Process optimization for silicon spin qubits

Student’s name: Owen Nettles Home Institution: University of Pennsylvania NNCI Site: MANTH @ UPenn REU Principal Investigator: Dr. Anthony Sigillito, Department of Electrical and Systems Engineering, University of Pennsylvania REU Mentor: Noah Johnson, Department of Electrical and Systems Engineering, University of Pennsylvania Abstract: Quantum computers have the potential to solve a class of problems that classical computers can not. In order to algorithmically solve these problems, quantum computers need millions to hundreds of millions of qubits. However, the current largest quantum computer only has about a thousand qubits and it is unclear what the best platform is to scale by orders of magnitude. Spin qubits in silicon are a promising candidate as silicon electronics have already demonstrated outstanding scalability. To create a spin qubit, we need to isolate an electron and store information in its spin. One step of this process is creating a heterostructure that confines electrons into a two dimensional layer called a quantum well layer. To ensure that the information stored inside each qubit is robust, the quantum well layer must be pristine. We can create high quality quantum well layers while growing the substrate, but a necessary annealing step during device fabrication can cause crystal dislocations at the boundary of the well layer, degrading the device quality. We hypothesize that lowering the anneal temperature will reduce the likelihood of dislocations. Here, we investigate the magnetotransport properties of hall bar devices annealed at different temperatures with the aim of identifying an optimal temperature for qubit fabrication. Our measurements give us direct insight on material parameters that impact qubit performance, such as valley splitting, mobility, and quantum lifetime.