Quantum Rings in Electromagnetic Fields

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordThis chapter is devoted to optical properties of so-called Aharonov-Bohm quantum rings (quantum rings pierced by a magnetic flux resulting in AharonovBohm oscillations of their electronic spectra) in external electromagnetic fields. It studies two problems. The first problem deals with a single-electron AharonovBohm quantum ring pierced by a magnetic flux and subjected to an in-plane (lateral) electric field. We predict magneto-oscillations of the ring electric dipole moment. These oscillations are accompanied by periodic changes in the selection rules for inter-level optical transitions in the ring allowing control of polarization properties of the associated terahertz radiation. The second problem treats a single-mode microcavity with an embedded Aharonov-Bohm quantum ring which is pierced by a magnetic flux and subjected to a lateral electric field. We show that external electric and magnetic fields provide additional means of control of the emission spectrum of the system. In particular, when the magnetic flux through the quantum ring is equal to a half-integer number of the magnetic flux quanta, a small change in the lateral electric field allows for tuning of the energy levels of the quantum ring into resonance with the microcavity mode, thus providing an efficient way to control the quantum ring-microcavity coupling strength. Emission spectra of the system are discussed for several combinations of the applied magnetic and electric fields

An Authentic Ecg Simulator

An ECG (electrocardiogram) simulator is an electronic tool that plays an essential role in the testing, design, and development of ECG monitors and other ECG equipment. Principally an ECG simulator provides ECG monitors with an electrical signal that emulates the human heart\u27s electrical signal so that the monitor can be tested for reliability and important diagnostic capabilities. However, the current portable commercially available ECG simulators are lacking in their ability to fully test ECG monitors. Specifically, the portable simulators presently on the market do not produce authentic ECG signals but rather they endeavor to create the ECG signals mathematically. They even attempt to mathematically create arrhythmias (irregular heartbeats of which there are many different types). Arrhythmia detection is an important capability for any modern ECG monitor because arrhythmias are often the critical link to the diagnosis of heart conditions or cardiovascular disease. The focus of this thesis is the design and implementation of a portable ECG simulator. The important innovation of this prototype simulator is that it will not create its ECG signals mathematically, but rather it will store ECG data files on a memory module and use this data to produce an authentic ECG signal. The data files will consist of different types of ECG signals including different types of arrhythmias. The data files are obtained via the internet and require formatting and storing onto a memory chip. These files are then processed by a digital to analog converter and output on a four lead network to produce an authentic ECG signal. The system is built around the ultra-low power Texas Instruments MSP430 microcontroller

Numerical implementation of the Hilbert transform

Many people have abnormal heartbeats from time to time. A Holter monitor is a device used to record the electrical impulses of the heart when people do ordinary activities. Holter monitoring systems that can record heart rate and rhythm when you feel chest pain or symptoms of an irregular heartbeat (called an arrhythmia) and automatically perform electrocardiogram (ECG) signal analysis are desirable.The use of the Hilbert transform (HT) in the area of electrocardiogram analysis is investigated. A property of the Hilbert transform, i.e., to form the analytic signal, was used in this thesis. Subsequently pattern recognition can be used to analyse the ECG data and lossless compression techniques can be used to reduce the ECG data for storage.The thesis discusses one part of the Holter Monitoring System, Input processing.Four different approaches, including the Time-Domain approach, the Frequency-Domain approach, the Boche approach and the Remez filter approach for calculating the Hilbert transform of an ECG wave are discussed in this thesis. By comparing them from the running time and the ease of software and hardware implementations, an efficient approach (the Remez approach) for use in calculating the Hilbert transform to build a Holter Monitoring System is proposed. Using the Parks-McClellan algorithm, the Remez approach was present, and a digital filter was developed to filter the data sequence. Accurate determination of the QRS complex, in particular, accurate detection of the wave peak, is important in ECG analysis and is another task in this thesis. A program was developed to detect the wave peak in an ECG wave.The whole algorithm is implemented using Altera’s Nios SOPC (system on a program chip) Builder system development tool. The performance of the algorithm was tested using the standard ECG waveform records from the MIT-BIH Arrhythmia database. The results will be used in pattern recognition to judge whether the ECG wave is normal or abnormal

Memory-Assisted Quantum Key Distribution with a Single Nitrogen-Vacancy Center

Memory-assisted measurement-device-independent quantum key distribution (MA-MDI-QKD) is a promising scheme that aims to improve the rate-versus-distance behavior of a QKD system by using the state-of-the-art devices. It can be seen as a bridge between current QKD links to quantum repeater based networks. While, similar to quantum repeaters, MA-MDI-QKD relies on quantum memory (QM) units, the requirements for such QMs are less demanding than that of probabilistic quantum repeaters. Here, we present a variant of MA-MDI-QKD structure that relies on only a single physical QM: a nitrogen-vacancy center embedded into a cavity where its electronic spin interacts with photons and its nuclear spin is used for storage. This enables us to propose a simple but efficient MA-MDI-QKD scheme resilient to memory errors and capable of beating, in terms of rate and reach, existing QKD demonstrations. We also show how we can extend this setup to a quantum repeater system, reaching, thus, larger distances

