It is very irritating when people complain here that it's not faster than classical or other such complaints.
Please, it is still a research project, it's not like a regular computer just faster, it is novel research.
Regarding the quantum side, I would love to know if by programmable qubit are they referring to an error corrected qubit or just one where gates can be applied.
I suspect it means error corrected qubits. I was wondering if there was work being done on algorithms that are noise resistant and as such can take advantage of the raw qubit count instead of the error corrected qubit count.
I would love to work in this area but I think it's all research at the moment. It's really interesting, how it actually works, not just the hand wavy abstractions.
Programmable qubit is almost certainly referring to one where gates can be applied, non-error-corrected. The error correction overhead would be much larger than 4-to-1.
Although note, the above is if you are referring to error correction in the traditional sense of error correcting codes. According to Ars Technica's article [1], the non-programmable qubits are being used for leakage removal: coupling to the computational/programmable qubits and stabilizing them, but not being used for any computation themselves. This is far from error correcting codes in the mathematical sense, but it does have a similar purpose of reducing noise.
For what you are wondering about in your penultimate sentence is possible for any algorithms, I am not sure, but it's a very good question. However, I know that for general algorithms, there is a range of error reduction techniques you can use short of full QEC, IBM has a decent blog post about them [2]. Usually, the trade-off is error reduction vs increased number of shots and post-processing (so vs time, not space).
Generally if they say "qubit" they mean physical qubit, and if they say "logical qubit" they mean error-corrected (and would spend lots of time talking about whatever improvements to error correction they've made). In publicity stuff, unqualified, it will definitely mean physical qubit.
It's better to think of QPUs as highly specialized coprocessors that do certain things really well. You would only every really use them for problems they're good at. Like ALU vs FPU vs GPU.
Shor's algorithm is the quintessential example, but there are other algorithms (mostly graph algorithms) that are NP and hard would be very efficient on a quantum computer.
It’s healthier to think of neither depth nor speed. The space of problems best suited for quantum computers is altogether orthogonal to those dimensions.
IBM isn't in the research business. It's a for profit company that wants to sell you these machines for an incredible amount of money.
But it's all a scam since these machines can do nothing useful, except allowing you to try out programming simple quantum algorithms.
BTW they keep obfuscating the difference between logical and physical qubits. Logical qubits is what it's all about but this article sort of uses them interchangeably. Most of the time they're talking about physical qubits, though.
Someone once calculated that you'd need a million physical qubits to crack RSA-4096. That shows you how much farther we have to go for these machines to be useful.
And the reference is from IBM itself. So how can we be sure it isn't just PR?
One example: one of the countries with the largest population and thus an incredible large domestic market is China. When they do anything (or the government steers the industry to do anything) they often do it at a scale not known in the already developed world.
And now the west is withholding certain technology from China since it seems to be aggressive as well. Not as aggressive as Russia or the USA, but still. So they don't get various technology anymore. But so far all I know that one level in the chinese Huawai development center could host more researches than IBMs Zürich lab. Could. Not does.
And as a consequence they bumped out their research in this area.
And now my assumption: knowing how large-scale things in China are often done, I guess that they do their industrial research equally in a large scale. So I wouldn't wonder that e.g. Huawei has by now a larger research division than IBM.
The archived article from IBM mentions 3000 researchers. That's not THAT much. Just one of the 4 german institutionalized research agencies (Fraunhofer, Max Planck, etc) has more researchers. For me, it's not unthinkable that a big chinese company has 4000 researchers by now. Especially since they HAVE to research/steal key technology these days.
I would claim that IBM is an "applied research organization." Their research has the sole purpose of developing a product that they can sell. They're not like Bell Labs that does lots of basic research.
IBM's huge, modular dilution fridge is an interesting idea for superconducting plasmon qubits [1]. I really can't help but wonder what the power consumption will be for both it at datacentre scale and also what a fundamental barrier to anything remotely "at home" that is. I've worked with dil fridges a lot. They're neither cheap nor commonplace and famously most of the world's helium has a nasty habit of leaving at the top of the atmosphere (very marginally cooling it!) as it is so light, and the sources of helium are mostly underground and collected by machines blown up in the middle east or russia recently, as a byproduct of oil and gas extraction.
I keep wondering how long before funding for quantum computer development dries up due to lack of significant progress. I mean, we've been hearing stories about "breakthroughs" in the field for over three decades now and still these machines can't do anything useful. Some companies are even selling quantum machines (D-Wave) and its customers are still trying to figure out what to do with them.
IMHO RSA-4096 will be secure for the foreseeable future, but governments and intelligence agencies are so spooked about their secret communications possibly leaking out that they're mandating "quantum proof" encryption now.
But they don't actually seem to have any good use case except for breaking cryptography? And by the time they're actually able to do it (if ever), most of the stuff will be probably migrated to quantum resistant algorithms.
Perhaps, but it's highly unlikely it can outperform classical machines. If it actually had that capability, it would be front and center in the announcement.
Is this new processor capable of achieving reliable and practically useful results beyond the capabilities of classical machines? The answer is almost certainly, no.
Yes, and this was true starting with IBM Boston. I think anything before Dec 2025 could be picked apart as too noisy in particular due to crosstalk problems, for example on Pittsburgh. From the IBM Boston QPU build to the R2s, the fidelity allows for compute beyond what classical computers can do for quantum applications.
