Hybrid rare-earth ion superconductor systems for quantum information processing. / Wisby, Ilana.

2017. 159 p.

Research output: ThesisDoctoral Thesis

Unpublished

Documents

Abstract

Interfacing rare-earth doped crystals with superconducting circuit architectures provides an attractive platform for quantum memory and transducer devices. This work demonstrates the development and implementation of an alternative approach for creating a scalable quantum memory system. The process utilises a local ion implantation technique to control both the location and density of spins, without introducing additional dielectric interfaces which are thought to introduce noise. The hybrid device is fabricated by a controlled ion implantation of rare-earth ions in well-de ned micron-sized areas of a substrate, which are aligned to lithographically de ned microresonators: a highly scalable technique.

This work first demonstrates that within the limit of our experimental sensitivity, the fabrication procedure does not degrade the internal quality factors of the resonators, which remain above 105. We next investigate the properties of the implanted spin system through angular dependent microresonator electron spin resonance (micro-ESR) spectroscopy. We extract corresponding coupling rates of the order of 1 MHz and spin linewidths of 50 − 150 MHz. We find, that despite the high energy near-surface implantation, the resulting micro-ESR spectra are in excellent agreement with the modelled Hamiltonian, supporting the notion that the dopant ions are well integrated into their relevant lattice sites whilst maintaining crystalline symmetries. Furthermore, we observe clear undesirable contributions from different microwave field components of our microresonator, emphasising the need for controllable local implantation.
Original languageEnglish
QualificationPh.D.
Awarding Institution
Supervisors/Advisors
  • Meeson, Phil, Supervisor
  • Lindstrom, Tobias, Supervisor, External person
Thesis sponsors
  • National Physical Laboratory
Award date1 Jun 2017
Publication statusUnpublished - 2017
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 28093104