Stages, Milestones, and Tipping Points for Quantum Computing

44 min readMar 1, 2023

Although it is easy to identify stages and milestones for quantum computing, identification of tipping points is a more problematic matter. Which milestones or stages should be regarded as tipping points, and based on what criteria? Can any of the milestones or stages be regarded as the singular most critical tipping point for all of quantum computing? This informal paper does not identify a particular tipping point, but does explore the issues and the possibilities.

Caveat: My comments here are all focused only on general-purpose quantum computers. Some may also apply to special-purpose quantum computing devices, but that would be beyond the scope of this informal paper. For more on this caveat, see my informal paper:

Topics discussed in this informal paper:

In a nutshell
The problem
Background
Why care about a tipping point or why bother calling out a particular milestone or stage?
Milestones, tipping points, critical mass, breakthroughs, advances, etc.
Malcolm Gladwell’s conception of a tipping point
Tipping point vs. milestones
Should enthusiasm be considered a tipping point?
Should the availability of real quantum computing hardware be considered a tipping point?
Should the availability of development tools be considered a tipping point?
Financial vs. functional milestones and tipping points
Should vendor revenue or profitability be considered a tipping point?
Should vendor funding and investment flows be considered a tipping point?
External, business-oriented effects as possible tipping points
Maybe a twofold tipping point for organizations
Maybe two main tipping points
Somehow, a critical mass is needed for a tipping point
Maybe my three stages of adoption for quantum computing are decent candidates for tipping points
The ENIAC Moment as a possible tipping point
The first configurable packaged quantum solution as a possible tipping point
The FORTRAN Moment as a possible tipping point
A high-level quantum programming model as a possible tipping point
A high-level quantum programming language as a possible tipping point
Maybe achievement of my proposal for a quantum computer with 48 fully-connected near-perfect qubits would be a tipping point
Maybe widespread use of 40-qubit quantum algorithms would be a tipping point
Maybe transitioning out of the pre-commercialization stage would be a tipping point
Adoption of quantum computing as a tipping point
No, prototyping and experimentation are not a tipping point
Should full quantum error correction and fault-tolerant quantum computing be the essential tipping point?
Full quantum error correction and fault-tolerant quantum computing as a tipping point
Maybe near-perfect qubits will be the essential tipping point
Full any-to-any qubit connectivity will be necessary but not sufficient for a tipping point
Performance and quantum advantage as a tipping point
We need to see a lengthy catalog of production-scale quantum applications which exhibit significant quantum advantage for practical real-world problems
And maybe quantum supremacy should be the critical tipping point
Wasn’t 50–60 qubits supposed to be the performance tipping point?
No, hundreds, thousands, or millions of qubits won’t be tipping points
Maximum quantum circuit size as a tipping point
Support for quantum Fourier transform and quantum phase estimation as a tipping point
Support for quantum computational chemistry as a tipping point
Maybe the combination of a more ideal qubit technology and quantum processor architecture would be an ideal tipping point
Do we need to wait for the hardware to hit a tipping point or is simulation of scalable quantum algorithms sufficient?
Is our own imagination and creativity the real limiting factor in hitting a tipping point rather than hardware or algorithms per se?
To each their own… tipping point
Personas — each may have their own conception of a tipping point
Use cases — each may have their own conception of a tipping point
Would cracking 2048-bit encryption keys with Shor’s factoring algorithm be a reasonable tipping point?
Might QRAM be a tipping point?
Might a universal quantum computer be a tipping point?
Might quantum networking be a tipping point?
What metrics can we trust for judging tipping points? Can we trust any of them?
Has quantum computing had a viral moment or is one yet to come?
What technical gating factors will it take to achieve a true viral moment for practical quantum computing?
No, we’re not there yet
No, we’re not even close
How much longer?
Are there any near-term tipping points?
Tipping point for a quantum winter?
For reference, tipping point(s) for classical computing
Walls, barriers, and obstacles for quantum computing
Conclusions

In a nutshell

There are plenty of possibilities for tipping points for quantum computing.
It’s almost literally a fielder’s choice for what stage or stages or milestone or milestones to use as the singular essential tipping point or to go with multiple tipping points.
Different personas and use cases could have their own perceptions of what should constitute a tipping point. To each their own.
I personally don’t think that we have already passed a tipping point. Practical quantum computing is not yet a slam dunk certainty.
And I personally don’t think that we have any imminent near-term tipping points staring at us in the face. Not in the coming year. And not likely in the next year. But maybe two to five years from now.
A strong candidate for a tipping point will be performance and quantum advantage.
Maybe quantum supremacy should be the critical tipping point. But for production-scale practical real-world problems, not contrived computer science experiments.The point where no classical computer could compete in any reasonable amount of time, or even ever. Or maybe some significant quantum advantage is good enough?
Wasn’t 50–60 qubits supposed to be the performance tipping point? But other factors matter more than raw qubit count.
No, hundreds, thousands, or millions of qubits won’t be tipping points. Raw qubit count alone will not constitute a tipping point. Qubit fidelity and connectivity will be the more constraining technical factors.
Maybe the combination of a more ideal qubit technology and quantum processor architecture would be an ideal tipping point. If it better supports significant quantum parallelism. And enables dramatic or at least significant quantum advantage. Either qubit technology or quantum processor architecture alone could be a tipping point, but the combination could seal the deal.
Do we need to wait for the hardware to hit a tipping point or is simulation of scalable quantum algorithms sufficient? I say the latter — simulate 24 to 40-qubit quantum algorithms now.
Is our own imagination and creativity the real limiting factor in hitting a tipping point rather than hardware or algorithms per se? Yes, we need to unleash our creative potential rather than be limited by current and near-term quantum hardware.
A strong candidate for a tipping point will be the availability of near-perfect qubits.
Full any-to-any qubit connectivity will be necessary but not sufficient for a tipping point. Near-perfect qubit fidelity will be required as well.
A strong candidate for a tipping point will be support for quantum circuits with upwards of 2,500 gates. Maximum quantum circuit size is a key technical constraint to enable larger and more complex quantum algorithms.
A strong candidate for a tipping point will be support for quantum Fourier transform and quantum phase estimation. Especially needed for quantum computational chemistry.
A strong candidate for a tipping point will be support for quantum computational chemistry. Relies on quantum Fourier transform and quantum phase estimation.
A strong candidate for a tipping point will be the availability of 40-qubit quantum algorithms. Or even 24, 28, 32, or 36-qubit algorithms.
A strong candidate for a tipping point will be the availability of a quantum computer with 48 fully-connected near-perfect qubits.
A strong candidate for a tipping point will be the advent of practical quantum computing.
A strong candidate for a tipping point will be the transition out of the pre-commercialization stage of quantum computing.
No, prototyping and experimentation are not a tipping point. They are valuable and useful precursors to more serious quantum algorithm design and quantum application development, but not a tipping point by themselves.
My three stages of adoption of quantum computing will be strong candidates for tipping points for quantum computing.
A strong candidate for a tipping point will be The ENIAC Moment. Advent of production-scale practical real-world quantum applications.
A strong candidate for a tipping point will be the advent of configurable packaged quantum solutions. Easy to put quantum applications into use without elite quantum teams.
A strong candidate for a tipping point will be The FORTRAN Moment. High-level programming model enabling full custom quantum algorithm and application development without quantum expertise or super-elite quantum teams. Shift from a dedicated quantum computing team (or outsourcing) to regular IT teams.
A strong candidate for a tipping point will be a high-level quantum programming model. Still relies on quite a few additional technical gating factors.
A strong candidate for a tipping point will be a high-level quantum programming language. Depends on a high-level quantum programming model, but the language might seal the deal.
A strong candidate for a tipping point is when the technology is ready for development of production-scale practical real-world quantum applications.
A strong candidate for a tipping point is when deployed production-scale practical real-world quantum applications are achieving substantial quantum advantage and delivering significant and measurable real business value.
A strong candidate for a tipping point would be a lengthy catalog of production-scale quantum applications which exhibit significant quantum advantage for practical real-world problems.
Demonstration of full quantum error correction and fault-tolerant quantum computing. For a modest error correction code distance (d, say 3, 5, 7, or 9 for 9, 25, 49, or 81 physical qubits per logical qubit) and a modest logical qubit count (say 8 to 20 qubits.) Not sufficient to deliver real value, but sufficient to prove that full quantum error correction and fault-tolerant quantum computing are not total fantasy.
A strong candidate for a tipping point is when full quantum error correction and fault-tolerant quantum computing can function at a level sufficient for at least some production-scale practical real-world quantum applications. For a substantial error correction code distance (d, say 29 or 31 — roughly 1,000 physical qubits per logical qubit) and a moderate logical qubit count (say 48 to 128 qubits.)
QRAM might be a distant future tipping point for a future generation of quantum computing, but not for quantum computing as it is currently envisioned.
A universal quantum computer merging both classical and quantum computing might be a distant future tipping point for a future generation of quantum computing, but not for quantum computing as it is currently envisioned.
Quantum networking is unlikely to be a tipping point. The capabilities of a standalone quantum computer will need to pass a tipping point before networking them will have any utility.
What metrics can we trust for judging tipping points? Can we trust any of them?
For reference, tipping point(s) for classical computing. So many great choices but so difficult to pick just one. Or even a few.

