|dc.description.abstract||States of confined electrons in semiconductors are promising candidates for quantum bits with high controllability, scalability, and coherence. Particularly, spin quantum dots offer direct integration with the modern MOS technology, whereas the exotic Majorana bound states are virtually immune to decoherence. In all cases, high-quality material system design is necessary for the fabrication of quantum devices, and
the physical quantities that drive qubit operations require optimal pulse engineering for deterministic quantum control.
The first goal of our study is to develop a consistent procedure of epitaxial InGaAs metallization with a flat Al layer and a pristine metal-semiconductor interface, necessary for the future observation of Majorana quasiparticles.
The comprehensive analysis of the kinetics of Al on III-V heterostructures we carried out shows that the effects of deposition rate and methods of Al surface protection are understudied.
With cross-sectional transmission electron microscopy, we demonstrate high heterostructure quality using As₄ as a capping layer and an order of magnitude larger Al deposition rate than previously reported.
Based on the subsequent analysis for different Al growth rates and cappings, we conclude that faster rates are beneficial to minimize heat transfer to the wafer, protect the uncapped Al surface from rearrangement, and improve its morphology.
Our second goal is to simulate the operation of a voltage- and ESR-controlled, quantum-dot-based spin quantum processor in silicon.
To achieve this, we devise methods to extract the Hubbard model and spin interaction parameters from the electric potential landscape simulations of realistic device geometries. In addition, we present a novel, numerically efficient algorithm for voltage and ESR field pulse engineering that yields a theoretical 100% fidelity, preserves charge stability, and automatically incorporates all cross-couplings between quantum dots. The general optimal control formulation makes it possible to use the method in conjunction with gradient optimization routines. The algorithms are implemented as parts of a general-purpose, open-source Python package for semiconductor quantum dot simulations.
We expect that the obtained results will further facilitate the development of semiconductor qubits, and become a stepping stone towards the realization of hybrid quantum dot-Majorana devices.||en