Universal Quasi-Level Parameter for the Characterization of Laser Operation

Jirauschek, Christian

doi:10.1109/jphot.2018.2863025

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…We have developed a robust method to calculate the extraction efficiency p e , utilizing a rate equation model in analogy to Jirauschek (2018) and calculating the absorption efficiency using transition rates extracted either from Monte Carlo simulations or obtained directly by solving Fermi's golden rule for elastic and inelastic scattering processes (Jirauschek and Kubis 2014;Jirauschek 2017). The wavefunctions and eigenenergies necessary for the calculations of scattering rates in the EMC are generated by a Schrödinger-Poisson solver based on the transfer matrix method (TMM) (Jirauschek 2009).…”

Section: Modeling Methodsmentioning

confidence: 99%

Bayesian optimization of quantum cascade detectors

et al. 2021

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A Bayesian optimization algorithm in combination with a scattering based simulation approach is used for the optimization of quantum cascade detectors (QCDs). QCDs operate in the mid-infrared and terahertz regime and are, together with quantum cascade lasers, appropriate for the integration into on-chip applications such as gas sensors. Our modeling approach is based on a rate equation model and a Kirchhoff resistance network for noise modeling, using scattering rates calculated with Fermi’s golden rule, or alternatively extracted from an ensemble Monte Carlo transport approach. The appropriate surrogate model of Bayesian optimization is based on Gaussian process regression, which can handle noisy offsets on the objective function evaluations inherent in ensemble Monte Carlo simulations. Here, we focus on the optimization of a matured mid-infrared QCD design detecting at 4.7 $$\upmu {\mathrm{m}}$$ μ m . For optimization we choose as figure of merit the specific detectivity, which is a measure for the signal-to-noise ratio. As the trade-off between high extraction efficiency and low detector conductance is important for good detection performance, we search for the perfect layer composition and vary the thicknesses of different cascade layers. Due to the high-temperature requirements interesting for cost-effective and mobile on-chip sensing applications, a simulation temperature of 300 K is selected. Our optimization strategy yields an improvement of specific detectivity by a factor of $${\sim 2-3}$$ ∼ 2 - 3 at room temperature using two different parameter sets. Furthermore, we investigate the sensitivity of our approach to fabrication tolerances, showing robustness of the optimized designs against growth fluctuations under fabrication conditions.

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Section: Modeling Methodsmentioning

confidence: 99%

Bayesian optimization of quantum cascade detectors

et al. 2021

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“…where R p is the peak responsivity, R 0 the detector resistance, T the temperature and k B the Boltzmann constant. We have developed a robust method calculating R p by solving perturbed rate equations in analogy to [7], [14] and calculating the absorption efficiency using transition rates calculated by Fermi's golden rule [3].…”

Section: Methodsmentioning

confidence: 99%

Numerical Optimization of Quantum Cascade Detector Heterostructures

Popp

Haider

Franckié

et al. 2020

2020 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD)

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We demonstrate a Bayesian optimization framework for quantum cascade (QC) devices in the mid-infrared (mid-IR) and terahertz (THz) regime. The optimization algorithm is based on Gaussian process regression (GPR) and the devices are evaluated using a perturbed rate equation approach based on scattering rates calculated self-consistently by Fermi's golden rule or alternatively extracted from an Ensemble Monte Carlo (EMC) simulation tool. Here, we focus on the optimization of a mid-IR quantum cascade detector (QCD) at a wavelength of 4.7 µm with respect to the specific detectivity as a measure for the signal to noise ratio. At a temperature of 220 K we obtain an improvement in specific detectivity by a factor ∼ 2.6 to a value of 2.6 × 10 8 Jones.

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Ensemble Monte Carlo modeling of quantum cascade detectors

Jirauschek

Popp

Haider

et al. 2021

Journal of Applied Physics

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We present a method to perform accurate and efficient simulations of photovoltaic quantum cascade detector (QCD) structures based on the ensemble Monte Carlo (EMC) approach. Since the photocurrent is typically orders of magnitude smaller than the pump current in a quantum cascade laser (QCL), a direct application of QCL simulation techniques is not sufficiently accurate. We demonstrate that by exploiting thermodynamic equilibrium relations for the electron populations and scattering rates, the EMC method can be adapted to yield reliable results for the essential QCD figures of merit, such as responsivity and specific detectivity. The modeling approach is validated against available experimental results for various mid-infrared and terahertz QCD designs and furthermore compared to simulations based on the non-equilibrium Green’s function method.

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Universal Quasi-Level Parameter for the Characterization of Laser Operation

Cited by 4 publications

References 17 publications

Bayesian optimization of quantum cascade detectors

Bayesian optimization of quantum cascade detectors

Numerical Optimization of Quantum Cascade Detector Heterostructures

Ensemble Monte Carlo modeling of quantum cascade detectors

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