Proposal for a Quantum Capabilities Label for Quantum Computers, Algorithms, and Applications

  1. In a nutshell
  2. The needs
  3. Goals
  4. Demand transparency — transparency is mandatory
  5. What won’t be covered by this proposal
  6. Capabilities and metrics
  7. Units for capabilities and metrics
  8. Quantum computer vs. quantum processor
  9. Proposed list of quantum computing capabilities
  10. Other capabilities and characteristics
  11. Principles of Operation and Implementation Specifications for all details on a quantum computer
  12. Some capabilities may not be known at present
  13. Quantum computer label
  14. Combined label for a family of quantum computer models
  15. Abbreviated quantum computer label
  16. #AQ (Algorithmic Qubits)
  17. Quantum Volume (QV) limit of 50 qubits
  18. A list of capabilities to provide a fuller picture than a single metric
  19. Other benchmarks
  20. Differences for the label for a quantum algorithm or application
  21. Present quantum algorithm and application requirements as both formulas and representative values in tabular form
  22. Not all quantum algorithms and applications have requirements for all capabilities of a quantum computer
  23. Labels for speculative or future quantum computers, algorithms, and applications
  24. Qubit count
  25. Quantum error correction (QEC)
  26. Qubit fidelity
  27. Gate fidelity
  28. Measurement fidelity
  29. Qubit fidelity under quantum error correction
  30. Logical qubits — in the future
  31. Qubit connectivity
  32. Qubit topology
  33. Fine granularity of phase and probability amplitude
  34. Coherence time
  35. Maximum circuit depth vs. maximum circuit size — is there opportunity for parallelism?
  36. Maximum circuit size vs. total circuit size
  37. Total circuit size vs. maximum circuit depth — is there opportunity for parallelism?
  38. Precision of quantum Fourier transform (QFT)
  39. Quantum advantage for quantum algorithms and applications
  40. Define metadata to facilitate searching, sorting, and matching for both quantum computers and quantum algorithms and applications
  41. Overall letter grade?
  42. Graphic treatment of label
  43. Identification information — essential but beyond the scope of this proposal
  44. Essential details for papers on quantum computers, algorithms, and applications
  45. Essential details for press releases for quantum computers, algorithms, and applications
  46. Essential details for journalists writing about quantum computers, algorithms, and applications
  47. Basis for a report card on progress in quantum computing
  48. Focus here is primarily quantum computer hardware, not software
  49. My original proposal for this topic
  50. Summary and conclusions

In a nutshell

  1. Readers and reviewers need to quickly grasp the capabilities of a particular quantum computer, or of the capabilities required by a particular quantum algorithm or application.
  2. Demand transparency. Transparency is mandatory. No excuses.
  3. A label is proposed which is an abbreviated summary of quantum computing capabilities. Primarily performance and capacity.
  4. Easy to grasp at a quick glance. No need for a careful reading or deep study.
  5. Applies equally to quantum computers, quantum algorithms, and quantum applications.
  6. For quantum algorithms and applications it lists the required quantum computing capabilities. But they’re generally from the same list of capabilities as a quantum computer.
  7. Full details are available elsewhere. The proposed label is a small subset of the full details which can be found in the Principles of Operation and Implementation Specifications documents for particular quantum computers, and similarly the specifications or source code or published papers on a quantum algorithm or application would give the full details about the required quantum computing capabilities.
  8. Select the small set of essential details. The point of this paper is to identify a very small set of such details which give a decent sense of the overall capabilities or requirements of a particular quantum computer, algorithm, or application at a quick glance.
  9. Ideal for metadata for a database. The brevity of the details on the label would make it ideal for metadata for a database search for quantum computers, algorithms, and applications.
  10. Facilitate comparisons. A modest set of capabilities should make it easier to compare and contrast two or more quantum computers, quantum algorithms, or quantum applications.
  11. Who supports what. Having compatible capabilities used between quantum computers and algorithms and applications should make it easier to ascertain which quantum computers will support a given quantum algorithm or application, as well as which algorithms and applications are supported by a particular quantum computer.
  12. Call attention to important details. The label should also have the effect of calling attention to capabilities which are not currently given enough attention, such as degree of fine granularity of phase and probability amplitude and lack of support for high-precision quantum Fourier transform (QFT).
  13. Focus on quantitative details rather than hype. The label should also have the effect of calling attention to specific quantitative measures of the capabilities of quantum computers as well as calling attention to hardware requirements of quantum algorithms and applications. In contrast to today’s hype, rhetoric, hand-waving, and overall confusion.
  14. A family label as well. Either a table which combines all of the labels of the individual models of the family for easy comparison, or a single label with ranges for any metrics which are not constant across all models of quantum computers in the family.
  15. An abbreviated label as well. A briefer subset of the most important information.
  16. Label can be applied to speculative or future quantum computers, algorithms, and applications as well. An estimated date would be helpful.
  17. Rich graphical treatment is warranted. But it is beyond the scope of this paper, and beyond my own interest and ability.
  18. Generally the label for quantum algorithms and applications will parallel the label for quantum computers, with some differences. Some capabilities may not be relevant or no useful metric value is available.
  19. Quantum advantage for quantum algorithms and applications. Roughly what performance advantage does the quantum approach have over the best classical solution. This is an exception in that it is a capability rather than a required capability.
  20. Identification information — essential but beyond the scope of this proposal. There is also identification information which needs to be included on the label, but the details of identification are beyond the scope of this proposal.
  21. Essential details for papers on quantum computers, algorithms, and applications. The label also defines the essential information that should be presented in any paper on a quantum computer, algorithm, or application.
  22. Essential details for press releases for quantum computers, algorithms, and applications. The label also defines the essential information that should be presented in a press release for a quantum computer, algorithm, or application.
  23. Essential details for journalists writing about quantum computers, algorithms, and applications. The label also defines the essential information that journalists should be aware of when writing about a quantum computer, algorithm, or application.
  24. The label can also be used as the basis for a report card on progress in quantum computing capabilities. Each of the listed capabilities is where progress is needed.
  25. Focus here is primarily quantum computer hardware, not software. There are lots of software capabilities as well, very worthy of attention, but that’s beyond the scope of this paper.

