arXiv subjects

Miguel Casanova

Publications and source records attributed to Miguel Casanova.

3 recordsLinked to original sources

arXiv2026

Quantum model reduction based on Oja's flow

We propose a novel approach to numerically derive approximate reduced dynamical models for Markovian quantum open systems without perturbative iterations, projecting the evolution to the subspace associated to their slowest degrees of freedom. The two algorithms we develop are based on Oja's continuous-time principal component flow: the first returns the optimal reduction to the slowest decaying operator-subspace, and is extended to time-dependent dynamics, while the second one is designed to reduce the dynamics on a subspace of the system's Hilbert space, and thus preserve conditional complete positivity. The methods represent a non-perturbative alternative to well-established Adiabatic Elimination (AE) methods, and the second can be used to find noise-protected subspace codes for quantum information processing. Both are tested on a paradigmatic central spin model.

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arXiv2025

Quantum Wall States for Noise Mitigation and Eternal Purity Bounds

The present work analyzes state-stabilization techniques for decoupling a subsystem from environmental interactions. The proposed framework uses analytical and numerical tools to find an approximate decoherence-free subspace (DFS) with enhanced passive noise isolation. Active state-stabilizing control on a subsystem mediating dominant environmental interactions, which we call wall subsystem, creates an effective quantum wall state. The proposed method controls only the wall subsystem, leaving the logical subsystem untouched. This simplifies logic operations in the protected subsystem, and makes it suitable for integration with other quantum information protection techniques, such as dynamical decoupling (DD). We demonstrated its effectiveness in enhancing the performance of selective or complete DD. Under suitable conditions, our method maintains system purity above a threshold for all times, achieving eternal purity preservation. Theoretical analysis links this behavior to the asymptotic spectrum of the Hamiltonian when the control gain grows unbounded.

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arXiv2024

Finding Quantum Codes via Riemannian Optimization

We propose a novel optimization scheme designed to find optimally correctable subspace codes for a known quantum noise channel. To each candidate subspace code we first associate a universal recovery map, as if the code was perfectly correctable, and aim to maximize a performance functional that combines a modified channel fidelity with a tuneable regularization term that promotes simpler codes. With this choice optimization is performed only over the set of codes, and not over the set of recovery operators. The set of codes of fixed dimension is parametrized as a complex-valued Stiefel manifold: the resulting non-convex optimization problem is then solved by gradient-based local algorithms. When perfectly correctable codes cannot be found, a second optimization routine is run on the recovery Kraus map, also parametrized in a suitable Stiefel manifold via Stinespring representation. To test the approach, correctable codes are sought in different scenarios and compared to existing ones: three qubits subjected to bit-flip errors (single and correlated), four qubits undergoing local amplitude damping and five qubits subjected to local depolarizing channels. Approximate codes are found and tested for the previous examples as well pure non-Markovian dephasing noise acting on a $7/2$ spin, induced by a $1/2$ spin bath, and the noise of the first three qubits of IBM's \texttt{ibm\_kyoto} quantum computer. The fidelity results are competitive with existing iterative optimization algorithms, with respect to which we maintain a strong computational advantage, while obtaining simpler codes.

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