Properties and applications of injection locking in 1.55 μm quantum-dash mode-locked semiconductor lasers

Mode-locked semiconductor lasers are compact pulsed sources with ultra-narrow pulse widths and high repetition-rates. In order to use these sources in real applications, their performance needs to be optimised in several aspects, usually by external control. We experimentally investigate the behaviour of recently-developed quantum-dash mode-locked lasers (QDMLLs) emitting at 1.55 μm under external optical injection. Single-section and two-section lasers with different repetition frequencies and active-region structures are studied. Particularly, we are interested in a regime which the laser remains mode-locked and the individual modes are simultaneously phase-locked to the external laser. Injection-locked self-mode-locked lasers demonstrate tunable microwave generation at first or second harmonic of the free-running repetition frequency with sub-MHz RF linewidth. For two-section mode-locked lasers, using dual-mode optical injection (injection of two coherent CW lines), narrowing the RF linewidth close to that of the electrical source, narrowing the optical linewidths and reduction in the time-bandwidth product is achieved. Under optimised bias conditions of the slave laser, a repetition frequency tuning ratio >2% is achieved, a record for a monolithic semiconductor mode-locked laser. In addition, we demonstrate a novel all-optical stabilisation technique for mode-locked semiconductor lasers by combination of CW optical injection and optical feedback to simultaneously improve the time-bandwidth product and timing-jitter of the laser. This scheme does not need an RF source and no optical to electrical conversion is required and thus is ideal for photonic integration. Finally, an application of injection-locked mode-locked lasers is introduced in a multichannel phase-sensitive amplifier (PSA). We show that with dual-mode injection-locking, simultaneous phase-synchronisation of two channels to local pump sources is realised through one injection-locking stage. An experimental proof of concept is demonstrated for two 10 Gbps phase-encoded (DPSK) channels showing more than 7 dB phase-sensitive gain and less than 1 dB penalty of the receiver sensitivity.

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.

Hybrid photonic crystal lasers

Energy efficient Wavelength Division Multiplexing (WDM) is the key to satisfying the future bandwidth requirements of datacentres. As the silicon photonics platform is regarded the only technology able to meet the required power and cost efficiency levels, the development of silicon photonics compatible narrow linewidth lasers is now crucial. We discuss the requirements for such laser systems and report the experimental demonstration of a compact uncooled external-cavity mW-class laser architecture with a tunable Si Photonic Crystal resonant reflector, suitable for direct Frequency Modulation.

Dynamics of coupled modes in two-section semiconductor lasers with saturable absorption

Semiconductor lasers have the potential to address a number of critical applications in advanced telecommunications and signal processing. These include applications that require pulsed output that can be obtained from self-pulsing and mode-locked states of two-section devices with saturable absorption. Many modern applications place stringent performance requirements on the laser source, and a thorough understanding of the physical mechanisms underlying these pulsed modes of operation is therefore highly desirable. In this thesis, we present experimental measurements and numerical simulations of a variety of self-pulsation phenomena in two-section semiconductor lasers with saturable absorption. Our theoretical and numerical results will be based on rate equations for the field intensities and the carrier densities in the two sections of the device, and we establish typical parameter ranges and assess the level of agreement with experiment that can be expected from our models. For each of the physical examples that we consider, our model parameters are consistent with the physical net gain and absorption of the studied devices. Following our introductory chapter, the first system that we consider is a two-section Fabry-Pérot laser. This example serves to introduce our method for obtaining model parameters from the measured material dispersion, and it also allows us to present a detailed discussion of the bifurcation structure that governs the appearance of selfpulsations in two-section devices. In the following two chapters, we present two distinct examples of experimental measurements from dual-mode two-section devices. In each case we have found that single mode self-pulsations evolve into complex coupled dualmode states following a characteristic series of bifurcations. We present optical and mode resolved power spectra as well as a series of characteristic intensity time traces illustrating this progression for each example. Using the results from our study of a twosection Fabry-Pérot device as a guide, we find physically appropriate model parameters that provide qualitative agreement with our experimental results. We highlight the role played by material dispersion and the underlying single mode self-pulsing orbits in determining the observed dynamics, and we use numerical continuation methods to provide a global picture of the governing bifurcation structure. In our concluding chapter we summarise our work, and we discuss how the presented results can inform the development of optimised mode-locked lasers for performance applications in integrated optics.

Theory and optimisation of 1.3 and 1.55 μm (Al)InGaAs metamorphic quantum well lasers

The use of InGaAs metamorphic buffer layers (MBLs) to facilitate the growth of lattice-mismatched heterostructures constitutes an attractive approach to developing long-wavelength semiconductor lasers on GaAs substrates, since they offer the improved carrier and optical confinement associated with GaAs-based materials. We present a theoretical study of GaAs-based 1.3 and 1.55 μm (Al)InGaAs quantum well (QW) lasers grown on InGaAs MBLs. We demonstrate that optimised 1.3 μm metamorphic devices offer low threshold current densities and high differential gain, which compare favourably with InP-based devices. Overall, our analysis highlights and quantifies the potential of metamorphic QWs for the development of GaAs-based long-wavelength semiconductor lasers, and also provides guidelines for the design of optimised devices.