Majorana bound state engineering via efficient real-space parameter optimization

TL;DR

This paper presents a novel numerical optimization method for tuning parameters in Majorana wires, enhancing the robustness of Majorana bound states by leveraging spatial inhomogeneities, which were previously considered detrimental.

Contribution

The authors develop an efficient real-space parameter optimization algorithm applicable to noninteracting models, enabling systematic design of Majorana states with improved stability.

Findings

Spatial inhomogeneities can be beneficial for Majorana state engineering.

The method improves the robustness of Majorana bound states.

Optimization explores largely uncharted parameter spaces.

Abstract

Recent progress toward the fabrication of Majorana-based qubits has sparked the need for systematic approaches to optimize experimentally relevant parameters for the realization of robust Majorana bound states. Here, we introduce an efficient numerical method for the real-space optimization of tunable parameters, such as electrostatic potential profiles and magnetic field textures, in Majorana wires. Combining ideas from quantum control and quantum transport, our algorithm, applicable to any noninteracting tight-binding model, operates on a largely unexplored parameter space and opens new routes for Majorana bound states with enhanced robustness. Contrary to common belief, we find that spatial inhomogeneities of parameters can be a resource for the engineering of Majorana bound states.