A study of the sensitivity of switched-current wave analog filters to mismatching and clock-feedthrough errors

The influence of the main source of errors in Switched-Current (SI) filters over the performance of Wave Analog Filters (WAE) is evaluated. Models of mismatching and clock-feedthrough (CF) are deduced for basic building blocks, and applied to study the sensitivity of a third-order filter. Monte Carlo simulations performed using a behavior simulator prove that CF are dominant over mismatching effects

Polarization Imaging Sensors in Advanced Feature CMOS Technologies

The scaling of CMOS technology, as predicted by Moore\u27s law, has allowed for realization of high resolution imaging sensors and for the emergence of multi-mega-pixel imagers. Designing imaging sensors in advanced feature technologies poses many challenges especially since transistor models do not accurately portray their performance in these technologies. Furthermore, transistors fabricated in advanced feature technologies operate in a non-conventional mode known as velocity saturation. Traditionally, analog designers have been discouraged from designing circuits in this mode of operation due to the low gain properties in single transistor amplifiers. Nevertheless, velocity saturation will become even more prominent mode of operation as transistors continue to shrink and warrants careful design of circuits that can exploit this mode of operation. In this research endeavor, I have utilized velocity saturation mode of operation in order to realize low noise imaging sensors. These imaging sensors incorporate low noise analog circuits at the focal plane in order to improve the signal to noise ratio and are fabricated in 0.18 micron technology. Furthermore, I have explored nanofabrication techniques for realizing metallic nanowires acting as polarization filters. These nanoscopic metallic wires are deposited on the surface of the CMOS imaging sensor in order to add polarization sensitivity to the CMOS imaging sensor. This hybrid sensor will serve as a test bed for exploring the next generation of low noise and highly sensitive polarization imaging sensors

Diseño CMOS de un sistema de visión “on-chip” para aplicaciones de muy alta velocidad

Falta palabras claveEsta Tesis presenta arquitecturas, circuitos y chips para el diseño de sensores de visión CMOS con procesamiento paralelo embebido. La Tesis reporta dos chips, en concreto: El chip Q-Eye; El chip Eye-RIS_VSoC.. Y dos sistemas de visión construidos con estos chips y otros sistemas “off-chip” adicionales, como FPGAs, en concreto: El sistema Eye-RIS_v1; El sistema Eye-RIS_v2. Estos chips y sistemas están concebidos para ejecutar tareas de visión a muy alta velocidad y con consumos de potencia moderados. Los sistemas resultantes son, además, compactos y por lo tanto ventajosos en términos del factor SWaP cuando se los compara con arquitecturas convencionales formadas por sensores de imágenes convencionales seguidos de procesadores digitales. La clave de estas ventajas en términos de SWaP y velocidad radica en el uso de sensores-procesadores, en lugar de meros sensores, en la interface de los sistemas de visión. Estos sensores-procesadores embeben procesadores programables de señal-mixta dentro del pixel y son capaces tanto de adquirir imágenes como de pre-procesarlas para extraer características, eliminar información redundante y reducir el número de datos que se transmiten fuera del sensor para su procesamiento ulterior. El núcleo de la tesis es el sensor-procesador Q-Eye, que se usa como interface en los sistemas Eye-RIS. Este sensor-procesador embebe una arquitectura de procesamiento formada por procesadores de señal-mixta distribuidos por pixel. Sus píxeles son por tanto estructuras multi-funcionales complejas. De hecho, son programables, incorporan memorias e interactúan con sus vecinos para realizar una variedad de operaciones, tales como: Convoluciones lineales con máscaras programables; Difusiones controladas por tiempo y nivel de señal, a través de un “grid” resistivo embebido en el plano focal; Aritmética de imágenes; Flujo de programación dependiente de la señal; Conversión entre los dominios de datos: imagen en escala de grises e imagen binaria; Operaciones lógicas en imágenes binarias; Operaciones morfológicas en imágenes binarias. etc. Con respecto a otros píxeles multi-función y sensores-procesadores anteriores, el Q-Eye reporta entre otras las siguientes ventajas: Mayor calidad de la imagen y mejores prestaciones de las funcionalidades embebidas en el chip; Mayor velocidad de operación y mejor gestión de la energía disponible; Mayor versatilidad para integración en sistemas de visión industrial. De hecho, los sistemas Eye-RIS son los primeros sistemas de visión industriales dotados de las siguientes características: Procesamiento paralelo distribuido y progresivo; Procesadores de señal-mixta fiables, robustos y con errores controlados; Programabilidad distribuida. La Tesis incluye descripciones detalladas de la arquitectura y los circuitos usados en el pixel del Q-Eye, del propio chip Q-Eye y de los sistemas de visión construidos en base a este chip. Se incluyen también ejemplos de los distintos chips en operaciónThis Thesis presents architectures, circuits and chips for the implementation of CMOS VISION SENSORS with embedded parallel processing. The Thesis reports two chips, namely: Q-eye chip; Eye-RIS_VSoC chip, and two vision systems realized by using these chips and some additional “off-chip” circuitry, such as FPGAs. These vision systems are: Eye-RIS_v1 system; Eye-RIS_v2 system. The chips and systems reported in the Thesis are conceived to perform vision tasks at very high speed and with moderate power consumption. The proposed vision systems are also compact and advantageous in terms of SWaP factors as compared with conventional architectures consisting of standard image sensor followed by digital processors. The key of these advantages in terms of SWaP and speed lies in the use of sensors-processors, rather than mere sensors, in the front-end interface of vision systems. These sensors-processors embed mixed-signal programmable processors inside the pixel. Therefore, they are able to acquire images and process them to extract the features, removing the redundant information and reducing the data throughput for later processing. The core of the Thesis is the sensor-processor Q-Eye, which is used as front-end in the Eye-RIS systems. This sensor-processor embeds a processing architecture composed by mixed-signal processors distributed per pixel. Then, its pixels are complex multi-functional structures. In fact, they are programmable, incorporate memories and interact with its neighbors in order to carry out a set of operations, including: Linear convolutions with programmable linear masks; Time- and signal-controlled diffusions (by means of an embedded resistive grid); Image arithmetic; Signal-dependent data scheduling; Gray-scale to binary transformation; Logic operation on binary images; Mathematical morphology on binary images, etc. As compared with previous multi-function pixels and sensors-processors, the Q-Eye brings among other the following advantages: Higher image quality and better performances of functionalities embedded on chip; Higher operation speed and better management of energy budget; More versatility for integration in industrial vision systems. In fact, the Eye-RIS systems are the first industrial vision systems equipped with the following characteristics: Parallel distributed and progressive processing; Reliable, robust mixed-signal processors with handled errors; Distributed programmability. This Thesis includes detailed descriptions of architecture and circuits used in the Q-Eye pixel, in the Q-Eye chip itself and in the vision systems developed based on this chip. Also, several examples of chips and systems in operation are presented

