Architectures for Multinode Superconducting Quantum Computers

  1. James Ang,
  2. Gabriella Carini,
  3. Yanzhu Chen,
  4. Isaac Chuang,
  5. Michael Austin DeMarco,
  6. Sophia E. Economou,
  7. Alec Eickbusch,
  8. Andrei Faraon,
  9. Kai-Mei Fu,
  10. Steven M. Girvin,
  11. Michael Hatridge,
  12. Andrew Houck,
  13. Paul Hilaire,
  14. Kevin Krsulich,
  15. Ang Li,
  16. Chenxu Liu,
  17. Yuan Liu,
  18. Margaret Martonosi,
  19. David C. McKay,
  20. James Misewich,
  21. Mark Ritter,
  22. Robert J. Schoelkopf,
  23. Samuel A. Stein,
  24. Sara Sussman,
  25. Hong X. Tang,
  26. Wei Tang,
  27. Teague Tomesh,
  28. Norm M. Tubman,
  29. Chen Wang,
  30. Nathan Wiebe,
  31. Yong-Xin Yao,
  32. Dillon C. Yost,
  33. and Yiyu Zhou
Many proposals to scale quantum technology rely on modular or distributed designs where individual quantum processors, called nodes, are linked together to form one large multinode
quantum computer (MNQC). One scalable method to construct an MNQC is using superconducting quantum systems with optical interconnects. However, a limiting factor of these machines will be internode gates, which may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require a range of techniques, including improvements in entanglement generation, the use of entanglement distillation, and optimized software and compilers, and it remains unclear how improvements to these components interact to affect overall system performance, what performance from each is required, or even how to quantify the performance of each. In this paper, we employ a `co-design‘ inspired approach to quantify overall MNQC performance in terms of hardware models of internode links, entanglement distillation, and local architecture. In the case of superconducting MNQCs with microwave-to-optical links, we uncover a tradeoff between entanglement generation and distillation that threatens to degrade performance. We show how to navigate this tradeoff, lay out how compilers should optimize between local and internode gates, and discuss when noisy quantum links have an advantage over purely classical links. Using these results, we introduce a roadmap for the realization of early MNQCs which illustrates potential improvements to the hardware and software of MNQCs and outlines criteria for evaluating the landscape, from progress in entanglement generation and quantum memory to dedicated algorithms such as distributed quantum phase estimation. While we focus on superconducting devices with optical interconnects, our approach is general across MNQC implementations.

The QICK (Quantum Instrumentation Control Kit): Readout and control for qubits and detectors

  1. Leandro Stefanazzi,
  2. Ken Treptow,
  3. Neal Wilcer,
  4. Chris Stoughton,
  5. Salvatore Montella,
  6. Collin Bradford,
  7. Gustavo Cancelo,
  8. Shefali Saxena,
  9. Horacio Arnaldi,
  10. Sara Sussman,
  11. Andrew Houck,
  12. Ankur Agrawal,
  13. Helin Zhang,
  14. Chunyang Ding,
  15. and David I. Schuster
We introduce a Xilinx RFSoC-based qubit controller (called the Quantum Instrumentation Control Kit, or QICK for short) which supports the direct synthesis of control pulses with carrier
frequencies of up to 6 GHz. The QICK can control multiple qubits or other quantum devices. The QICK consists of a digital board hosting an RFSoC (RF System-on-Chip) FPGA \cite{zcu111}, custom firmware and software and an optional companion custom-designed analog front-end board. We characterize the analog performance of the system, as well as its digital latency, important for quantum error correction and feedback protocols. We benchmark the controller by performing standard characterizations of a transmon qubit. We achieve an average Clifford gate fidelity of avg=99.93%. All of the schematics, firmware, and software are open-source \cite{QICKrepo}.