The needs

A user of a quantum computer (or a customer buying one) or a programmer using a quantum algorithm or developing a quantum application (or a manager responsible for the use of quantum algorithms and applications) needs to know the following:

  1. The capabilities of a quantum computer. The resources which are available and what capabilities they provide.
  2. The capabilities required by a quantum algorithm or application. The quantum computing resources and capabilities which a quantum algorithm requires.

Goals

  1. Transparency. What capabilities does a particular quantum computer have, or what capabilities does a particular quantum algorithm or application require.
  2. Utility. How easily can we tell what sorts of algorithms or applications can be run on a particular quantum computer, and how easily can we identify what quantum computers are capable of supporting a particular quantum algorithm or application.
  3. Make it easy to tell what kind of quantum computer is needed to support a particular quantum algorithm or application.
  4. Make it easy to tell what sorts of algorithms or applications can be supported by a particular quantum computer.
  5. Define metadata to facilitate searching, sorting, and matching for both quantum computers and quantum algorithms and applications. The capabilities for quantum computers and requirements for quantum algorithms and applications would greatly facilitate creation and querying of databases of quantum computers and quantum algorithms and applications.
  6. Make it easier to see where quantum computers need improvements.
  7. Make it easier to see how far ahead of quantum computer hardware quantum algorithms and applications really are.
  8. Make it easier to see what improvements are needed for quantum computers to run existing quantum algorithms and applications.
  9. Provide information needed to help set research priorities.
  10. Get a sense of how close quantum computers, algorithms, and applications are to supporting production-scale commercialization of quantum computing.
  11. Gain a fuller picture of capabilities than is possible using a single metric.
  12. Provide the essential details for papers on quantum computers, algorithms, and applications. Assure that readers quickly get to the point about what quantum computing capabilities are involved.
  13. Provide the essential details for press releases for quantum computers, algorithms, and applications. Assure that readers quickly get past all of the hype.
  14. Provide the essential details for journalists to write about quantum computers, algorithms, and applications. Assure that readers quickly get past all of the hype.
  15. Provide a list of capabilities which can also be used as the basis for a report card on progress of quantum computing.
  16. Generally nudge people in the direction of quantitative detail rather than hype.

Demand transparency — transparency is mandatory

We deserve transparency on capabilities of quantum computers, algorithms, and applications.

  1. Expect transparency. Transparency is a reasonable default expectation.
  2. Assume transparency. We shouldn’t have to lift a finger to get transparency.
  3. Wait for transparency. Maybe hold off on products and services which lack sufficient transparency.
  4. Request transparency. We shouldn’t have to ask for transparency, but…
  5. Insist on transparency. We shouldn’t have to go beyond asking politely and nicely, but…
  6. Demand transparency. Hold their feet to the fire. Transparency shouldn’t be optional. And lack of transparency shouldn’t be tolerated.
  7. Transparency is mandatory. No ifs, ands, or buts. No excuses. Just do it!
  8. Without transparency, you have nothing!

