This dissertation focuses on two connected areas: quantum computation and quantum control. Two proposals to construct a quantum computer, using nuclear magnetic resonance (NMR) and superconductivity, are introduced. We give details about the modeling, qubit realization, one and two qubit gates and measurement in the language that mathematicians can understand and fill gaps in the original literatures. Two experimental examples using liquid NMR are also presented. Then we proceed to investigate an example of quantum control, that of a magnetometer using quantum feedback. Previous research has shown that feedback makes the measurement robust to an unknown parameter, the number of atoms involved, with the assumption that the feedback is noise free. To evaluate the effect of the feedback noise, we extend the original model by an input noise term. We then compute the steady state performance of the Kalman filter for both the closed-loop and open-loop cases and retrieve the estimation error variances. The results are compared and criteria for evaluating the effects of input noise are obtained. Computations and simulations show that the level of input noise affects the measurement by changing the region where closed loop feedback is beneficial.
This dissertation focuses on two connected areas: quantum computation and quantum control. Two proposals to construct a quantum computer, using nuclear magnetic resonance (NMR) and superconductivity, are introduced. We give details about the modeling, qubit realization, one and two qubit gates and measurement in the language that mathematicians can understand and fill gaps in the original literatures. Two experimental examples using liquid NMR are also presented. Then we proceed to investigate an example of quantum control, that of a magnetometer using quantum feedback. Previous research has shown that feedback makes the measurement robust to an unknown parameter, the number of atoms involved, with the assumption that the feedback is noise free. To evaluate the effect of the feedback noise, we extend the original model by an input noise term. We then compute the steady state performance of the Kalman filter for both the closed-loop and open-loop cases and retrieve the estimation error variances. The results are compared and criteria for evaluating the effects of input noise are obtained. Computations and simulations show that the level of input noise affects the measurement by changing the region where closed loop feedback is beneficial.
For several decades it has been appreciated that quantum computers hold incredible promise to perform calculations intractable to classical computation. However, this promise has be slow to realize. Dozens of quantum systems are currently being investigated for use in quantum information processing - none of which have yet demonstrated algorithms involving more than a handful of qubits and it remains unclear which, if any, of these systems will ultimately compose a scalable, robust quantum information processing architecture. In this thesis we employ analytical, optimal and algebraic control techniques to evaluate various quantum systems for their potential use in quantum information processing. In doing so, we have additionally identified several novel characterization procedures capable of probing both the coherent and incoherent dynamics of quantum systems. The first part of this thesis discusses work motivated by attempts to utilize donor qubits in silicon as quantum bits. We first propose a measurement of the state of a single donor electron spin using two-dimensional electron gas of a field-effect transistor and electrically detected magnetic resonance. We analyze the potential sensitivity of this measurement and show that it is a quantum nondemolition measurement of an electron-encoded state. We then present the first of two novel qubit characterization procedures. We consider the problem of rapidly characterizing a large number of similarly prepared qubits using techniques from optimal experiment design. All qubits are assumed to evolve according to the same physical processes, though the Hamiltonian parameters may vary from device to device - an inevitability in solid state qubits. We use the Cram\\'er-Rao bound on the variance of a point estimator to construct the optimal series of experiments to estimate these free parameters, and present a complete analysis of the optimal experimental configuration. Though applied to dipole- and exchange-coupled qubits, this technique is widely applicable to other systems. The second part of the thesis discusses the role that control can play in measuring and mitigating noise in qubit systems. Our first result describes a method for quickly simulating the effects of arbitrary markovian noise on qubit systems through the use of a numerically optimized, multi-state Markovian fluctuator. This ability to rapidly simulate the noisy qubit evolution allows us to compute control sequences capable of maximally decoupling the qubit from the noise source. We then introduce the second characterization procedure of the these, showing that a single measurable and controllable qubit may act as a spectrometer of dephasing noise. We show that the formalism of dynamical decoupling can be used to estimate the short-time correlation function of the noise source, while long time correlations may be estimated by a very simple series of free evolution experiments. This technique is applicable to the wide range of physical implementations which suffer from dephasing noise.The final part of this thesis demonstrates that trapped neutral atoms may be utilized for the robust simulation of complex systems exhibiting a topological phase. We present a method to simulate the toric code Hamiltonian stroboscopically, and demonstrate that our technique preserves the ground state degeneracy . Furthermore, we introduce a dissipative mechanism allowing for thermalization of the system to a finite temperature or direct cooling to the ground state manifold.
