Design of a Limiting Amplifier for an Optical Receiver

The HEP experiments that take place at CERN’s LHC demand a multi-gigabit optical link for an efficient transmission of the resulting generated data. An optoelectronic link arises as the best solution given its possibility of working at high data rates and due to fiber’s imunnity to electromagnetic noise. The design of this optical link is particularly demanding due to the stringent data rate specifications (5Gb/s), the BER specification (1012) and the constraints imposed by radiation. In HEP, radiation is always a constraint so, the Optical Receiver circuit must be hardened in order to tolerate that kind of environment - radiation-tolerant. The core of a standard optoeletronic receiver includes a Photodiode, a Transimpedance Amplifier (TIA) and a Limiting Amplifier (LA). This thesis proposes the study and implementation of one of these blocks (LA), as the main focus, as well as the analysis and design of all three other blocks. The two major design constraints regarding the LA are the bandwidth and minimising its power consumption, which were overcome by using two bandwidth enhancement techniques. The circuit yields a bandwidth of 4:8GHz with a power consumption under 19mW. Another fundamental block is the Output Buffer. The major request for this block was maintaining relatively low transition times and improving the signal’s integrity. It has a differential output swing around 400mV with Pre-emphasis levels larger than 130%. The third block is the Received Signal Strength Indicator (RSSI). From a system point of view it is useful to have a measure of the input signal’s power so that the communication channel is used in its full potential. With a power consumption smaller than 600μW the RSSI presents an input dynamic range larger than 50 dB. The fourth block implements a Squelch function, in order to suppress unwanted output toggling due to noise. All these elements were developed in a TSMC 65nm CMOS process with a 1:2V supply voltage

Diode-pumped Tm³⁺-doped sesquioxide lasers for ultrashort pulse applications in the 2μm region

This thesis presents the development of Tm³⁺-doped sesquioxide laser sources in the 2–2.1 μm spectral region. The primary focus of this development has been aimed towards high power diode-pumped mode-locked laser sources capable of femtosecond pulse generation. In addition to this, the early development of a compact and low threshold ultrafast laser inscribed waveguide laser has also been realised. Continuous wave characterisation of bulk solid-state crystalline Tm:LuScO₃ and ceramic Tm:Lu₂O₃ lasers has been completed using ~795 nm multimode single emitter laser diode pump sources. Average output powers of 660 mW and 901 mW, and emission wavelengths of 2.1 μm and 2.06 μm were achieved from the Tm:LuScO₃ and Tm:Lu₂O₃ lasers, respectively. In addition, both lasers demonstrated smooth and continuous tuning ranges spanning more than 160 nm in the ~2–2.1 μm spectral region. In the mode-locked regime, pulse durations as short as 170 fs were recorded at an average output power of 113 mW and an emission wavelength of 2094 nm from a diode-pumped mode-locked Tm:LuScO₃ laser through the use of an ion-implanted InGaAsSb quantum-well-based semiconductor saturable absorber mirror. A diode-pumped Tm:Lu₂O₃ laser, utilising the same semiconductor saturable absorber mirror, was able to generate pulses as short as 278 fs at an average output power of 555 mW and a wavelength of 2081 nm through the use of a steeply diving optic axis birefringent filter. This same filter was also used to demonstrate broadly tunable femtosecond pulses in both laser configurations. Subsequent amplification of the ultrashort pulse laser sources realised maximum amplified average output powers of 540 mW and 855 mW, respectively. The results presented in this thesis demonstrate the potential for diode-pumped Tm³⁺-doped sesquioxide laser sources to be developed into an enabler technology for the advancement of a number of photonics applications and techniques in the mid-infrared region."The work was supported by the Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/L01596X/1] and Fraunhofer UK Research Limited studentship funding." -- Acknowledgement

Phase-advanced attitude sensing and control for fixed-wing micro aerial vehicles in turbulence

