Physics and Applications of Laser Diode Chaos

An overview of chaos in laser diodes is provided which surveys experimental achievements in the area and explains the theory behind the phenomenon. The fundamental physics underpinning this behaviour and also the opportunities for harnessing laser diode chaos for potential applications are discussed. The availability and ease of operation of laser diodes, in a wide range of configurations, make them a convenient test-bed for exploring basic aspects of nonlinear and chaotic dynamics. It also makes them attractive for practical tasks, such as chaos-based secure communications and random number generation. Avenues for future research and development of chaotic laser diodes are also identified.Comment: Published in Nature Photonic

Nonlinear Dynamics in Optoelectronics Structures with Quantum Well

The author presents some results on nonlinear dynamics in optoelectronics nanostructures as lasers with quantum wells and quantum well solar cells using mathematical modeling and numerical simulations of the phenomena which take place in such kinds of structures. The nonlinear dynamics takes the complexity of the phenomena into account, which govern the field-substance interaction. Computational software was elaborated to study the nonlinear phenomena in such quantum devices, which put into evidence their complex nonlinear dynamics, characterized by bifurcation points and chaos, and the critical values of the parameters being determined. The mathematical modeling and numerical simulations for the quantum well solar cells for optimizing the values of their optical parameters (refraction index, reflectance, and absorption) were also analyzed, so that the conversion efficiency of the devices can be improved. Although in our study we have considered only rectangular quantum wells, the hybrid model allows computing the optimum values of the parameters whatsoever the form of the quantum wells. The developed numerical models and the obtained results are consistent with the existing data in the literature for the optoelectronics of quantum well structures, having important implications in the applications

