Modeling Short-range Quantum Networks for Scaling Superconducting Quantum Computation

A core challenge for superconducting quantum computers is to scale up the number of qubits without increasing noise or cross-talk. Distributing a quantum computer across nearby, small qubit arrays, known as chiplets, addresses several relevant challenges. We propose chiplet architectures connected over microwave links with potential to exceed monolithic performance on near-term hardware. We model and compare architectures in a way that bridges the physical and network layers. We find evidence that short-range microwave networks may yield overall lower-noise operations despite higher noise figures at links. Chiplet topologies, latencies, and bandwidths may also compete reasonably with monolithic analogs, especially in applications that map naturally to distributed architectures. In the long term, short-range networks may underlie quantum computers just as local area networks underlie classical datacenters and supercomputers. Understanding these local networks requires quantum-based models, differing from classical expectations..



Based on work with Kaitlin N. Smith (ColdQuanta), Poolad Imany (National Institute of Standards and Technology; University of Colorado Boulder), Kevin L. Silverman (National Institute of Standards and Technology) & Frederic T. Chong (Dept. of Computer Science, University of Chicago).