The scale of fixed-wing Micro Aerial Vehicles (MAVs) lend them to many unique applications. These applications often require low speed flights close to the ground, in the vicinity of large obstacles and in the wake of buildings. A particular challenge for MAVs is attitude control in the presence of high turbulence. Such flights pose a challenging operational environment for MAVs, and in particular, ensuring sufficient attitude control in the presence of significant turbulence. Low-level flight in the atmospheric boundary layer without sufficient attitude control is hazardous, mainly due to the high levels of turbulence intensity close to the ground. MAV accidents have occurred due to the lack of a reliable attitude control system in turbulent conditions as reported in the literature. Challenges associated with flight control of fixed-wing MAVs operating in complex environments are significantly different to any larger scale vehicle. The scale of MAVs makes them particularly sensitive to atmospheric disturbances thus limiting their operation. A review of the literature revealed that rolling inputs from turbulence were the most challenging whereby conventional inertial-based attitude control systems lack the responsiveness for roll control in high turbulence environments. The solution might lie with flying animals, which have adapted to flight within turbulence. The literature survey identified bio-inspired phase-advanced sensors as a promising sensory solution for complementing current reactive attitude sensors. The development of a novel bio-inspired phase-advanced sensor and associated control system, which can sense the flow disturbances before an attitude perturbation, is the focus of this research. The development of such a system required an in-depth understanding of the features of the disturbing phenomena; turbulence. Correlation studies were conducted between the oncoming turbulence and wing-surface pressure variations. It was found that the highest correlation exists between upstream flow pitch angle variation and the wing-surface pressure fluctuations. However, due to the insufficient time-forward advantage, surface pressure sensing was not used for attitude control. A second sensing approach was explored to cater for the control system’s time-lags. Multi-hole pressure probes were embedded in the wings of the MAV to sense flow pitch angle and magnitude variation upstream of the wing. The sensors provide an estimate of the disturbing turbulence. This approach caters for the time-lags of the system providing sufficient time to counteract the gust before it results in an inertial response. Statistical analysis was used to assess the disturbance rejection performance of the phase-advanced sensory system, which was benchmarked against a conventional inertial-based sensory system in a range of turbulence conditions. Unconstrained but controlled test flights were conducted inside the turbulence environment of two wind-tunnels, in addition to outdoor flight testing in the atmosphere. These three different turbulence conditions enabled testing of a wide range of turbulence spectra believed to be most detrimental to the MAV. A significant improvement in disturbance rejection performance was observed in relation to conventional inertial-based sensory systems. It can be concluded that sensory systems providing time-forward estimates of turbulence can complement conventional inertial-based sensors to improve the attitude stability performance

Astronomy with integral field spectroscopy:: observation, data analysis and results

With a new generation of facility instruments being commissioned for 8 metre telescopes, integral field spectroscopy will soon be a standard tool in astronomy, opening a range of exciting new research opportunities. It is clear, however, that reducing and analyzing integral field data is a complex problem, which will need considerable attention before the full potential of the hardware can be realized. The purpose of this thesis is therefore to explore some of the scientific capabilities of integral field spectroscopy, developing the techniques needed to produce astrophysical results from the data. Two chapters are dedicated to the problem of analyzing observations from the densely-packed optical fibre instruments pioneered at Durham. It is shown that, in the limit where each spectrum is sampled by only one detector row, data maybe treated in a similar way to those from an image slicer. The properties of raw fibre data are considered in the context of the Sampling Theorem and methods for three dimensional image reconstruction are discussed. These ideas are implemented in an IRAF data reduction package for the Thousand Element Integral Field Unit (TEIFU), with source code provided on the accompanying compact disc. Two observational studies are also presented. In the first case, the 3D infrared image slicer has been used to test for the presence of a super-massive black hole in the giant early-type galaxy NGC 1316. Measurements of the stellar kinematics do not reveal a black hole of mass 5 x l0(^9)M©, as predicted from bulge luminosity using the relationship of Kormendy & Richstone (1995). The second study is an investigation into the origin of [Fell] line emission in the Seyfert galaxy NGC4151, using Durham University's SMIRFS-IFU. By mapping [Fell] line strength and velocity at the galaxy centre, it is shown that the emission is associated with the optical narrow line region, rather than the radio jet, indicating that the excitation is primarily due to photoionizing X-rays.Finally, a report is given on the performance of TEIFU, which was commissioned at the William Herschel Telescope in 1999. Measurements of throughput and fibre response variation are given and a reconstructed test observation of the radio galaxy 3C 327 is shown, demonstrating the functionality of the instrument and software

Bi-multilingual Language Engagement Shapes the Brain’s Functional Connectivity: An Aging Study on Resting State Brain Rhythms Correlated to Executive Functions

Bi-multilingualism have been argued to help maintain cognitive functioning in aging through increased resilience to cognitive decline, known as cognitive reserves (CR). Researchers have argued that bi-multilingualism imposes unique cognitive demands that can change the brain’s structural and functional integrity. In order to investigate the effects of multilingual engagement on cognition, behaviourally and neurologically, resting state (RS) oscillations were collected through electroencephalography (EEG) in healthy Norwegian-English bi multilingual adults in various stages of adulthood. Additionally, behavioural responses in terms of reaction times (RT) were captured through a non-linguistic flanker task and further correlated to RS dynamics. Negative main effects of language experience, operationalised as multilingual diversity (MLD), were found in the alpha and gamma bands, while also indications in said frequency bands indicated a flattening effect of age-related cognitive decline for those with a higher MLD. The MLD did not indicate increased flanker efficiency, where only older age significantly increased RTs. No correlations were found between the RS functional connectivity and flanker performance. These findings might suggest that higher multilingual engagement will slow down the age-related decline in the brain’s functional connectivity, as this negative main effect of MLD is likely due to no CR trade-off for the younger participants

