Model for Pre-commercialization Required Before Quantum Computing Is Ready for Commercialization

  • Pre-commercialization seeks to eliminate all major technical uncertainties which might impede commercialization, thorough research, prototyping, and experimentation.
  • Commercialization uses off the shelf technologies and proven research results to engineer low-risk commercial products in a reasonably short period of time.
  1. This paper is only a proposed model for approaching commercialization of quantum computing
  2. First things first — much more research is required
  3. The gaps: Why can’t quantum computing be commercialized right now?
  4. What effort is needed to fill the gaps
  5. Quantum advantage is the single greatest technical obstacle to commercialization
  6. Quantum computing remains a mere laboratory curiosity
  7. The critical need for quantum computing is much further and deeper research
  8. What do commercialization and pre-commercialization mean?
  9. Put most simply, pre-commercialization is research as well as prototyping and experimentation
  10. Put most simply, commercialization focuses on a product engineering team — commercial product-oriented engineers and software developers rather than scientists
  11. Pre-commercialization is the Wild West while commercialization is more like urban planning
  12. Most production-scale application development will occur during commercialization
  13. Premature commercialization risk
  14. No great detail on commercialization proper since focus here is on pre-commercialization
  15. Commercialization can be used in a variety of ways
  16. Unclear how much research must be completed before commercialization of quantum computing can begin
  17. What fraction of research must be completed before commercialization of quantum computing?
  18. Research will always be ongoing and never-ending
  19. Simplified model of the main stages from pre-commercialization through commercialization
  20. The heavy lift milestones for commercializing quantum computing
  21. Short list of the major stages in development and adoption of quantum computing as a new technology
  22. More detailed list of stages in development of quantum computing as a product
  23. Stage milestones towards quantum computing as a commercial product
  24. The benefits and risks of quantum error correction (QEC) and logical qubits
  25. Three stages of deployment for quantum computing: The ENIAC Moment, configurable packaged quantum solutions, and The FORTRAN Moment
  26. Highlights of pre-commercialization activities
  27. Highlights of initial commercialization
  28. Post-commercialization — after the initial commercialization stage
  29. Highlights for subsequent stages of commercial deployment, maybe up to ten of them
  30. Prototyping and experimentation — hardware and software, firmware and algorithms, and applications
  31. Pilot projects — prototypes
  32. Proof of concept projects (POC) — prototypes
  33. Rely primarily on simulation for most prototyping and experimentation
  34. Primary testing of hardware should focus on functional testing, stress testing, and benchmarking — not prototyping and experimentation
  35. Prototyping and experimentation should initially focus on simulation of hardware expected in commercialization
  36. Late in pre-commercialization, prototyping and experimentation can focus on actual hardware — once it meets specs for commercialization
  37. Prototyping and experimentation on actual hardware earlier in pre-commercialization is problematic and an unproductive distraction
  38. Products, services, and releases — for both hardware and software
  39. Products which enable quantum computing vs. products which are enabled by quantum computing
  40. Potential for commercial viability of quantum-enabling products during pre-commercialization
  41. Preliminary quantum-enabled products during pre-commercialization
  42. How much of research results can be used intact vs. need to be discarded and re-focused and re-implemented with a product engineering focus?
  43. Hardware vs. cloud service
  44. Prototyping and experimentation — applied research vs. pre-commercialization
  45. Prototyping products and experimenting with applications
  46. Prototyping and experimentation as an extension of research
  47. Trial and error vs. methodical process for prototyping and experimentation
  48. Alternative meanings of pre-commercialization
  49. Requirements for commercialization
  50. Production-scale vs. production-capacity vs. production-quality vs. production-reliability
  51. Commercialization of research
  52. Stages for uptake of new technology
  53. Is quantum computing still a mere laboratory curiosity? Yes!
  54. When will quantum computing cease being a mere laboratory curiosity? Unknown. Not soon.
  55. By definition quantum computing will no longer be a mere laboratory curiosity as soon as it has achieved initial commercialization
  56. Could quantum computing be considered no longer a mere laboratory curiosity as soon as pre-commercialization is complete? Possibly.
  57. Could quantum computing be considered no longer a mere laboratory curiosity as soon as commercialization is begun? Plausibly.
  58. Quantum computing will clearly no longer be a mere laboratory curiosity once initial commercialization stage 1.0 has been achieved
  59. Four overall stages of research
  60. Next steps — research
  61. What is product development or productization?
  62. Technical specifications
  63. Product release
  64. When can pre-commercialization begin? Now! We’re doing it now.
  65. When can commercialization begin? That’s a very different question! Not soon.
  66. Continually update vision of what quantum computing will look like
  67. Need to utilize off the shelf technology
  68. It takes significant time to commercialize research results
  69. The goal is to turn raw research results into off the shelf technology which can then be used in commercial products
  70. Will there be a quantum winter? Or even more than one?
  71. But occasional Quantum Springs and Quantum Summers
  72. Quantum Falls?
  73. In truth, it will be a very long and very slow slog
  74. No predicting the precise flow of progress, with advances and setbacks
  75. Sorry, but there won’t be any precise roadmap to commercialization of quantum computing
  76. Existing roadmaps leave a lot to be desired, and prove that we’re in pre-commercialization
  77. No need to boil the ocean — progression of commercial stages
  78. The transition from pre-commercialization to commercialization: producing detailed specifications for requirements, architecture, functions and features, and fairly detailed design
  79. Critical technical gating factors for initial stage of commercialization
  80. Quantum advantage is the single greatest technical gating factor for commercialization
  81. Variational methods are a short-term crutch, a distraction, and an absolute dead-end
  82. Exploit quantum Fourier transform (QFT) and quantum phase estimation (QPE) on simulators during pre-commercialization
  83. Final steps before a product can be released for commercial production deployment
  84. No further significant research can be required to support the initial commercialization product
  85. Commercialization requires that the technology be ready for production deployment
  86. Non-technical gating factors for commercialization
  87. Quantum computer science
  88. Quantum software engineering
  89. No point to commercializing until substantial fractional quantum advantage is reached
  90. Fractional quantum advantage progress to commercialization
  91. Qubit capacity progression to commercialization
  92. Maximum circuit depth progression to commercialization
  93. Alternative hardware architectures may be needed for more than 64 qubits
  94. Qubit technology evolution over the course of pre-commercialization, commercialization, and post-commercialization
  95. Initial commercialization stage 1 — C1.0
  96. The main criterion for initial commercialization is substantial quantum advantage for a realistic application, AKA The ENIAC Moment
  97. Differences between validation, testing, and evaluation for pre-commercialization vs. commercialization
  98. Validation, testing, and evaluation during pre-commercialization
  99. Validation, testing, and evaluation for initial commercialization stage 1.0
  100. Initial commercialization stage 1.0 — The ENIAC Moment has arrived
  101. Initial commercialization stage 1.0 — Routinely achieving substantial quantum advantage
  102. Initial commercialization stage 1.0 — Achieving substantial quantum advantage every month or two
  103. Okay, maybe a nontrivial fraction of minimal quantum advantage might be acceptable for the initial stage of commercialization
  104. Minimum Viable Product (MVP)
  105. Automatically scalable quantum algorithms
  106. Configurable packaged quantum solutions
  107. Shouldn’t quantum error correction (QEC), logical qubits, and The FORTRAN Moment be required for the initial commercialization stage? Yes, but not feasible.
  108. Should a higher-level programming model be required for the initial commercialization stage? Probably, but may be too much to ask for.
  109. Not everyone will trust a version 1.0 of any product anyway
  110. General release
  111. Criteria for evaluating the success of initial commercialization stage 1.0
  112. Quantum ecosystem
  113. Subsequent commercialization stages — Beyond the initial ENIAC Moment
  114. Post-commercialization efforts
  115. Milestones in fine phase granularity to support quantum Fourier transform (QFT) and quantum phase estimation (QPE)
  116. Milestones in quantum parallelism and quantum advantage
  117. When might commercialization of quantum computing occur?
  118. Slow, medium, and fast paths to pre-commercialization and initial commercialization
  119. How long might pre-commercialization take?
  120. What stage are we at right now? Still early pre-commercialization.
  121. When might pre-releases and preview releases become available?
  122. Dependencies
  123. Some products which enable pre-commercialization may not be relevant to commercialization
  124. Risky bets: Some great ideas during pre-commercialization may not survive in commercialization
  125. A chance that all work products from pre-commercialization may have to be discarded to transition to commercialization
  126. Analogy to transition from ABC, ENIAC, and EDVAC research computers to UNIVAC I and IBM 701 and 650 commercial systems
  127. Concern about overreach and overdesign — Multics vs. UNIX, OS/2 vs. Windows, IBM System/38, Intel 432, IBM RT PC ROMP vs. PowerPC, Trilogy
  128. Full treatment of commercialization — a separate paper, eventually
  129. Beware betaware
  130. Vaporware — don’t believe it until it yourself
  131. Pre-commercialization is about constant change while commercialization is about stability and carefully controlled and compatible evolution
  132. Customers and users prefer carefully designed products, not cobbled prototypes
  133. Customers and users will seek the stability of methodical commercialization, not the chaos of pre-commercialization
  134. Need for larger capacity, higher performance, more accurate classical quantum simulators
  135. Hardware infrastructure and services buildout
  136. Hardware infrastructure and services buildout is not an issue, priority, or worry yet since the focus is on research
  137. Factors driving hardware infrastructure and services buildout
  138. Maybe a surge in demand for hardware infrastructure and services late in pre-commercialization
  139. Expect a surge in demand for hardware infrastructure and services once The ENIAC Moment has been reached
  140. Development of standards for QA, documentation, and benchmarking
  141. Business development during pre-commercialization
  142. Some preliminary commercial business development late in pre-commercialization
  143. Preliminary commercial business development early in initial commercialization stage
  144. Deeper commercial business development should wait until after pre-releases late in the initial commercialization stage
  145. Consortiums for configurable packaged quantum solutions
  146. Finalizing service level agreements (SLA) should not occur until late in the initial commercialization stage, not during pre-commercialization
  147. IBM — Still heavily focused on research as well as customers prototyping and experimenting
  148. Oracle — No hint of prime-time application commercialization
  149. Amazon — Research and facilitating prototyping and experimentation
  150. Pre-commercialization is the realm of the lunatic fringe
  151. Quantum Ready
  152. Quantum Ready — The criteria and timing will be a fielder’s choice based on needs and interests
  153. Quantum Ready — Be early, but not too early
  154. Quantum Ready — Critical technical gating factors
  155. Quantum Ready — When the ENIAC Moment has been achieved
  156. Quantum Ready — It’s never too early for The Lunatic Fringe
  157. Quantum Ready — Light vs. heavy technical talent
  158. Quantum Ready — For algorithm and application researchers anytime during pre-commercialization is fine, but for simulation only
  159. Quantum Ready — Caveat: Any work, knowledge, or skill developed during pre-commercialization runs the risk of being obsolete by the time of commercialization
  160. Quantum Ready — The technology will be constantly changing
  161. Quantum Ready — Leaders, fast-followers, and laggards
  162. Quantum Ready — Setting expectations for commercialization
  163. Quantum Ready — Or maybe people should wait for fault-tolerance?
  164. Quantum Ready — Near-perfect qubits might be a good time to get ready
  165. Quantum Ready — Maybe wait for The FORTRAN Moment?
  166. Quantum Ready — Wait for configurable packaged quantum solutions
  167. Quantum Ready — Not all staff within the organization have to get Quantum Ready at the same time or pace
  168. Shor’s algorithm implementation for large public encryption keys? Not soon.
  169. Quantum true random number generation as an application is beyond the scope of general-purpose quantum computing
  170. Summary and conclusions

