Simple model for quantum-dot semiconductor optical amplifiers using artificial neural networks

A simple and accurate dynamical modeling of quantum‐dot semiconductor optical amplifiers

“…; f p 7 ; ; w p  à T is the state vector of the system, u(t) = S in (t) is the input variable, y(t) = S out (t) is the output variable, F 1 is the resultant rate of carriers transition rates, and F 2 is the relation of optical gain, that is, (19). Using (23)-(26), we develop the SSM of QD-SOA in the form of (27). The state update equations are given by the following differential equations:…”

Quantum-Dot Semiconductor Optical Amplifiers: State Space Model versus Rate Equation Model

“…( , +1 + , +1 + , +1 ) . The effective capture and escape rates for holes in the VB levels are similar to (26) and (27), except that the superscript is replaced by . Since the rate equations and consequently the state update equations are not explicit functions of time, QD-SOA is an autonomous system.…”

“…In some other papers, the holes dynamics is included by using quasi-Fermi level in the valence band (VB) [26]. Also, the dynamics of electron and hole are considered separately in some articles [4,[27][28][29][30][31]. This model is known as "electron-hole model" [30], where the rate equations for electrons and holes are written separately.…”

Computational intelligence in photonics technology and optical networks: A survey and future perspectives

“…Evolution strategies have been employed for the optimization of semiconductor quantum devices, dealing there with fundamental issues such as transition energies, compositional parameters, applied electric field, or devices' geometry [1,17,18,27,46,47] targeting to applications like lasers or second harmonic generation for the production of multiple optical wavelengths.…”