Superconducting circuits have emerged as a leading platform for quantum computation and simulation, due largely to the significant improvements in qubit coherence times and high-fidelity quantum control achieved over the past few decades. However, to implement a practical quantum algorithm with state-of-the-art error-correcting codes requires many more long-lived physical qubits, each utilizing substantial experimental resources for control and readout. This presents a scalability problem for quantum circuits with N >> 1 physical qubits.
To address this scalability problem, we investigate various hardware-efficient circuit architectures for quantum information processing. We leverage the wide, tunable parameter space available in circuit quantum electrodynamics to engineer custom Hamiltonians and dissipation, operating at frequencies ranging from 10s of MHz to over 10 GHz. Example systems we explore include parametrically-modulated resonators, qubits protected by autonomous quantum error correction, and circuits with intrinsic noise protection.