This paper is only a proposed model for approaching commercialization of quantum computing

First things first — much more research is required

The gaps: Why can’t quantum computing be commercialized right now?

  1. Haven’t achieved quantum advantage. No point in commercializing a new computing technology which has no substantial advantage over classical computing.
  2. Too few qubits.
  3. Gate error rate is too high. Can’t get correct and reliable results.
  4. Severely limited qubit connectivity. Need full connectivity or very low error rate for SWAP networks, or some innovative connectivity scheme.
  5. Very limited coherence time. Severely limits circuit depth.
  6. Very limited circuit depth. Limited by coherence time.
  7. Insufficiently fine granularity for phase and probability amplitude. Precludes quantum Fourier transform (QFT) and quantum phase estimation (QPE).
  8. No support for quantum Fourier transform (QFT) and quantum phase estimation (QPE). Needed for quantum computational chemistry and other applications.
  9. Measurement error rate is too high.
  10. Need quantum error correction (QEC) or near-perfect qubits. 99.99% to 99.999% fidelity.
  11. Need modular quantum processing unit (QPU) designs.
  12. Need higher-level programming models. Current programming model is too primitive.
  13. Need for high-level quantum-native programming languages. Currently working at the equivalent of classical assembly language or machine language — individual quantum logic gates.
  14. Too difficult to transform an application problem statement into a quantum algorithmic application. Need for methodology and automated tools.
  15. Too few applications are in a form that can readily be implemented on a quantum computer. Need for methodology.
  16. Lack of a rich library of high-level algorithmic building blocks.
  17. Need for quantum algorithm and application metaphors, design patterns, frameworks, and libraries.
  18. Inability to achieve dramatic quantum advantage. Or even a reasonable fraction.
  19. No real ability to debug complex quantum algorithms and applications.
  20. Unable to classically simulate more than about 40 qubits.
  21. No conceptual models or examples of automatically scalable 40-qubit quantum algorithms.
  22. No conceptual models or examples of realistic and automatically scalable quantum applications.
  23. No conceptual models or examples of complete and automatically scalable configurable packaged quantum solutions.
  24. Not ready for production deployment in general. Still a mere laboratory curiosity.

What effort is needed to fill the gaps

  1. Much more research. Enhancing existing technologies. Discovery of new technologies. New architectures. New approaches to deal with technologies. New programming models.
  2. Much more innovation.
  3. Much more algorithm efforts.
  4. Much greater reliance on classical quantum simulators. Configured to act as realistic quantum computers, current, near-term, medium-term, and longer-term.
  5. Robust technical documentation.
  6. Robust training materials.
  7. General reliance on open source, transparency, and free access to all technologies.
  8. Comprehensive examples for algorithms, metaphors, design patterns, frameworks, applications, and configurable packaged quantum solutions.
  9. Resistance to urges and incentives to prematurely commercialize the technology.
  10. Many prototypes, experimentation, and much engineering evolution. Who knows what the right mix is for successful quantum solutions to realistic application problems.

Quantum advantage is the single greatest technical obstacle to commercialization

Quantum computing remains a mere laboratory curiosity

The critical need for quantum computing is much further and deeper research

What do commercialization and pre-commercialization mean?

  1. Research. Discovery, understanding, and invention of the science and raw technology. Some products require deep research, some do not.
  2. Prototyping and experimentation. What might a product look like? How might it work? How might people use it? Try out some ideas and see what works and what doesn’t. Some products require a lot of trial and error, some do not.
  3. Productization. We know what the product should look like. Now build it. Product engineering. Much more methodical, avoiding trial and error.
  1. Research alone. Prototyping and experimentation will be considered part of commercialization. Common view for a research lab.
  2. Research as well as prototyping and experimentation. Vague and rough ideas need to be finalized before commercialization can begin. Commercialization, productization, product development, and product engineering will all be exact synonyms.
  1. Much more research is needed. Lots of research.
  2. No firm vision or plan for the product. What the product will actually look like, feel like, and how it will actually be used. So…
  3. Much prototyping and experimentation is needed. Lots of it. This will shape and determine the vision and details of the product.
  1. Pre-commercialization means research as well as prototyping and experimentation. This will continue until the research advances to the stage where sufficient technology is available to produce a viable product that solves production-scale practical real-world problems. All significant technical issues have been resolved, so that commercialization can proceed with minimal technical risk.
  2. Commercialization means productization after research as well as prototyping and experimentation are complete. Productization means a shift in focus from research to a product engineering team — commercial product-oriented engineers and software developers rather than scientists.

Put most simply, pre-commercialization is research as well as prototyping and experimentation

Put most simply, commercialization focuses on a product engineering team — commercial product-oriented engineers and software developers rather than scientists

Pre-commercialization is the Wild West while commercialization is more like urban planning

Most production-scale application development will occur during commercialization

Premature commercialization risk

No great detail on commercialization proper since focus here is on pre-commercialization

Commercialization can be used in a variety of ways

  1. It is no longer a mere laboratory curiosity.
  2. It is finally ready for production deployment. Production-scale, production-capacity, production-reliability, production-quality practical real-world applications.

Unclear how much research must be completed before commercialization of quantum computing can begin

What fraction of research must be completed before commercialization of quantum computing?

Research will always be ongoing and never-ending

Simplified model of the main stages from pre-commercialization through commercialization

  1. Laboratory curiosity. Focus on research. Many questions and technological uncertainties to be resolved.
  2. The ENIAC moment. Finally achieve production-scale capabilities. But still for elite teams only.
  3. Initial Commercialization. An actual commercial product. No longer a mere laboratory curiosity.
  4. The FORTRAN moment. Beginning of widespread adoption. No longer only for elite teams.
  5. Mature commercialization. Widespread adoption. Methodical development and release of new features, new capabilities, and improvements in performance, capacity, and reliability.

The heavy lift milestones for commercializing quantum computing

  1. At least a few dramatic breakthroughs. Incremental advances will not be enough.
  2. Near-perfect qubits. Well beyond noisy. Four or five nines of fidelity.
  3. High intermediate-scale qubit capacity. 256 to 768 high-fidelity qubits.
  4. High qubit connectivity. If not full any to any, then at least enough that most algorithms won’t suffer. May (likely) require a more advanced quantum processor architecture.
  5. Extended qubit coherence and deeper quantum circuits. At least dozens, 100, 250, and preferably 1,000 gates.
  6. The ENIAC Moment. First credible application.
  7. Higher-level programming model and high-level programming language.
  8. Substantial libraries of high-level algorithmic building blocks.
  9. Substantial metaphors and design patterns.
  10. Substantial algorithm and application frameworks.
  11. Error correction and logical qubits.
  12. The FORTRAN Moment. Non-elite teams can develop quantum applications.
  13. First configurable packaged quantum solution.
  14. Significant number of configurable packaged quantum solutions.
  15. Quantum networking. Entangled quantum state between separate quantum computers.
  16. The BASIC Moment. Anybody can develop a practical quantum application.

