  While quantum computers promise to solve some scientifically and commercially
valuable problems thought intractable for classical machines, delivering on
this promise will require a large-scale quantum machine. Understanding the
impact of architecture design choices for a scaled quantum stack for specific
applications, prior to full realization of the quantum system, is an important
open challenge. To this end, we develop a framework for quantum resource
estimation, abstracting the layers of the stack, to estimate resources required
across these layers for large-scale quantum applications. Using a tool that
implements this framework, we assess three scaled quantum applications and find
that hundreds of thousands to millions of physical qubits are needed to achieve
practical quantum advantage. We identify three qubit parameters, namely size,
speed, and controllability, that are critical at scale to rendering these
applications practical. A goal of our work is to accelerate progress towards
practical quantum advantage by enabling the broader community to explore design
choices across the stack, from algorithms to qubits.
