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.
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.
An optimal quantum algorithm for "direct characterization of quantum dynamics" (DCQD) is introduced. The DCQD method can be utilized to completely determine the quantum dynamical superoperator acting on an open quantum system. In contrast to all other known quantum process tomography (QPT) schemes, this scheme relies on error-detection techniques and does not require any quantum state tomography. By analysis of the number of required experimental configurations and quantum operations in a given Hilbert space, it is demonstrated that this approach is more efficient than all other known QPT schemes. DCQD can be applied, by construction, to the task of partial characterization of quantum dynamics. Specifically, it is demonstrated that the DCQD algorithm can be efficiently used for Hamiltonian identification, and also for simultaneous determination of both the relaxation time T1 and dephasing time T2. Furthermore, it is argued that the DCQD scheme is experimentally implementable in a variety of prominent quantum information processing systems, and it is explicitly shown how it can be physically realized in photonic systems with present day technology. The ability of a quantum system to perform arbitrary or "universal" quantum operations is restricted to its naturally available/controllable interactions. It is shown that quantum systems with an effective exchange interaction can be made operationally universal by utilizing a subspace or a subsystem of the combined principal system and an auxiliary system. Moreover, it is demonstrated that universal fault-tolerant quantum computation can be performed on these systems without utilizing any form of single-qubit control. Characterization and control of open quantum systems are among the central and fundamental problems in quantum physics. A crucial primitive is the characterization of the dynamics of a quantum system that has an unknown interaction with its embedding environment. Another essential task is to control the decoherence of an open quantum system by using naturally available interactions. This thesis addresses the above fundamental problems in two separate parts. In the first part, a general theory for direct and complete characterization of quantum dynamics is introduced. In the second part, a scheme for performing arbitrary quantum operations on spin-based quantum systems is presented. This scheme can be implemented in the presence of environmental noise and faulty quantum operations without need to control the state of spins individually.
This thesis presents a collection of projects spanning different sub-fields of quantum science, undertaken with the goal of understanding and advancing quantum technologies. Broadly, it can be divided into two thematic parts — parameter estimation and open system dynamics. Each project addresses inverse and ill-posed problems in Physics, which lie at the heart of developing robust and scalable quantum devices.A central theme in quantum technology is the challenge of inference of microscopic system parameters from limited, indirect observations. The first part of the thesis investigates this through the problem of Hamiltonian reconstruction via local measurements. Indirect estimation of couplings in quantum systems relies on the measurement of the spectrum and the overlap of eigenvectors with some reference state. For a one-dimensional chain, this data can be obtained by local measurement on one end of the chain, thereby reducing the need for full Hamiltonian tomography. Information about couplings is extracted from the temporal data obtained by measuring the expectation values of the time evolution 𝑒−𝑖𝐻𝑡 for a reference state. In Chapter 3, we analyze the robustness of this estimation scheme under perturbations arising from beyond nearest neighbour interactions. We show that the error scales linearly with the strength of such interactions and on average, the error increases with the distance of interaction between sites.Chapter 4 examines whether coupling information can be extracted from local thermal measurements, using expectation values of the Gibbs state at varying temperatures rather than temporal data. We develop a procedure to obtain the coefficients of the Taylor expansion of these expectation values and relate them to the Hamiltonian parameters. For very small chains, this mapping can be carried out analytically, while for larger systems it reveals the algebraic structure that links local measurements to the underlying couplings and highlights the trade-offs between measurement resources, numerical stability, and identifiability. The analysis also clarifies how additional local fields or self-interaction terms enhance the information content of thermal data, suggesting a role for local thermal probes as practical tools for Hamiltonian verification and parameter estimation.Building on the ideas of controlling and inferring information about a quantum system, we now turn to active intervention through adaptive measurement. In Chapter 5, we develop a process tensor driven procedure for cooling the spin bath that is coupled to a nitrogen vacancy (NV) center in diamond. By modeling the sequence of intermediate quantum instruments acting on a correlated system-environment process, we optimize a pair of completely positive (CP) maps to maximize the population in a lower-energy state. Unlike existing approaches that rely solely on positive operator valued measures (POVMs), our method encompasses a broader class of CP maps, including adaptive feed-forward and mixed operations. We explicitly account for initial correlation between system and environment and distinguish between the controllable and uncontrollable parts of the dynamics. Our framework supports non-Markovian operations and benchmarks them against optimal Markovian strategies. The optimization is performed via Semi-definite Programming (SDP), ensuring global optimality. We also assess robustness to Hamiltonian noise and provide a proposal for implementation using NV center in diamonds.Finally, Chapter 6 explore the relaxation dynamics of topological qubits, focusing on a tetron qubit formed from two uncoupled Kitaev chains coupled to a finite fermionic bath. Using the correlation matrix formalism for purely quadratic couplings, we show that the relaxation is fundamentally independent of temperature when either the bath is large, or the zero-mode energy of the system is close to zero. This challenges a key assumption in the field that cooling enhances coherence. Interestingly, we find that introducing glassy disorder into the system slows down relaxation, offering a potential route to prolong qubit lifetimes.Collectively, these studies form a coherent narrative around extraction, control and utilization of quantum information under fundamental constraints. By tackling such inverse and often ill-posed problems, this thesis contributes new tools and insights essential for the realization of future quantum technologies.
