Practical implementations of quantum information processing will ultimately rely on our ability to control large-scale quantum systems. This control faces two major challenges: the exponential growth of the state space with the number of components, and the ability to control dissipation in these systems. While current small- and medium-scale quantum platforms rely on traditional approaches that reason at the level of individual quantum states and aim to isolate systems from their environment, such strategies become increasingly impractical as system size grows. The complexity of interactions and the presence of noise in realistic implementations demand scalable approaches that go beyond state-by-state control. Such approaches require a shift toward reasoning in terms of collections of states that share symmetries or dynamical properties, and towards dealing with systems being far from their equilibrium state because of their openness. This thesis explores methods to understand and engineer dissipation for stabilizing quantum states and subspaces, enabling autonomous error correction, and facilitating robust logical operations, all through the lens of subspaces of the exponentially large state space. In particular, we develop symmetry-protected and nonlinear stabilization schemes that not only stabilize states and subspaces but also exhibit intrinsic error-correcting features rooted in driven-dissipative dynamics. We introduce a novel error correction strategy based on gradual entropy removal, offering scalable implementations with reduced overhead. Finally, we investigate the interplay between dissipation and logical operations, uncovering both limitations and opportunities in realistic quantum sensing and gate protocols, with a special focus on finite-energy bosonic codes.
Practical implementations of quantum information processing will ultimately rely on our ability to control large-scale quantum systems. This control faces two major challenges: the exponential growth of the state space with the number of components, and the ability to control dissipation in these systems. While current small- and medium-scale quantum platforms rely on traditional approaches that reason at the level of individual quantum states and aim to isolate systems from their environment, such strategies become increasingly impractical as system size grows. The complexity of interactions and the presence of noise in realistic implementations demand scalable approaches that go beyond state-by-state control. Such approaches require a shift toward reasoning in terms of collections of states that share symmetries or dynamical properties, and towards dealing with systems being far from their equilibrium state because of their openness. This thesis explores methods to understand and engineer dissipation for stabilizing quantum states and subspaces, enabling autonomous error correction, and facilitating robust logical operations, all through the lens of subspaces of the exponentially large state space. In particular, we develop symmetry-protected and nonlinear stabilization schemes that not only stabilize states and subspaces but also exhibit intrinsic error-correcting features rooted in driven-dissipative dynamics. We introduce a novel error correction strategy based on gradual entropy removal, offering scalable implementations with reduced overhead. Finally, we investigate the interplay between dissipation and logical operations, uncovering both limitations and opportunities in realistic quantum sensing and gate protocols, with a special focus on finite-energy bosonic codes.
Quantum information processing holds immense promise, but its practical implementation is fundamentally challenged by dissipation, the irreversible loss of information and energy to the environment. The conventional approach treats dissipation as an obstacle to overcome, typically through resource-intensive quantum error correction. Such schemes impose overheads of orders of magnitude in terms of both qubits and operations. This creates significant space, control and time costs, making near-term practical implementation highly challenging. This thesis adopts a different viewpoint, harnessing dissipation for quantum algorithms. We explore the design, application, and conceptual advantages of dissipative quantum algorithms. We establish the foundational tools for this approach by demonstrating how to engineer a universal set of nonunitary operations using intrinsic, controllable dissipation. We present a hardware-efficient method, experimentally realized in a trapped-ion system, for implementing any two-qubit Markovian quantum channel without requiring ancilla qubits or measurements. This provides a practical and versatile toolbox for constructing dissipative algorithms on near-term quantum devices. Building on this, we apply these tools to an inherently dissipative task: the preparation of thermal states. We introduce a variational quantum-classical algorithm that integrates engineered nonunitary operations with unitary gates. By leveraging weak symmetries of the target Hamiltonian, we design efficient ansätze that significantly improve the fidelity of state preparation. Finally, we address one of the most significant barriers to scaling variational quantum algorithms: the prevalence of barren plateaus, where optimization gradients vanish exponentially with system size. We prove that dissipative algorithms, by incorporating periodic qubit resets, can mitigate both noise-induced and unitary barren plateaus. This mechanism allows for a class of scalable computations that are intractable for purely unitary approaches in the presence of noise. Together, these results demonstrate that dissipation is not just a source of error, but a powerful resource. By systematically developing the necessary operations, applying them to relevant problems, and identifying fundamental scalability advantages, this work showcases dissipative quantum computing as a compelling avenue in quantum information processing.