What won’t be covered by this proposal

This proposal covers all systems that meet the common interpretation of the term quantum computer. More technically, it covers two-level gate-based quantum computers. This excludes:

  1. Multi-level quantum computers with more than two levels. Only two-level qubits are covered here.
  2. Qutrits. Three-level qubits.
  3. Qudits. Ten-level qubits.
  4. Continuous-variable (CV) qumodes. As on photonic quantum computers.
  5. Squeezed states. As on photonic quantum computers.
  6. Fusion-based quantum computing (FBQC). Again, primarily photonic quantum computers.
  7. Non-gate quantum computers. Such as quantum annealing from D-Wave Systems. These are quite interesting, but beyond the scope of the information presented in this paper.
  8. Specialized quantum physics simulation hardware. Again, these are very interesting, but beyond the scope of the concept of quantum computation covered by this paper.

Capabilities and metrics

Generally, each capability of a quantum computer will be expressed as a metric. Or, we can say that a metric expresses the measure of a capability.

Units for capabilities and metrics

Generally, I don’t bother expressing what units are required for a given capability or metric. Usually it is fairly obvious or the common-sense expectation. Or it can vary, such as what unit of time to use (minute, second, millisecond, microsecond, nanosecond.)

Quantum computer vs. quantum processor

For the purposes of this informal paper, the following are all essentially synonymous unless clearly distinguished by context:

  1. Quantum computer.
  2. Quantum computer system.
  3. Quantum processor.
  4. Quantum processor unit (QPU).
  5. Quantum processing unit (QPU).
  6. QPU.

Proposed list of quantum computing capabilities

This is a clean, very limited subset of all of the capabilities either of a quantum computer or required for a quantum algorithm or application:

  1. Qubit technology. Superconducting transmon qubit, trapped-ion, neutral-atom, silicon spin, etc. Standardized abbreviations would be nice.
  2. Qubit count. Initially physical qubit count, but with quantum error correction it would be both logical qubit count and physical qubit count.
  3. Quantum error correction (QEC). Is it supported? Is there a specific scheme or multiple schemes supported? Are there any parameters supported? Can the ratio of physical to logical qubits be specified or controlled? This is still all off in the future.
  4. Qubit fidelity. Nines of qubit fidelity. If error correction is supported, both the fidelity based on any residual error rate and the fidelity of the raw physical qubits. For now, it would simply be the physical qubit fidelity. Can call out gate fidelity and measurement fidelity separately, but qubit fidelity should be the lesser of two-qubit gate fidelity and measurement fidelity.
  5. Qubit connectivity. Nearest neighbor, full, less than nearest neighbor, better than nearest neighbor. Unlimited or how limited. Standardized abbreviations would be nice.
  6. Fine granularity of phase and probability amplitude. Number of gradations. Generally approximated as a power of ten or a power of two — 100, 1,000, one million, a billion, or 2¹⁰, 2²⁰, 2³⁰. Generally needed for quantum Fourier transform (QFT) precision.
  7. Coherence time. For physical qubits. Under quantum error correction, logical qubits either have infinite, indefinite coherence or possibly some residual limitation on coherence time.
  8. Gate execution time and rate. Time to execute a single quantum logic gate as well as how many gates can be executed per second.
  9. Maximum circuit depth. Generally either the coherence time divided by the gate execution time or some arbitrary limit if coherence time is indefinite.
  10. Maximum circuit size. May be greater than the maximum circuit depth if gates can be executed in parallel. Otherwise it should be identical to the maximum circuit depth.
  11. Quantum Volume (QV). And log2(QV) as well, since it’s the number of qubits which can effectively be used in a significant computation.
  12. Benchmarks. Optionally, any other standardized benchmark results — benchmark name and metric value — other than Quantum Volume (QV).
  13. Quantum Fourier transform (QFT) precision. How many qubits can be transformed and achieve high quality results.
  14. Circuit executions per second. Maximum rate for the shortest circuits. Includes time to reset all qubits. Within a single network request. Comparable to IBM’s Circuit Layer Operations Per Second (CLOPS).
  15. Network requests per second. Distinct jobs and users.
  16. Runtime support. Any ability to support running of classical application code on the quantum computer. Qiskit Runtime is one example.
  17. Calibration overhead. Percentage of time spent running calibration process. Frequency. Time duration per calibration run.