The problem

The focus of this informal paper was originally intended to be tipping points and whether quantum computing really is near a critical tipping point, but the closer I looked at the issue, the more complicated it became.

First, I realized that many of the candidates for tipping points are really simply milestones. Some are more minor milestones, but some are more significant milestones as well.

That raises the question of whether there are numerous, incremental tipping points, or whether one (or more) of those stepping stone milestones really deserves to be granted the loftier status of being the essential, critical tipping point.

And that leaves us pondering whether there can realistically be only a single tipping point or whether there are at least a handful of milestones worthy of the lofty title of tipping point.

All of this leads up to recognizing that quantum computing is really going through a sequence of stages, each with numerous milestones.

Whether any of these stages is itself the tipping point, or whether each stage has its own critical tipping point is debatable.

Further, there are a very wide range of personas and use cases for quantum computing, each of which has its own stages, milestones, and potential tipping points, which are not necessarily all in sync.

In short, we can each have our own perspective on what the tipping point for quantum computing will be — or was.

Background

The genesis of this informal paper was a comment I made on a LinkedIn post about tipping points for quantum computing:

It’s a simple but complicated question. I may write about it in the coming weeks. I already have some notes, but too much to fit in this tiny box or even a short post. Short answer: “Maybe, sort of, but not quite, and it depends on what you mean and what your interests really are.” For example, researchers, hardware vendors, software vendors, tool vendors, algorithm designers, application developers, customers, users, and business managers could all have different answers. And various qubit technologies could have different answers (e.g., Intel silicon spin qubits or Microsoft topological qubits.) As well as whether your interest is evaluation, prototyping, and experimentation, or production-scale production deployment for full practical quantum computing. And if you believe that the goal is fault-tolerant quantum computing, then clearly we aren’t there yet.

Why care about a tipping point or why bother calling out a particular milestone or stage?

Why bother with identifying a tipping point at all? Some possibilities:

Pure ego.
Indication of achievement.
Scientific achievement.
Technical achievement.
Functional achievement.
To measure where we are.
To understand how far we have to go.
Prove that we can solve a problem.
Financial achievement.
Marketing advantage.
Sales tool.
Gating factor for whether to proceed with projects utilizing a technology.

I’m not here to pass judgment, just to identify what issues are in play.

Milestones, tipping points, critical mass, breakthroughs, advances, etc.

A lot of jargon gets tossed around so much that it becomes difficult to distinguish what’s what. For example:

Stage.
Phase.
Milestone.
Tipping point.
Turning a corner.
Turning point.
Critical mass. Generally implies a tipping point.
Gamechanger. Should be a synonym for tipping point, but generally used as mere hype.
Point of no return.
Inflection point.
Breakthrough. In theory, this is a good candidate for a tipping point, but too often it is just a hyped advance or incremental progress. Too often, a breakthrough is immediately followed by a long, slow slog to… the next breakthrough — rinse and repeat.
Breakout. Now we’re getting somewhere. Now we can really do something and see some tangible results from all of our hard work.
Advance. Generally not sufficient for a tipping point, but it well could be since sometimes relatively modest advances can sometimes have a significant impact.
Progress. Ditto. Generally a synonym for an advance. Whether progress is palpable and enables real work can be debatable. Sometimes progress is simply what happens between advances.
Threshold.
Boiling point.
Frontier.
Frenzy.
Enthusiasm.
Energy.
Commitment.
Staying power.
Sustainability.
Ongoing evolution.

To my mind, stages and milestones are the most critical. Merely using tipping point as a synonym for stage or milestone seems trivial.

And attempting to single out a particular stage or milestone as the essential and critical tipping point seems problematic and subjective at best.

Malcolm Gladwell’s conception of a tipping point

In his popular book The Tipping Point, Malcolm Gladwell defined a tipping point for any phenomenon as:

the moment of critical mass, the threshold, the boiling point

And he goes on to say:

Ideas and products and messages and behaviors spread like viruses do

For more on Gladwell’s conception of tipping points:

The assumption is generally that when people refer to tipping points, they tend to mean what Gladwell means, or at least what they imagine that Gladwell means.

Tipping point vs. milestones

It is really tempting to look at milestones and be so impressed by them that you want to call them tipping points, but it’s not particularly helpful if all milestones are treated as tipping points or if there are too many tipping points.

Milestones can be categorized as:

Mundane milestones.
Significant milestones.
Major milestones.

Maybe it’s the more significant or major milestones which really are good candidates for tipping points.

Should enthusiasm be considered a tipping point?