Short list of the major stages in development and adoption of quantum computing as a new technology

  1. Initial conception.
  2. Theory fleshed out.
  3. Rudimentary lab experiments.
  4. First real working lab quantum computer.
  5. Initial experimentation.
  6. Incremental growth of initial capabilities coupled with incremental experimentation, rinse and repeat.
  7. First hints of usable technology coupled with experimental iteration.
  8. Strong suggestion that usability is imminent with ongoing experimental iteration.
  9. The ENIAC moment. Still just a laboratory curiosity. Still not quite ready for commercialization.
  10. Multiple ENIAC moments.
  11. Flesh out the technology.
  12. Enhance the usability of the technology with experimental iteration. Occasionally elite deployments.
  13. The FORTRAN moment. The technology is finally usable and ready for mass adoption.
  14. Widen applicability and adoption of the technology, iteratively. Production deployments are common.
  15. Successive generations of the technology. Broaden adoption. Develop standards.

More detailed list of stages in development of quantum computing as a product

  1. Initial, tentative research. Focusing on theory.
  2. More, deeper research. Focusing on laboratory experimentation.
  3. Even more research. Honing in on solutions and applications.
  4. Peer-reviewed publication.
  5. Trial and error.
  6. Simulation.
  7. Hardware innovation.
  8. Hardware evolution.
  9. Hardware maturity.
  10. Hardware validation for production use.
  11. Algorithm support innovation.
  12. Algorithm design theory innovation.
  13. Support software and tools conceptualization.
  14. Support software and tools development. Including testing.
  15. Technology familiarization.
  16. Documentation.
  17. Full technology training.
  18. Experimental algorithm design.
  19. Prototyping stage.
  20. Prototype applications.
  21. Production prototype algorithm design.
  22. Production algorithm design.
  23. QA methodology development.
  24. QA tooling prototyping.
  25. QA tooling production design.
  26. QA tooling production development.
  27. QA tooling production checkout and validation. Ready for use for validating production applications.
  28. Training curriculum. Syllabus.
  29. Marketing literature. White papers. Brochures. Demonstration videos. Podcasts.
  30. Standards development.
  31. Standards adoption.
  32. Standards adherence.
  33. Standards adherence validation.
  34. Regulatory approval.

Stage milestones towards quantum computing as a commercial product

  1. Trial and error.
  2. Initial milestone. Something that seems to function.
  3. Evolution. Increasing functions, features, capabilities, capacity, performance, and reliability.
  4. Further functional milestones. Incremental advances. Occasional leaps.
  5. Initial belief in usability. “It’s ready!” — we think.
  6. Feedback from initial trial use. “Okay, but…”
  7. Further improvements. “This should do it!”
  8. Rinse and repeat. Possibly 4–10 times — or more.
  9. Questions about usability. Belief that “Okay, it’s not really ready.”
  10. A couple more trials and refinements.
  11. General acceptance that now it actually does appear ready.
  12. General release.
  13. 2–10 updates and refinements. Fine tune.
  14. Finally it’s ready. General belief that the technology actually is ready for production-scale development and deployment.
  15. Sequence of stages for testing for deployment readiness.
  16. SLA development. Service level agreement. Actual commitment, with actual penalties.
  17. Initial production deployment.
  18. Some possible — likely- hiccups.
  19. Further refinements based on reality of real-world production deployment.
  20. Final refinement that leads to successful deployment.
  21. Rinse and repeat for further production deployments. Further refinements.
  22. Acceptance of success. General belief that a sufficient number of successful production deployments have been made that production deployment is a low-risk proposition.
  23. Rinse and repeat for several more production deployments.
  24. Minimal hiccups and refinements needed.
  25. We’re there. General conclusion that production deployment is a routine matter.

The benefits and risks of quantum error correction (QEC) and logical qubits

Three stages of deployment for quantum computing: The ENIAC Moment, configurable packaged quantum solutions, and The FORTRAN Moment

Highlights of pre-commercialization activities

  1. Deeper research. Both theoretical and deep pure research, as well as basic and applied research. Plodding along, incrementally and sometimes with big leaps, increasing qubit capacity, reducing error rates, and increasing coherence time to enable production-scale quantum algorithms.
  2. Support software and tools for researchers. For researchers, not to be confused with what a commercial product of customers and users will need.
  3. Support software and tools conceptualization. What might be needed in a commercial product for customers and users.
  4. Support software and tools development. Including testing.
  5. Initial development of quantum computer science. A new field.
  6. Initial development of quantum software engineering. A new field.
  7. Initial development of a quantum software development life cycle (QSDLC) methodology. Similar to SDLC for classical computing, but adapted for quantum computing.
  8. Initial effort at higher level and higher performance algorithmic building blocks.
  9. Initial efforts at algorithm and application libraries, metaphors, design patterns, and frameworks.
  10. Initial efforts at configurable packaged quantum solutions.
  11. Development of new and higher-level programming models.
  12. Development of high-level quantum programming languages.
  13. Develop larger capacity, higher performance, more accurate classical quantum simulators. Enable algorithm designers and application developers to test out ideas without access to quantum hardware, especially for quantum computers expected over the next few years.
  14. Need for very elite staff. Until the FORTRAN Moment is reached in a post-initial stage of commercialization.
  15. Need for detailed and accessible technical specifications. Even in pre-commercialization.
  16. Basic but reasonable quality documentation.
  17. Basic but reasonable quality tutorials. Freely accessible.
  18. Some degree of technical training. Freely accessible.
  19. Initial efforts at development of standards for QA, documentation, and benchmarking.
  20. Preliminary but serious effort at testing. QA, unit testing, subsystem testing, system testing, performance testing, and benchmarking.
  21. Need to reach the ENIAC Moment. Something closely resembling a real, production-scale application that solves a practical real-world problem. There’s no point commercializing if this has not been achieved.
  22. Focus on near-perfect qubits. Good enough for many applications.
  23. Research in quantum error correction (QEC). Still many technical uncertainties. Much research is required.
  24. Defer full implementation of quantum error correction until a subsequent commercialization stage. It’s still too hard and too demanding to expect in the initial commercialization stage.
  25. Focus on methodology and development of scalable algorithms. Minimal function on current NISQ hardware, but automatic expansion of scale as the hardware improves.
  26. Focus on preview products. Usable to some extent — by elite staff, for evaluation of the technology, but not to be confused with viable commercial products. Not for production use. No SLA.
  27. No SLA. Service level agreements — contractual commitments and penalties for function, availability, reliability, performance, and capacity. No commercial production deployment prior to initial commercialization stage anyway.
  28. Minimal hardware infrastructure and services buildout.
  29. Significant intellectual property creation. Hopefully mainly open source.
  30. Some degree of intellectual property protection. Hopefully minimal exclusionary patents.
  31. Some degree of intellectual property licensing.
  32. Possibly some intellectual property theft.
  33. Only minimal focus on maintainability. Generally, work produced during pre-commercialization will be rapidly superseded by revisions. The focus is on speed of getting research results and speed of evolution of existing work, not long-term product maintainability.
  34. End result of pre-commercialization: sufficient detail to produce detailed specifications for requirements, architecture, functions and features, and fairly detailed design to kick off commercialization.

Highlights of initial commercialization

  1. Formalize results from pre-commercialization into detailed specifications for requirements, architecture, functions and features, and fairly detailed design to kick off commercialization. Chartering of a product engineering team.
  2. Focus on a minimum viable product (MVP) for initial commercialization.
  3. Substantial quantum advantage. 1,000,000X performance advantage over classic solutions. Or, at least a significant fraction — well more than 1,000X. Preferably full dramatic quantum advantage — a one-quadrillion performance advantage. This can be clarified as pre-commercialization progresses. At this moment we have no visibility.
  4. Significant advances in qubit technology. Mix of incremental advances and occasional giant leaps, but sufficient to move well beyond noisy NISQ qubits to some level of near-perfect qubits, a minimum of four to five nines of qubit fidelity for two-qubit gates and measurement.
  5. Focus on near-perfect qubits. Good enough for many applications.
  6. Research in quantum error correction (QEC). Still many technical uncertainties. Much research is required.
  7. Defer full implementation of quantum error correction until a subsequent commercialization stage. It’s still too hard and too demanding to expect in the initial commercialization stage.
  8. Serious degree of support software and tools development. Including testing.
  9. Further development of quantum computer science.
  10. Further development of quantum software engineering.
  11. Further development of a quantum software development life cycle (QSDLC) methodology.
  12. Some degree of higher level and higher performance algorithmic building blocks.
  13. Some degree of algorithm and application libraries, metaphors, design patterns, and frameworks.
  14. Some degree of configurable packaged quantum solutions.
  15. Some degree of example algorithms and applications. That reflect practical, real-world applications. And clearly demonstrate quantum parallelism.
  16. Development of new and higher-level programming models.
  17. May or may not include the development of a high-level quantum programming language.
  18. Continue to expand larger capacity, higher performance, more accurate classical quantum simulators. Enable algorithm designers and application developers to test out ideas without access to quantum hardware, especially for quantum computers expected over the next few years.
  19. Focus on methodology and development of scalable algorithms. Minimal function on current limited hardware, but automatic expansion of scale as the hardware improves.
  20. Need for higher quality documentation.
  21. Need for great tutorials. Freely accessible.
  22. Serious need for technical training. But still focused primarily on elite technical staff at this stage.
  23. Serious efforts at development of standards for QA, documentation, and benchmarking.
  24. Robust efforts at testing. QA, unit testing, subsystem testing, system testing, performance testing, and benchmarking.
  25. SLA. Service level agreements — contractual commitments and penalties for function, availability, reliability, performance, and capacity. Essential for commercial production deployment.
  26. Minimal interoperability. More of an aspiration than a reality.
  27. Sufficient hardware infrastructure and services buildout. To meet initial expected demand. And some expectation for initial growth.
  28. Increased intellectual property issues.
  29. Increased focus on maintainability. Work during commercialization needs to be durable and flexible. Reasonable speed to evolve features and capabilities.