Other capabilities and characteristics

Any number of other capability measures could be considered for inclusion on the label for either a quantum computer or a quantum algorithm or application, but for now, the goal is to keep the list relatively short and most relevant.

Principles of Operation and Implementation Specifications for all details on a quantum computer

The proposal of this paper covers only a small subset of the total capabilities of a quantum computer, sufficient to get a general sense of capabilities at a quick glance. For the full details of the total capabilities of a quantum computer, see the Principles of Operation document for the quantum computer, which tells a programmer everything they need to know about a computer system to write code for the system. Typically there would be one document for a whole family of processors.

  1. Framework for Principles of Operation for a Quantum Computer
  2. https://jackkrupansky.medium.com/framework-for-principles-of-operation-for-a-quantum-computer-652ead10bc48

Some capabilities may not be known at present

In an effort to be forward-looking, this proposal includes some capabilities which may not be fully characterized now or in the near future. The values on the label for such capabilities would simply have to be listed as unknown or not known. Over time the set of such capabilities should shrink and eventually completely evaporate, although additional capabilities may appear on occasion so that the set of unknown capabilities may never or infrequently dissipate completely.

  1. Quantum error correction (QEC). Still an area of very active research. Difficult to say with confidence what the metrics will actually look like.
  2. Fine granularity of phase and probability amplitude. Less important today but will increase in importance as quantum Fourier transform (QFT) becomes more feasible — due to the need for fine granularity of phase and probability amplitude.
  3. Quantum Fourier transform (QFT) precision. Won’t become important until fine granularity of phase is supported to enable high-precision quantum Fourier transform.

Quantum computer label

Some points particular to the label for a quantum computer system:

  1. Potential for multiple processors. A single quantum computer system with multiple processors, which may or may not work in tandem or independently. But this does not exist today.
  2. Possibly present as a table for all processors in a family. Each could have a completely separate label or join them as a table. Maybe both as a choice.
  3. When logical qubits are available and configurable, present as a table. List the possible configuration settings for physical qubits per logical qubit, or a sample list of values if it is a continuous value with a large number of possible settings.

Combined label for a family of quantum computer models

Although each model of quantum computer should always have its own label of capabilities, it will also be helpful and informative to have a combined label when there is a family of quantum computer models.

  1. A table which is simply the combination of all of the labels of the individual members of the family. Makes it easy to compare and contrast the models.
  2. A single merged label. Discrete metric values when they are constant across all models. A range of metric values when they vary across the models.

Abbreviated quantum computer label

For some purposes an even more abbreviated label might be appropriate to roughly and generally describe a quantum computer:

  1. Qubit count. Initially physical qubit count, but with quantum error correction it would be both logical qubit count and physical qubit count.
  2. Qubit fidelity. Nines of qubit fidelity.
  3. Qubit connectivity. Nearest neighbor, full, less than nearest neighbor, better than nearest neighbor.
  4. Fine granularity of phase and probability amplitude. Number of gradations.
  5. Maximum circuit depth. The coherence time divided by the gate execution time.
  6. Quantum Volume (QV). Maybe log2(QV) as well, since it’s the number of qubits which can effectively be used in a significant computation.

#AQ (Algorithmic Qubits)

IonQ has its own proprietary metric for its quantum computers, #AQ for Algorithmic Qubits.

  • we have roughly defined an #AQ of N as the size of the largest circuit you can successfully accomplish with N qubits and N² two-qubit gates.

Quantum Volume (QV) limit of 50 qubits

In theory, the Quantum Volume (QV) metric is limited to roughly 50 qubits, QV of 2⁵⁰, since assessing Quantum Volume requires doing a full classical simulation of the quantum circuit.

A list of capabilities to provide a fuller picture than a single metric

There have been attempts to try to reduce all of quantum computing to a single metric, such as Quantum Volume (QV) and Algorithmic Qubits (#AQ), but such approaches leave a lot to be desired.

Other benchmarks

Someday there will be a range of standardized benchmark tests which can be run on a candidate quantum computer, much as Quantum Volume (QV) is today, and it would be appropriate to report some of these benchmark results on the label for a quantum computer.

Differences for the label for a quantum algorithm or application

Not all of the capabilities for a quantum computer would be relevant to specifying the requirements for a particular quantum algorithm or application. Most of it is the same, but not all of it. In addition, there are requirements for the use of a quantum computer by a quantum algorithm or application which are not distinct capabilities of a quantum computer per se.