Cryogenic Control Beyond 100 Qubits

Quantum computation has been a major focus of research in the past two decades, with recent experiments demonstrating basic algorithms on small numbers of qubits. A large-scale universal quantum computer would have a profound impact on science and technology, providing a solution to several problems intractable for classical computers. To realise such a machine, today's small experiments must be scaled up, and a system must be built which provides control and measurement of many hundreds of qubits. A device of this scale is challenging: qubits are highly sensitive to their environment, and sophisticated isolation techniques are required to preserve the qubits' fragile states. Solid-state qubits require deep-cryogenic cooling to suppress thermal excitations. Yet current state-of-the-art experiments use room-temperature electronics which are electrically connected to the qubits. This thesis investigates various scalable technologies and techniques which can be used to control quantum systems. With the requirements for semiconductor spin-qubits in mind, several custom electronic systems, to provide quantum control from deep cryogenic temperatures, are designed and measured. A system architecture is proposed for quantum control, providing a scalable approach to executing quantum algorithms on a large number of qubits. Control of a gallium arsenide qubit is demonstrated using a cryogenically operated FPGA driving custom gallium arsenide switches. The cryogenic performance of a commercial FPGA is measured, as the main logic processor in a cryogenic quantum control system, and digital-to-analog converters are analysed during cryogenic operation. Recent work towards a 100-qubit cryogenic control system is shown, including the design of interconnect solutions and multiplexing circuitry. With qubit fidelity over the fault-tolerant threshold for certain error correcting codes, accompanying control platforms will play a key role in the development of a scalable quantum machine

A precision measurement of the rate of muon capture on the deuteron

Because quantum chromodynamics (QCD) is non-perturbative at low energies, strong in- teractions at the ∼ GeV scale are very challenging to understand. Theoretical progress has been made recently using QCD-based effective field theories (EFT). The short-distance physics of the effective theory is absorbed into a limited number of low energy constants (LECs), which are determined by direct experimental measurement. The MuSun experi- ment is measuring the rate Λd for muon capture on the deuteron, which is the simplest weak interaction in a two nucleon system. Λd will be used, in turn, to better determine a funda- mental LEC known as dR in the EFT. An improvement in the precision of this LEC will improve our understanding of several other processes in the two-nucleon sector: pp fusion, the main source of energy in the sun and other main-sequence stars and neutrino-deuteron scattering, as observed in the SNO experiment. The MuSun experiment determines Λd via a precision measurement of the negative muon lifetime in deuterium. The time difference between an incoming muon, which stops in deuterium, and the subsequent decay electron characterizes the muon disappearance rate. That disappearance rate is the sum of the ordinary muon decay rate and the nuclear capture rate. The ultimate goal of the MuSun experiment is to determine the nuclear capture rate (Λd) to a precision of 1.5 %, an order of magnitude improvement over previous efforts. The principal experimental development required to achieve this goal is a cryogenic (T ∼30K) time projection chamber, which not only serves as the deuterium gas target, but also provides an unambiguous measurement of muon stopping position - muons that stop in high Z materials outside the fiducial deuterium volume produce a very large systematic error. The low temperature helps minimize several other systematic errors. The MuSun experiment is taking place at the Paul Scherrer Institut in Villigen, Switzer- land. Over the past 5 years, the MuSun collaboration has staged 4 major experimental production runs. In this thesis, I present a measurement of the muon capture rate on deu- terium, as determined from data taken in the summer of 2013. The estimated statistical and systematic error is about 7.5%