Modular quantum computing and parametric controls in superconducting quantum circuits
Abstract: Most quantum computers are built as lattices of qubits with nearest-neighbor couplings. This has several advantages: these machines are readily scaled and are well suited to error correction via surface codes. However, when operated as computers this architecture imposes a substantial overhead in implementing algorithms, as gates between distant qubits require swapping states across the lattice until they reach neighboring sites. These SWAP operations can easily dominate the gate count of the circuit, and thus limit the computational power of the quantum computer. In this talk, I will discuss our efforts to construct an alternative modular architecture for superconducting QCs via parametric gates and controls. Our scheme is based on a so-called SNAIL device whose three-wave couplings we exploit to controllably couple quantum modes. In this talk I will review our recent experimental efforts, especially our realization of four transmon all-to-all quantum modules and a quantum state router  which can link four modules with highly coherent operations, as well as the prospects for scaling to larger modular quantum processors.
1. A modular quantum computer based on a quantum state router C. Zhou, P. Lu, M. Praquin, T.-C. Chien, R. Kaufman, X. Cao, M. Xia, R. Mong, W. Pfaff, D. Pekker, M. Hatridge. arXiv:2109.06848 (2021).
Bio: Michael Hatridge is an Assistant Professor of Physics at the University of Pittsburgh. He received his B.S. from Texas A&M University and Ph. D. from U.C. Berkeley under the supervision of John Clarke. His work focuses on the use of parametric drives to generate quantum controls, including single- and multi-qubit gates and engineered baths, as well as superconducting quantum circuits, including quantum-limited parametric amplifiers and modular quantum computers. He is a recipient of the Michelson postdoctoral fellowship, the NSF Career Award, the Sloan Research Fellowship, and the University of Pittsburgh’s Chancellor’s distinguished research award.