Personally, I would consider enthusiasm as a more trivial tipping point — mere popularity, as opposed to achieving significant real business value.

Should the availability of real quantum computing hardware be considered a tipping point?

Producing working quantum computing hardware is certainly a notable achievement, a real milestone, but I’m reluctant to call it a tipping point since there is so much more that is needed to achieve even basic practical quantum computing than running trivial quantum circuits.

Should the availability of development tools be considered a tipping point?

Development tools for quantum algorithms and quantum applications are indeed critical, but once again, the mere availability of such tools falls far short of practical quantum computing or delivering significant real business value.

Financial vs. functional milestones and tipping points

One of the main decision points or criteria is whether to focus on financial milestones or function milestones as candidates for tipping points.

Financial milestones include;

Investment funding.
Revenue. Pricing. Options. Volume.
Profit. Profit margin. Volume. Aggregate, net profit.
Sustainable financial condition over an extended and extending period of time. Maintaining and growing investment, revenue, and profit.

Functional milestones include:

Raw science.
Raw technology.
Technical gating factors.
Products and services development.
Products and services initial availability.
Products and services widely applicable.
Market development.
Products and services adopted widely.
Products and services pervasive.
Products and services evolved over time.

Market development includes:

Product planning.
Marketing communication.
Training.
Sales development. Business development.
Ecosystem development.

Should vendor revenue or profitability be considered a tipping point?

Some will consider vendor profitability or at least substantial revenue as a tipping point, but once again, I’d object since it avoids the issue of achieving production-scale practical quantum computing and significant real business value.

That said, vendors achieving significant revenue and significant profitability might well happen to coincide with achieving production-scale practical quantum computing and their customers achieving significant real business value.

But, it’s also possible and even likely that customers will invest a lot of money years in advance of actually achieving significant real business value.

So, maybe vendor financial health is not necessarily such a bad indicator of a tipping point.

But, it might be even better to look at the underlying technology that is driving revenue and profitability, and better to consider the technology itself as the tipping point.

Should vendor funding and investment flows be considered a tipping point?

Some people do have a serious financial orientation so that investment flows and funding of vendors will seem to them as critical factors, and at some point rise to the level of being a so-called tipping point.

Maybe the transition from trivial investment flows to significant investment flows will be considered critical enough to warrant being labeled as a tipping point.

And maybe the transition from significant investment flows to mega-investment flows will be considered an even bigger tipping point.

But, all of this evades the central concern of achieving production-scale practical quantum computing and delivering substantial real business value.

External, business-oriented effects as possible tipping points

There are plenty of internal and technological milestones and stages that could be considered tipping points, but maybe external, business-oriented effects should be the central focus. Such as:

Organizations are beginning to see substantial real business value actually materializing. Degrees of realization of substantial business value
Organizations are beginning production-scale deployments.
Infrastructure finally in place to enable production-scale applications.
Organizations using simulators more heavily for production-scale scalable algorithms in anticipation of the imminent arrival of production-scale hardware.
Organizations pursuing actual development of production-scale applications, using simulators.
Organizations are beginning to use simulators for production-scale scalable algorithms, anticipating the hardware to come within two to three years.
The ENIAC Moment. Production-scale practical real-world quantum applications.
Configurable packaged quantum solutions. Easy to put quantum applications into use without elite quantum teams.
The FORTRAN Moment. High-level programming model enabling full custom quantum algorithm and application development without quantum expertise or super-elite quantum teams. Shift from a dedicated quantum computing team (or outsourcing) to regular IT teams.
Full promise of quantum computing is achieved on a widespread basis.

Maybe a twofold tipping point for organizations

Maybe the significance of quantum computing for most organizations can be split into two categories:

Organizations can conceptualize, design, develop, deploy, and operate quantum applications with ease and at relatively low cost.
Organizations experience significant real business value.

The latter matters most, but the former is a necessary prerequisite.

Should only the latter be the true tipping point, or should the former be a tipping point as well, a technology tipping point in contrast with the latter being a tipping point for the business in addition to being a technology tipping point?

Maybe two main tipping points

Coming up with a single tipping point is a real challenge, but maybe there are two main tipping points of interest for quantum computing:

Technical feasibility of practical quantum computing. Hardware, software, tools, algorithms, and applications.
Achieving substantial business value.

Somehow, a critical mass is needed for a tipping point

The concept of a critical mass is essential to a tipping point. What exactly there is a critical mass of is not predetermined, but a critical mass of something is required. The something could be:

Technical features and functions.
Technical capacity.
Technical performance.
Overall technical capability.
Installed base.
Customers.
Users.
Algorithms.
Algorithm capacity.
Applications.
Aggregate investment.
Aggregate revenue.
Aggregate profit.

Maybe my three stages of adoption for quantum computing are decent candidates for tipping points

We’re currently deep in the pre-commercialization stage of quantum computing, characterized by research, prototyping, and experimentation. But eventually we’ll break out of this stage with three main subsequent stages:

The ENIAC Moment. The moment when a super-elite team is able to demonstrate the first production-scale practical real-world quantum application.
Availability of configurable packaged quantum solutions. Enable customers to deploy packaged quantum solutions customized for their own organization’s needs without any need for elite quantum technical staff or any need to touch or even look at quantum algorithms or quantum application code.
The FORTRAN Moment. A true high-level quantum programming model which enables non-elite IT teams to design, develop, and deploy quantum applications without any quantum-specific technical knowledge.

Each of these stages would be breathtaking tipping points.

For more on these stages, see my informal paper:

For more on pre-commercialization, see my informal paper:

The ENIAC Moment as a possible tipping point

The ENIAC Moment will be the moment when a super-elite team is able to demonstrate the first production-scale practical real-world quantum application. This would be an excellent candidate for a tipping point. A lot of technical gating factors will have to come together to make this happen.

The first such quantum application might not be sufficient to really get the ball rolling. It may be necessary to have several such quantum applications before the full power of the moment, the tipping point, really sinks in.

The first configurable packaged quantum solution as a possible tipping point

The initial availability of a configurable packaged quantum solutions would enable customers to deploy packaged quantum solutions customized for their own organization’s needs without any need for elite quantum technical staff or any need to touch or even look at quantum algorithms or quantum application code. This would be an excellent candidate for a tipping point. A lot of technical gating factors will have to come together to make this happen.

The FORTRAN Moment as a possible tipping point

The FORTRAN Moment will be the moment when a non-elite IT technical team is able to design, develop, and deploy a quantum application without any quantum-specific technical knowledge.

The availability of a true high-level quantum programming model and matching high-level quantum programming language would be an excellent candidate for a tipping point. A lot of technical gating factors will have to come together to make this happen.

A high-level quantum programming model as a possible tipping point

The current low-level quantum programming model is a severe impediment to developing quantum algorithms and applications. The advent of a high-level programming model could be a real tipping point, but a variety of other technical gating factors may have to come together to achieve a true tipping point.