Low-Power Reconfigurable Sensing Circuitry for the Internet-of-Things Paradigm

With ubiquitous wireless communication via Wi-Fi and nascent 5th Generation mobile communications, more devices -- both smart and traditionally dumb -- will be interconnected than ever before. This burgeoning trend is referred to as the Internet-of-Things. These new sensing opportunities place a larger burden on the underlying circuitry that must operate on finite battery power and/or within energy-constrained environments. New developments of low-power reconfigurable analog sensing platforms like field-programmable analog arrays (FPAAs) present an attractive sensing solution by processing data in the analog domain while staying flexible in design. This work addresses some of the contemporary challenges of low-power wireless sensing via traditional application-specific sensing and with FPAAs. A large emphasis is placed on furthering the development of FPAAs by making them more accessible to designers without a strong integrated-circuit background -- much like FPGAs have done for digital designers

FEEDFORWARD ARTIFICIAL NEURAL NETWORK DESIGN UTILISING SUBTHRESHOLD MODE CMOS DEVICES

This thesis reviews various previously reported techniques for simulating artificial neural networks and investigates the design of fully-connected feedforward networks based on MOS transistors operating in the subthreshold mode of conduction as they are suitable for performing compact, low power, implantable pattern recognition systems. The principal objective is to demonstrate that the transfer characteristic of the devices can be fully exploited to design basic processing modules which overcome the linearity range, weight resolution, processing speed, noise and mismatch of components problems associated with weak inversion conduction, and so be used to implement networks which can be trained to perform practical tasks. A new four-quadrant analogue multiplier, one of the most important cells in the design of artificial neural networks, is developed. Analytical as well as simulation results suggest that the new scheme can efficiently be used to emulate both the synaptic and thresholding functions. To complement this thresholding-synapse, a novel current-to-voltage converter is also introduced. The characteristics of the well known sample-and-hold circuit as a weight memory scheme are analytically derived and simulation results suggest that a dummy compensated technique is required to obtain the required minimum of 8 bits weight resolution. Performance of the combined load and thresholding-synapse arrangement as well as an on-chip update/refresh mechanism are analytically evaluated and simulation studies on the Exclusive OR network as a benchmark problem are provided and indicate a useful level of functionality. Experimental results on the Exclusive OR network and a 'QRS' complex detector based on a 10:6:3 multilayer perceptron are also presented and demonstrate the potential of the proposed design techniques in emulating feedforward neural networks

Bottom-up design of artificial neural network for single-lead electrocardiogram beat and rhythm classification

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined in terms of perfecting individual sub-systems to improve the over all system performance is used. Sub-systems include pre-processing, QRS detection and fiducial point estimations, feature calculations, and pattern classification. Inaccuracies in time-domain fiducial point estimations are overcome with the derivation of features in the frequency domain. Feature extraction in frequency domain is based on a spectral estimation technique (combination of simulation and subtraction of a normal beat). Auto-regressive spectral estimation methods yield a highly sensitive spectrum, providing several local features with information on beat classes like flutter, fibrillation, and noise. A total of 27 features, including 16 in time domain and 11 in frequency domain are calculated. The entire data and problem are divided into four major groups, each group with inter-related beat classes. Classification of each group into related sub-classes is performed using smaller feed-forward neural networks. Input feature sub-set and the structure of each network are optimized using an iterative process. Optimal implementations of feed-forward neural networks provide high accuracy in beat classification. Associated neural networks are used for the more deterministic rhythm-classification task. An accuracy of more than 85% is achieved for all 13 classes included in this study. The system shows a graceful degradation in performance with increasing noise, as a result of the noise consideration in the design of every sub-system. Results indicate a neural network-based bottom-up design of single-lead ECG classification is able to provide very high accuracy, even in the presence of noise, flutter, and fibrillation

Quantum Rings in Electromagnetic Fields

This thesis is devoted to optical properties of Aharonov-Bohm quantum rings in external electromagnetic fields. It contains two problems. The first problem deals with a single-electron Aharonov-Bohm quantum ring pierced by a magnetic flux and subjected to an in-plane (lateral) electric field. We predict magneto-oscillations of the ring electric dipole moment. These oscillations are accompanied by periodic changes in the selection rules for inter-level optical transitions in the ring allowing control of polarization properties of the associated terahertz radiation. The second problem treats a single-mode microcavity with an embedded Aharonov-Bohm quantum ring, which is pierced by a magnetic flux and subjected to a lateral electric field. We show that external electric and magnetic fields provide additional means of control of the emission spectrum of the system. In particular, when the magnetic flux through the quantum ring is equal to a half-integer number of the magnetic flux quantum, a small change in the lateral electric field allows tuning of the energy levels of the quantum ring into resonance with the microcavity mode, providing an efficient way to control the quantum ring-microcavity coupling strength. Emission spectra of the system are calculated for several combinations of the applied magnetic and electric fields.FP7 Initial Training Network "Spin-Optronics