Alex ARENAS MORENO

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Modular Framework and Composite Metric Design for Superconducting Qubit Optimization

This Bachelor’s Thesis, developed in collaboration with Qilimanjaro Quantum Tech and executed at large scale on MareNostrum 5 at the Barcelona Supercomputing Center, focuses on the characterization and optimization of the physical parameters of a SQUID-fluxonium superconducting qubit for analog quantum computing. The work required studying the theoretical foundations of superconducting qubits, fluxonium circuits, dispersive readout, and Hamiltonian tunability. This theoretical basis was then used to translate the physical intuition behind a “good” qubit configuration into quantitative metrics that could be evaluated computationally. On this basis, the thesis implements a modular computational framework in which the physical model, metric definitions, optimization processes, data-saving routines, and visualization tools are built as independent components, allowing the workflow to be extended to future metrics, constraints, and qubit configurations. The framework explores physical circuit parameters, evaluates each candidate over external flux-control maps, and combines the resulting metrics into a global score, providing a foundational tool for quantum chip optimization.

25-MAR-2026

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