A high-level quantum programming language as a possible tipping point

Although a high-level quantum programming model alone might be a potential tipping point, a matching high-level quantum programming language might help to seal the deal.

Maybe achievement of my proposal for a quantum computer with 48 fully-connected near-perfect qubits would be a tipping point

I endeavored to conceptualize the requirements for a practical quantum computer, a minimal configuration which would enable practical quantum applications. The essential capabilities:

48 qubits.
Near-perfect qubits. Four nines or at least 3.5 nines of qubit fidelity.
Full qubit connectivity. To support complex quantum algorithms.
At least 2,500-gate circuits. To support reasonably complex quantum algorithms.
Fine granularity of phase and probability amplitude. To support 20-bit quantum Fourier transform and quantum phase estimation. Enable quantum computational chemistry.
20-bit quantum Fourier transform and quantum phase estimation. Enable quantum computational chemistry. Enable a 1,000,000X quantum advantage.
1,000,000X quantum advantage. Significant quantum advantage is the whole point of quantum computing.

That could really get the ball rolling for practical quantum computing. A definite tipping point.

For more on my proposal, see my informal paper:

Maybe widespread use of 40-qubit quantum algorithms would be a tipping point

At present, it is very rare to see published (and tested) quantum algorithms using more than 20 or even 16 qubits, even though 24, 28, and 32-qubit algorithms can readily be run on simulators even if reliable quantum hardware is not yet available. No significant quantum advantage will be achieved with such trivial algorithms. We need to see 24, 28, 32, 36, and even 40-qubit quantum algorithms before we can reasonably assert that any tipping point has been achieved.

For more on my thinking about the need for 40-qubit quantum algorithms, see my informal paper:

Maybe transitioning out of the pre-commercialization stage would be a tipping point

We’re currently deep in the pre-commercialization stage of quantum computing, characterized by research, prototyping, and experimentation. Kind of hard to hit a tipping point in that stage, other than to mark that it’s time to move on to commercialization.

The risk is that people are tempted to prematurely move on to commercialization — what I call premature commercialization — claiming a false tipping point when much pre-commercialization work remains to be done. Including and especially research. Lots of research is still needed.

But when the time does come, when sufficient research has been completed, when sufficient prototyping has been completed, when sufficient experimentation has been completed, and when product planners really do have all of the information they need to plan and execute development of viable products and services suitable to enable practical quantum computing and eventual delivery of substantial real business value, then it could make sense to call that a tipping point.

But even then, is it the exit from pre-commercialization that is the real tipping point, or is it the actual delivery of viable products and services suitable to enable practical quantum computing and the actual realization of substantial real business value that is the real tipping point? Both are legitimate milestones, but what exactly should the criteria be for a true tipping point?

For more on pre-commercialization, see my informal paper:

For more on premature commercialization, see my informal paper:

Adoption of quantum computing as a tipping point

Raw technology or even products and services sitting on a shelf or in a catalog are not terribly useful by themselves. What’s really needed, the real tipping point, is adoption — and deployment.

There are two stages of adoption:

Enabling adoption. Marshaling all of science, engineering, technology, products, and services so that adoption is possible — enabled.
Successful adoption. Making use of the technology. Development, deployment, operation, use, and eventually realization of substantial real business value.

No, prototyping and experimentation are not a tipping point

We’re currently deep in the pre-commercialization stage of quantum computing, characterized by research, prototyping, and experimentation, but as valuable as prototyping and experimentation are, they do not constitute a tipping point for practical quantum computing.

They are indeed a very useful precursor to more serious efforts to design quantum algorithms and develop quantum applications, but although that is very necessary, it is not sufficient for a true tipping point.

The transition out of the pre-commercialization stage would be a more reasonable candidate for a tipping point for quantum computing. That would be the point at which the primary focus is no longer mere prototyping and experimentation.

Should full quantum error correction and fault-tolerant quantum computing be the essential tipping point?

There are plenty of people who really believe in the value of the NISQ era, while at the same time harboring the full expectation that the noise problems of NISQ will be fully resolved with full quantum error correction (QEC), which will take us to the era of fault-tolerant quantum computing, and that will be the ultimate tipping point.

Just a few years ago I was one of those people, but as I dug deeper into quantum error correction, I realized that there were many difficult hurdles and that full quantum error correction might in fact be an insurmountable hurdle. Instead, I came to believe that near-perfect qubits would be a much better near-term and medium term objective.

So, in short, no, I don’t believe that full quantum error correction and fault-tolerant quantum computing will be the essential tipping point for quantum computing.

But near-perfect qubits may in fact be the tipping point.

For more on my journey into the land of quantum error correction, see my informal paper:

Full quantum error correction and fault-tolerant quantum computing as a tipping point

There should be no question that achieving full quantum error correction and fault-tolerant quantum computing would be a truly consequential tipping point — if it can be achieved. Personally, I don’t seriously believe that we will get there, at least not any time soon (not in the next five years), but that shouldn’t stop us from nominating it as a very consequential tipping point.

Note: I may have the math wrong here for computing physical qubits per logical qubit for various surface code distances, d. I used d² so that d = 5 requires 5² = 25 physical qubits, but the proper formula might be 2 * d² minus 1 so that d = 5 requires 2 * 5² minus 1 = 2 * 25 minus 1 = 50 minus 1 = 49 physical qubits, and d = 3 requires 2 * 3² minus 1 = 2 * 9 minus 1 = 18 minus 1 = 17. So, 1,000 physical qubits per logical qubit would imply d = 21 or d = 23 rather than d = 29 or d = 31 as given below. And even this math may not be valid for variations of surface code. But I’ll stick with the simpler formula for now to just give a ballpark sense of the magnitude.

Two separate tipping points, or at least major milestones for an overall tipping point:

Demonstration of full quantum error correction and fault-tolerant quantum computing. For a modest error correction code distance (d, say 3, 5, 7, or 9 for 9, 25, 49, or 81 physical qubits per logical qubit) and a modest logical qubit count (say 8 to 20 qubits.) Not sufficient to deliver significant real business value, but sufficient to prove that full quantum error correction and fault-tolerant quantum computing are not total fantasy.
A strong candidate for a tipping point is when full quantum error correction and fault-tolerant quantum computing can function at a level sufficient for at least some production-scale practical real-world quantum applications. For a substantial error correction code distance (d, say 29 or 31 — roughly 1,000 physical qubits per logical qubit) and a moderate qubit count (say 48 to 128 qubits.)

Significant milestones or possibly even tipping points along the way:

Error correction code distance. From d = 3 to 31.
Physical qubits per logical qubit. From 9 to 1,000.
Logical qubit count. From 5 to 500.

Some milestones for error correction code distance:

3. The minimum. But at least it’s a start.
5, 7, 9. Still minimal. But showing progress.
13, 15, 17. Moderate. Real progress. But still not suitable for real applications.
21, 23, 25. Getting there.
29, 31. We’re there. At least in theory. Now we can test whether practice can fulfill theory.

