We propose a general scheme for dissipatively preparing arbitrary pure quantum states on a multipartite qubit register in a finite number of basic control blocks. Our “splitting-subspace” approach relies on control resources that are available in a number of scalable quantum technologies (complete unitary control on the target system, an ancillary resettable qubit and controlled-not gates between the target and the ancilla), and can be seen as a “quantum-controller” implementation of a sequence of classical feedback loops. We show how a large degree of flexibility exists in engineering the required conditional operations, and make explicit contact with a stabilization protocol used for dissipative quantum state preparation and entanglement generation in recent experiments with trapped ions.
We propose a general scheme for dissipatively preparing arbitrary pure quantum states on a multipartite qubit register in a finite number of basic control blocks. Our “splitting-subspace” approach relies on control resources that are available in a number of scalable quantum technologies (complete unitary control on the target system, an ancillary resettable qubit and controlled-not gates between the target and the ancilla), and can be seen as a “quantum-controller” implementation of a sequence of classical feedback loops. We show how a large degree of flexibility exists in engineering the required conditional operations, and make explicit contact with a stabilization protocol used for dissipative quantum state preparation and entanglement generation in recent experiments with trapped ions.
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.
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.
We propose a new method for pure-state and subspace preparation in quantum systems, which employs the output of a continuous measurement process and switching dissipative control to improve convergence speed, as well as robustness with respect to the initial conditions. In particular, we prove that the proposed closed-loop strategy makes the desired target globally asymptotically stable both in mean and almost surely, and we show it compares favorably against a time-based and a state-based switching control law, with significant improvements in the case of faulty initialization.
We propose a new method for pure-state and subspace preparation in quantum systems, which employs the output of a continuous measurement process and switching dissipative control to improve convergence speed, as well as robustness with respect to the initial conditions. In particular, we prove that the proposed closed-loop strategy makes the desired target globally asymptotically stable both in mean and almost surely, and we show it compares favorably against a time-based and a state-based switching control law, with significant improvements in the case of faulty initialization.
Dissipation engineering is a powerful framework for quantum state preparation and autonomous error correction in few-qubit systems. In this work, we examine the scalability of this approach and give three criteria which any dissipative state stabilization protocol should satisfy to be truly scalable as the number of qubits grows. Besides the requirement that it can be constructed in a resource-efficient manner from simple-to-engineer building blocks, a scalable protocol must also exhibit favorable scaling of the stabilization time with the increase in system size. We present a family of protocols which employ fixed-depth qubit-qubit interactions alongside engineered linear dissipation to stabilize an N-qubit W state. We find that a modular approach to dissipation engineering, with several overlapping few-qubit dissipators rather than a single N-qubit dissipator, is essential for our protocol to be scalable. With this approach, as the number of qubits increases our protocol exhibits low-degree polynomial scaling of the stabilization time and linear growth of the number of control drives in the best case. While the proposed protocol is most easily accessible with current state-of-the-art circuit-QED architectures, the modular dissipation engineering approach presented here can be readily adapted to other platforms and for stabilization of other interesting quantum states.
Abstract A variety of tasks in quantum control, ranging from purification and cooling to quantum stabilisation and open-system simulation, rely on the ability to implement a target quantum channel over a specified time interval within prescribed accuracy. This can be achieved by engineering a suitable unitary dynamics of the system of interest along with its environment, which, depending on the available level of control, is fully or partly exploited as a coherent quantum controller . After formalising a controllability framework for completely positive trace-preserving quantum dynamics, we provide sufficient conditions on the environment state and dimension that allow for the realisation of relevant classes of quantum channels, including extreme channels, stochastic unitaries or simply any channel. The results hinge on generalisations of Stinespring’s dilation via a subsystem principle . In the process, we show that a conjecture by Lloyd on the minimal dimension of the environment required for arbitrary open-system simulation, albeit formally disproved, can in fact be salvaged, provided that classical randomisation is included among the available resources. Existing measurement-based feedback protocols for universal simulation, dynamical decoupling and dissipative state preparation are recast within the proposed coherent framework as concrete applications, and the resources they employ discussed in the light of the general results.