Neuromorphic nanophotonic systems for artificial intelligence

Over the last decade, we have witnessed an astonishing pace of development in the field of artificial intelligence (AI), followed by proliferation of AI algorithms into virtually every domain of our society. While modern AI models boast impressive performance, they also require massive amounts of energy and resources for operation. This is further fuelling the research into AI-specific, optimised computing hardware. At the same time, the remarkable energy efficiency of the brain brings an interesting question: Can we further borrow from the working principles of biological intelligence to realise a more efficient artificial intelligence? This can be considered as the main research question in the field of neuromorphic engineering. Thanks to the developments in AI and recent advancements in the field of photonics and photonic integration, research into light-powered implementations of neuromorphic hardware has recently experienced a significant uptick of interest. In such hardware, the aim is to seize some of the highly desirable properties of photonics not just for communication, but also to perform computation. Neurons in the brain frequently process information (compute) and communicate using action potentials, which are brief voltage spikes that encode information in the temporal domain. Similar dynamical behaviour can be elicited in some photonic devices, at speeds multiple orders of magnitude higher. Such devices with the capability of neuron-like spiking are of significant research interest for the field of neuromorphic photonics. Two distinct types of such excitable, spiking systems operating with optical signals are studied and investigated in this thesis. First, a vertical cavity surface emitting laser (VCSEL) can be operated under a specific set of conditions to realise a high-speed, all-optical excitable photonic neuron that operates at standard telecom wavelengths. The photonic VCSEL-neuron was dynamically characterised and various information encoding mechanisms were studied in this device. In particular, a spiking rate-coding regime of operation was experimentally demonstrated, and its viability for performing spiking domain conversion of digital images was explored. Furthermore, for the first time, a joint architecture utilising a VCSEL-neuron coupled to a photonic integrated circuit (PIC) silicon microring weight bank was experimentally demonstrated in two different functional layouts. Second, an optoelectronic (O/E/O) circuit based upon a resonant tunnelling diode (RTD) was introduced. Two different types of RTD devices were studied experimentally: a higher output power, µ-scale RTD that was RF coupled to an active photodetector and a VCSEL (this layout is referred to as a PRL node); and a simplified, photosensitive RTD with nanoscale injector that was RF coupled to a VCSEL (referred to as a nanopRL node). Hallmark excitable behaviours were studied in both devices, including excitability thresholding and refractory periods. Furthermore, a more exotic resonate and-fire dynamical behaviour was also reported in the nano-pRL device. Finally, a modular numerical model of the RTD was introduced, and various information processing methods were demonstrated using both a single RTD spiking node, as well as a perceptron-type spiking neural network with physical models of optoelectronic RTD nodes serving as artificial spiking neurons.Over the last decade, we have witnessed an astonishing pace of development in the field of artificial intelligence (AI), followed by proliferation of AI algorithms into virtually every domain of our society. While modern AI models boast impressive performance, they also require massive amounts of energy and resources for operation. This is further fuelling the research into AI-specific, optimised computing hardware. At the same time, the remarkable energy efficiency of the brain brings an interesting question: Can we further borrow from the working principles of biological intelligence to realise a more efficient artificial intelligence? This can be considered as the main research question in the field of neuromorphic engineering. Thanks to the developments in AI and recent advancements in the field of photonics and photonic integration, research into light-powered implementations of neuromorphic hardware has recently experienced a significant uptick of interest. In such hardware, the aim is to seize some of the highly desirable properties of photonics not just for communication, but also to perform computation. Neurons in the brain frequently process information (compute) and communicate using action potentials, which are brief voltage spikes that encode information in the temporal domain. Similar dynamical behaviour can be elicited in some photonic devices, at speeds multiple orders of magnitude higher. Such devices with the capability of neuron-like spiking are of significant research interest for the field of neuromorphic photonics. Two distinct types of such excitable, spiking systems operating with optical signals are studied and investigated in this thesis. First, a vertical cavity surface emitting laser (VCSEL) can be operated under a specific set of conditions to realise a high-speed, all-optical excitable photonic neuron that operates at standard telecom wavelengths. The photonic VCSEL-neuron was dynamically characterised and various information encoding mechanisms were studied in this device. In particular, a spiking rate-coding regime of operation was experimentally demonstrated, and its viability for performing spiking domain conversion of digital images was explored. Furthermore, for the first time, a joint architecture utilising a VCSEL-neuron coupled to a photonic integrated circuit (PIC) silicon microring weight bank was experimentally demonstrated in two different functional layouts. Second, an optoelectronic (O/E/O) circuit based upon a resonant tunnelling diode (RTD) was introduced. Two different types of RTD devices were studied experimentally: a higher output power, µ-scale RTD that was RF coupled to an active photodetector and a VCSEL (this layout is referred to as a PRL node); and a simplified, photosensitive RTD with nanoscale injector that was RF coupled to a VCSEL (referred to as a nanopRL node). Hallmark excitable behaviours were studied in both devices, including excitability thresholding and refractory periods. Furthermore, a more exotic resonate and-fire dynamical behaviour was also reported in the nano-pRL device. Finally, a modular numerical model of the RTD was introduced, and various information processing methods were demonstrated using both a single RTD spiking node, as well as a perceptron-type spiking neural network with physical models of optoelectronic RTD nodes serving as artificial spiking neurons

Monolithic 1.3 μm InAs/GaAs Quantum Dot Lasers on Silicon: Simulation and Experiment

1.3 μm quantum dot (QD) lasers epitaxially grown on silicon have attracted great interest as light source for silicon photonics and other optical communication applications. This work focuses on improving the understanding of the physical mechanisms limiting the performance of these devices, and on studying the laser dynamics with respect to data transmission potential through simulation and experiment. Dislocation-induced carrier loss is a major concern for the performance of QD lasers on silicon. Part of this work aims, therefore, at identifying the processes degrading the laser characteristics as well as on understanding the performance disparity between silicon-based QD and quantum well (QW) devices. By using two specially extended types of rate equation travelling-wave models it is found that enhanced carrier loss at higher dislocation densities leads to a much larger laser threshold increase in QW than in QD lasers. The QD laser’s increased tolerance to dislocations can be explained based on efficient and ultrafast carrier capture into the QDs, where high energy barriers prevent them from migrating into defects. The carrier density reduction in the higher energy continuum layers is eventually reflected in a lower current injection efficiency and thus reduced light-current slope, confirming experimentally observed trends of 1.3 μm QD lasers on silicon. In particular, a large minority carrier diffusion length is identified as a key parameter inhibiting laser operation in QW-based devices. The other part of this work focuses on investigating the QD lasers’ dynamics by means of gain switching, small-signal and large-signal modulation. 150 ps short gain-switched pulses, modulation bandwidths of 1.6 GHz to 2.3 GHz, and optical eyes at 1.5 Gb/s are obtained from 2.5 mm long ridge-waveguide lasers grown and fabricated at University College London. Numerical simulations reveal that the observed high-speed limitations are a result of limited gain and a long photon lifetime, whereas suitability for 10 Gb/s operation is predicted in an optimised laser design. It was, furthermore, found that neither dislocation-induced carrier loss nor optical loss limit the modulation characteristics fundamentally. The reduced carrier lifetime is, however, reflected in stronger damping of the small-signal modulation curves. Apart from that, the overall device dynamics remain governed by the QD physics.Qualcomm Inc. School of Technology PhD scholarshi