Some milestones for physical qubits per logical qubit:

9. For d = 3.
25. For d = 5.
49. For d = 7.
81. For d = 9.
169. For d = 13.
225. For d = 15.
289. For d = 17.
441. For d = 21.
529. For d = 23.
625. For d = 25.
841. For d = 29.
961. For d = 31.

Some milestones for logical qubit count:

5.
8.
12.
15.
16.
18.
20.
24.
28.
32.
36.
40.
44.
48.
50.
56.
64.
72.
80.
96.
100.
110.
128.
160.
192.
256.
384.
512.

Maybe near-perfect qubits will be the essential tipping point

Near-perfect qubits (four nines or at least 3.5 nines of qubit fidelity) won’t be perfect, but will enable a wide range of quantum algorithms and quantum applications. This could be a real and meaningful tipping point and enable a lot of use cases for quantum computing.

I would personally rate this as one of my top candidates for a tipping point for quantum computing. A number of other technical gating factors must also be met, but this may be the biggest and hardest one.

For more on near-perfect qubits, see my informal paper:

Full any-to-any qubit connectivity will be necessary but not sufficient for a tipping point

Near-perfect qubit fidelity will be required in addition to full any-to-any qubit connectivity in order to hit a tipping point for quantum computing. Full any-to-any qubit connectivity alone will not be enough.

Trapped-ion quantum computers currently have full any-to-any qubit connectivity, by definition, but their qubit fidelity is not sufficient to enable larger quantum algorithms which would be sufficient to say that a tipping point has been reached.

Performance and quantum advantage as a tipping point

The whole point of quantum computing is supposed to be a perceived dramatic performance advantage, so-called exponential speedup.

Quantum advantage could be a variety of levels:

Any advantage, even trivial.
Minimal quantum advantage. Maybe 1,000X a classical solution.
Substantial or significant quantum advantage. Maybe 1,000,000X a classical solution.
Dramatic quantum advantage. Maybe one quadrillion X a classical solution.
Quantum supremacy. No classical computer could compete in any reasonable amount of time, or even ever.

Any of these levels could be considered a tipping point.

For more on quantum advantage and quantum supremacy in general, see my informal paper:

For more on dramatic quantum advantage, see my informal paper:

For more on minimal or substantial or significant quantum advantage, see my informal paper:

For some additional nuances of quantum advantage, see my informal paper:

We need to see a lengthy catalog of production-scale quantum applications which exhibit significant quantum advantage for practical real-world problems

A handful of production-scale quantum applications demonstrating significant quantum advantage for practical real-world problems would certainly be an interesting and significant tipping point, but a lengthy catalog of such quantum applications would be a much more impressive tipping point.

Somewhere between a few and many would be the true tipping point, where a mere trickle turns into a flood. That’s the true meaning of a tipping point, that transition, the boiling point.

And maybe quantum supremacy should be the critical tipping point

Maybe quantum supremacy should be the critical tipping point, the point where no classical computer could compete in any reasonable amount of time, or even ever.

Or maybe some significant quantum advantage is good enough?

For more on quantum supremacy and quantum advantage, see my informal paper:

Wasn’t 50–60 qubits supposed to be the performance tipping point?

At one point, like five years ago, it was accepted wisdom that a quantum computer with 50 to 60 qubits could perform computations at a rate that no classical computer could compete with.

Well, we now have quantum computers with 53, 65, 80, and 127 qubits, but… what happened?

Well, it turned out that raw qubit count alone was not enough. Other factors mattered as well, such as:

Qubit fidelity.
Qubit connectivity.
Coherence time. Limits maximum circuit size. And limits qubit fidelity.
Maximum circuit size. Limited by coherence time.
Fine granularity of phase and probability amplitude. Required for non-trivial quantum Fourier transform and quantum phase estimation, such as needed for quantum computational chemistry.

Maybe 50 to 60 qubits will still turn out to be a tipping point, once these other factors are addressed as well.

No, hundreds, thousands, or millions of qubits won’t be tipping points

Raw qubit count alone will not constitute a tipping point. Qubit fidelity and connectivity will be the more constraining technical factors.

We already have quantum computers with 40, 53, 65, 80, and 127 qubits, but we rarely see quantum algorithms using more than 20 qubits. The recent record for Quantum Volume (QV) was 32768 — equivalent to 15 qubits.

So, hitting milestones for hundreds, thousands, or millions of qubits won’t be a tipping point which opens up the floodgates for quantum algorithms and quantum applications.

Maximum quantum circuit size as a tipping point

Maximum quantum circuit size is a critical gating factor for quantum computing to enable larger and more complex quantum algorithms. There is no clear and singular tipping point identified at this stage, but something is needed. Some candidates for maximum circuit size as a tipping point to enable larger and more complex quantum algorithms, such as to support quantum Fourier transform and quantum phase estimation, particularly to enable quantum computational chemistry:

250 gates. On the low end.
500 gates. On the low end.
750 gates. Still on the low end.
1,000 gates. Starting to get interesting.
1,500 gates. More interesting.
2,500 gates. Good candidate for a tipping point.
5,000 gates. May be past the tipping point.
7,500 gates. Likely past the tipping point.
10,000 gates. Slam dunk as past the tipping point.

Whether 1,000, 1,500, or 2,500 should be used as a tipping point is debatable, but either is a decent candidate.

Note that supporting such maximum quantum circuit sizes will be critically dependent on coherence time, gate execution time, and qubit fidelity. Maximum quantum circuit size as a singular tipping point may avoid the need to use any of those other three factors as a distinct tipping point, but it may make sense to list all relevant technical gating factors as tipping points.

Support for quantum Fourier transform and quantum phase estimation as a tipping point

Quantum Fourier transform and quantum phase estimation are the most powerful algorithmic techniques known for quantum computing, such as needed for quantum computational chemistry.

Unfortunately they are very intensive and a host of technical gating factors will be needed to enable them, including qubit fidelity, qubit connectivity, fine granularity of phase, and maximum quantum circuit size.

But once all of these requirements are met, support for quantum Fourier transform and quantum phase estimation would be an excellent candidate for a tipping point for quantum computing.

Support for quantum computational chemistry as a tipping point

People are attempting to implement quantum computational chemistry today, to a limited degree, but the results are rather unimpressive. Typically, inefficient variational methods are used. But they’re used precisely because the hardware is not sufficient to support quantum phase estimation.

Support for quantum Fourier transform and quantum phase estimation should enable quantum computational chemistry in its full, quantum glory.

The moment when quantum chemists are finally able to fully utilize quantum Fourier transform and quantum phase estimation should be a true watershed moment for quantum computational chemistry — and would be a great candidate for a tipping point for quantum computing.

Maybe the combination of a more ideal qubit technology and quantum processor architecture would be an ideal tipping point

Qubit technology and quantum processor architecture are both very critical technical gating factors for effective and practical quantum computing. Getting both to a significantly better position could indeed be a real tipping point.

