Towards high fidelity entanglement with dressed state qubits

This thesis describes the development of an entanglement experiment for ytterbium ions making use of a new entanglement method utilizing microwaves and a static magnetic field gradient. This thesis will begin by modelling the populations of the main levels in ytterbium using rate equations to find the optimum parameters required for the preparation and detection of qubit states. Coherent manipulation of these qubit states will be shown and coherence times of the states measured. Additionally a highly stable double resonance frequency locking setup for the ytterbium cooling lasers is built. This thesis will go on to give an overview of the main entanglement schemes and will give a justification as to why microwaves combined with a magnetic field gradient is the most suitable method. The magnetic field gradient creates an effective Lamb-Dicke parameter which allows microwave fields to couple to the motional states of magnetic field sensitive qubit states. The use of magnetic field sensitive states can however make the qubit highly susceptible to decoherence from magnetic field fluctuations. A method to decrease this decoherence by two orders of magnitude using a microwave dressed state qubit will be demonstrated and optimised and a new coherent manipulation method of the dressed state qubit will be presented which allows for arbitrary Bloch sphere rotations. The production of the highest recorded magnetic field gradient of 24T

Scalable and high-sensitivity readout of silicon quantum devices

Quantum computing is predicted to provide unprecedented enhancements in computational power. A quantum computer requires implementation of a well-defined and controlled quantum system of many interconnected qubits, each defined using fragile quantum states. The interest in a spin-based quantum computer in silicon stems from demonstrations of very long spin-coherence times, high-fidelity single spin control and compatibility with industrial mass-fabrication. Industrial scale fabrication of the silicon platform offers a clear route towards a large-scale quantum computer, however, some of the processes and techniques employed in qubit demonstrators are incompatible with a dense and foundry-fabricated architecture. In particular, spin-readout utilises external sensors that require nearly the same footprint as qubit devices. In this thesis, improved readout techniques for silicon quantum devices are presented and routes towards implementation of a scalable and high-sensitivity readout architecture are investigated. Firstly, readout sensitivity of compact gate-based sensors is improved using a high-quality factor resonator and Josephson parametric amplifier that are fabricated separately from quantum dots. Secondly, an integrated transistor-based control circuit is presented using which sequential readout of two quantum dot devices using the same gate-based sensor is achieved. Finally, a large-scale readout architecture based on random-access and frequency multiplexing is introduced. The impact of readout circuit footprint on readout sensitivity is determined, showing routes towards integration of conventional circuits with quantum devices in a dense architecture, and a fault-tolerant architecture based on mediated exchange is introduced, capable of relaxing the limitations on available control circuit footprint per qubit. Demonstrations are based on foundry-fabricated transistors and few-electron quantum dots, showing that industry fabrication is a viable route towards quantum computation at a scale large enough to begin addressing the most challenging computational problems

Advanced Syncom, volume 1 Summary report

Synchronous communications satellite configuration, instrumentation, handling and test equipment, and systems desig

A Discrete-Time Technique for Linearity Enhancement of Wideband Receivers

A new signal processing technique is introduced to enhance the linearity performance of wideband radio frequency (RF) receivers. The proposed technique combines the advancements in mixer first architectures with a library of binary sequences as local oscillator signals to enable wide instantaneous bandwidth and high linearity for the RF receiver. To do so, N-bit pseudo-random-binary-sequences (PRBS) are used as local oscillator signals. The RF input signal is multiplied with the PRBS at the mixer and then averaged over the full sequence. This in effect reduces the amplitude of the signal and improves the overall linearity of the system. In order to enable full reconstruction of the input signal N channels are used with each employing a shifted version of a PRBS. The effect of the proposed technique on different aspects of the system performance such as noise and linearity is discussed. In addition, the effect of nonidealities stemming from hardware implementation on the overall performance are studied. A prototype integrated circuit (IC) is implemented in 130\,nm CMOS technology to demonstrate the feasibility of the proposed technique. The design procedure of each circuit block is described and simulation results are used to evaluate the performance. The device is fabricated and characterized using a custom data acquisition system. Measurement results show good agreement with the expected values from simulation and analytical analysis. Calibration techniques are introduced to minimize the effect of DC offsets, gain mismatches, and timing skews. Modifications to the implemented CMOS circuit are proposed to enable such calibrations and further enhance the overall performance of the system. The requirements for the precision of calibration techniques are derived and used to find the specifications of circuit block that are designed to enable these techniques. Calibration of DC offsets along with gain mismatches is carried out for the fabricated IC and results are shown. A digitally assisted technique is proposed to enable the calibration of timing skews. In addition, a review of additional implementation shortcomings that can affect the system performance are reviewed. Finally, a conclusion of the dissertation is presented along with potential future work for further enhancement of the system performance

Nanoparticle devices for brain-inspired computing.

The race towards smarter and more efficient computers is at the core of our technology industry and is driven by the rise of more and more complex computational tasks. However, due to limitations such as the increasing costs and inability to indefinitely keep shrinking conventional computer chips, novel hardware architectures are needed. Brain-inspired, or neuromorphic, hardware has attracted great interest over the last decades. The human brain can easily carry out a multitude of tasks such as pattern recognition, classification, abstraction, and motor control with high efficiency and extremely low power consumption. Therefore, it seems logical to take inspiration from the brain to develop new systems and hardware that can perform interesting computational tasks faster and more efficiently. Devices based on percolating nanoparticle networks (PNNs) have shown many features that are promising for the creation of low-power neuromorphic systems. PNN devices exhibit many emergent brain-like properties and complex electrical activity under stimulation. However, so far PNNs have been studied using simple two-contact devices and relatively slow measuring systems. This limits the capabilities of PNNs for computing applications and questions such as whether the brain-like properties continue to be observed at faster timescales, or what are the limits for operation of PNN devices remain unanswered. This thesis explores the design, fabrication, and testing of the first successful multi- contact PNN devices. A novel and simple fabrication technique for the creation of working electrical contacts to nanoparticle networks is presented. Extensive testing of the multi-contact PNN devices demonstrated that electrical stimulation of multiple input contacts leads to complex switching activity. Complex switching activity exhibited different patterns of switching behaviour with events occurring on all contacts, on few contacts, or only on a single contact. The device behaviour is investigated for the first time at microsecond timescales, and it is found that the PNNs exhibit stochastic spiking behaviour that originates in single tunnel gaps and is strikingly similar to that observed in biological neurons. The stochastic spiking behaviour of PNNs is then used for the generation of high quality random numbers which are fundamental for encryption and security. Together the results presented in this thesis pave the way for the use of PNNs for brain-inspired computing and secure information processing