Enhanced Modulation Dynamic Performance of Optically-Injected Widely-Tunable Semiconductor Lasers

This dissertation is devoted to a comprehensive theoretical and modelling study of dynamic modulation characteristics of semiconductor wide-wavelength tunable laser diodes (TLDs). The two major goals were to investigate how modulation properties of a TLD depend on the wavelength tuning, and how the modulation performance of a TLD can be enhanced in terms of the achievable speed and improved frequency chirping behaviour under the direct modulation regimes using external light for optical injection-locking (OIL). It is demonstrated that modulation performance of free running (FR) widely tunable lasers strongly depends on the tuned lasing wavelength. The relaxation oscillation frequency (ROF) of FR TLD increases from 2.2 GHz to 5.5 GHz with tuning. The main results of investigation of modulation dynamics of OIL TLDs include demonstration of substantial (up to an order of magnitude) increase of the ROF and the modulation bandwidth in comparison with the FR regime and investigation of dependence of ROF on the wavelength tuning. The ROF increases to 24 GHz. We prove that the ROF of the OIL TLD is defined by the difference between the injected master laser’s light frequency and the cavity shifted mode frequency. The latter non-lasing mode has been identified as corresponding to the amplified spontaneous emission and was clearly reproduced in CW spectra of a steady-state OIL TLD. This finding has important practical implications as it allows to directly relating the CW lasing spectra fine features with dynamic performance of the OIL TLDs. Important results were obtained for case of large-signal modulation of the OIL TLD and for a large frequency detuning for side-mode optical injection regime when the master laser’s light is injected near the side-mode of FR TLD with large SMSR. Direct large-signal modulation of the OIL TLD using pseudo-random bit sequence shows superior performance in terms of enhanced modulation speed

Suppressing Diffusion-Mediated Exciton Annihilation in 2D Semiconductors Using the Dielectric Environment

Atomically thin semiconductors such as monolayer MoS2 and WS2 exhibit nonlinear exciton-exciton annihilation at notably low excitation densities (below ~10 excitons/um2 in MoS2). Here, we show that the density threshold at which annihilation occurs can be tuned by changing the underlying substrate. When the supporting substrate is changed from SiO2 to Al2O3 or SrTiO3, the rate constant for second-order exciton-exciton annihilation, k_XX [cm2/s], is reduced by one or two orders of magnitude, respectively. Using transient photoluminescence microscopy, we measure the effective room-temperature exciton diffusion coefficient in chemical-treated MoS2 to be D = 0.06 +/- 0.01 cm2/s, corresponding to a diffusion length of LD = 350 nm for an exciton lifetime of {\tau} = 20 ns, which is independent of the substrate. These results, together with numerical simulations, suggest that the effective exciton-exciton annihilation radius monotonically decreases with increasing refractive index of the underlying substrate. Exciton-exciton annihilation limits the overall efficiency of 2D semiconductor devices operating at high exciton densities; the ability to tune these interactions via the dielectric environment is an important step toward more efficient optoelectronic technologies featuring atomically thin materials

Optical feedback in semiconductor lasers

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