  1. Gate execution time and rate.
  2. Quantum Volume (QV).
  3. Circuit executions per second.
  4. Network requests per second.
  1. Qubit technology. Hopefully, and in theory, most quantum algorithms and applications will be independent of the qubit technology. But, in some cases, maybe they may be dependent.
  2. Scaling requirements. Based on input data size. Capability requirements should be presented as a formula based on input data size. As well as a table or graph (or both) showing capability requirements for a sample of representative input data sizes.
  3. Shot requirements. Circuit repetitions (shot count or shots) required based on input data size and any algorithm input parameters. Should be a formula, but also presented as a table to show actual shot couts for a sample of input data sizes. Shot requirement has two components: shots due to error rate, and shots due to the inherent probabilistic nature of quantum computations.
  4. Some additional general capabilities might not be relevant. For example, quantum Fourier transform (QFT) precision.
  5. Maximum circuit depth. May be less than maximum circuit size if gates can be executed in parallel. Otherwise it should be the same as the total circuit size. Could vary based on input data size, so see scaling requirements above.
  6. Total circuit size. Replaces maximum circuit size. Total count of quantum logic gates in the circuit for the algorithm. May be greater than the maximum circuit depth if gates can be executed in parallel. Otherwise it should be identical to the maximum circuit depth. Could vary based on input data size, so see scaling requirements above.
  7. Quantum advantage for quantum algorithms and applications. Roughly what performance advantage does the quantum approach have over the best classical solution.

Present quantum algorithm and application requirements as both formulas and representative values in tabular form

One of the biggest differences of the requirements of a quantum algorithm or application from the capabilities of a quantum computer is that they will commonly not be fixed constants, but vary or scale based on the size of the input data and any input parameter values.

Not all quantum algorithms and applications have requirements for all capabilities of a quantum computer

Some, many, or even most quantum algorithms and applications can have shorter labels than a typical quantum computer since they are simply not dependent on various capabilities, typically because the algorithm or application is simpler, less sophisticated, or uses fewer of the capabilities.

Labels for speculative or future quantum computers, algorithms, and applications

Although the primary focus of this paper is actual, current, real quantum computers, algorithms, and applications, the concept of a label for capabilities is also applicable to speculative or future quantum computers, algorithms, and applications. In fact, I would strongly encourage it.

Qubit count

Qubit count is the simplest capability of a quantum computer to specify — how many qubits there are.

Quantum error correction (QEC)

If quantum error correction is supported by a quantum computer, then there are two qubit counts — the logical qubit count and the physical qubit count.

  1. A choice of coding scheme. The name of the coding or correction scheme.
  2. The number of physical qubits per logical qubit. Either this is a parameter which can be changed, or it is computed automatically by dividing the number of physical qubits by the number of logical qubits.
  3. Any other parameters for the coding scheme. Some schemes may have additional parameters.

Qubit fidelity

Qubit fidelity is an extremely important factor in quantum computing. There are a variety of methods for representing qubit fidelity, but I see that nines of qubit fidelity is the simplest and easiest to make sense out of — the more nines the better.

  1. Below 1 nine — below 90% reliability.
  2. 1 nine — 90% reliability.
  3. Below 1.5 nines — below 95% reliability.
  4. 1.5 nines — 95% reliability.
  5. 1.75 nines — 97.5%.
  6. 1.8 nines — 98%.
  7. 1.85 nines — 98.5%.
  8. 2 nines — 99%.
  9. 2.25 nines — 99.25%.
  10. 2.5 nines — 99.5%.
  11. 2.75 nines — 99.75%.
  12. 3 nines — 99.9%.
  13. 3.25 nines — 99.925%.
  14. 3.5 nines — 99.95%.
  15. 3.75 nines — 99.975%.
  16. 4 nines — 99.99%.
  17. 4.25 nines — 99.9925%.
  18. 4.5 nines — 99.995%.
  19. 4.75 nines — 99.9975%.
  20. 5 nines — 99.999%.
  1. Whether 2 to 2.5 nines of qubit fidelity is sufficient for any applications is a stretch.
  2. 2.75 to 3 to 3.25 nines of qubit fidelity are verging on near-perfect qubits, good enough for some applications.
  3. 3.5 nines may be close enough to near-perfect qubits for many applications.
  4. 3.75 nines will be close enough to near-perfect qubits for many applications.
  5. 4 nines of qubit fidelity will generally be near-perfect qubits sufficient for most applications.