The combination needs to better support significant quantum parallelism.

And it needs to enable dramatic or at least significant quantum advantage.

Either qubit technology or quantum processor architecture alone could be a tipping point, but the combination could seal the deal.

There are so many more detailed technical gating factors that constrain achieving a more ideal qubit technology as well as for a more ideal quantum processor architecture. Any or some combination of them could also be candidates for tipping points if it is clear that they will inevitably or promptly lead to a more ideal qubit technology as well as a more ideal quantum processor architecture.

I’m tempted to call the combination of a more ideal qubit technology and a more ideal quantum processor architecture as the most ideal tipping point, but it will ultimately depend on how the technology incrementally unfolds, which factor gets to the tipping point stage first.

Do we need to wait for the hardware to hit a tipping point or is simulation of scalable quantum algorithms sufficient?

Do we need to wait for the hardware or is simulation good enough? That’s an interesting question and it seems as if people presume that we must wait for quantum computer hardware to advance before we can hit a tipping point for quantum algorithms.

But I believe that simulation of scalable quantum algorithms is a better path to a quantum tipping point than sitting around waiting for better hardware or contorting and distorting our quantum algorithms in absurd ways to accommodate current quantum hardware.

Granted, we may only be able to simulate up to 40 to 50 qubits, but that could be sufficient if we carefully design our quantum algorithms to be scalable, so that algorithms which work at 32 to 40 qubits should work for 50 to 80 qubits, or more.

And the simulator needs to be configured to match the capabilities of real hardware expected in two to five years.

Besides, we currently have virtually nothing in the way of quantum algorithms utilizing 24 to 40 qubits. So even if better hardware arrived tomorrow, we wouldn’t be prepared to use it and utilize it effectively. Better to get busy on 24 to 40-qubit algorithms now, simulate them, and be ready for better hardware when it does arrive.

We do need more advanced algorithm analysis tools to detect gate patterns and gate parameters which are not scalable, such as dependence on fine granularity of phase and probability amplitude. And limits of coherence time and maximum circuit size.

In short, we should focus on simulating 24 to 40-qubit quantum algorithms now.

For more on scalable quantum algorithms, see my informal paper:

Is our own imagination and creativity the real limiting factor in hitting a tipping point rather than hardware or algorithms per se?

Too many people are focused on trying too hard to squish and twist their quantum algorithms to run on current quantum hardware.

We really do need to distance ourselves from the limitations of existing and near-term quantum hardware.

Let our imaginations and creativity guide us to new and novel algorithms and architectures that will enable more powerful tipping points.

And then we can focus on simulation and analysis of scalable quantum algorithms rather than relying on existing real hardware until our more ideal hardware can eventually be brought into existence.

So, the essential question is how we can indeed manage to unleash our own hidden, masked, and repressed potential.

To each their own… tipping point

Even if we could identify and characterize a clear tipping point (or multiple tipping points) for quantum computing, each persona or use case might have a distinct interpretation of what or when that tipping point might be. Some may need:

Greater capacity. More qubits.
Greater qubit fidelity. Lower error rate.
Greater qubit connectivity. For more complex quantum circuits.
Greater circuit size. Longer coherence time and/or shorter gate execution time for more complex quantum algorithms.
An algorithmic breakthrough. For their particular use case.
More time to develop their application. For their use case, algorithm, and situation.

Personas — each may have their own conception of a tipping point

Each persona may have their own needs for quantum computing, and hence their own tipping points.

The main categories of personas interested in quantum computing:

Researchers.
Vendors.
Customers.
Investors.
Analysts.
Policymakers.
Media. Technical and non-technical.

Stages of research:

Theory.
Experimental.
Applied.

Areas of research:

Hardware.
Software.

Areas of hardware research:

Qubit technology. Not at all clear if we are even close to the ultimate qubit technology needed for practical quantum computing.
Error mitigation, suppression, and correction.
Hardware programming model.
Processor architecture.
System architecture.
Modular systems.
Networked systems.

Areas of software research:

Infrastructure software.
Development tools.
Software programming model.
Quantum programming languages.
Algorithms.
Applications.
Benchmarking.
Simulators.

Categories of vendors:

Hardware.
Hardware components.
Software.
Development tools.
Algorithms.
Applications.
Training.
Consulting.
Services.

Categories of customers:

Different industries. Different needs. Different capabilities needed. Different capacities and performance needed.
Purchase off-the-shelf products and services from vendors.
In-house development of tools, algorithms, applications, and solutions.
Users.
IT. Deploy and maintain access to quantum applications.
Technical management.
General management.
Executive management.
Business managers. Responsible for the needs for specific lines of business. Intensely focused on business value.

Just as one example:

Researchers. May reach two or more tipping points: 1) conception of scientific advances, 2) realization of scientific results in the lab, and 3) upon publication of critical enabling science results.
Vendors. May reach a tipping point upon delivery and distribution of products enabled by that science.
Customer technical staff. May see three or more tipping points: 1) access to enabling technology, 2) production-scale development underway using the technology, 3) testing of completed products or applications, and 4) production deployment and operation of production-scale quantum solutions.
Customer management. May see three or more tipping points: 1) realization that development of solutions using the technology are underway, 2) solutions are deployed and in use, 3) business value is measurably achieved, with degrees of value achieved.

There are a lot of distinct tipping points in there. Which should be anointed as the singular essential tipping point?

For more information on personas, use cases, and access patterns, see my informal paper:

Use cases — each may have their own conception of a tipping point

Each use case or quantum application category or even each particular deployment of a particular quantum application may have its own conception of a tipping point.

For example, even for the category of quantum computational chemistry, for a specific computation, different users may have different tipping points based on complexity of the molecules being studied. Some users may be working with only relatively simple molecules, while other users may be working with significantly more complex molecules.

The only point here is that the actual tipping point could matter based on the particular use case. The actual tipping points for particular use cases are far beyond the scope of this informal paper.

For more information on use cases, see my informal paper:

For more information on application categories for quantum computing, see my informal paper:

Would cracking 2048-bit encryption keys with Shor’s factoring algorithm be a reasonable tipping point?

Cracking 2048-bit encryption keys with Shor’s factoring algorithm would certainly be a very notable tipping point, but it isn’t going to happen any time soon (like within the next few years), and in my view is not ever going to happen at all, even with an ideal quantum computer.

This may in fact be the most distant tipping point we can envision at this stage, other than cracking even larger keys, such as 3072, 4096, and 8192-bit encryption keys.

For more on the reasons why it is unlikely that Shor’s factoring algorithm will likely never work for larger encryption keys, see my informal paper:

Might QRAM be a tipping point?

The concept of a quantum random access memory (QRAM) might be a key enabling technical feature for quantum computing, facilitating larger and faster input and output of classical data, possibly even enabling quantum computing to directly access, work work, and even generate so-called big data, but the concept is still not well understood or even known whether it might even be technically feasible, or when it might be feasible, so although it is very intriguing and has great potential, it is premature to consider it a tipping point for quantum computing.

