Platforms based on semiconductors for application in quantum computing

Abstract

This thesis is composed of three parts. In the first part, a study of transport in semiconductor nanowires is carried out, in which the multichannel scattering occurs in a certain finite region, providing a reentrance in the conductance. This reentrance is analyzed in zero magnetic field configuration for cases where there is a strong spin-orbit coupling and for a structural deformation in the nanowire, where it suffers a localized expansion. Furthermore, both cases are also investigated in the presence of a magnetic field, where the reentrance also appears in higher energy channels. In the second part of this thesis, machine learning is applied to successfully determine physical parameters of two qubits in coupled semiconductor quantum dots, with the aim of locally measuring the qubits and reducing the necessary measurements performed in the laboratory. In the third part of the thesis, the study focuses on the interaction of distant qubits formed by quantum dots. These qubits are modeled by a spin chain with nearest neighbor interactions and the goal is to implement SWAP and CNOT quantum logic gates in this spin network. Finally, by using SWAP gates, it is possible to propagate quantum information along the spin chain. When noise effects are taken into account, there is a relevant difference in the order of application of the logic gates, which leads to an increase or decrease in the effectiveness of the application of quantum gates.