Quantum information processing offers potential improvements to a wide range \nof computing endevaors, including cryptography, chemistry simulations and \nmachine learning. The development of practical quantum information processing \ndevices is impeded, however, by challenges arising from the apparent exponential \ndimension of the space one must consider in characterizing quantum \nsystems, verifying their correct operation, and in designing useful control \nsequences. In this work, we address each in turn by providing useful \nalgorithms that can be readily applied in experimental practice. \n \nIn order to characterize the dynamics of quantum systems, we apply statistical \nmethods based on Bayes' rule, thus enabling the use of strong prior \ninformation and parameter reduction. We first discuss an \nanalytically-tractable special case, and then employ a numerical algorithm, \nsequential Monte Carlo, that uses simulation as a resource for characterization. We \ndiscuss several examples of SMC and show its application in nitrogen vacancy \ncenters and neutron interferometry. \nWe then discuss how characterization techniques such as SMC can be used to \nverify quantum systems by using credible region estimation, model selection, \nstate-space modeling and hyperparameterization. Together, these techniques \nallow us to reason about the validity of assumptions used in analyzing quantum \ndevices, and to bound the credible range of quantum dynamics. \n \nNext, we discuss the use of optimal control theory to design robust control \nfor quantum systems. We show extensions to existing OCT algorithms that allow \nfor including models of classical electronics as well as quantum dynamics, \nenabling higher-fidelity control to be designed for cutting-edge experimental \ndevices. Moreover, we show how control can be implemented in parallel across \nnode-based architectures, providing a valuable tool for implementing \nproposed fault-tolerant protocols. \n \nWe close by showing how these algorithms can be augmented using quantum \nsimulation resources to enable addressing characterization and control design \nchallenges in even large quantum devices. In particular, we will introduce a \nnovel genetic algorithm for quantum control design, MOQCA, that utilizes \nquantum coprocessors to design robust control sequences. Importantly, MOQCA is \nalso memetic, in that improvement is performed between genetic steps. We then \nextend sequential Monte Carlo with quantum simulation resources to enable \ncharacterizing and verifying the dynamics of large quantum devices. By using \nnovel insights in epistemic information locality, we are able to learn \ndynamics using strictly smaller simulators, leading to an algorithm we call \nquantum bootstrapping. We demonstrate by using a numerical example of learning \nthe dynamics of a 50-qubit device using an 8-qubit simulator.
Quantum mechanics allows for the processing of information in entirely new ways, surpassing the computational limits set by classical physics. Termed `quantum information processing', scaling this scheme relies on simultaneously increasing the number of qubits -- the fundamental unit of quantum computation -- whilst reducing their error rates. With this comes a variety of challenges, including the ability to readout the quantum state of large numbers of qubits, as well as to control their evolution in order to mitigate errors. This thesis aims to address these challenges by developing techniques for the readout and control of quantum systems. The first series of experiments focuses on the readout of GaAs/AlGaAs semiconductor quantum systems, primarily relating to the technique of dispersive gate sensing (DGS). DGS is used to probe electron transmission in an open system, a quantum point contact, demonstrating an ability to resolve characteristic features of a one-dimensional ballistic channel in the limit where transport is not possible. DGS is also used to observe anomalous signals in the potential landscape of quantum-dot defining gate electrodes. A technique for time domain multiplexing is also presented, which allows for readout resources, in the form of microwave components, to be shared between multiple qubits, increasing the capacity of a single readout line. The second series of experiments validates control techniques using trapped 171Yb+ ions. Classical error models are engineered using high-bandwidth IQ modulation of the microwave source used to drive qubit rotations. Reductions in the coherent lifetime of the quantum system are shown to match well with quantitative models. This segues in to developing techniques to understand and suppress noise in the system. This is achieved using the filter-transfer function approach, which casts arbitrary quantum control operations on qubits as noise spectral filters.
