Microarchitectures for Heterogeneous Superconducting Quantum Computers

  1. Samuel Stein,
  2. Sara Sussman,
  3. Teague Tomesh,
  4. Charles Guinn,
  5. Esin Tureci,
  6. Sophia Fuhui Lin,
  7. Wei Tang,
  8. James Ang,
  9. Srivatsan Chakram,
  10. Ang Li,
  11. Margaret Martonosi,
  12. Fred T. Chong,
  13. Andrew A. Houck,
  14. Isaac L. Chuang,
  15. and Michael Austin DeMarco
Noisy Intermediate-Scale Quantum Computing (NISQ) has dominated headlines in recent years, with the longer-term vision of Fault-Tolerant Quantum Computation (FTQC) offering significant
potential albeit at currently intractable resource costs and quantum error correction (QEC) overheads. For problems of interest, FTQC will require millions of physical qubits with long coherence times, high-fidelity gates, and compact sizes to surpass classical systems. Just as heterogeneous specialization has offered scaling benefits in classical computing, it is likewise gaining interest in FTQC. However, systematic use of heterogeneity in either hardware or software elements of FTQC systems remains a serious challenge due to the vast design space and variable physical constraints. This paper meets the challenge of making heterogeneous FTQC design practical by introducing HetArch, a toolbox for designing heterogeneous quantum systems, and using it to explore heterogeneous design scenarios. Using a hierarchical approach, we successively break quantum algorithms into smaller operations (akin to classical application kernels), thus greatly simplifying the design space and resulting tradeoffs. Specializing to superconducting systems, we then design optimized heterogeneous hardware composed of varied superconducting devices, abstracting physical constraints into design rules that enable devices to be assembled into standard cells optimized for specific operations. Finally, we provide a heterogeneous design space exploration framework which reduces the simulation burden by a factor of 10^4 or more and allows us to characterize optimal design points. We use these techniques to design superconducting quantum modules for entanglement distillation, error correction, and code teleportation, reducing error rates by 2.6x, 10.7x, and 3.0x compared to homogeneous systems.

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.

Optimized Surface Code Communication in Superconducting Quantum Computers

  1. Ali Javadi-Abhari,
  2. Pranav Gokhale,
  3. Adam Holmes,
  4. Diana Franklin,
  5. Kenneth R. Brown,
  6. Margaret Martonosi,
  7. and Frederic T. Chong
, and several-hundred-qubit"]machines are around the corner. Machines of this scale have the capacity to demonstrate quantum supremacy, the tipping point where QC is faster than the fastest classical alternative for a particular problem. Because error correction techniques will be central to QC and will be the most expensive component of quantum computation, choosing the lowest-overhead error correction scheme is critical to overall QC success. This paper evaluates two established quantum error correction codes—planar and double-defect surface codes—using a set of compilation, scheduling and network simulation tools. In considering scalable methods for optimizing both codes, we do so in the context of a full microarchitectural and compiler analysis. Contrary to previous predictions, we find that the simpler planar codes are sometimes more favorable for implementation on superconducting quantum computers, especially under conditions of high communication congestion.