Design of Feedback Control Laws for Information Transfer in Spintronics Networks

Abstract

Information encoded in networks of stationary, interacting spin-1/2 particles is central for many applications ranging from quantum spintronics to quantum information processing. Without control, however, information transfer through such networks is generally inefficient. Currently available control methods to maximize the transfer fidelities and speeds mainly rely on dynamic control using time-varying fields and often assume instantaneous readout. We present an alternative approach to achieving efficient, high-fidelity transfer of excitations by shaping the energy landscape via the design of time-invariant feedback control laws without recourse to dynamic control. Both instantaneous readout and the more realistic case of finite readout windows are considered. The technique can also be used to freeze information by designing energy landscapes that achieve Anderson localization. Perfect state or super-optimal transfer and localization are enabled by conditions on the eigenstructure of the system and signature properties for the eigenvectors. Given the eigenstructure enabled by super-optimality, it is shown that feedback controllers that achieve perfect state transfer are, surprisingly, also the most robust with regard to uncertainties in the system and control parameters.

13 pages, 14 figures, accepted for IEEE TAC

References in corpus (6)

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Cited by in corpus (13)

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• Statistically Characterising Robustness and Fidelity of Quantum Controls and Quantum Control Algorithms
• Structured singular value analysis for spintronics network information transfer control
• Robustness of Energy Landscape Controllers for Spin Rings under Coherent Excitation Transport
• Robustness of energy landscape control for spin networks under decoherence
• Robustness of Energy Landscape Control to Dephasing
• Quantum control landscape for generation of $H$ and $T$ gates in an open qubit with both coherent and environmental drive
• Reinforcement Learning vs. Gradient-Based Optimisation for Robust Energy Landscape Control of Spin-1/2 Quantum Networks
• Time Domain Sensitivity of the Tracking Error
• Control landscape of measurement-assisted transition probability for a three-level quantum system with dynamical symmetry
• Control landscapes for high-fidelity generation of C-NOT and C-PHASE gates with coherent and environmental driving
• Two-level control over quantum state creation via entangled equal-probability state
• Geometric Interpretation of Sensitivity to Structured Uncertainties in Spintronic Networks