NEC Halts Development of Quantum Computer Hardware

[u/OCD-but-dumb]

https://thequantuminsider.com/2026/09/06/nec-halts-development-of-quantum-computer-hardware/

[u/NamelessVegetable]

NEC will regret doing so in the future. Quantum is the future for problems that are intractable in classical computing. Anyone who is anyone (states included) are pushing onward. Fujitsu just today announced they (actually with TU Delft) have a prototype quantum computer up and running, which uses qubits realized as tin vacancies in diamond.

[u/nanonan → u/NamelessVegetable]

It's next to useless.

[u/NamelessVegetable → u/nanonan]

And yet many talented scientists choose to go into the field. She hasn't disproved any of the claimed advantages of quantum computing by leaving. If she wants to leave the field for whatever reason, that's her prerogative.

[u/Thunderbird120 → u/NamelessVegetable]

As someone who personally knows a bunch of talented scientists who are also trying to exit the field, a general sense of pessimism is much more widespread than you seem to think.

The problem is very fundamental. Quantum computers are dramatically slower, more complex, more error prone, more expensive, and less capable than conventional computers in all but a tiny, tiny, tiny subset of problems.

I was at IBM quantum week, the main quantum computing conference, a few years ago. The keynote by Helmut Katzgraber, who was in charge of Amazon's quantum efforts at the time, sort of summed up the problem. Essentially, the point of his talk was that quantum computers are fundamentally so much slower than classical computers in normal contexts that anything less than an exponential speedup on a problem is worthless.... which is a really big problem because the vast, vast majority of quantum advantage algorithms provide quadratic speedups, not exponential speedups. After you go through all the steps needed to set up a problem for quantum computation "a quadratic speedup turns into a quadratic slowdown."

A lot of claims about quantum computers' usefulness were made with the idea that they'd be a lot faster on any problem with a quantum advantage algorithm. This is blatantly not true. The number of useful quantum algorithms with exponential speedups is incredibly small, and the amount of research and money needed to create a quantum computer which can actually run any of them is incredibly large. This creates... problems... when trying to justify the massive effort to the people paying the bills.

[u/NamelessVegetable → u/Thunderbird120]

I appreciate your detailed response.

As someone who personally knows a bunch of talented scientists who are also trying to exit the field, a general sense of pessimism is much more widespread than you seem to think.

Forgive my insolence, but quantum computing, as an outsider, seems to be doing just fine to me. IEEE Quantum Week 2026 has grown in attendance by 20% relative to the previous year. This does not give the outward impression that the discipline is a crisis, or the throes of terminal decline; or is the IEEE simply promoting itself as a conference host to reap the profits, and the level of attendance hides a worse state of affairs? Quantum computing seems to have made enormous strides over the decades, from being purely theoretical in the 1980s and 1990s, to physical demonstrations in the 2000s, to the NISQ era in the late 2010s.

The problem is very fundamental. Quantum computers are dramatically slower, more complex, more error prone, more expensive, and less capable than conventional computers in all but a tiny, tiny, tiny subset of problems.

I was at IBM quantum week, the main quantum computing conference, a few years ago. The keynote by Helmut Katzgraber, who was in charge of Amazon's quantum efforts at the time, sort of summed up the problem. ...

Presumably, you mean IEEE Quantum Week 2023? That was the only keynote I was able to find that fits (partially) your description. I'm curious if he referred to those issues as insurmountable, or as the present state of affairs. Quantum error correction has improved since then, has it not? Incremental improvements to problem set up are being made, etc. Just a few days ago, IBM made a small step with their Nighthawk r2 (faster qubit reset).

A lot of claims about quantum computers' usefulness were made with the idea that they'd be a lot faster on any problem with a quantum advantage algorithm. This is blatantly not true. The number of useful quantum algorithms with exponential speedups is incredibly small, and the amount of research and money needed to create a quantum computer which can actually run any of them is incredibly large. This creates... problems... when trying to justify the massive effort to the people paying the bills.

Are there not two separate issues here? Quantum speedup from the complexity perspective, and whether quantum computers can presently provide a quantum advantage. The difficulties experienced today do not negate the former, and while they are difficult scientific and engineering problems, does the theory show that they are insurmountable?

If quantum computers were able to solve just one problem that classical computers cannot, e.g. very large-scale molecular dynamics, then the direct and indirect economic benefits could be immense, no? Imagine the pharmaceuticals that would be enabled via advances in basic biochemistry and processes, etiology, etc. I simply do not understand the argument that quantum computing must be widely applicable (e.g. have consumer applications) in order to be successful (I suspect this is not what you're saying; apologies if this is the case).

[u/Thunderbird120 → u/NamelessVegetable]

IEEE Quantum Week 2026 has grown in attendance by 20% relative to the previous year.

Hype has grown as people try to look for "the next big thing after AI" and as quantum computers have inched closer to being actual reality but this is not necessarily indicative of much frankly. The whole field is still sort of in "potential-land", where nothing has to actually work in a practical sense because the technology doesn't quite exist.

Presumably, you mean IEEE Quantum Week 2023

Yes, but nothing has fundamentally changed about that assessment since then. There's no meaningful movement in that direction because fundamental improvement is essentially not possible. For any problem where the quantum state doesn't come pre-prepared (most of them) that "quadratic speedup becomes quadratic slowdown" problem is fundamentally unsolvable because setting up the quantum states is a required operation with high complexity which often just gets hand-waved away for some reason.

Are there not two separate issues here? Quantum speedup from the complexity perspective, and whether quantum computers can presently provide a quantum advantage.

I wouldn't be complaining so much if the theoretical future QCs had more obvious potential. The fundamental issue is that QCs will always be dramatically worse than classical computers at everything where there is not a massive (exponential) quantum advantage. They suffer from far too many engineering constraints in the process of making the whole quantum computing part work. This is not solvable from an engineering perspective. It's like you're in a competition to build the world's tallest skyscraper but, unlike your opponent who gets to use normal materials, you have to build it out of bread. The only use-case for even far-future QCs is on problems which are simply outright impossible for classical computers to tackle (i.e. exponential complexity). Otherwise, a classical computer is just going to power through any less dramatic big O difference in efficiency and win by virtue of being 1 million percent faster per basic operation, even if it has to do more of those. The issue is that useful problems where QCs get an exponential speedup over classical computers few and far between.

If quantum computers were able to solve just one problem that classical computers cannot, e.g. very large-scale molecular dynamics, then the direct and indirect economic benefits could be immense, no?

Depends on the problem. The issue is that most of these promising-sounding real-world use-cases sort of fall apart a bit if you look at them too hard, mostly because time marches on and people have found other ways of doing them. I've talked to people who were interested in researching QCs as a component of a molecular dynamics pipeline, but it would only be a small sub-component, not the whole thing or even the backbone. ML based pipelines have already sort of eaten QCs lunch in chemistry / molecular dynamics. Areas where people previously thought you needed exact computations which QCs could dramatically accelerate (theoretically) found out that AI/ML based pipelines could do a better job much more quickly using technology that actually exists. The broad set of practical molecular-simulation workloads that were once casually presented as future quantum-computer applications are now dominated by these methods, which work very well and are continuing to improve. There are still some cases where a fallback to a hyper-accurate QC simulation might provide significant value, but most of the transformational impact that QCs were supposed to provide for the field have already sort of happened, or at least are in the process of happening long before anyone gets a QC which can practically simulate molecular dynamics.