd Krauskopf ◽  
Jamie J. Walker
2009 ◽  
Vol 79 (3) ◽  
Author(s):  
A. Loose ◽  
B. K. Goswami ◽  
H.-J. Wünsche ◽  
F. Henneberger

2016 ◽  
Vol 42 (1) ◽  
pp. 163 ◽  
Author(s):  
D. Brunner ◽  
R. Luna ◽  
A. Delhom i Latorre ◽  
X. Porte ◽  
I. Fischer

Photonics ◽  
2022 ◽  
Vol 9 (1) ◽  
pp. 47
Author(s):  
Xavier Porte ◽  
Daniel Brunner ◽  
Ingo Fischer ◽  
Miguel C. Soriano

Semiconductor lasers can exhibit complex dynamical behavior in the presence of external perturbations. Delayed optical feedback, re-injecting part of the emitted light back into the laser cavity, in particular, can destabilize the laser’s emission. We focus on the emission properties of a semiconductor laser subject to such optical feedback, where the delay of the light re-injection is large compared to the relaxation oscillations period. We present an overview of the main dynamical features that emerge in semiconductor lasers subject to delayed optical feedback, emphasizing how to experimentally characterize these features using intensity and high-resolution optical spectra measurements. The characterization of the system requires the experimentalist to be able to simultaneously measure multiple time scales that can be up to six orders of magnitude apart, from the picosecond to the microsecond range. We highlight some experimental observations that are particularly interesting from the fundamental point of view and, moreover, provide opportunities for future photonic applications.


Photonics ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 124 ◽  
Author(s):  
Krishan Harkhoe ◽  
Guy Van der Sande

Reservoir computing has rekindled neuromorphic computing in photonics. One of the simplest technological implementations of reservoir computing consists of a semiconductor laser with delayed optical feedback. In this delay-based scheme, virtual nodes are distributed in time with a certain node distance and form a time-multiplexed network. The information processing performance of a semiconductor laser-based reservoir computing (RC) system is usually analysed by way of testing the laser-based reservoir computer on specific benchmark tasks. In this work, we will illustrate the optimal performance of the system on a chaotic time-series prediction benchmark. However, the goal is to analyse the reservoir’s performance in a task-independent way. This is done by calculating the computational capacity, a measure for the total number of independent calculations that the system can handle. We focus on the dependence of the computational capacity on the specifics of the masking procedure. We find that the computational capacity depends strongly on the virtual node distance with an optimal node spacing of 30 ps. In addition, we show that the computational capacity can be further increased by allowing for a well chosen mismatch between delay and input data sample time.


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