It might be that QRAM has a brighter future much further out, but that’s too far out to try talking about it in any degree of specific detail at this juncture.

In short, theoretically QRAM could well indeed have great potential as a tipping point for a future generation of quantum computing, but for now, it is not even on the table for quantum computing as it is currently envisioned.

But by all means we should encourage and fund deep research on QRAM.

For more on my own views on QRAM, see the QRAM section of my informal paper:

Might a universal quantum computer be a tipping point?

A universal quantum computer merging both classical and quantum computing would have tremendous potential. That would make it a very compelling tipping point, but we are not even close to fully conceptualizing such a merger.

So, while a universal quantum computer would be a very appealing tipping point for a future generation of quantum computing, such an outcome for quantum computing is not even on the table for the foreseeable future as quantum computing is currently envisioned.

For more on my own vision for a universal quantum computer, see my informal paper:

Might quantum networking be a tipping point?

Quantum networking is unlikely to be a tipping point since the capabilities of a standalone quantum computer will need to pass a tipping point before networking them will have any utility.

A network of quantum computers will enable an ensemble of quantum processors with a larger number of qubits and enable distributed quantum computing, but each processor will still need a critical mass of quantum computing capabilities for the ensemble to have meaningful utility. It will be that critical mass within each processor that will likely be a tipping point before the networking of the processors will have utility.

One could consider quantum networking as a tipping point for distributed quantum computing, but once again, even that tipping point will still require a critical mass of capabilities for each of the distributed quantum processors.

What metrics can we trust for judging tipping points? Can we trust any of them?

It’s an open question as to what metrics or benchmarks we can trust for judging tipping points for quantum computing.

There are so many metrics and so many parameters and assumptions for the metrics.

The assumptions may work well for some applications but not for others.

Individual metrics might be reasonably robust, at least in isolation, at least sometimes. But how to choose which metrics will work best for a particular application or organization can be quite an daunting and onerous task.

Maybe, eventually, this will all sort itself out, with some core set of robust metrics. But until then, it will be quite a minefield and more a matter of subjective interpretation than objective fact.

Has quantum computing had a viral moment or is one yet to come?

One could argue that IBM making its quantum computers available to all comers in the cloud in 2016 sure seemed to be a viral moment, but if anything, it simply jumped the gun, spreading enthusiasm and premature promises but not presaging actual availability of production-scale practical quantum computers.

So, to answer the question, yes, quantum computing has had a viral moment, but, no, it wasn’t a viral moment for production-scale practical quantum computing and has not resulted in production-scale practical real-world quantum applications being developed and deployed in production, or the delivery of substantial real business value.

What technical gating factors will it take to achieve a true viral moment for practical quantum computing?

A number of technical gating factors need to be achieved before practical quantum computing will be… practical:

Qubit technology. With low enough noise, sufficient connectivity, sufficient coherence time, and an optimal combination of qubit count and maximum circuit size.
Quantum algorithms. That are capable of exploiting the qubit technology and deliver valuable results with an exponential speedup in performance.
Quantum applications. Exploiting both the qubit technology and quantum algorithms.
Identification of exciting use cases. For which quantum applications are feasible using the available qubit technology and quantum algorithms. And which deliver dramatic business value. And achieve a dramatic quantum advantage over classical solutions.

No, we’re not there yet

Sorry, but we have not yet achieved the technical gating factors listed above.

No, we’re not even close

Sorry, but we’re not even close to achieving the technical gating factors listed above.

A lot more research is needed.

How much longer?

It’s a slam dunk that we won’t get there this year.

It’s a virtual slam dunk that we won’t get there next year.

It’s plausible that we should get there in two to five years.

There are too many contingencies to narrow it down closer than that.

Are there any near-term tipping points?

I’ll refrain from weighing in as to whether there are any imminent near-term tipping points just around the corner, some special major milestone just waiting to happen.

I suspect not. But, as I like to say, never say never. Just don’t count on it, though.

To me, it just feels that we have another two or three years of hard-core research and engineering on the hardware side as well as on the algorithm side before we can even begin to imagine that we really are at a magical and special tipping point.

Sure, we’ll have plenty of milestones and maybe a couple of stages, but whether any of that amounts to a true, Gladwell-style tipping point remains to be seen.

Tipping point for a quantum winter?

I don’t think that a quantum winter is imminent, but it’s a possibility 18 to 30 months from now if we don’t start hitting more critical milestones — or technical tipping points — over the next year or two.

Ultimately, a tipping point for a quantum winter would be a dramatic slowing of investment and hiring, or an outright onset of significant layoffs. Or, maybe just public recognition that some technological wall or at least temporary technical barrier has been reached or is imminent.

A quantum winter wouldn’t necessarily be the end of the world. It might just be a prolonged slow period. It might only last a year or two or three, during which reality gradually catches up with past promises which jumped the gun.

For more on my thinking about quantum winter, see my informal paper:

For reference, tipping point(s) for classical computing

What exactly was the tipping point or tipping points, plural, for classical computing? Great question. But no clear answer.

Classical computing went through so many stages and evolved so greatly over the decades, that it’s difficult to label a single development as the singular essential tipping point.

But some top candidates for a singular tipping point might be:

Core memory.
File systems. Especially with hierarchy.
High-level programming languages (FORTRAN, et al).
The transistor.
The integrated circuit.
CMOS chips.
Semiconductor memory (DRAM).
Databases.
Artificial Intelligence (AI). Tools and applications.
Minicomputer.
PDP-10 operating systems. TOPS-10, Tenex, TOPS-20.
ARPANET.
VAX/VMS operating system.
Multics/UNIX operating system.
Microprocessor and microcomputer.
Personal computer (PC).
DOS operating system.
MacOS and Windows operating systems.
Personal productivity applications.
Laptop computers. Battery-powered and easily portable.
Server.
Networking.
The Internet.
Media. Audio, video, images. Printers.
Tablet, smart phone, and wristwatch computing devices and applications.
Semiconductor mass storage (Flash SSD).
Internet of things (IOT).
Robotics.

So many great choices. But does any really stand out that much more than the other — either now or at the time?

Functional capabilities which could also be tipping points included:

Processor architecture.
Processor speed.
Memory technology.
Memory capacity.
Storage technology.
Storage capacity.
Mode of operation.
Communication.
Networking.
Software.
Alternative computing devices.
Technology transitions.
Other technology transitions.

Modes of operation which could also be tipping points:

Single user.
Real-time.
Batch.
RJE. Remote job entry. Remote batch.
Timesharing.
Networking. ARPANET, online services.
Personal computers.
GUI. Graphical user interfaces.
Battery-powered and portable. Primarily laptops.
Servers.
Distributed computing.
Networked services.

Software capabilities which could also be tipping points:

Operating systems.
Support software.
Software development tools.
Applications.
Personal productivity applications.
Social media.