Gate fidelity

Technically, a lot of what is nominally referred to as qubit fidelity is really gate fidelity — how reliably can a quantum logic gate be executed on a qubit, or more importantly, between two interacting qubits.

Measurement fidelity

Technically, another significant fraction of what is nominally referred to as qubit fidelity is really measurement fidelity — how reliably can a qubit be measured.

Qubit fidelity under quantum error correction

The preceding sections presumed that there was no support for quantum error correction (QEC). Once quantum error correction is supported, then we get two sets of numbers:

  1. Qubit fidelity of physical qubits. What we just discussed.
  2. Qubit fidelity of logical qubits. Reflect any residual or lingering error rate after quantum error correction.
  1. Base qubit fidelity. How close to near-perfect qubits are the physical qubits.
  2. Choice of physical qubits per logical qubit.
  3. Choice of coding scheme.
  4. Other parameters of the coding scheme.
  5. Residual impact on coherence time.
  6. Residual gate execution error rate.
  7. Residual two-gate gate execution error rate.
  8. Residual qubit measurement error rate.

Logical qubits — in the future

At present, we have no sense of full, automatic, and transparent quantum error correction (QEC). As a result, we have no sense of perfect logical qubits — all we have are raw physical qubits.

  1. Physical qubits only. Where we are today and for the indefinite future.
  2. Mix or choice of logical and physical qubits. Some quantum algorithms or applications may opt to stick with raw physical qubits for raw capacity, raw performance, or compatibility, while other quantum algorithms or applications may opt to go with perfect logical qubits.
  3. Logical qubits only. Physical qubits are only under the hood. All that the quantum algorithms and applications see are perfect logical qubits.

Qubit connectivity

Qubit connectivity is tricky. Ideally, you should be able to connect any two qubits in a two-input gate, but that isn’t always true.

  1. Nearest neighbor connectivity. Any two physically adjacent qubits can be connected. Such as Google Sycamore.
  2. Full connectivity. Best. Common for trapped-ion and neutral-atom qubits.
  3. Less than nearest neighbor connectivity. Typical for IBM as they optimized minimization of crosstalk.
  4. Better than nearest neighbor connectivity. None that I am aware of at this time.
  1. Is full connectivity supported? If so, we’re good to go.
  2. Where are we relative to pure nearest neighbor? Assuming a rectangular grid with four connections: up, down, left, and right. Are we exactly nearest neighbor, less than nearest neighbor, or somewhat greater than nearest neighbor (but not full connectivity)?

Qubit topology

I didn’t call out qubit topology (how qubits are arranged and connected) for the label. In theory, applications and algorithms shouldn’t really care about qubit topology, but ultimately it does affect connectivity, which algorithms do rely on. But the approach I took here is to focus on qubit fidelity and connectivity rather than qubit topology.

Fine granularity of phase and probability amplitude

Unlike the basis states of the quantum state of a qubit which are strictly binary 0 and 1, phase and probability are continuous values, real numbers between 0.0 and 1.0 (and the negative values as well.) This begs the question of exactly how many distinct values can be represented by phase or probability amplitude. In theory, an infinite number, in practice, implemented by actual digital and analog circuit components, there won’t be an infinity of values.

  1. 100.
  2. 1,000.
  3. One million.
  4. A billion.
  5. A trillion.
  6. A quadrillion. I kind of doubt there could be more gradations than this or even close to this.
  7. 2¹⁰. 1024.
  8. 2¹⁶. 64K.
  9. 2²⁰. One million.
  10. 2³⁰. One billion.
  11. 2³². Four billion. Corresponds to a 32-bit integer.
  12. 2⁴⁰. One trillion.
  13. 2⁵⁰. One quadrillion.

Coherence time

The quantum state of a qubit tends to decay over time.

Maximum circuit depth vs. maximum circuit size — is there opportunity for parallelism?

Technically, a quantum circuit is a graph, so that theoretically portions of the circuit could be executed in parallel so that more quantum logic gates could get executed before the coherence time expires.

Maximum circuit size vs. total circuit size

Maximum circuit size and total circuit size are really the same thing, just that the former is used for a quantum computer to indicate the largest circuit that is supported, while the latter is used for a quantum algorithm or application to indicate the actual size of the quantum circuit.

Total circuit size vs. maximum circuit depth — is there opportunity for parallelism?

Technically, a quantum circuit is a graph, so that theoretically portions of the circuit could be executed in parallel so that more quantum logic gates could get executed before the coherence time expires.