Post-commercialization — after the initial commercialization stage

Highlights for subsequent stages of commercial deployment, maybe up to ten of them

  1. Multiple ENIAC Moments.
  2. Multiple configurable packaged quantum solutions.
  3. Consortiums for configurable packaged quantum solutions.
  4. Ongoing focus on methodology and development of scalable algorithms. Limited function on current hardware, but automatic expansion of scale as the hardware improves.
  5. Dramatic quantum advantage. A one-quadrillion performance advantage over classical solutions. May take a few additional commercialization stages for the hardware to advance.
  6. Ongoing advances in qubit technology. Mix of incremental advances and occasional giant leaps.
  7. Maturation of support software and tools development. Including testing.
  8. Maturation of quantum computer science.
  9. Maturation of quantum software engineering.
  10. Maturation of a quantum software development life cycle (QSDLC) methodology.
  11. Extensive higher level and higher performance algorithmic building blocks.
  12. Extensive algorithm and application libraries, metaphors, design patterns, and frameworks.
  13. Extensive configurable packaged quantum solutions. Very common. The common quantum application deployment for most organizations.
  14. Excellent collection of example algorithms and applications. That reflect practical, real-world applications. And clearly demonstrate quantum parallelism.
  15. Full exploitation of new and higher-level programming models.
  16. Development of high-level quantum programming languages.
  17. Full quantum error correction (QEC) and perfect logical qubits. Will take a few stages beyond the initial commercialization.
  18. The FORTRAN Moment is reached. Widespread adoption is now possible.
  19. Training of non-elite staff for widespread adoption. Gradually expand from elite-only technical staff during the initial stage to non-elite technical staff as the product gets easier to use with higher-level algorithmic building blocks and higher-level programming models and languages.
  20. Increasing interoperability.
  21. Dramatic hardware infrastructure and services buildout. To meet demand. And anticipate growth.
  22. Increased intellectual property issues.
  23. The BASIC Moment is reached. Anyone can develop a practical quantum application.
  24. Quantum networking.
  25. Quantum artificial intelligence.
  26. Universal quantum computer. Merging full classical computing features.

Prototyping and experimentation — hardware and software, firmware and algorithms, and applications

  1. Hardware.
  2. Firmware.
  3. Software.
  4. Algorithms.
  5. Applications.
  6. Test data.

Pilot projects — prototypes

Proof of concept projects (POC) — prototypes

Rely primarily on simulation for most prototyping and experimentation

Primary testing of hardware should focus on functional testing, stress testing, and benchmarking — not prototyping and experimentation

Prototyping and experimentation should initially focus on simulation of hardware expected in commercialization

Late in pre-commercialization, prototyping and experimentation can focus on actual hardware — once it meets specs for commercialization

Prototyping and experimentation on actual hardware earlier in pre-commercialization is problematic and an unproductive distraction

Products, services, and releases — for both hardware and software

Products which enable quantum computing vs. products which are enabled by quantum computing

  1. Quantum-enabled products. Products which are enabled by quantum computing. Such as quantum algorithms, quantum applications, and quantum computers themselves.
  2. Quantum-enabling products. Products which enable quantum computing. Such as software tools, compilers, classical quantum simulators, and support software. They run on classical computers and can be run even if quantum computing hardware is not available. Also includes classical hardware components and systems, as well as laboratory equipment.

Potential for commercial viability of quantum-enabling products during pre-commercialization

  1. Quantum software tools.
  2. Compilers and translators.
  3. Algorithm analysis tools.
  4. Support software.
  5. Classical quantum simulators.
  6. Hardware components used to build quantum computers.

Preliminary quantum-enabled products during pre-commercialization

How much of research results can be used intact vs. need to be discarded and re-focused and re-implemented with a product engineering focus?

  1. Features.
  2. Functions.
  3. Capabilities.
  4. Performance.
  5. Capacity.
  6. Reliability.
  7. Error handling.
  8. QA testing.
  9. Ease of use.
  10. Maintainability.
  11. Interoperability.

Hardware vs. cloud service

Prototyping and experimentation — applied research vs. pre-commercialization

Prototyping products and experimenting with applications

  1. Products are prototyped.
  2. Applications are experimented with.

Prototyping and experimentation as an extension of research

Trial and error vs. methodical process for prototyping and experimentation

Alternative meanings of pre-commercialization

  1. Research alone. Anything after research is commercialization.
  2. Final stage just before commercialization, culminates in commercialization. Product engineering and development complete. Internal testing complete. Documentation complete. Training development complete. Ready for alpha and beta testing.
  3. Everything before production product engineering. Preliminary lab research — demonstrate basic capability. Full-scale research. Prototype products, evolution. Development of product requirements. Final prototype product. Essentially what I settled on — research and prototyping and experimentation, with the intention of answering all the critical technical questions, ready to hand off to the product engineering team.
  4. Everything before a preliminary vision of what a production product would look like. Lab experimentation. Iterative research, searching for the right technology capable of satisfying production needs. Iterative development of production requirements. Finally have a sense of what a functional production product would look like — and how to get there within a relatively small number of years. Iterate until final production requirement specification ready — and the research to support it.
  5. Everything after all research for the initial production product is complete. Sense that no further research is needed for initial production product release
  6. Everything after The ENIAC Moment. But then what nomenclature should be used for the stages before the ENIAC moment?
  7. Everything until The ENIAC Moment is behind us. A good runner-up candidate for pre-commercialization.

Requirements for commercialization

  1. Research must be complete. Not necessarily all research for all of time, but sufficient research to design and build the initial product and a few stages after that. Enough research to eliminate all major scientific and technological uncertainties for the next few stages of a product or product line.
  2. Vague or rough product ideas must be clarified or rejected. A clear vision of the product is needed.
  3. A product plan must be developed. What must the product do and how will it do it?
  4. Budgeting and pricing. How much will it cost to design and develop the product? How large a team will be required, for how long, and how much will they be paid? How much equipment and space will be needed and how much will it cost? How much will it cost to build each unit of the product? How much will the product be sold for? How much will it cost to support, maintain, and service the product? How much of that cost can be recouped from recurring revenue as opposed to factoring it into the unit pricing?

Production-scale vs. production-capacity vs. production-quality vs. production-reliability

  1. Production-scale. Capable of addressing large-scale practical real-world problems. The combination of input capacity, processing capacity, and output capacity.
  2. Production-capacity. Focusing specifically on the size of data to be handled.
  3. Production-quality. All of the functions and features required for addressing real-world problems — and it all works flawlessly, with no bugs, and resilience — handling a wide range of anomalous situations.
  4. Production-reliability. Focus on flawless and resilient operation.

Commercialization of research

  1. Pure academic research. Capitalizing on the results of academic research and recouping research expenses. Generally focused on licensing of intellectual property.
  2. Pure corporate research. Refocusing pure research results on practical customer problems.

Stages for uptake of new technology

  1. Awareness. Letting people know that it exists.
  2. Basic conceptual understanding.
  3. Learning the technology details. Including formal training.
  4. Prototyping and experimentation.
  5. Evaluation of initial efforts.
  6. Planning for development projects.
  7. Architect for production design.
  8. Production design.
  9. Production development and implementation.
  10. Production QA testing.
  11. Production testing.
  12. Production stress testing, load testing.
  13. Production testing validation.
  14. Production deployment.
  15. Production operation.
  16. Monitoring.
  17. Updates to the technology. Including big fixes, security vulnerabilities, performance and capacity improvements, and functional enhancements.

Is quantum computing still a mere laboratory curiosity? Yes!

  • A laboratory curiosity is a scientific discovery or engineering creation which has not yet found practical application in the real world.

When will quantum computing cease being a mere laboratory curiosity? Unknown. Not soon.

By definition quantum computing will no longer be a mere laboratory curiosity as soon as it has achieved initial commercialization

Could quantum computing be considered no longer a mere laboratory curiosity as soon as pre-commercialization is complete? Possibly.

Could quantum computing be considered no longer a mere laboratory curiosity as soon as commercialization is begun? Plausibly.

Quantum computing will clearly no longer be a mere laboratory curiosity once initial commercialization stage 1.0 has been achieved

Four overall stages of research

  1. Basic and deep research needed before commercialization can even be considered.
  2. Cumulative research needed for the initial commercialization.
  3. Incremental research needed for the next few stages of commercialization.
  4. Longer term research needed for commercialization five to ten years or more in the future.

Next steps — research

  1. Substantial research on all fronts.
  2. Incremental improvements on all fronts.
  3. Dramatic advances on all fronts.

What is product development or productization?

