Resource requirements for observable estimation, enabled by QuPython

I will present an analysis of the resources required to estimate observables in the quantum simulation of a first principles model for a condensed phase system. The complexity of the associated algorithms is severe enough that this is greatly facilitated by a high-level quantum programming language QuPython. This tool allows us to graduate from asymptotic estimates of T-gates and qubit counts to numerically quantitative ones. In addition to informing requirements for application-scale quantum computation like observable estimation, this also showcases several high-level features, and an extensible framework, built on top of the popular Python programming language.