A SNAIL-mediated Cascaded Random Access Quantum Memory (Part 1)

ORAL

Abstract

Multimode cavities are a promising, hardware-efficient platform for quantum memories: they host several long-lived modes and enable universal, random-access control via coupling to a nonlinear element within the framework of circuit QED. The simplest architecture for such a memory involves a multimode cavity directly coupled to a control circuit (e.g., a transmon). However, this leaves the memory vulnerable to ancilla-induced mode nonlinearities and interactions, additional decoherence, and backaction from ancilla errors. The Cascaded Random Access Quantum Memory (C-RAQM) [1] addresses these issues by coupling the multimode memory to an intermediate buffer cavity via a tunable coupler that transfers states between the memory and the buffer. The buffer serves as a cache memory, where operations are executed using a coupled transmon, while providing an additional layer of protection for the memory from ancilla errors.

We introduce a C-RAQM device comprising seamless flute cavities, a SNAIL coupler, and a transmon ancilla. In part one of this two-part talk, we will discuss the device design and core capabilities, the optimization of flux delivery for biasing the SNAIL, and decoherence limits for SNAIL-activated beam-splitter operations.

[1] Z. Li, et al., arXiv:2503.13953 (2025).

*This work is supported by the Army Research Office under Grant Number W911NF-23-1-0096 and W911NF-23-1-0251 and the U.S. Department of Energy, Office of Science and National Quantum Information Science Research Centers, Superconducting Quantum Materials and Systems Center (SQMS) under contract number DE-AC02-07CH11359.

Presenters

  • Andre J Barbosa

    • Rutgers University

Authors

  • Andre J Barbosa

    • Rutgers University
  • Thomas J DiNapoli

    • Rutgers University
  • Prathyankara Narasimhan

    • Rutgers University
  • Jordan Huang

    • Rutgers University
  • Aikaterini Kargioti

    • University of Texas at Austin
    • The University of Texas at Austin
  • Xinyuan You

    • Fermi National Accelerator Laboratory (Fermilab)
  • Yao Lu

    • Fermi National Accelerator Laboratory (Fermilab)
  • Shyam Shankar

    • University of Texas at Austin
  • Srivatsan Chakram Sundar

    • Rutgers University