A computational approach to motivated behaviour and apathy

The loss of motivation and goal-directed behaviour is characteristic of apathy. Across a wide range of neuropsychiatric disorders, including Huntington’s disease (HD), apathy is poorly understood, associated with significant morbidity, and is hard to treat. One of the challenges in understanding the neural basis of apathy is moving from phenomenology and behavioural dysfunction to neural circuits in a principled manner. The computational framework offers one such approach. I adopt this framework to better understand motivated behaviour and apathy in four complementary projects. At the heart of many apathy formulations is impaired self-initiation of goal-directed behaviour. An influential computational theory proposes that “opportunity cost”, the amount of reward we stand to lose by not taking actions per unit time, is a key variable in governing the timing of self-initiated behaviour. Using a novel task, I found that free-operant behaviour in healthy participants both in laboratory conditions and in online testing, conforms to predictions of this computational model. Furthermore, in both studies I found that in younger adults sensitivity to opportunity cost predicted behavioural apathy scores. Similar pilot results were found in a cohort of patients with HD. These data suggest that opportunity cost may be an important computational variable relevant for understanding a core feature of apathy – the timing of self-initiated behaviour. In my second project, I used a reinforcement learning paradigm to probe for early dysfunction in a cohort of HD gene carriers approximately 25 years from clinical onset. Based on empirical data and computational models of basal ganglia function I predicted that asymmetry in learning from gains and losses may be an early feature of carrying the HD gene. As predicted, in this task fMRI study, HD gene carriers demonstrated an exaggerated neural response to gains as compared to losses. Gene carriers also differed in the neural response to expected value suggesting that carrying the HD gene is associated with altered processing of valence and value decades from onset. Finally, based on neurocomputational models of basal ganglia pathway function, I tested the hypothesis that apathy in HD would be associated with the involvement of the direct pathway. Support for this hypothesis was found in two related projects. Firstly, using data from a large international HD cohort study, I found that apathy was associated with motor features of the disease thought to represent direct pathway involvement. Secondly, I tested this hypothesis in vivo using resting state fMRI data and a model of basal ganglia connectivity in a large peri-manifest HD cohort. In keeping with my predictions, whilst emerging motor signs were associated with changes in the indirect pathway, apathy scores were associated with connectivity changes in the direct pathway connectivity within my model. For patients with apathy across neuropsychiatry there is an urgent need to understand the neural basis of motivated behaviour in order to develop novel therapies. In this thesis, I have used a computational framework to develop and test a range of hypotheses to advance this understanding. In particular, I have focussed on the computational factors which drive us to self-initiate, their potential neural underpinnings and the relevance of these models for apathy in patients with HD. The data I present supports the hypothesis that opportunity cost and basal ganglia pathway connectivity may be two important components necessary to generate motivated behaviour and contribute to the development of apathy in HD

The application of digital techniques to an automatic radar track extraction system

'Modern' radar systems have come in for much criticism in recent years, particularly in the aftermath of the Falklands campaign. There have also been notable failures in commercial designs, including the well-publicised 'Nimrod' project which was abandoned due to persistent inability to meet signal processing requirements. There is clearly a need for improvement in radar signal processing techniques as many designs rely on technology dating from the late 1970's, much of which is obsolete by today’s standards. The Durham Radar Automatic Track Extraction System (RATES) is a practical implementation of current microprocessor technology, applied to plot extraction of surveillance radar data. In addition to suggestions for the design of such a system, results are quoted for the predicted performance when compared with a similar product using 1970's design methodology. Suggestions are given for the use of other VLSI techniques in plot extraction, including logic arrays and digital signal processors. In conclusion, there is an illustrated discussion concerning the use of systolic arrays in RATES and a prediction that this will represent the optimum architecture for future high-speed radar signal processors

How does the brain extract acoustic patterns? A behavioural and neural study

In complex auditory scenes the brain exploits statistical regularities to group sound elements into streams. Previous studies using tones that transition from being randomly drawn to regularly repeating, have highlighted a network of brain regions involved during this process of regularity detection, including auditory cortex (AC) and hippocampus (HPC; Barascud et al., 2016). In this thesis, I seek to understand how the neurons within AC and HPC detect and maintain a representation of deterministic acoustic regularity. I trained ferrets (n = 6) on a GO/NO-GO task to detect the transition from a random sequence of tones to a repeating pattern of tones, with increasing pattern lengths (3, 5 and 7). All animals performed significantly above chance, with longer reaction times and declining performance as the pattern length increased. During performance of the behavioural task, or passive listening, I recorded from primary and secondary fields of AC with multi-electrode arrays (behaving: n = 3), or AC and HPC using Neuropixels probes (behaving: n = 1; passive: n = 1). In the local field potential, I identified no differences in the evoked response between presentations of random or regular sequences. Instead, I observed significant increases in oscillatory power at the rate of the repeating pattern, and decreases at the tone presentation rate, during regularity. Neurons in AC, across the population, showed higher firing with more repetitions of the pattern and for shorter pattern lengths. Single-units within AC showed higher precision in their firing when responding to their best frequency during regularity. Neurons in AC and HPC both entrained to the pattern rate during presentation of the regular sequence when compared to the random sequence. Lastly, development of an optogenetic approach to inactivate AC in the ferret paves the way for future work to probe the causal involvement of these brain regions