  1. Requirements. What functions and capabilities are required? What problems or applications does the product address? What are the performance and capacity requirements?
  2. Functional specifications. What are the details of those functions?
  3. Architectural design. How will the overall product be structured — its architecture and major components or subsystems.
  4. Detailed design. All details from the overall architecture, major subsystems, minor subsystems, and decomposed down to the smallest components.
  5. Development of all levels of the product. Electrical and mechanical engineering. Software engineering. Coding.
  6. Documentation. All details that anyone with an interest in the product will or might need to know.
  7. Testing. Development of a testing plan. Development of testing infrastructure. Development of individual tests. Test automation. Test result evaluation. Unit testing, subsystem testing, system testing, performance testing, stress testing.
  8. Packaging. Putting the product in a form that is ready to be delivered to customers and ready for users.
  9. Benchmarking. Testing to compare the performance and capacity of the product to other products in the same market or existing solutions to the same problems that the new product addresses.
  10. Regulatory requirements. Address government regulations or licensing requirements.
  11. Release engineering. Getting ready for shipment to customers, distribution, installation, shakedown testing, and deployment.

Technical specifications

  1. Requirements. What the product or technology must, must not, should, and should not do.
  2. Architecture. Overall structure of the system. The major subsystems and how they interact.
  3. Design. How each subsystem or component works.
  4. Functional. What functions the product performs, that are visible to users.
  5. Implementation details. All fine technical details that may be needed to understand how the system operates. Including numerical parameters and expected performance data.

Product release

  1. Turn the product designs over to manufacturing. Ready to replicate the design.
  2. Marketing of the product. Promotion. Building awareness of the product.
  3. Sales. Selling the product.
  4. Distribution. Actual delivery of the product to customers and users.
  5. Support. Assisting customers and users with issues related to use of the product.
  1. Plan for deployment.
  2. Acquire the necessary infrastructure for deployment.
  3. Plan all details of deployment. Including operational details. And cybersecurity plans.
  4. Deployment.
  5. Deployment testing. Confirm that the service performs as expected. Including stress testing and load testing.
  6. Advance marketing of the service. Awareness of the service before it becomes available.
  7. Advance sales of the service.
  8. Service rollout. Make the service available to customers.
  9. Ongoing marketing of the service. Ongoing building of awareness.
  10. Ongoing sales of the service.
  11. Monitoring. Detect and address anomalies. Cybersecurity monitoring. Load balancing. Reporting, such as utilization. Analytics.
  12. Support. Addressing all customer and user issues.
  13. Upgrades. Update software and occasionally hardware.

When can pre-commercialization begin? Now! We’re doing it now.

When can commercialization begin? That’s a very different question! Not soon.

Continually update vision of what quantum computing will look like

Need to utilize off the shelf technology

It takes significant time to commercialize research results

The goal is to turn raw research results into off the shelf technology which can then be used in commercial products

Will there be a quantum winter? Or even more than one?

  1. Sufficient qubit fidelity to support efficient quantum error correction (QEC).
  2. Achieving quantum error correction efficiently and accurately — even for a relatively small number of qubits.
  3. Achieving enough physical qubits to achieve a sufficient capacity of logical qubits through quantum error correction.
  4. Achieving sufficiently fine granularity of quantum phase and probability amplitude to enable quantum Fourier transform (QFT) and quantum phase estimation (QPE) for a reasonably large number of qubits sufficient to enable quantum computational chemistry.
  5. Conceptualizing — and developing — a diverse and robust library of algorithmic building blocks sufficient to enable complex quantum algorithms and applications.
  6. Achieving The ENIAC Moment for even a single production-scale application.
  7. Achieving The ENIAC Moment for multiple production-scale applications.
  8. Conceptualizing — and developing — sufficiently high-level programming models to make quantum algorithm design practical for non-elite teams.
  9. Conceptualizing — and developing — high-level quantum-native programming languages to support the high-level programming models using high-level algorithmic building blocks to make it easier for non-elite teams to design algorithms and develop production-scale quantum applications.
  10. Achieving The FORTRAN Moment for a single production-scale application.
  11. Achieving The FORTRAN Moment for multiple production-scale applications.
  12. Opening the floodgates for exploiting The FORTRAN Moment for widespread production-scale applications.

But occasional Quantum Springs and Quantum Summers

Quantum Falls?

In truth, it will be a very long and very slow slog

No predicting the precise flow of progress, with advances and setbacks

Sorry, but there won’t be any precise roadmap to commercialization of quantum computing

Existing roadmaps leave a lot to be desired, and prove that we’re in pre-commercialization

No need to boil the ocean — progression of commercial stages

The transition from pre-commercialization to commercialization: producing detailed specifications for requirements, architecture, functions and features, and fairly detailed design

Critical technical gating factors for initial stage of commercialization

  1. Near-perfect qubits. At least four nines of qubit fidelity — 99.99%. Possibly five nines — 99.999%.
  2. Circuit depth. Generally limited by coherence time. No clear threshold at this stage but definitely going to be a critical gating factor. Whether it is 50, 100, 500, or 1,000 is unclear. Significantly more than it is now.
  3. Qubit coherence time. Sufficient to support needed circuit depth.
  4. Near-full qubit connectivity. Either full any to any qubit connectivity or higher qubit fidelity to permit SWAP networks to simulate near-full connectivity.
  5. 64 qubits. Roughly. No precise threshold. Maybe 48 qubits would be enough, or maybe 72 or 80 qubits might be more appropriate. Granted, I think people would prefer to see 128 to 256 qubits, but 64 to 80 might be sufficient for the initial commercialization stage.
  6. Alternative architectures may be required. Especially for more than 64 qubits. Or even for 64, 60, 56, 50, and 48 qubits in order to deal with limited qubit connectivity.
  7. Fine phase granularity to support quantum Fourier transform (QFT) and quantum phase estimation (QPE). At least 20 or 30 qubits = 2²⁰ to 2³⁰ gradations — one million to one billion gradations. Even 20 qubits may be a hard goal to achieve.
  8. Quantum Fourier transform (QFT) and quantum phase estimation (QPE). Needed for quantum computational chemistry and other applications. Needed to achieve quantum advantage through quantum parallelism. Relies on fine granularity of phase.
  9. Conceptualization and methods for calculating shot count (circuit repetitions) for quantum circuits. This will involve technical estimation based on quantum computer science coupled with engineering process based on quantum software engineering. See my paper below.
  10. Moderate improvements to the programming model. Unlikely that a full higher-level programming model will be available soon (before The FORTRAN Moment), but some improvements might be possible.
  11. Moderate library of high-level algorithmic building blocks.
  12. The ENIAC Moment. A proof that something realistic is possible.
  13. Substantial quantum advantage. Full, dramatic quantum advantage is not so likely, but an advantage of at least a million or a billion is a reasonable expectation — much less will be seen as not really worth the trouble. This will correspond to roughly 20 to 30 qubits in a single Hadamard transform — 2²⁰ = one million, 2³⁰ = one billion. An advantage of one trillion — 2⁴⁰ may or may not be reachable by the initial stage of commercialization. Worst case, maybe minimal quantum advantage — 1,000X to 50,000X — might be acceptable for the initial stage of commercialization.
  14. 40-qubit quantum algorithms. Quantum algorithms utilizing 32 to 48 qubits should be common. Both the algorithms and hardware supporting those algorithms. 48 to 72-qubit algorithms may be possible, or not — they may require significantly greater qubit fidelity.
  15. Classical quantum simulators for 48-qubit algorithms. The more the better, but that may be the practical limit in the near term. We should push the researchers for 50 to 52 or even 54 qubits of full simulation.
  16. Overall the technology is ready for production deployment.
  17. No further significant research is needed to support the initial commercialization product. Further research for subsequent commercialization stages, but not for the initial commercialization stage. The point is that research belongs in the pre-commercialization stage.

Quantum advantage is the single greatest technical gating factor for commercialization

Variational methods are a short-term crutch, a distraction, and an absolute dead-end

  1. Low qubit fidelity.
  2. Lack of fine granularity of phase.
  3. Low gate fidelity.
  4. Limited circuit depth.
  5. Low measurement fidelity.

Exploit quantum Fourier transform (QFT) and quantum phase estimation (QPE) on simulators during pre-commercialization

Final steps before a product can be released for commercial production deployment

  1. Packaging as a deployable product.
  2. Service level agreement (SLA). Contractual commitment, with penalties.
  3. Cybersecurity.
  4. Scheduling tasks for execution.
  5. Load balancing.
  6. Monitoring quantum cloud.
  7. Automated software and firmware updates.

No further significant research can be required to support the initial commercialization product

Commercialization requires that the technology be ready for production deployment

Non-technical gating factors for commercialization

  1. Development of quantum computer science as a new field of study.
  2. Development of quantum software engineering as a new field of study.
  3. Development of a quantum software development life cycle (QSDLC) methodology.
  4. Development of a quantum technical talent pool.
  5. Development of a quantum ecosystem.

Quantum computer science

Quantum software engineering

No point to commercializing until substantial fractional quantum advantage is reached

  1. 10,000X — 1%
  2. 100,000X — 10%
  3. 250,000X — 25%
  4. 500,000X — 50%
  5. 750,000X — 75%

Fractional quantum advantage progress to commercialization

  1. 10,000X — 1%
  2. 100,000X — 10%
  3. 250,000X — 25%
  4. 500,000X — 50%
  5. 750,000X — 75%
  6. 1,000,000X — 100%
  1. 100,000X — 10%
  2. 500,000X — 50%
  3. 750,000X — 75%
  4. 1,000,000X — 100%
  5. 10,000,000X — 1,000X
  6. 100,000,000X — 10,000X
  7. 1,000,000,000X — 10,000X

Qubit capacity progression to commercialization

  1. 48 qubits. A bare minimum.
  2. 50 qubits.
  3. 54 qubits.
  4. 56 qubits.
  5. 60 qubits.
  6. 64 qubits. A fairly reasonable start.
  7. 72 qubits. A more reasonable start..
  8. 80 qubits. A good start.
  9. 96 qubits. A fairly strong start.
  10. 128 qubits. A strong start.
  11. 256 qubits. A clear sweet spot. A very strong start.

