vtomole

You're right. I didn't sufficiently separate experimental physics QC from engineering QC.

On the engineering end, the question on if a large-scale quantum computer can be built is leaning to be "yes" so far. DARPA QBI https://www.darpa.mil/research/programs/quantum-benchmarking... was made to answer this question and 11 teams have made it to Stage B. Of course, only people who believe DARPA will trust this evidence, but that's all I have to go on.

On the application front, the jury is still out for applications that are not related to simulation or cryptography: https://arxiv.org/abs/2511.09124

Quantum theory predicts this: https://en.wikipedia.org/wiki/Threshold_theorem. An experiment can show that this prediction is false. This is a scientific problem not an engineering one. Physical theories have to be verified with experiments. If the results of the experiment don't match what the theory predicts then you have to do things like re-examine data, revise the theory e.t.c.

Good point. I didn't sufficiently delineate what counts as a scientific problem and what counts as an engineering problem in QC.

Quantum theory, like all physical theories, makes predictions. In this case, quantum theory predicts that if the physical error rate of qubits is below a threshold, then error correction can be used to increase the quality of a logical at arbitrarily high levels. This prediction can be false. We currently don't know all of the potential noise sources that will prevent us from building a quantum logic gate that is of similar quality as a classical logic gate.

Building thousands of these logical qubits is an engineering problem similar to Dyson spheres and space elevators. You're right that the lower levels of building 1 really good logical qubit doesn't mean that we can build thousands of them, but when you are talking about building thousands of them you've escaped physics and moved into engineering.

Sure, I'm not disagreeing that this processor is noisy, just providing enough context to say that it's fine. Historically, these devices improve enough to be under threshold at which point it doesn't matter that they are noisy cause error correction protocols can be run on top of them.

This processor is state-of-the-art for silicon quantum computing. It's where modalities like superconducting were 15 years ago, and superconducting does not create noise these days https://www.nature.com/articles/s41586-024-08449-y

https://www.nature.com/articles/s41586-025-09848-5 performs CZ gates on up to 256 qubits with fidelities of 99.5%, which is good enough to run surface codes below threshold.

Quantum theory is so unlikely to be wrong that if large-scale fault tolerant quantum computers could not be built, the effort to try to build them will not be a dead end, but instead a revolution in physics.

Quantum theory says that quantum computers are physically plausible. Quantum theory lies in the realm of physics, not mathematics. As a physical theory, it makes predictions about what is plausible in the real world. One of those predictions is that it's possible to build a large-scale fault tolerant quantum computer.

The way to test out this theory is to try out an experiment to see if this is so. If this experiment fails, we'll have to figure out why theory predicted it but the experiment didn't deliver.

Depends on what we mean by "early days on hardware".

If we mean "we've have been working on this for almost 3 decades. That's a very long time to be working on something!". I agree.

If we mean "We just now only have a few logical qubits that outperform their physical counterparts and we'll need thousands of these logical qubits to run anything useful" then we are still in the early days.

"early days" means that the 1998 computer didn't have qubits that were below the error correction threshold. Now we have hundreds of qubits below threshold. We'll need millions of qubits like these for quantum computing to be useful. If that take decades, this is the "early days" relatively.

It's not only early days in hardware, it's early days in practical applications as well: https://arxiv.org/abs/2511.09124

> Is there a guarantee that these things can and will work given enough time?

Quantum theory predicts that they will work given enough time. If they don't work, there is something about physics that we are missing.

The graphs aren't telling you that QC hardware is not improving at a super-exponential pace?

There are no real world use cases today. The hardware is not advanced enough yet, but it's improving exponentially.

Oops, updated. Thanks!

QC progress happens super-exponentially: https://news.ycombinator.com/item?id=46383233

Silicon is not one of the leading modalities for quantum computers, but it has progressed a lot in the past ~2-3 years. Here are a few key advancements that have happened as of late:

- Intel can now do 2D which means a Surface code can be run on these devices: https://arxiv.org/abs/2412.14918

- HRL can now do 2D as well: https://arxiv.org/abs/2502.08861

- They are solving the wiring problem: https://www.nature.com/articles/s41565-023-01491-3

- Their interconnects are high fidelity: https://www.nature.com/articles/s41586-025-09827-w

No, and Shor's is not a good benchmark for these early quantum computers: https://algassert.com/post/2500

Which version did you read? I read this one: https://www.amazon.com/Meditations-Penguin-Classics-Hardcove..., which provides a lot of context. Here are my thoughts on it: https://vtomole.com/blog/2025/12/14/aurelius

Turns out, a lot of Plato this year. See https://vtomole.com/ for the list.

Yes, QC is far enough that it's "anyone's guess", but the field is actively working on sliding the answer to this problem from "anyone's guess" to "a bit more certain". It will never be 100% certain until the useful QC appears but we can decrease the probability of our predictions being pure guesswork. As an example, DARPA is funding a project to find the first high impact QC applications https://www.darpa.mil/work-with-us/publications-highlighting... along with finding when the first hardware to run those applications can be built https://www.darpa.mil/work-with-us/quantum-benchmarking-init....

QC startups should be funded because industry is a crucial component of QC progress and large-scale QC labs (Google, IBM e.t.c) can't work on all the ideas. The ideas that come from startups do accelerate QC development.

One application we care about is using quantum computers to build high resolution telescopes https://arxiv.org/abs/1107.2939. A wide area network is required because the telescopes need to be far apart.

You're welcome.

A quantum internet is absolutely necessary for creating a useful quantum computer, the same way the internet (LAN) is needed to create a supercomputer. A supercomputer is essentially many computers connected together. A quantum computer that solves problems we care about will be similar: https://arxiv.org/abs/2212.10609.

Right. We are now arguing over the nuances of what would make quantum computers useful, which I address in a comment where I say "Everything matters" later in this thread.

Most people who work in this field doubt that every quantum simulation problem we care about will be classical tractable in practice, that is, non worst-case. If we believed that, we might as well give up and continue to use the robust, mature classical computers we have and will continue to have better instances of for the foreseeable future.

Yes. It's a spectrum. In the worst case, quantum computers only help us gain a deep understanding of quantum physics. In the best case, they beat classical computers on optimizations problems as well. Materials science falls somewhere along this spectrum.

The people who claim that current quantum computers are useful for classical problems contribute to "Quantum hype" which is frowned upon by most members of the community.

I agree. "Everything" matters when it comes to these applications: complexity theory, heuristics, constant factors, quantum error correction overhead, qubit quality, improvements in classical algorithms, CPU and GPU improvements e.t.c. Doesn't make sense to put too much stock in just one of these components at the cost of others.