Projecting requirements for superconducting qubit systems at utility scale applications

How big would a quantum computer need to be to solve problems that are intractable on classical hardware? We present a method, built on the measurement-based quantum computing paradigm, to estimate the resources required to execute fault-tolerant applications at a scale large enough to solve useful problems. When provided with an algorithm and a specific superconducting qubit architecture, the framework produces an estimate of required resources to execute that algorithm. The architecture considered consists of individual modules filled with a square lattice of transmon qubits connected to each other via a coherent quantum interconnect. We use our method to estimate hardware resource requirements for a range of quantum signal processing applications, up to problem sizes known to be challenging for classical tensor-network methods. We can also quantify the bottlenecks and tradeoffs in chip design, module interconnectivity, and thermal management and measure their impact on the infrastructure and time required to execute a given application.