Quantum engineering has seen rapid growth in the past two decades. Physicists, mathematicians and engineers have been working in unison to control a number of diverse systems in the quantum regime. Quantum control involving feedback has become particularly topical, as using information gained from a system can lead to more stable operation of a control protocol. Quantum feedback can be split into two paradigms: measurement based feedback and coherent feedback. Although it is increasingly evident that retaining the coherence of the feedback signal provides an intrinsic advantage over measurement-based feedback, coherent feedback is still a new paradigm. In particular, there are a limited number of options for coherently estimating a state within a feedback loop. As a step towards better understanding and implementation of quantum feedback, this thesis reports on modelling, estimation and control of quantum systems. The first topic is physical realisability of a variety of quantum systems, especially finite level systems and their outgrowths. Bilinear quantum stochastic differential equations (QSDEs) have to be employed to characterise these systems, which is a significant complement to the previous work on linear QSDEs. In light of the fact that direct and indirect couplings play a vital role in quantum network and control, we also provide state-space models for different classes of coupled open quantum systems incorporating both bidirectional and directional interactions. The second topic is coherent observers and optimal filtering. It is well established that classically estimation using the Kalman filter can provide improved performance over direct feedback schemes, and similar demonstrations have been performed for measurement-based quantum feedback. In this thesis I present coherent observers, including least mean squares estimators, which are driven by the coherent output of a specified quantum plant and designed such that some subset of the observer and plant's expectation values converge in the asymptotic limit. Not only can estimators "observe" mean quantities of quantum plant, but also they can "estimate" quantum correlations such as entanglement. This is of much importance to coherent feedback design in the absence of measurement steps without loss of fidelity. Last but not least, several topics regarding stabilisation and control design of quantum systems are discussed in my thesis. To be specific, tools for quantum stability analysis (e.g. Lyapunov conditions) are provided. Both measurement-based feedback and coherent feedback control design are taken into account. A measurement-based optimal controller for opto-mechanical systems aimed at synchronising different mechanical modes is presented, which is application-oriented. Moreover, A general observer-based coherent feedback control framework is studied, and I demonstrate a pole-placement approach via coherent observers that can be applied to various scenarios.
Quantum computers can potentially solve real and relevant mathematical and physical problems that are intractable using classical machines. However, the experimental realization of quantum computers represents a significant challenge, because several opposing experimental requirements must be met. A set of coupled quantum bits must be manipulated and measured while coherently retaining entangled quantum states. Yet the manipulation and measurement processes almost inevitably lead to the decay of these fragile states.
This thesis work takes significant steps towards building a practical quantum computer using nuclear spins and liquid state nuclear magnetic resonance (NMR) techniques. I present experimental results for proof of principle of quantum computing in a series of small implementations of quantum algorithms, culminating in the implementation of an adiabatic quantum optimization algorithm. The performance of adiabatic algorithms compared with classical optimization methods is unknown, but small quantum computers could provide crucial insight into answering this question. Furthermore, adiabatic algorithms also shed new light on the usefulness of quantum resources for computational tasks and hence they represent an important class of algorithms.
The second part of this thesis presents several methods developed for improving the control over NMR quantum computing experiments. Even though liquid state NMR quantum computers have well known and accepted scaling limitations, the developed tools are of general use. I will show how several tools are directly transferable to two other implementations of quantum computers; one using optical methods and the other using loops of superconducting material.
This work provides insight into what is needed to build a practical quantum computer, and delivers several tools and techniques that will be useful in future large-scale implementations of quantum computers.