We present novel techniques for modelling and mitigating the effects of time-dependent noise created by interactions between a quantum system and its environment, and by errors in applied controls. Our scope encompasses quantum storage and nontrivial QIP tasks in both single- and multi-qubit systems, with a particular focus on control operations applied to trapped-ion qubits. The work begins with the introduction of a computationally efficient approach to characterizing the impact of time-dependent noise in single-qubit systems, in terms of the spectral characteristics of the noise and a set of generalized control filter functions. In conjunction with brute-force numerical simulation, we show that this novel analytical technique can used to model the evolution of a noisy single-qubit system subject to an arbitrary piecewise-constant control sequence, and to accurately predict the effects of experimentally engineered noise in single-qubit trapped ion systems. We also obtain a number of new and important results that extend the range of utility of state-preserving dynamical decoupling control sequences. These device-independent results provide a means to create a practically useful high-fidelity, long-time quantum memory in both single- and multi-qubit systems. We go on to explain how, given the freedom to arbitrarily and quasi-instantaneously change the phase of the interaction between a system of qubits and a finite collection of oscillators, frequency-specific phase modulation protocols can be implemented that decouple the qubits from targeted oscillator modes at pre-determined times. This technique can be used to generate fast, high-fidelity multi-qubit entangling operations in, for example, ion trap QIP devices.
Quantum systems are the foundation of quantum technology development. To harness these systems, one must extract information from them and be able to control their dynamics. This thesis presents a body of work, containing both published and unpublished papers, that focuses on two key research areas: quantum continuous measurement and quantum bath sensing. While these topics may seem distinct, they are fundamentally connected through the framework of open quantum systems. As such, this thesis is structured into two parts. The first part of this thesis is dedicated to diffusive continuous quantum measurement, where the system of interest is continuously monitored through a coupled Markovian bath or meter. A key challenge in this context is the numerical errors introduced in quantum trajectory simulations caused by the finite time resolution ( 𝑡) in real experiments. To address this, we propose a systematic framework to assess theoretical tools used in processing measurement records. Focusing on a single Lindblad channel, we analyze the errors of existing measurement (or Kraus) operators in literature, in orders of 𝑡 under conditions that ensure valid average evolution (complete positivity, convex linearity, and trace preservation). We also analyze a stronger condition: finding the order at which these existing measurement operators match the Lindblad equation. Based on these analyzes, we propose a Kraus operator that satisfies the conditions for valid quantum evolution and matches the Lindblad master equation to second order in 𝑡, surpassing all existing approaches. Moreover, to evaluate how well our operator reproduces exact quantum trajectories, we analyze two qubit measurement examples where exact maps can be derived: 𝑧-basis measurement and fluorescence (dissipative) measurement. We show analytically that our proposed operator achieves the smallest average trace distance to the exact quantum trajectories compared to existing methods. Finally, we extend this Kraus operator to multiple Lindblad channels with a driving Hamiltonian. We test our analytical findings numerically using the two qubit examples, considering both single and multiple Lindblad channels with a driving Hamiltonian. The numerical results confirm our theoretical predictions. The second part of this thesis focuses on quantum bath sensing, where we use a quantum system (qubit) to extract information about its surrounding baths. Specifically, we develop protocols to detect nonclassical pure-dephasing noise in a single-qubit system coupled to temporally correlated (non-Markovian) baths. Inspired by the Ramsey protocol, we introduce a coherent intervention (𝜋 2 -pulse) within the protocol, which can reveal the quantum noise - noise correlations affecting the probe qubit that originate from quantum degrees of freedom. Our protocols are simple, experimentally viable, and rigorously derived for general bath models. Using an exactly solvable bosonic bath model, we analyse how key noise parameters respond to fixed control schemes, identifying the optimal strategy for detecting the quantum noise. From the perspective of bath dynamics, we further decompose the qubit-bath state, demonstrating that only Gaussian components of the bath contribute to quantum noise, highlighting the bath's role in system dynamics. Finally, we extend the modified Ramsey protocol by incorporating multi-axis 𝜋 2 pulse and demonstrate that it can emulate the modified Ramsey protocol with any completely positive trace-preserving intervention. This applies to both Gaussian and non-Gaussian baths under the pure-dephasing assumption.