Maximum circuit depth progression to commercialization

  1. 25 gates. Absolute worst case minimum for product.
  2. 50 gates.
  3. 75 gates.
  4. 100 gates. A reasonable expectation for the initial product.
  5. 250 gates. Plausible for the initial product.
  6. 500 gates.
  7. 1,000 gates. May be a decent goal for the initial product.
  8. 2,500 gates.
  9. 5,000 gates.
  10. 7,500 gates.
  11. 10,000 gates.
  1. 100 gates.
  2. 250 gates.
  3. 500 gates.
  4. 1,000 gates. Hopefully within a few releases after initial commercialization.
  5. 2,500 gates.
  6. 5,000 gates.
  7. 10,000 gates.
  8. 25,000 gates.
  9. 50,000 gates.
  10. 75,000 gates.
  11. 100,000 gates.
  12. 250,000 gates.
  13. 500,000 gates.
  14. 750,000 gates.
  15. 1,000,000 gates.
  16. 10,000,000 gates.
  17. 100,000,000 gates.

Alternative hardware architectures may be needed for more than 64 qubits

Qubit technology evolution over the course of pre-commercialization, commercialization, and post-commercialization

Initial commercialization stage 1 — C1.0

The main criterion for initial commercialization is substantial quantum advantage for a realistic application, AKA The ENIAC Moment

  1. A production-scale practical real-world application.
  2. Substantial quantum advantage has been achieved. A quantum advantage of roughly 1,000,000X a classical computing solution.

Differences between validation, testing, and evaluation for pre-commercialization vs. commercialization

  1. During pre-commercialization. The goal is to evaluate raw technology components for suitability for use in a product. May or may not involve getting feedback from potential customers and users.
  2. During commercialization. The goal is to evaluate the packaged product for suitability for use in customer applications.

Validation, testing, and evaluation during pre-commercialization

  1. Some degree of quality assurance (QA) testing. Including unit testing, subsystem testing, system testing, and interoperability testing.
  2. Significant degree of documentation development. How to properly use the product. How to troubleshoot problems.
  3. Periodic preview releases. The evolving product ideas are treated as if a product — a preview product, packaged and distributed or otherwise made available to organizations and users, as if they were customers. The notions of alpha, beta, and pre-releases are not so relevant.

Validation, testing, and evaluation for initial commercialization stage 1.0

  1. Extensive quality assurance (QA) testing. Including unit testing, subsystem testing, system testing, and interoperability testing.
  2. Extended design and code reviews. Both hardware and software. Look very carefully for any hidden flaws rather than wait for them to be reported as “bugs.”
  3. Documentation development and review. How to properly use the product. How to troubleshoot problems.
  4. Extended sequence of alpha, beta, and pre-releases. To enable evaluation by real potential customers and users and to get their feedback. May require incremental improvements to the product.
  5. Culminates (or at least climaxes) with the arrival of The ENIAC Moment. Finally a real customer can achieve a production-scale practical real-world application.
  6. Benchmarking. Determine and document how the hardware, algorithms, and key applications really perform.

Initial commercialization stage 1.0 — The ENIAC Moment has arrived

  1. Elite teams.
  2. A lot of hard work.
  3. Significant hardware advances.
  4. Significant research.

Initial commercialization stage 1.0 — Routinely achieving substantial quantum advantage

Initial commercialization stage 1.0 — Achieving substantial quantum advantage every month or two

Okay, maybe a nontrivial fraction of minimal quantum advantage might be acceptable for the initial stage of commercialization

Minimum Viable Product (MVP)

  1. Less than four nines of qubit fidelity. Such as 3, 3.25, 3.5, or 3.75 nines. Three nines might be reasonable in conjunction with full connectivity so that SWAP networks are not needed.
  2. More-limited qubit connectivity. Not full connectivity. But possibly with greater qubit fidelity to support longer SWAP networks.
  3. Fewer qubits. Maybe 48 or even only 44 or 40. Less than 40 is rather unlikely. Possibly in conjunction with great qubit fidelity.
  4. Limited granularity of phase and probability amplitude. May not support larger applications in terms of how many qubits can participate in a quantum Fourier transform (QFT) or quantum phase estimation (QPE). But still needs to support some significant granularity, enough to enable key applications such as quantum computational chemistry.
  5. Smaller fractional quantum advantage. Significantly less than full significant quantum advantage (1,000,000X), such as 10,000X to 100,000X.
  1. Quantum error correction (QEC) and logical qubits. Too much of a stretch. Focus on near-perfect qubits.
  2. The FORTRAN Moment. Requires QEC. Essential for widespread adoption, but not for initial adoption.

Automatically scalable quantum algorithms

Configurable packaged quantum solutions

Shouldn’t quantum error correction (QEC), logical qubits, and The FORTRAN Moment be required for the initial commercialization stage? Yes, but not feasible.

Should a higher-level programming model be required for the initial commercialization stage? Probably, but that is probably too much to ask for.

Not everyone will trust a version 1.0 of any product anyway

General release

Criteria for evaluating the success of initial commercialization stage 1.0

  • A substantial number of organizations are able to proceed with design, development, and deployment of production-scale practical real-world quantum applications that will fulfill the grand promise of quantum computing — quantum advantage.

Quantum ecosystem

  1. Hardware vendors.
  2. Software vendors. Tools and support software
  3. Consulting firms.
  4. Algorithms.
  5. Applications.
  6. Open source whenever possible. Algorithms, applications and tools. Hardware and firmware as well. Freely accessible plans so that anyone could build a quantum computer. Libraries, metaphors, design patterns, application frameworks, and configurable packaged quantum solutions. Training materials. Tutorials. Examples. All open source.
  7. Community. Including online discussion and networking. Meetups, both in-person and virtual.
  8. Analysts. Technical research as well as financial markets.
  9. Journalists. Technical and mainstream media.
  10. Publications. Academic journals, magazines, books. Videos and podcasts.
  11. Conferences. Presentation of papers, tutorials, and trade show exhibits. Personal professional networking opportunities.
  12. Vendors. Hardware, software, services, algorithms, applications, solutions, consulting, training, conferences.

Subsequent commercialization stages — Beyond the initial ENIAC Moment

  1. C1.0 — Reached The ENIAC Moment. All of the pieces are in place.
  2. C1.5 — Reached multiple ENIAC Moments.
  3. C2.0 — First configurable packaged quantum solution.
  4. C2.5 — Reached multiple configurable packaged quantum solutions. And maybe or hopefully finally achieve full, dramatic quantum advantage somewhere along the way as well.
  5. C3.0 — Quantum Error Correction (QEC) and logical qubits. Very small number of logical qubits.
  6. C3.5 — Incremental improvements to QEC and increases in logical qubit capacity.
  7. C4.0 — Reached The FORTRAN Moment. And maybe full, dramatic quantum advantage as well.
  8. C4.5 — Widespread custom applications based on QEC, logical qubits, and FORTRAN Moment programming model. Presumption that full, dramatic quantum advantage is the norm by this stage.
  9. C5.0 — The BASIC Moment. Much easier to develop more modest applications. Anyone can develop a quantum application achieving dramatic quantum advantage.
  10. C5.5 — Ubiquitous quantum computing ala personal computing.
  11. C6.0 — More general AI, although not full AGI.
  12. C7.0 — Quantum networking. Networked quantum state.
  13. C8.0 — Integration of quantum sensing and quantum imaging with quantum computing. Real-time quantum image processing.
  14. C9.0 — Incremental advances along the path to a mature technology.
  15. C10.0 — Universal quantum computer. Merging full classical computing.

Post-commercialization efforts

  1. Maturity of quantum error correction and logical qubits. Initial support likely will be for a fairly low capacity of logical qubits.
  2. Finer granularity for phase to support larger quantum Fourier transform (QFT) and quantum phase estimation (QPE). 30 to 50 qubits, and beyond. 30 qubits = 2³⁰ = one billion quantum states, 40 qubits = 2⁴⁰ = one trillion quantum states, 40 qubits = 2⁵⁰ = one quadrillion quantum states. Eventually enable achievement of full, dramatic quantum advantage.
  3. Higher-level programming model(s).
  4. High-level algorithmic building blocks.
  5. Conceptualization and development for The FORTRAN Moment. Complex applications can be developed by non-elite teams.
  6. Conceptualization and development of problem statement languages. Shorthand notations for declaring the needs of the application problem which can then be fully and automatically be transformed into quantum algorithms and applications.
  7. Conceptualization and development for The BASIC Moment. Much easier simple applications. Anyone can develop quantum applications which achieve dramatic quantum advantage.
  8. Alternative qubit technologies.
  9. Alternative hardware architectures may be required. Especially for more than 64 qubits. Or even for 64, 60, 56, 50, and 48 qubits in order to deal with limited qubit connectivity. But 128, 256, 1K, and more qubits are likely to require innovative hardware architectures.
  10. Advances in quantum parallelism and quantum advantage. Initial commercialization, such as The ENIAC Moment may not achieve full, dramatic quantum advantage. Increasing fractional quantum advantage as qubit fidelity and phase granularity increase.
  11. Achieve full, dramatic quantum advantage. A one quadrillion advantage.
  12. Wider range of configurable packaged quantum solutions.
  13. Integration of quantum sensing and quantum imaging with quantum computing. Real-time quantum image processing.
  14. Quantum multiprocessing. Multiple quantum processors in the same quantum computer system. Coordinated operation.
  15. Quantum networking. Networked quantum state. At any distance.
  16. Full artificial general intelligence (AGI). Far beyond current state of the art AI.
  17. Room temperature quantum computing.
  18. Photonic quantum computing.
  19. Quantum minicomputers. May have less performance and less capacity, but cheaper, smaller, and more accessible.
  20. Universal quantum computer. Merging full classical computing.

