# Structured singular value analysis for spintronics network information transfer control

## TL;DR

This paper applies structured singular value analysis to quantum spintronics networks, demonstrating that control laws can achieve high fidelity with minimal sensitivity to structured perturbations, using advanced numerical optimization and $$-design tools.

## Contribution

It extends sensitivity analysis to large structured variations in quantum networks, revealing a crossover region where control objectives become aligned.

## Key findings

- Control laws achieve near-maximum fidelity.
- Sensitivity to structured perturbations is nearly vanishing.
- A crossover region links conflicting control objectives.

## Abstract

Control laws for selective transfer of information encoded in excitations of a quantum network, based on shaping the energy landscape using time-invariant, spatially-varying bias fields, can be successfully designed using numerical optimization. Such control laws, already departing from classicality by replacing closed-loop asymptotic stability with alternative notions of localization, have the intriguing property that for all practical purposes they achieve the upper bound on the fidelity, yet the (logarithmic) sensitivity of the fidelity to such structured perturbation as spin coupling errors and bias field leakages is nearly vanishing. Here, these differential sensitivity results are extended to large structured variations using $\mu$-design tools to reveal a crossover region in the space of controllers where objectives usually thought to be conflicting are actually concordant.