Alternative computing devices and form factors which could also be tipping points:

Mainframe.
Minicomputer.
Supercomputer.
Multiprocessor.
Superminicomputer.
Embedded system.
Microprocessor and microcomputer.
Personal computer.
Laptop computer.
Server.
Cluster.
Cloud.
Tablet.
Smart phone.
Wearable. Wristwatch.
Internet of things.

Technology transitions which could also be tipping points:

Unit record equipment. Punched cards.
Electromechanical relays.
Vacuum tubes.
Discrete transistors.
SSI integrated circuit chips. Small-scale integration
MSI chips. Medium-scale integration
LSI chips. Large-scale integration
VLSI chips. Very large-scale integration
Smaller processors and microcontrollers. PIC, Arduino.

Other technology transitions which could also be tipping points:

Memory.
Storage.
Input devices.
Output devices.
Display devices.
Media input and output. Microphone, camera, speaker, display, printers, scanners.
Communications and networking interfaces.

Again, so many great choices for tipping points. But does any really stand out that much more than the others — either now or at the time?

Walls, barriers, and obstacles for quantum computing

Technically, this isn’t directly relevant to this current informal paper, but more the flip side — what can interfere with progress rather than what constitutes progress for quantum computing.

Walls, barriers, and obstacles are the opposite of stages, milestones, and tipping points for quantum computing.

I might do a future informal paper focusing on the walls, barriers, and obstacles which interfere with progress for quantum computing.

Conclusions

There are plenty of possibilities for tipping points for quantum computing.
It’s almost literally a fielder’s choice for what stage or stages or milestone or milestones to use as the singular essential tipping point or to go with multiple tipping points.
Different personas and use cases could have their own perceptions of what should constitute a tipping point. To each their own.
I personally don’t think that we have already passed a tipping point. Practical quantum computing is not yet a slam dunk certainty.
And I personally don’t think that we have any imminent near-term tipping points staring at us in the face. Not in the coming year. And not likely in the next year. But maybe two to five years from now.
A strong candidate for a tipping point will be performance and quantum advantage.
Maybe quantum supremacy should be the critical tipping point. But for production-scale practical real-world problems, not contrived computer science experiments.The point where no classical computer could compete in any reasonable amount of time, or even ever. Or maybe some significant quantum advantage is good enough?
Wasn’t 50–60 qubits supposed to be the performance tipping point? But other factors matter more than raw qubit count.
No, hundreds, thousands, or millions of qubits won’t be tipping points. Raw qubit count alone will not constitute a tipping point. Qubit fidelity and connectivity will be the more constraining technical factors.
Maybe the combination of a more ideal qubit technology and quantum processor architecture would be an ideal tipping point. If it better supports significant quantum parallelism. And enables dramatic or at least significant quantum advantage. Either qubit technology or quantum processor architecture alone could be a tipping point, but the combination could seal the deal.
Do we need to wait for the hardware to hit a tipping point or is simulation of scalable quantum algorithms sufficient? I say the latter — simulate 24 to 40-qubit quantum algorithms now.
Is our own imagination and creativity the real limiting factor in hitting a tipping point rather than hardware or algorithms per se? Yes, we need to unleash our creative potential rather than be limited by current and near-term quantum hardware.
A strong candidate for a tipping point will be the availability of near-perfect qubits.
Full any-to-any qubit connectivity will be necessary but not sufficient for a tipping point. Near-perfect qubit fidelity will be required as well.
A strong candidate for a tipping point will be support for quantum circuits with upwards of 2,500 gates. Maximum quantum circuit size is a key technical constraint to enable larger and more complex quantum algorithms.
A strong candidate for a tipping point will be support for quantum Fourier transform and quantum phase estimation. Especially needed for quantum computational chemistry.
A strong candidate for a tipping point will be support for quantum computational chemistry. Relies on quantum Fourier transform and quantum phase estimation.
A strong candidate for a tipping point will be the availability of 40-qubit quantum algorithms. Or even 24, 28, 32, or 36-qubit algorithms.
A strong candidate for a tipping point will be the availability of a quantum computer with 48 fully-connected near-perfect qubits.
A strong candidate for a tipping point will be the advent of practical quantum computing.
A strong candidate for a tipping point will be the transition out of the pre-commercialization stage of quantum computing.
No, prototyping and experimentation are not a tipping point. They are valuable and useful precursors to more serious quantum algorithm design and quantum application development, but not a tipping point by themselves.
My three stages of adoption of quantum computing will be strong candidates for tipping points for quantum computing.
A strong candidate for a tipping point will be The ENIAC Moment. Advent of production-scale practical real-world quantum applications.
A strong candidate for a tipping point will be the advent of configurable packaged quantum solutions. Easy to put quantum applications into use without elite quantum teams.
A strong candidate for a tipping point will be The FORTRAN Moment. High-level programming model enabling full custom quantum algorithm and application development without quantum expertise or super-elite quantum teams. Shift from a dedicated quantum computing team (or outsourcing) to regular IT teams.
A strong candidate for a tipping point will be a high-level quantum programming model. Still relies on quite a few additional technical gating factors.
A strong candidate for a tipping point will be a high-level quantum programming language. Depends on a high-level quantum programming model, but the language might seal the deal.
A strong candidate for a tipping point is when the technology is ready for development of production-scale practical real-world quantum applications.
A strong candidate for a tipping point is when deployed production-scale practical real-world quantum applications are achieving substantial quantum advantage and delivering significant and measurable real business value.
A strong candidate for a tipping point would be a lengthy catalog of production-scale quantum applications which exhibit significant quantum advantage for practical real-world problems.
Demonstration of full quantum error correction and fault-tolerant quantum computing. For a modest error correction code distance (d, say 3, 5, 7, or 9 for 9, 25, 49, or 81 physical qubits per logical qubit) and a modest logical qubit count (say 8 to 20 qubits.) Not sufficient to deliver real value, but sufficient to prove that full quantum error correction and fault-tolerant quantum computing are not total fantasy.
A strong candidate for a tipping point is when full quantum error correction and fault-tolerant quantum computing can function at a level sufficient for at least some production-scale practical real-world quantum applications. For a substantial error correction code distance (d, say 29 or 31 — roughly 1,000 physical qubits per logical qubit) and a moderate logical qubit count (say 48 to 128 qubits.)
QRAM might be a distant future tipping point for a future generation of quantum computing, but not for quantum computing as it is currently envisioned.
A universal quantum computer merging both classical and quantum computing might be a distant future tipping point for a future generation of quantum computing, but not for quantum computing as it is currently envisioned.
Quantum networking is unlikely to be a tipping point. The capabilities of a standalone quantum computer will need to pass a tipping point before networking them will have any utility.
What metrics can we trust for judging tipping points? Can we trust any of them?
For reference, tipping point(s) for classical computing. So many great choices but so difficult to pick just one. Or even a few.

For more of my writing: List of My Papers on Quantum Computing.