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Annalen der Physik

Geometry‐Aware Decoherence Maps for Tunable Quantum‐Dot Qubits: A Physics‐Informed Surrogate Modeling Study

Maurice Tiotsop

Published Aug 1, 2026• 0 citations
Publisher

Abstract

ABSTRACT Quantum‐dot qubits offer strong tunability, but their sensitivity to geometry, external fields, and model parameters makes decoherence prediction computationally demanding. Here, we present a physics‐informed surrogate modeling framework to construct geometry‐aware decoherence maps for tunable quantum‐dot qubits. Using an effective two‐level model with parabolic and triangular confinement and a physically motivated phenomenological Lindblad‐rate model, we compute the transition frequency, an entropy‐based information metric, and a coherence‐time proxy over a controlled multidimensional parameter sweep. The resulting 250‐sample dataset is used to train two compact, toolbox‐free surrogate models: a quadratic polynomial model and a Gaussian radial basis function surrogate. Both reproduce the physics model with under 5‐fold cross‐validation and provide 260–950 faster predictions than direct diagonalization. A composite operating‐point score is evaluated across 66 weighting choices to assess robustness. Within this simplified model, near‐parabolic confinement yields a more stable spectral response and broader robust operating region, whereas triangular distortion enhances electric‐field tunability but narrows the coherence‐preserving window. The electric field is the dominant control parameter, while the magnetic field has a weaker secondary role. These results illustrate a transferable surrogate‐assisted strategy for rapid qubit design‐space exploration.

DOI
10.1002/andp.70277

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ABSTRACT Quantum‐dot qubits offer strong tunability, but their sensitivity to geometry, external fields, and model parameters makes decoherence prediction computationally demanding. Here, we present a physics‐informed surrogate modeling framework to construct geometry‐aware decoherence maps for tunable quantum‐dot qubits. Using an effective two‐level model with parabolic and triangular confinement and a physically motivated phenomenological Lindblad‐rate model, we compute the transition frequency, an entropy‐based information metric, and a coherence‐time proxy over a controlled multidimensional parameter sweep. The resulting 250‐sample dataset is used to train two compact, toolbox‐free surrogate models: a quadratic polynomial model and a Gaussian radial basis function surrogate. Both reproduce the physics model with under 5‐fold cross‐validation and provide 260–950 faster predictions than direct diagonalization. A composite operating‐point score is evaluated across 66 weighting choices to assess robustness. Within this simplified model, near‐parabolic confinement yields a more stable spectral response and broader robust operating region, whereas triangular distortion enhances electric‐field tunability but narrows the coherence‐preserving window. The electric field is the dominant control parameter, while the magnetic field has a weaker secondary role. These results illustrate a transferable surrogate‐assisted strategy for rapid qubit design‐space exploration.
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Silicon-based donor flip-flop qubits offer a promising path toward scalable, fault-tolerant quantum computing by combining the long coherence times of nuclear spins with fast, fully electrical control and long-range dipole-dipole coupling between qubits. However, realizing high-fidelity entangling operations in this platform remains challenging. The entangling interaction is intrinsically coupled to electron orbital dynamics, which can lead to leakage into non-computational states and unwanted phase accumulation. Furthermore, in multi-qubit architectures, residual dipolar couplings from spectator qubits distort the effective interaction landscape. In this work, we employ a numerical simulation framework, FlipFlopQSim, that models the spin-orbital dynamics of interacting flip-flop qubits to extract effective logical operations from realistic electrical control pulses. Using Makhlin invariants, we map the entangling landscape generated by electrically controlled dipole-dipole interactions and identify operating regions locally equivalent to canonical two-qubit gates, such as iSWAP\sqrt{iSWAP}iSWAP​ and iSWAPiSWAPiSWAP. We then optimize the control parameters of physically realizable, electrically driven RzR_zRz​ rotations to implement the necessary local corrections and maximize composite gate fidelity. Finally, we scale our analysis to multi-qubit registers with various geometries and connectivity patterns to evaluate spectator-induced distortions. Our results demonstrate that high-fidelity entangling operations cannot be optimized in isolation; rather, they require a co-design approach that simultaneously optimizes pulse control, local phase compensation, and physical device geometry. This work provides a robust numerical framework for assessing the scalability of electrically controlled silicon quantum processors and outlines key design principles for robust multi-qubit gate implementation.
Geometric quantum computation offers a practical strategy toward robust quantum computation due to its inherent error tolerance. However, the rigorous geometric conditions lead to complex and/or error-disturbed quantum controls, especially for logical qubits that involve more physical qubits, whose error tolerance is effective in principle, but their experimental demonstration is still demanding. Thus, how to best simplify the needed control and manifest its full advantage has become the key to widespread applications of geometric quantum computation. Here we propose a fast and robust geometric scheme, with decoherence-free subspace encoding, and present its physical implementation on superconducting quantum circuits, where we only utilize the experimentally demonstrated parametrically tunable coupling to achieve high-fidelity geometric control over logical qubits. Numerical simulation verifies that it can efficiently combine the error tolerance from both the geometric phase and logical-qubit encoding, displaying our gate-performance superiority over the conventional dynamical one without encoding, in terms of both gate fidelity and robustness. Therefore, our scheme can consolidate both error suppression methods for logical-qubit control, which sheds light on the future large-scale quantum computation.