Milestones in fine phase granularity to support quantum Fourier transform (QFT) and quantum phase estimation (QPE)

  1. 8 bits. Too limited to be of much practical value, but a technical milestone.
  2. 12 bits. Even this is too much, at present.
  3. 16 bits.
  4. 20 bits. This would be a significant technical achievement.
  5. 24 bits.
  6. 28 bits.
  7. 32 bits.
  8. 36 bits.
  9. 40 bits. Current limit of what can be simulated on a classical computer.
  10. 44 bits.
  11. 48 bits.
  12. 56 bits. Possibly the upper limit of what could be simulated on a classical computer.
  13. 64 bits.
  14. 72 bits.
  15. 80 bits.
  16. 96 bits.
  17. 128 bits.
  18. 160 bits.
  19. 256 bits.
  20. 512 bits.
  21. 1K bits.
  22. 2K bits.
  23. 4K bits
  24. 8K bits. Sufficient for using Shor’s factoring algorithm to factor a 4K-bit public encryption key.
  1. 28 bits. Really the minimum we should accept.
  2. 32 bits.
  3. 36 bits.
  4. 40 bits. Current limit of what can be simulated on a classical computer.
  5. 44 bits. A good goal to pursue. If not in C1.0, then relatively soon thereafter.
  6. 48 bits.
  7. 56 bits. Possibly the upper limit of what could be simulated on a classical computer.
  8. 64 bits.
  9. 72 bits.
  10. 80 bits.
  11. 96 bits.
  1. 64 bits.
  2. 72 bits.
  3. 80 bits.
  4. 96 bits.
  5. 128 bits.
  6. 160 bits.
  7. 256 bits.
  8. 512 bits.

Milestones in quantum parallelism and quantum advantage

  1. 10 qubits = 2¹⁰ quantum states — advantage of one thousand.
  2. 16 qubits = 2¹⁶ quantum states — advantage of 64K.
  3. 20 qubits = 2²⁰ quantum states — advantage of one million.
  4. 24 qubits = 2²⁴ quantum states.
  5. 28 qubits = 2²⁸ quantum states.
  6. 30 qubits = 2³⁰ quantum states — advantage of one billion.
  7. 32 qubits = 2³² quantum states.
  8. 36 qubits = 2³⁶ quantum states.
  9. 40 qubits = 2⁴⁰ quantum states — advantage of one trillion.
  10. 44 qubits = 2⁴⁴ quantum states.
  11. 48 qubits = 2⁴⁸ quantum states.
  12. 50 qubits = 2⁵⁰ quantum states — advantage of one quadrillion. Dramatic quantum advantage.
  13. 56 qubits = 2⁵⁶ quantum states.
  14. 64 qubits = 2⁶⁴ quantum states.
  15. 72 qubits = 2⁷² quantum states.
  16. 80 qubits = 2⁸⁰ quantum states.
  17. 96 qubits = 2⁹⁶ quantum states.
  18. 128 qubits = 2¹²⁸ quantum states.

When might commercialization of quantum computing occur?

  1. Within 2 years? No, no chance.
  2. 3 years? Unlikely.
  3. 4 years? Slim to modest possibility. Flip a coin.
  4. 5 years? Moderately likely. But not a slam dunk.
  5. 6 years? Fair bet.
  6. 7 years? Fairly solid chance.

Slow, medium, and fast paths to pre-commercialization and initial commercialization

  • Pre-commercialization. Minimal: 2 years. Nominal: 4 years. Maximal: 10 years.
  • Commercialization. Minimal: 2 years. Nominal: 3 years. Maximal: 5 years.
  • Total. Minimal: 4 years. Nominal: 7 years. Maximal: 15 years.

How long might pre-commercialization take?

  1. As long as it takes. Estimates are all problematic. Anybody’s guess.
  2. Minimum of 2 years. If all goes well — actually if all goes perfectly.
  3. Nominally 4 years. Assuming no major obstacles. Add a year to cover a few contingencies.
  4. Worst case 10 years. Okay, it could be even worse than that or never happen.

What stage are we at right now? Still early pre-commercialization.

When might pre-releases and preview releases become available?

Dependencies

  1. Internal dependencies. Within a single product or technology. Subsystems, modules, and components within a system, for example.
  2. External dependencies. Between products or technologies. Software depending on hardware, or algorithms dependent on software or tools, for example.
  1. Within pre-commercialization. Sequencing and timing of activities within per-commercialization.
  2. Between commercialization and pre-commercialization. Pre-commercialization activities which must be completed before commercialization can commence.
  3. Within commercialization. Sequencing and timing of activities within commercialization.

Some products which enable pre-commercialization may not be relevant to commercialization

Risky bets: Some great ideas during pre-commercialization may not survive in commercialization

A chance that all work products from pre-commercialization may have to be discarded to transition to commercialization

Analogy to transition from ABC, ENIAC, and EDVAC research computers to UNIVAC I and IBM 701 and 650 commercial systems

  1. Incremental technology improvements.
  2. Architectural innovations.
  3. Accumulation of experience actually using the computers for practical applications.
  4. Focus on the needs of real customers.

Concern about overreach and overdesign — Multics vs. UNIX, OS/2 vs. Windows, IBM System/38, Intel 432, IBM RT PC ROMP vs. PowerPC, Trilogy

  1. Multics. A magnificent research project, which actually resulted in a commercial product (for Honeywell), but with only limited commercial success. Much greater success has occurred for UNIX, which was based on Multics, but dramatically simplified to make it more viable on a wider range of commercial hardware platforms.
  2. OS/2. A grand effort to supersede Windows, which did become a commercial product, but with only limited success. Windows itself continued to evolve and grow and achieved even greater success. Windows NT was a whole new operating system, with arguably even greater features and capabilities than OS/2, but focused on both addressing a commercial customer base as well as growing the original Windows user base. Just a few years of advances in microprocessor performance and memory capacity made a huge difference.
  3. IBM System/38. A dramatic technical advance with 48-bit addressing and integrated database, but far beyond the needs of the targeted customer base. This technological and business misstep provided an opening for competitors to steal IBM customers.
  4. Intel 432. Another dramatic technical advance, with a novel processor directly supporting high-level programming languages,and the Ada programming language in particular. Technical overreach (overdesign). A complete flop but a lot of great ideas. In contrast, the Intel 386 and 486 rapidly took off.
  5. IBM RT PC ROMP. Another dramatic technical advance, Reduced Instruction Set Computer (RISC), which failed miserably, both technically and commercially. Succeeded by the PowerPC architecture, which was very successful for some time, especially for Apple. The latter was actually more sophisticated in addition to being more successful, but wouldn’t have been feasible at the time of the RT/ROMP. The Intel 386 also capitalized on the weak performance of ROMP, even though being technically less sophisticated.
  6. Trilogy. Legendary mainframe pioneer Gene Amdahl, who worked on the IBM 704, IBM 709, Stretch (became IBM 7030), was chief architect of the IBM System/360, and founder of mainframe pioneer Amdahl Corporation, started a new mainframe company, Trilogy Systems, intent on using wafer scale integration to put an entire mainframe CPU on a chip — using virtually the whole wafer for a single chip (in 1980). Alas, the project failed miserably. Ironically, the CPU chip of average desktops, servers, laptops, tablets and even smartphones today are far more complex but much smaller, cheaper, faster, and with far greater capacity. Timing is everything. Their timing sucked. A great example of overreach. Although the ideas were fantastic and logically sound, other than a number of nasty implementation details.

Full treatment of commercialization — a separate paper, eventually

Beware betaware

Vaporware — don’t believe it until you see it yourself

Commercial grade and industrial grade quality of products

  1. Commercial grade. Generally means good enough for most customers and users. Generally free of bugs and other defects, and generally high quality. Customers and users are generally happy with what they get.
  2. Industrial grade. Goes well beyond commercial grade. Designed to work in extreme environments and under extreme stress, where any bugs or defects could cause disastrous consequences. May not be needed in most commercial settings, but required whenever human life or limb or mission-critical business processes or financial transactions or personal privacy or national security are at stake. Think rockets, satellites, missiles, implanted medical devices, and Wall Street and the Federal Reserve.

