Intensity noise properties of quantum cascade lasers

Gensty, T.; Elsäßer, Wolfgang; Mann, Ch.

doi:10.1364/opex.13.002032

Cited by 57 publications

(30 citation statements)

References 13 publications

(17 reference statements)

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“…For example, it has been found experimentally, and verified theoretically, that the scaling behavior of the intensity noise as a function of the emitted power is different with respect to interband lasers, resulting directly from the cascaded level scheme and the different carrier lifetime. 2,3 The linewidth enhancement factor (␣ factor) determines the dynamics of semiconductor lasers, because it accounts for the coupling between amplitude and phase of the light as defined in Eq. (1),…”

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Measurements of the α factor of a distributed-feedback quantum cascade laser by an optical feedback self-mixing technique

et al. 2006

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We demonstrate measurements of the ␣ factor of a distributed-feedback quantum cascade laser (QCL) by using a newly modified self-mixing interferometric technique exploring the laser itself as the detector. We find a strong dependence of the ␣ factor on the injection current, ranging from −0.44 at 120 mA to 2.29 at 180 mA, which can be attributed to the inherent physics of QCLs. © 2006 Optical Society of America OCIS codes: 140.5960, 140.3070, 040.5570, 120.3180. Today, quantum cascade lasers (QCLs) have evolved to be among the most important light sources in the mid-infrared (MIR) to far-infrared (FIR) wavelength range. The lasing transition in QCLs occurs between subsequently cascaded quantized energy levels within the conduction band. Hence the emitted wavelength does not depend on the energy bandgap as in conventional semiconductor lasers, but it is determined by the energy difference of discrete levels in the conduction band originating from the bandgapengineered design of the laser device.1 With the advent of this new type of laser structure, a series of questions on the laser performance and the relevant physical mechanisms have been brought up. For example, it has been found experimentally, and verified theoretically, that the scaling behavior of the intensity noise as a function of the emitted power is different with respect to interband lasers, resulting directly from the cascaded level scheme and the different carrier lifetime.2,3 The linewidth enhancement factor (␣ factor) determines the dynamics of semiconductor lasers, because it accounts for the coupling between amplitude and phase of the light as defined in Eq. (1),Here, r and i are the real and the imaginary parts of the susceptibility, respectively, and n is the carrier density. 4 The ␣ factor therefore describes how gain and refractive index change with respect to each other when the carrier density varies.5 From the very beginning of the first technological realizations of QCLs, there has been an urgent need to measure the ␣ factor of QCLs and to check whether the particular level scheme gives rise to a different physics, e.g., ifQCLs exhibit an ␣ factor close to zero as expected for a nondetuned atomiclike level scheme. The standard technique used for interband semiconductor lasers is the Hakki-Paoli method, which relies on measuring the wavelength shift of the longitudinal laser modes below threshold. However, this method gives only access to ␣ values below threshold, and for low ␣ values its accuracy may be affected by temperature effects. 6 An approach based on injection locking 7 is the only method, to date, that has been applied to QCLs above threshold.Our purpose in this paper is fourfold. First, we apply the self-mixing (SM) technique to the MIR spectral range using QCLs. Second, by directly using the laser itself as a detector instead of an external photodetector, we are able to obtain nice and clean SM signals. Third, by applying a modified analysis method, we are able to extract the ␣ factor from the measurement of these wavefo...

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Measurements of the α factor of a distributed-feedback quantum cascade laser by an optical feedback self-mixing technique

et al. 2006

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“…We consider the rate equations formulated by Gensty et al [11] and Gensty and Elsäßer [12]. The active region of a QC laser consists of a period of N p cascaded gain stages (N p = 25 − 35).…”

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“…The phonon scattering times between level 3 and level 2, between level 3 and level 1, and between level 2 and level 1 are denoted by τ 32 , τ 31 , and τ 21 , respectively. τ p is the photon lifetime [11,12]. Typical values of the time constants are documented in Table I.…”

Section: Formulationmentioning

confidence: 99%

Nonlinear dynamics of an injected quantum cascade laser

2013

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The stability properties of an injected quantum cascade laser are investigated analytically on the basis of current estimates of the laser parameters. We show that in addition to stable locking, Hopf bifurcations leading to pulsating intensities are possible. We discuss the stability diagrams in terms of the detuning and the injection rate for different values of the linewidth enhancement factor. The analysis indicates domains of coexistence between two stable steady states (bistability) or between a stable steady state and stable periodic oscillations. All predictions are verified numerically by determining bifurcation diagrams from the laser rate equations.

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“…This noise is quantified as relative intensity noise (RIN), which is the ratio of the power variance of the optical signal to the mean optical power squared. Quantum cascade lasers have a measured RIN on the order of −150 dB Hz −1 with an output of 10-dBm mean optical power [43]. To convert to a SNR, we use the relation [44] where B is the noise bandwidth, assumed equal to the modulation rate, and m is the modulation index, equal to 1−E, where E is the extinction ratio of the modulator.…”

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confidence: 99%

Physical-Layer Modeling and System-Level Design of Chip-Scale Photonic Interconnection Networks

Chan

Hendry

Bergman

et al. 2011

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

107

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Abstract-Photonic technology is becoming an increasingly attractive solution to the problems facing today's electronic chip-scale interconnection networks. Recent progress in silicon photonics research has enabled the demonstration of all the necessary optical building blocks for creating extremely highbandwidth density and energy-efficient links for on-chip and off-chip communications. From the feasibility and architecture perspective however, photonics represents a dramatic paradigm shift from traditional electronic network designs due to fundamental differences in how electronics and photonics function and behave. As a result of these differences, new modeling and analysis methods must be employed in order to properly realize a functional photonic chip-scale interconnect design. In this paper, we present a methodology for characterizing and modeling fundamental photonic building blocks which can subsequently be combined to form full photonic network architectures. We also describe a set of tools which can be utilized to assess the physical-layer and system-level performance properties of a photonic network. The models and tools are integrated in a novel open-source design and simulation environment. We present a case study of two different photonic networks-on-chip to demonstrate how our improved understanding and modeling of the physical-layer details of photonic communications can be used to better understand the system-level performance impact.Index Terms-Optical communications, optical crosstalk, optical losses, photonic interconnection networks, simulation software, system analysis and design.

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Intensity noise properties of quantum cascade lasers

Cited by 57 publications

References 13 publications

Measurements of the α factor of a distributed-feedback quantum cascade laser by an optical feedback self-mixing technique

Measurements of the α factor of a distributed-feedback quantum cascade laser by an optical feedback self-mixing technique

Nonlinear dynamics of an injected quantum cascade laser

Physical-Layer Modeling and System-Level Design of Chip-Scale Photonic Interconnection Networks

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