Precision of quantum Fourier transform (QFT)

Some applications such as quantum computational chemistry or Shor’s factoring algorithm need the advanced quantum parallelism of quantum Fourier transform (QFT). The width or precision of the transform can be problematic, being critically dependent on fine granularity of phase and probability amplitude.

Quantum advantage for quantum algorithms and applications

The whole point of pursuing a quantum solution to a problem rather than a classical solution is to achieve a dramatic performance speedup. This entry of the label for a quantum algorithm or application will summarize the advantage. It will be roughly the performance advantage that a quantum algorithm or application offers over the best classical solution.

Define metadata to facilitate searching, sorting, and matching for both quantum computers and quantum algorithms and applications

The capabilities for quantum computers and requirements for quantum algorithms and applications defined in this paper would greatly facilitate the creation and querying of databases of quantum computers and quantum algorithms and applications.

Overall letter grade?

It certainly is tempting to want to provide an overall letter grade for a quantum computer or quantum algorithm or application, but both are too multidimensional to be scored with a simple scalar.

Graphic treatment of label

It would probably be advantageous to have a distinctive graphical treatment for the label for quantum computers and quantum algorithms and applications, but that’s beyond the scope of this paper and beyond my own personal interest and ability.

  1. Full page. All of the suggested capabilities. Try to simplify the text a moderate amount.
  2. Mini-side bar box. A very modest subset of the information. A true quick glance.
  1. Qubit count.
  2. Qubit fidelity. Nines of qubit fidelity.
  3. Qubit connectivity.
  4. Fine granularity of phase and probability amplitude. Number of gradations.
  5. Maximum circuit depth.
  6. Quantum Volume (QV). Maybe log2(QV) as well, since it’s the number of qubits which can effectively be used in a significant computation.

Identification information — essential but beyond the scope of this proposal

There is also identification information which needs to be included on the label, but the details of identification are beyond the scope of this proposal. For example:

  1. Vendor name. Both overall quantum computer system vendor and the quantum processing unit (QPU) vendor, which may be different.
  2. Family name. Family of processors to which this processor belongs. Or, if the label is for the entire family rather than a particular member of the family.
  3. Model name or number. The specific model of a quantum computer system, within a family.
  4. Configuration options. Any configuration settings which were chosen which cause a different label even for the same basic model.
  5. Version, release, or revision. When capabilities of a quantum computer, algorithm, or application may change due to updates.
  6. Dates. When was the information on the label captured and recorded. When did the quantum computer, algorithm, or application first go into service — or expected to enter service. Optionally, when did the quantum computer, algorithm, or application go out of service.

Essential details for papers on quantum computers, algorithms, and applications

The label also defines the essential information that should be presented in any paper on a quantum computer, algorithm, or application. Whether formal academic papers in peer-reviewed journals or less formal white papers, the information included in the label proposed by this paper would allow readers to quickly get a sense of what quantum computing capabilities are involved. What is the paper actually talking about.

Essential details for press releases for quantum computers, algorithms, and applications

The label also defines the essential information that should be presented in a press release for a quantum computer, algorithm, or application.

Essential details for journalists writing about quantum computers, algorithms, and applications

The label also defines the essential information that journalists should be aware of when writing about a quantum computer, algorithm, or application.

Basis for a report card on progress in quantum computing

The label can also be used as the basis for a report card on progress in quantum computing capabilities. Each of the listed capabilities is where progress is needed, as well as what progress has been made.

  1. Where we are relative to what is needed. Gives a sense of how much further progress is needed. Are we 90% there? 50%?
  2. What improvement has been made. Has progress even been made? Over some indicated reporting period like quarterly, semiannually, annually, or biannually. Maybe show all four.

Focus here is primarily quantum computer hardware, not software

The proposal of this paper focuses primarily on quantum computer hardware capabilities. There are lots of software capabilities as well, such as:

  1. Infrastructure software.
  2. System management.
  3. Utilities.
  4. Tools.
  5. Compilers.
  6. Programming languages.
  7. Libraries.
  8. Application frameworks.
  1. Documentation.
  2. Testing.
  3. Training.
  4. Educational materials.
  5. Support.
  6. Services.
  7. Reliability.
  8. Maintenance.
  9. Frequent or timely upgrades.

My original proposal for this topic

For reference, here is the original proposal I had for this topic. It may have some value for some people wanting a more concise summary of this paper.