Quantum computing holds immense promise for revolutionizing computation, yet its practical realization is severely hampered by the pervasive issue of quantum noise. This noise, arising from various sources including environmental interactions and imperfect control, introduces errors into quantum computations, degrading their fidelity. This paper explores novel control algorithms designed to mitigate the detrimental effects of quantum noise. We investigate the underlying mechanisms generating noise and propose a method based on precise qubit control and calibration to minimize its impact. The core claim is that effective noise control is crucial for achieving reliable quantum computation. The proposed algorithms leverage feedback control and adaptive calibration techniques to dynamically compensate for noise fluctuations, aiming to enhance the accuracy and robustness of quantum algorithms. The mathematical framework presented includes noise models, control equations, and performance metrics, demonstrating the feasibility and potential of this approach. Specifically, we introduce a closed-loop control system described by the equation: (Δsn+1 = K(en - sn)) + wn+1, where Δsn+1 represents the change in state, K is the gain, en is the desired state, sn is the actual state, and wn+1 is the noise term. We also examine the effect of decoherence, modeled as: ds = Hdt + Vd, where ds is the time evolution of the quantum state, H is the Hamiltonian describing the system, dt is the time step, and Vd is the damping term due to noise. The research aims to contribute towards the development of more robust and practical quantum computers.
Preface FOUNDATIONS OF QUANTUM INFORMATICS Spins: The Stern-Gerlach experiment and spin filter EPR, Bell's inequalities, and hidden variables The Landauer principle QUANTUM COMPUTATION AND QUANTUM SYSTEMS Turing machines and binary logic gates Quantum mechanical systems Hilbert spaces Complex finite dimensional Hilbert Spaces Quantum Turing machines Universality of elementary quantum gates Quantum algorithms Quantum adder and multiplier Quantum error correction codes Lasers: a heuristic introduction Quantum computing devices and requirements TWO-LEVEL ATOMS AND CAVITY QED Two-level atoms Quantization of the electromagnetic field Cavity QED Cavity QED for the quantum phase gate Quantum eraser Quantum disentanglement eraser IMPERFECT QUANTUM OPERATIONS Fidelity Density matrices Time evolution of density matrices Examples of master equations Fidelity calculations ION TRAPS Introduction Ion qubits Summary of ion preparation Coherence Quantum gates Large scale confined-ion quantum computer Trap architecture and performance Teleportation of coherent information Experimental DFS logic gates Quantum error correction by ion traps Summary of ion quantum computation QUANTUM LOGIC USING COLD, CONFINED ATOMS Introduction Atom trapping and detection Atom interactions with external fields Atom trapping Qubits and gates Controlled two-qubit gates Coherence properties of atom gates Assessment QUANTUM DOTS QUANTUM COMPUTING GATES Introduction Electrons in quantum dots microcavity Coupled electron spins Biexciton in a single quantum dot Conclusions LINEAR OPTICS COMPUTERS Classical electrodynamics - Classical computers Quantum electrodynamics - Quantum computers Teleportation Summary and outlook SUPERCONDUCTING QUANTUM COMPUTING DEVICES Introduction Superconductivity More on Cooper pairs and Josephson junctions Superconducting circuits: classical Superconducting circuits: quantum Quantum gates Measurement NMR QUANTUM COMPUTING Nuclear magnetic resonance Basic technology with NMR Solid state NMR Shor's algorithm and its experimental realization Quantum algorithm for lattice-gas systems Conclusion Appendix A: The Fock-Darwin States Appendix B: Evaluation of the exchange energy Appendix C: Transformation of quantum states: SU(2) and SO(3) Appendix D: The Homeomorphism from SU(2) to SO(3)
This article investigates the effects of input noise on a magnetometer with quantum feedback. Previous research has shown that feedback makes the measurement robust to an unknown parameter, the number of atoms involved, with the assumption that the feedback is noise free. To evaluate the effects of the feedback noise, we extend the original model by an input noise term. We then analyze the steady state performance of the Kalman filter for both the closed-loop and open-loop cases and retrieve the second moment of the estimation error. The results are compared and criteria for evaluating the effects of input noise are obtained. Robust and optimal designs are also discussed. Computations and simulations show how quantitatively the input noise increases the estimation error and changes the region where the closed-loop case behaves better than the open-loop case.