Current quantum computing architectures face a thermodynamic bottleneck where the energy cost of classical error correction scales superlinearly with system size. Reliance on exogenous classical control imposes a latency and power penalty that renders hybrid paradigms unscalable for exascale applications. An architecture for autonomous dissipative quantum processing is defined to replace active feedback with hardware-intrinsic stability. By encoding logical information into the dark state of a driven-dissipative Liouvillian, error correction functions as a continuous thermodynamic process of entropy export. We explicitly define the implementation of logical Clifford gates via adiabatic code deformation and the physical realization of 4-body stabilizer terms using Fluxonium-based superinductor arrays. Thermal analysis confirms that the heat load (<0.5 W/cm2) remains within the cooling capacity of Stirling engines at 77 K, bounded by the Kapitza resistance of the diamond substrate. This establishes a rigorous pathway to self-contained quantum processors operating at thermodynamic limits.
Noise and errors are inevitable parts of any practical implementation of a quantum computer. As a result, large-scale quantum computation will require ways to detect and correct errors in quantum information. Here we present such a quantum error-correcting scheme for correcting the dominant phase and decay errors in superconducting qubit architectures using a hybrid approach combining autonomous correction based on engineered dissipation with traditional measurement-based quantum error correction. Using numerical simulations with realistic device parameters for superconducting circuits, we show that this scheme can achieve a five- to tenfold increase in storage time while using only six qubits for the encoding and two ancillary qubits for the operation of the autonomous correction, providing a potentially large reduction of qubit overhead compared to typical measurement-based error-correction schemes. Furthermore, the scheme relies on standard interactions and qubit driving available in most major quantum computing platforms, making it implementable in a wide range of architectures.
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.
Quantum computers promise to solve computational problems that are inaccessible to classical machines. The reliable execution of large-scale quantum algorithms requires robust operations in the presence of noise. Quantum error correction addresses this challenge by encoding quantum information redundantly across several physical qubits, such that errors can be detected and corrected during a computation. However, no single error-correcting code intrinsically supports an inherently robust, fault-tolerant implementation of all gates needed for universal quantum computing. Moreover, most modern approaches to both quantum error correction and the implementation of universal logical operations on encoded qubits rely on mid-circuit measurements and feed-forward control. These types of operations are technologically demanding, often slow, and prone to high error rates, and they limit the overall success probability of quantum algorithms. In this thesis, we develop fault-tolerant protocols and circuits for quantum error correction and universal logical computation, with an emphasis on implementations compatible with current hardware systems. We first focus on fault-tolerant quantum error correction on small codes. By comparing different protocols, we identify trade-offs between compact circuit constructions and their robustness to noise. We then assess their practical performance by comparing numerical simulations of noisy circuits with experimental data. Beyond the preservation of encoded information, we study how universal logic can be implemented in a fault-tolerant manner on encoded qubits. A central approach considered in this thesis is code switching, in which logical information is transferred between two distinct error-correcting codes that support complementary sets of inherently fault-tolerant logical gates. In combination, these codes give access to a complete universal fault-tolerant logical gate set. In this thesis, we determine conditions that allow us to construct fault-tolerant protocols for code switching. We adapt these protocols to the capabilities of current hardware, thereby enabling the first experimental realization of universal fault-tolerant logic by means of code switching. However, the overall performance of these schemes is limited by slow and noisy mid-circuit measurements. To address this bottleneck, we construct a suite of measurement-free fault-tolerant universal operations that do not require any measurements during the execution of an algorithm. In this framework, error correction and logical operations are implemented coherently as part of the quantum circuit, without mid-circuit measurements or in-sequence classical control. We introduce measurement-free code-switching schemes that can be scaled to arbitrary code distances through concatenation, and which thereby provide, in principle, arbitrarily strong error suppression. We further tailor our approach to the capabilities of current trapped-ion quantum processors. New circuit constructions support the first experimental implementation of a logical quantum algorithm without mid-circuit measurements, demonstrated through Grover's search on three encoded qubits. Together, the results of this thesis expand the toolbox for early fault-tolerant quantum computation. They show how protocols for quantum error correction and universal logical gates can be designed without mid-circuit measurements with realistic hardware constraints in mind, opening new pathways towards universal quantum logic.
Dissipatively stabilized cat qubits provide a promising route toward fault-tolerant quantum computation, exhibiting exponential suppression of bit-flip errors with increasing phase-space separation of the logical states, while incurring only a linear increase in phase-flip errors. Existing implementations rely on engineered two-photon dissipation via nonlinear coupling to a lossy environment, an approach largely confined to superconducting platforms and limited by spurious decay channels and finite dissipation rates. Here, we propose a fundamentally different stabilization paradigm based on repeated interactions with an auxiliary two-level system mediated by a quadratic Hamiltonian, enabling dissipative stabilization without reservoir engineering. Our approach overcomes key limitations of existing schemes and is compatible with a wider class of experimental platforms. Furthermore, it preserves the noise bias and extends to squeezed cat qubits, rendering single-photon loss errors partially correctable.