Master thesis defense by Julius Monberg

A model of research alignment, development and optimization of data structures across NQCP

 The data landscape involved in developing a fault-tolerant quantum computer (FTQC) is complex and heterogeneous, and prioritization of projects needs to be optimized across teams working on highly disparate research fields. This thesis presents a metric-driven model for project planning and clear communication of research between teams, for the identification of pain points and capability gaps. Two novel perspectives on using metrics of interest (MOIs) are presented, with a focus on developing a trade-off analysis. This trade-off is based on how MOIs functionally depend on a reduced set of principal MOIs that represent the interaction between technological layers of a FTQC. A basic work flow for using resource estimation to inform a MOI trade-off function is also presented. A concrete example of work from NQCP showing a resource estimation of implementing the time evolution of the trimethylenemethane (TMM) molecule on quantum hardware is mapped to the model developed in this thesis, showing how resource estimations can inform MOI dependencies and directly lead to the necessary input for a trade-off function.