Title of article :
Impact of Carrier Relaxation Time on the Performance of Quantum Dot Laser with Planar Cavities ‎Using ‎Artificial ‎Neural ‎Networks
Author/Authors :
Izadyar ، Mohsen Department of Physics‎ - ‎Faculty of Basic Sciences‎ - ‎Shahid Sattari University‎ , Eshaghnezhad ، Mohammad Department of Mathematics‎ - ‎Faculty of Basic Sciences‎ - ‎Shahid Sattari University‎ , Davoodi Yeganeh ، Hossein Quantum Research Center‎ - ‎Shahid Sattari University‎
From page :
67
To page :
83
Abstract :
This study presents a model of ‎a quantum dot laser with a planar cavity, employing numerical methods and artificial neural networks for simulation purposes. The investigation focuses on the influence of critical parameters, including the injection current into the active layer of the quantum dot laser and the carrier relaxation time to a lower energy state level. The model delves into the intricate carrier and photon dynamics within the laser, solving a system of coupled equations that describe these interactions. The fourth-order Runge-Kutta method is utilized to solve these equations numerically. ‎‎The results indicate that increased pumping power enhances the stable power levels and the peak power output of the laser. Additionally, analysis of the power versus intensity of current ($P-I$) characteristic curve‎ ‎ reveals that a longer carrier relaxation time to a lower energy state leads to a higher threshold current and a reduction in the quantum efficiency of the device‎. ‎The study also examines the laser switch-on time against the injection current. Finally, the deterioration in the quality of quantum dots and quantum wells is scrutinized‎. To gain deeper insights into the effect of increased pumping current on laser switch-on time‎, ‎the study complements numerical findings with the application of artificial neural networks, yielding significant results.
Keywords :
Quantum dot laser‎ , ‎Simulation‎ , ‎Differential equations‎ , ‎Laser dynamics‎ , ‎Artificial neural network
Journal title :
Control and Optimization in Applied Mathematics
Journal title :
Control and Optimization in Applied Mathematics
Record number :
2779623
Link To Document :
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