  • Proposal for a Good Housekeeping label for quantum computers and quantum algorithms. Quickly tells you all the basics you need to know about the capabilities of a particular quantum computer or the capabilities required by a particular quantum algorithm. Qubit technology (superconducting transmon qubit, trapped-ion, neutral-atom, silicon spin, etc.) Qubit count. Qubit fidelity (nines.) Qubit connectivity (nearest neighbor, full, less than nearest neighbor, better than nearest neighbor.) Granularity of phase and probability amplitudes (number of gradations.) Coherence time. Gate execution time. Maximum circuit depth. Quantum Volume. Qubits of quantum Fourier transform (QFT) for high quality results. CLOPS — circuit repetitions per second. NLOPS — network requests per second. Can call out measurement fidelity separately, but qubit fidelity should be the lesser of two-qubit gate fidelity and measurement fidelity. Sure, there’s plenty of additional info to be disclosed, but these basics should be a short summary upfront.

Summary and conclusions

  1. Readers and reviewers need to quickly grasp the capabilities of a particular quantum computer, or of the capabilities required by a particular quantum algorithm or application.
  2. Demand transparency. Transparency is mandatory. No excuses.
  3. A label is proposed which is an abbreviated summary of quantum computing capabilities. Primarily performance and capacity.
  4. Easy to grasp at a quick glance. No need for a careful reading or deep study.
  5. Applies equally to quantum computers, quantum algorithms, and quantum applications.
  6. For quantum algorithms and applications it lists the required quantum computing capabilities. But they’re generally from the same list of capabilities as a quantum computer.
  7. Full details are available elsewhere. The proposed label is a small subset of the full details which can be found in the Principles of Operation and Implementation Specifications documents for particular quantum computers, and similarly the specifications or source code or published papers on a quantum algorithm or application would give the full details about the required quantum computing capabilities.
  8. Select the small set of essential details. The point of this paper is to identify a very small set of such details which give a decent sense of the overall capabilities or requirements of a particular quantum computer, algorithm, or application at a quick glance.
  9. Ideal for metadata for a database. The brevity of the details on the label would make it ideal for metadata for a database search for quantum computers, algorithms, and applications.
  10. Facilitate comparisons. A modest set of capabilities should make it easier to compare and contrast two or more quantum computers, quantum algorithms, or quantum applications.
  11. Who supports what. Having compatible capabilities used between quantum computers and algorithms and applications should make it easier to ascertain which quantum computers will support a given quantum algorithm or application, as well as which algorithms and applications are supported by a particular quantum computer.
  12. Call attention to important details. The label should also have the effect of calling attention to capabilities which are not currently given enough attention, such as degree of fine granularity of phase and probability amplitude and lack of support for high-precision quantum Fourier transform (QFT).
  13. Focus on quantitative details rather than hype. The label should also have the effect of calling attention to specific quantitative measures of the capabilities of quantum computers as well as calling attention to hardware requirements of quantum algorithms and applications. In contrast to today’s hype, rhetoric, hand-waving, and overall confusion.
  14. A family label as well. Either a table which combines all of the labels of the individual models of the family for easy comparison, or a single label with ranges for any metrics which are not constant across all models of quantum computers in the family.
  15. An abbreviated label as well. A briefer subset of the most important information.
  16. Label can be applied to speculative or future quantum computers, algorithms, and applications as well. An estimated date would be helpful.
  17. Rich graphical treatment is warranted. But it is beyond the scope of this paper, and beyond my own interest and ability.
  18. Generally the label for quantum algorithms and applications will parallel the label for quantum computers, with some differences. Some capabilities may not be relevant or no useful metric value is available.
  19. Quantum advantage for quantum algorithms and applications. Roughly what performance advantage does the quantum approach have over the best classical solution. This is an exception in that it is a capability rather than a required capability.
  20. Identification information — essential but beyond the scope of this proposal. There is also identification information which needs to be included on the label, but the details of identification are beyond the scope of this proposal.
  21. Essential details for papers on quantum computers, algorithms, and applications. The label also defines the essential information that should be presented in any paper on a quantum computer, algorithm, or application.
  22. Essential details for press releases for quantum computers, algorithms, and applications. The label also defines the essential information that should be presented in a press release for a quantum computer, algorithm, or application.
  23. Essential details for journalists writing about quantum computers, algorithms, and applications. The label also defines the essential information that journalists should be aware of when writing about a quantum computer, algorithm, or application.
  24. The label can also be used as the basis for a report card on progress in quantum computing capabilities. Each of the listed capabilities is where progress is needed.
  25. Focus here is primarily quantum computer hardware, not software. There are lots of software capabilities as well, very worthy of attention, but that’s beyond the scope of this paper.

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Freelance Consultant

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