Coupled rate equation modeling of self-assembled quantum dot photoluminescence

Sales, F.V. de; Cruz, J.R.; Silva, S.W. da; Soler, Maria A. G.; Morais, P.C.; Silva, M.J. da; Quivy, A. A.; Leite, J. R.

doi:10.1016/s0026-2692(03)00107-1

“…The possible thermal escape of electrons from the dots could also be considered with a low probability of occurrence due to the low energy associated with room temperature [22]. Several papers have also reported on a direct capture mechanism of carriers from barrier to QD [8,23].…”

Section: Resultsmentioning

confidence: 99%

“…A rate equation model was proposed based on coupleddifferential equations of the carrier dynamics described in figure 3. Possible state-filling of both QD and WL states was considered in this numerical model [23,29]. The differential equations for the barrier (n B ), WL (n W ), and QD (n D ) regions are presented in equations ( 3)- (5).…”

Section: Numerical Simulation Using Rate Equation Modelmentioning

confidence: 99%

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Ultrafast photocarrier dynamics in InAs/GaAs self-assembled quantum dots investigated via optical pump-terahertz probe spectroscopy

Juguilon,

Lumantas-Colades,

Omambac

et al. 2024

J. Phys. D: Appl. Phys.

0

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Optical pump-terahertz probe (OPTP) spectroscopy was performed to measure the lifetime of photogenerated carriers in the barrier and the wetting layer (WL) regions of an indium arsenide on gallium arsenide (InAs/GaAs) single-layer self-assembled quantum dot (QD) sample. A modified rate equation model of carrier dynamics was proposed where possible state-filling in both QD and WL is considered. Drude model fitting was also performed to extract the time-dependent plasma frequency and phenomenological scattering time from the terahertz transmission spectra. The results of the OPTP experiment show two prominent recombination processes that occur at different timescales after photoexcitation. These two processes were attributed to carrier recombination in the GaAs barrier and the quantum well-like states of the wetting layer based on the fitted lifetimes. Calculations using the coupled differential rate equations were also able to replicate the experimental trend at low fluence. The lack of agreement between experimental data and numerical calculations at high optical fluence was mainly attributed to the possible saturation of the GaAs density of states. Lastly, the results of the parameter fitting for the plasma frequency and scattering time indicate a transition from the barrier to the WL recombination as the dominant carrier recombination mechanism within the time scale of the OPTP scan. This further lends credence to the proposed model for carrier dynamics in SAQD systems under state-filling conditions.

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“…To reproduce the fluorescence signals generated by a large number of QD networks, we construct a mathematical model of electron transitions within individual QDs using a deterministic approach. Previous models have assumed that electrons in a QD transition between multiple energy levels [19][20][21]. We develop a two-level system for electrons in QDs, incorporating FRET and level occupancy effects.…”

Section: Rate Equation Of Qdsmentioning

confidence: 99%

Design of quantum dot networks for improving prediction performance in reservoir computing

Yamanouchi,

Shimomura,

Tanida

2024

Preprint

0

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A quantum dot (QD) network generates various fluorescence signals based on nonlinear energy dynamics which depend on its structure and composition and is utilized for a component of physical reservoir computing. However, existing designs rely on random QD networks, which is not be optimal for enhancing the prediction performance. In this paper, we propose a method for designing effective quantum dot (QD) networks to improve the performance of reservoir computing. The fluorescence signals from numerous virtual QD networks can be reproduced through numerical simulation based on a deterministic mathematical model, and the QD networks generating the most significant signals contributing to the prediction performance are identified. We demonstrated that QD reservoir computing using designed QD networks predicts time-series data more accurately than using random QD networks in the numerical simulations.

show abstract

“…To reproduce the fluorescence signals generated by a large number of QD networks, we construct a mathematical model of electron transitions within individual QDs using a deterministic approach. Previous models have assumed that electrons in a QD transition between multiple energy levels [19][20][21]. We develop a two-level system for electrons in QDs, incorporating FRET and level occupancy effects.…”

Section: Rate Equation Of Qdsmentioning

confidence: 99%

Design of quantum dot networks for improving prediction performance in reservoir computing

Yamanouchi,

Shimomura,

Tanida

2024

Preprint

0

View full text Add to dashboard Cite

A quantum dot (QD) network generates various fluorescence signals based on nonlinear energy dynamics which depend on its structure and composition and is utilized for a component of physical reservoir computing. However, existing designs rely on random QD networks, which is not be optimal for enhancing the prediction performance. In this paper, we propose a method for designing effective quantum dot (QD) networks to improve the performance of reservoir computing. The fluorescence signals from numerous virtual QD networks can be reproduced through numerical simulation based on a deterministic mathematical model, and the QD networks generating the most significant signals contributing to the prediction performance are identified. We demonstrated that QD reservoir computing using designed QD networks predicts time-series data more accurately than using random QD networks in the numerical simulations.

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Coupled rate equation modeling of self-assembled quantum dot photoluminescence

Cited by 3 publications

References 3 publications

Ultrafast photocarrier dynamics in InAs/GaAs self-assembled quantum dots investigated via optical pump-terahertz probe spectroscopy

Ultrafast photocarrier dynamics in InAs/GaAs self-assembled quantum dots investigated via optical pump-terahertz probe spectroscopy

Design of quantum dot networks for improving prediction performance in reservoir computing

Design of quantum dot networks for improving prediction performance in reservoir computing

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