Pre-commercialization is about constant change while commercialization is about stability and carefully controlled and compatible evolution

Customers and users prefer carefully designed products, not cobbled prototypes

Customers and users will seek the stability of methodical commercialization, not the chaos of pre-commercialization

Need for larger capacity, higher performance, more accurate classical quantum simulators

Hardware infrastructure and services buildout

Hardware infrastructure and services buildout is not an issue, priority, or worry yet since the focus is on research

Factors driving hardware infrastructure and services buildout

  1. Count of customers.
  2. Count of quantum applications at each customer.
  3. Frequency and duration of execution of each application.
  4. Count of quantum algorithms used by each application.
  5. Count of invocations of each quantum algorithm (circuit.)
  6. Count of circuit repetitions (shots) for each quantum algorithm invocation.
  7. Count of gates in each quantum circuit. Both total gate count and maximum depth.
  8. Rate of growth expected. In all of the above factors. Annual or otherwise.
  9. Redundancy to account for geographic redundancy, hardware failures, maintenance, peaks periods, and service level agreements (SLA).
  10. Service level agreements (SLA). Additional redundancy required. Guaranteed availability and response time.
  11. Monitoring and management.
  12. Cybersecurity. Monitoring, threat detection, mitigation.
  1. Average over time.
  2. High and low seasonal rates.
  3. Day of week usage patterns.
  4. Holiday usage patterns.
  5. Peak rates. May be multiple peaks.

Maybe a surge in demand for hardware infrastructure and services late in pre-commercialization

Expect a surge in demand for hardware infrastructure and services once The ENIAC Moment has been reached

Development of standards for QA, documentation, and benchmarking

  1. Informal development of QA, doc, benchmarking. Especially during pre-commercialization.
  2. Rudiments of conventions.
  3. Initiation of standards process.
  4. Standards underway.
  5. Initial standards.
  6. Validation of standards.
  7. Approval process.
  8. Initial adoption of standards.
  9. Incremental corrections and enhancements to standards.
  10. Vigorous acceptance of standards.
  11. Pragmatic reasons for failure to fully adopt the new standards.
  12. Vigorous adoption of standards.
  13. Incremental evolution of standards as the technology evolves.

Business development during pre-commercialization

  1. The technology is not ready for production deployment.
  2. The technology has not even been proven to work.
  3. There are no production-quality production-scale applications, nor are they feasible. They will have to wait for commercialization.
  4. Expectations for the eventual product haven’t been set — or at least they shouldn’t be set until more is known about the technology.
  5. A service level agreement (SLA) would be wholly inappropriate at this stage. Except maybe for availability and throughput for experiments.
  6. No clarity as to the timeframe when the technology or a finished commercial product might become available.
  1. Building technology awareness. But not product awareness, yet, since there are no production-ready products, yet.
  2. Promoting prototyping and experimentation.
  3. Promoting technology familiarization.
  4. Marketing consulting services. Rather than product acquisition and deployment.
  5. Marketing quantum-enabling products. To be used during pre-commercialization. Such as tools and support software. And hardware components used to build quantum computers.

Some preliminary commercial business development late in pre-commercialization

Preliminary commercial business development early in initial commercialization stage

Deeper commercial business development should wait until after pre-releases late in the initial commercialization stage

Consortiums for configurable packaged quantum solutions

Finalizing service level agreements (SLA) should not occur until late in the initial commercialization stage, not during pre-commercialization

IBM — The epitome of pre-commercialization, still heavily focused on research as well as customers prototyping and experimenting

  1. IBM is still focused very heavily on research. Organizationally, the bulk of their effort is research.
  2. No hint of a true product engineering team at IBM. This is still a research project. Still prototyping new hardware and new software. No sense of what a commercial product would look like.
  3. IBM non-research staff facilitating customer experimentation and prototyping. Busy encouraging customers to experiment with the new, unproven, and evolving technology. Building excitement and enthusiasm, but no commercial products.
  4. IBM customers focused on prototyping and experimentation. No hint of efforts towards production-scale algorithms or applications yet.

Oracle — No hint of prime-time application commercialization

Amazon — Research and facilitating prototyping and experimentation

  1. As a customer and user of quantum computing and developer of complex and data-intensive applications.
  2. As a cloud service provider.

Pre-commercialization is the realm of the lunatic fringe

Quantum Ready

  • We are currently in a period of history when we can prepare for a future where quantum computers offer a clear computational advantage for solving important problems that are currently intractable. This is the “quantum ready” phase.
  • Think of it this way: What if everyone in the 1960s had a decade to prepare for PCs, from hardware to programming over the cloud, while they were still prototypes? In hindsight, we can all see that jumping in early would have been the right call. That’s where we are with quantum computing today. Now is the time to begin exploring what we can do with quantum computers, across a variety of potential applications. Those who wait until fault-tolerance might risk losing out on much nearer-term opportunities.

Quantum Ready — The criteria and timing will be a fielder’s choice based on needs and interests

Quantum Ready — Be early, but not too early

Quantum Ready — Critical technical gating factors

  1. Near-perfect qubits. At least four nines of qubit fidelity (99.99%), preferably five nines (99.999%). Still far short of true fault tolerance, but close enough that many simple to moderate-complexity algorithms can be implemented without superhuman effort.
  2. 40-qubit algorithms are common. Or at least 32-qubits. At least in the academic literature.
  3. Automatically scalable algorithms are common. Investing in non-scalable algorithms is a very serious blunder.
  4. Robust collection of high-level algorithmic building blocks. Can construct reasonably complex quantum algorithms without superhuman effort.
  5. A substantial fraction of quantum advantage is readily achievable and common. Again, without superhuman effort.

Quantum Ready — When the ENIAC Moment has been achieved

Quantum Ready — It’s never too early for The Lunatic Fringe

Quantum Ready — Light vs. heavy technical talent

Quantum Ready — For algorithm and application researchers anytime during pre-commercialization is fine, but for simulation only

Quantum Ready — Caveat: Any work, knowledge, or skill developed during pre-commercialization runs the risk of being obsolete by the time of commercialization

Quantum Ready — The technology will be constantly changing

Quantum Ready — Leaders, fast-followers, and laggards

Quantum Ready — Setting expectations for commercialization

Quantum Ready — Or maybe people should wait for fault-tolerance?

Quantum Ready — Near-perfect qubits might be a good time to get ready

Quantum Ready — Maybe wait for The FORTRAN Moment?

Quantum Ready — Wait for configurable packaged quantum solutions

Quantum Ready — Not all staff within the organization have to get Quantum Ready at the same time or pace

Shor’s algorithm implementation for large public encryption keys? Not soon.

Quantum true random number generation as an application is beyond the scope of general-purpose quantum computing

Summary and conclusions

  1. To be clear, this paper is only a proposed model for approaching commercialization of quantum computing. How reality plays out is anybody’s guess.
  2. Commercialization is where all the real action will be, the holy grail of quantum computing.
  3. But first we need to complete a vast amount of research, prototyping, and experimentation, which we call pre-commercialization. Only then can the nascent industry proceed to commercialization.
  4. Research is the first, foremost, and main focus of pre-commercialization.
  5. It’s not clear how much research will be needed to complete pre-commercialization to be ready for commercialization.
  6. Ongoing research will continue indefinitely, never-ending, even once sufficient research has been performed to fully enable the initial commercialization stage — C1.0.
  7. Lots of prototyping will be needed to complete pre-commercialization. To figure out what an eventual product might really look like.
  8. Vast amounts of experimentation will be needed to discern which ideas work and which ideas don’t.
  9. Plenty of preview releases can be made available along the way in pre-commercialization, comparable to the alpha, beta, and pre-releases which will be made available during commercialization.
  10. Rely primarily on simulation for most prototyping and experimentation. Configured to match target hardware, primarily expected commercialization, not hardware that is not ready for commercialization.
  11. Primary testing of hardware should focus on functional testing, stress testing, and benchmarking — not prototyping and experimentation. Test based on carefully defined specifications. During both pre-commercialization and commercialization.
  12. Prototyping and experimentation should initially focus on simulation of hardware expected in commercialization. Not hardware which is not ready for commercialization.
  13. Late in pre-commercialization, prototyping and experimentation can focus on actual hardware — once it meets specs for commercialization.
  14. Prototyping and experimentation on actual hardware earlier in pre-commercialization is problematic and an unproductive distraction. Distortion of algorithms to work with hardware which is not ready for commercialization. Focus on correct results using simulation.
  15. The initial commercialization stage, C1.0, will be the first commercial product version of a quantum computer — with applications.
  16. There will be ten or more subsequent commercialization stages with incremental features and capabilities. C1.0 will only be the beginning of commercialization and won’t fulfill all promises, which will come in the subsequent stages, C1.5, C2.0, C2.5, etc.
  17. Quantum Ready — The criteria and timing for when a particular organization should get Quantum Ready will be a fielder’s choice based on needs and interests. Some will need to be quite early while others can afford to wait until the technology has stabilized and matured — leaders, fast-followers, and laggards, and everything in between.
  18. A subsequent paper will be needed to provide a detailed roadmap for full commercialization. No commitment is made as to the timeframe for that paper, but it won’t be soon since so much work, years, of pre-commercialization lie ahead of us. That said, there is a fair amount of coverage of commercialization in this paper, likely sufficient for most purposes over the next five years.
  19. Business development during pre-commercialization is rather distinct from business development during commercialization. Focused on technology awareness, familiarization with the technology, prototyping, experimentation, and consulting services, rather than development and deployment of production-quality, production-scale applications and production deployment.
  20. There will be plenty of opportunity for marketing quantum-enabling products during pre-commercialization, such as tools, support software, services, and hardware components needed to build quantum computers.

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Freelance Consultant

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Jack Krupansky

Jack Krupansky

Freelance Consultant

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