Qinf u853735128_qi

Workshop #33 at IEEE Quantum Week 2023

• Session 1 — 10:00–11:30 (PDT, GMT-7) — Roadmap for Superconducting QC
• Session 2 — 13:00–14:30 (PDT, GMT-7) — Roadmap for Ion Trap QC
• Session 3 — 15:15–16:45 (PDT, GMT-7) — Roadmaps for Other QC Approaches

Summary: See how others are planning a path to fully error-corrected quantum computing and provide input on what needs to happen and by when. The experience will be valuable to anyone involved in technology planning, research and development management, or interested in the big picture

Abstract: Technology roadmapping helped the semiconductor community to successfully coordinate research and development efforts for over two decades. The IEEE International Roadmap for Devices and Systems (IRDS) uses an updated roadmapping process driven both bottom-up by devices and top-down by systems application requirements. The IRDS Cryogenic Electronics and Quantum Information Processing (CEQIP) team has been monitoring the status of quantum computing and recently began developing technology roadmaps. Key to the development of roadmaps is identification of technology needs, hard problems, and timelines for development. Each of three workshop sessions will cover one or more approaches to quantum computing: superconducting, ion traps, and other. Each session will feature a short introduction to the roadmapping process, a few presentations, and an interactive roadmapping session

Workshop Program

Session 1 — 10:00–11:30 — Roadmap for Superconducting QC

• 10:00-10:15      Introduction to the technology roadmapping process
• 10:15-10:30      Julian Kelly; Director, Quantum Hardware; Google Quantum AI
• 10:30-10:45      Kaveh Delfanazari, Glasgow University and IRDS
• 10:45-11:00      Jon Felbinger; Deputy Director, Quantum Economic Development Consortium (QED-C); SRI and
  Setso Metodi; Chair of the SRI Quantum Technology Manufacturing Roadmap (QTMR) Testbeds Working Group; SNL
• 11:00-11:30      Interactive roadmapping session

Session 2 — 13:00-14:30 — Roadmap for Ion Trap QC

• 13:00-13:15      Introduction to the technology roadmapping process
• 13:15-13:30      John Gamble; Director System Architecture and Performance; IonQ
• 13:30-13.45      Patty Lee; Chief Scientist, Technology Development; Quantinuum
• 13:45-14:00      Jon Felbinger; Deputy Director, Quantum Economic Development Consortium (QED-C); SRI and
  Setso Metodi; Chair of the SRI Quantum Technology Manufacturing Roadmap (QTMR) Testbeds Working Group; SNL
• 14:00-14:30      Interactive roadmapping session

Session 3 — 15:15-16:45 — Roadmaps for Other QC Approaches

• 15:15-15:30      Introduction to the technology roadmapping process
• Photonic Quantum Computing Roadmap
• 15.30-15:50      Jon Felbinger; Deputy Director, Quantum Economic Development Consortium (QED-C); SRI and
  Setso Metodi; Chair of the SRI Quantum Technology Manufacturing Roadmap (QTMR) Testbeds Working Group; SNL
• 15:50-16:10 Interactive roadmapping session
• Spin Quantum Computing Roadmap
• 16:10-16:30      Jon Felbinger; Deputy Director, Quantum Economic Development Consortium (QED-C); SRI and
  Setso Metodi; Chair of the SRI Quantum Technology Manufacturing Roadmap (QTMR) Testbeds Working Group; SNL
• 16:30-16:45      Interactive roadmapping session

Presentation information:

• Length: 13 minutes + 2 minutes for questions
• Presentations will be recorded, but will only be available to registered conference participants for a limited time (1-2 months) after the meeting.
• Guidance:
  • Assume that participants have some knowledge of your approach to quantum computing. A 1-slide overview should be sufficient.
  • Focus on technology needs and timelines. This is an opportunity to show what your team is working on as well as what you would like others to do and by when.
  • An example presentation by the IRDS CEQIP team can be provided, if you are interested. 

There will be an open Zoom talk by Marco Fellous Asiani January 26, 2023 at 5 PM Eastern Standard Time. There are interested participants in Korea/Japan, USA, and EU, so sorry if the time is unusual for your region.

For technical background, see https://arxiv.org/pdf/2209.05469.pdf.

The talk will be 40-45 minutes, but we can keep the Zoom running for at least an hour. You may forward a link to this page to others.

If you are interested in attending, please email erikdebenedictis@gmail.com and ask to be added to the calendar invitation.

MNR: A Metric-Noise-Resource methodology to optimize resource consumption of the full-stack architecture of quantum computers for long-term scalability

Marco Fellous Asiani

In the race to build quantum computers for large problems intractable by classical computing, optimizing their architecture to maximize their scalability potential might become crucial. With this aim in mind, we propose a methodology dubbed Metric-Noise-Resource (MNR), able to quantify and optimize all aspects of the full-stack quantum computer, bringing together concepts from quantum hardware (e.g., physics of the qubits), quantum software (e.g., quantum algorithms and quantum error correction), and enabling technologies (e.g., cryogenics, control electronics, and wiring). By asking to minimize the appropriate cost function under the constraint of implementing a successful computation, one can optimize the entire computing architecture, from quantum hardware, quantum software to enabling technologies. We apply our framework in an idealized model of a full-stack quantum computer based on futuristic superconducting qubits, and we estimate minimum energy bills required to implement error-corrected quantum algorithms. We identify various trade-offs between qubit’s quality, classical electronics consumption, quantum algorithms shape, qubit’s overhead, cryostat temperatures, etc. Considering Shor’s factoring algorithm breaking RSA cryptosystem, we compare the energy our optimized quantum computer would consume to the one of a classical computer solving the same task for various key sizes. There, we exhibit regimes of energy advantage occurring before the computational one, providing another potential motivation for the development of quantum computers. In some regimes of high energy consumption, the holistic “global” approach behind our methodology can reduce consumption by orders of magnitudes compared to “local” optimizations that do not consider the entire computing system. It can be done in surprising manners that couldn’t be guessed with simple estimates. Overall, the framework developed is universal: it can be applied to any quantum computing platform. It could be used to perform benchmarks between quantum computers, drive hardware parts and architectural developments, and finally define clear multidisciplinary roadmaps in the quest for scalability.