As a pure research project with possible implications in the indefinite future, this is very interesting.
The problem is that the US approach to funding research has backed itself into a corner. Every research advance in a technologically relevant industry has to be presented as though a commercial product is just around the corner, because no-one will pay for the research otherwise.
Eventually, though, the market will get tired of the endless unfulfilled projections and you'll get a "quantum winter".
in terms of progress quantum winter most likely already happened during COVID and there will no longer be any pause in progress.
between 2021-2024 technical progress was not impressive, and companies failed to build what they were trying to at the pace they wanted to. Since the end of 2024 this is no longer the case and progress is constant. To me it seems increasingly likely that by 2030 we'll have fault tolerant compute across multiple modalities including IBM's superconductors.
“Winter” in this case refers to drying up of investor interest and confidence, due to promises and expectations not being lived up to. The classic example is “AI winter”, of which there were two major ones. The result of that is lack of funding and a dramatic reduction in research.
It is very irritating when people complain here that it's not faster than classical or other such complaints.
Please, it is still a research project, it's not like a regular computer just faster, it is novel research.
Regarding the quantum side, I would love to know if by programmable qubit are they referring to an error corrected qubit or just one where gates can be applied.
I suspect it means error corrected qubits. I was wondering if there was work being done on algorithms that are noise resistant and as such can take advantage of the raw qubit count instead of the error corrected qubit count.
I would love to work in this area but I think it's all research at the moment. It's really interesting, how it actually works, not just the hand wavy abstractions.
Programmable qubit is almost certainly referring to one where gates can be applied, non-error-corrected. The error correction overhead would be much larger than 4-to-1.
Although note, the above is if you are referring to error correction in the traditional sense of error correcting codes. According to Ars Technica's article [1], the non-programmable qubits are being used for leakage removal: coupling to the computational/programmable qubits and stabilizing them, but not being used for any computation themselves. This is far from error correcting codes in the mathematical sense, but it does have a similar purpose of reducing noise.
For what you are wondering about in your penultimate sentence is possible for any algorithms, I am not sure, but it's a very good question. However, I know that for general algorithms, there is a range of error reduction techniques you can use short of full QEC, IBM has a decent blog post about them [2]. Usually, the trade-off is error reduction vs increased number of shots and post-processing (so vs time, not space).
[1] https://arstechnica.com/science/2026/11/ibm-to-offer-access-...
[2] https://www.ibm.com/quantum/blog/qec-continuum
Generally if they say "qubit" they mean physical qubit, and if they say "logical qubit" they mean error-corrected (and would spend lots of time talking about whatever improvements to error correction they've made). In publicity stuff, unqualified, it will definitely mean physical qubit.
I don't see why Quantum would be faster than classical. I see quantum having more depth than speed.
I however no knowledge of the subject other than that you can turn a binary bit in to a 2.
It's better to think of QPUs as highly specialized coprocessors that do certain things really well. You would only every really use them for problems they're good at. Like ALU vs FPU vs GPU.
What problems are they good at?
Shor's algorithm is the quintessential example, but there are other algorithms (mostly graph algorithms) that are NP and hard would be very efficient on a quantum computer.
It’s healthier to think of neither depth nor speed. The space of problems best suited for quantum computers is altogether orthogonal to those dimensions.
IBM isn't in the research business. It's a for profit company that wants to sell you these machines for an incredible amount of money.
But it's all a scam since these machines can do nothing useful, except allowing you to try out programming simple quantum algorithms.
BTW they keep obfuscating the difference between logical and physical qubits. Logical qubits is what it's all about but this article sort of uses them interchangeably. Most of the time they're talking about physical qubits, though.
Someone once calculated that you'd need a million physical qubits to crack RSA-4096. That shows you how much farther we have to go for these machines to be useful.
"IBM is the largest industrial research organization in the world" (https://en.wikipedia.org/wiki/IBM)
Well, that is from 2020, according to their reference: https://en.wikipedia.org/wiki/IBM#cite_note-196
And the reference is from IBM itself. So how can we be sure it isn't just PR?
One example: one of the countries with the largest population and thus an incredible large domestic market is China. When they do anything (or the government steers the industry to do anything) they often do it at a scale not known in the already developed world.
And now the west is withholding certain technology from China since it seems to be aggressive as well. Not as aggressive as Russia or the USA, but still. So they don't get various technology anymore. But so far all I know that one level in the chinese Huawai development center could host more researches than IBMs Zürich lab. Could. Not does.
And as a consequence they bumped out their research in this area.
And now my assumption: knowing how large-scale things in China are often done, I guess that they do their industrial research equally in a large scale. So I wouldn't wonder that e.g. Huawei has by now a larger research division than IBM.
The archived article from IBM mentions 3000 researchers. That's not THAT much. Just one of the 4 german institutionalized research agencies (Fraunhofer, Max Planck, etc) has more researchers. For me, it's not unthinkable that a big chinese company has 4000 researchers by now. Especially since they HAVE to research/steal key technology these days.
I would claim that IBM is an "applied research organization." Their research has the sole purpose of developing a product that they can sell. They're not like Bell Labs that does lots of basic research.
If it's IBM it's a marketing project ;)
[dead]
IBM's huge, modular dilution fridge is an interesting idea for superconducting plasmon qubits [1]. I really can't help but wonder what the power consumption will be for both it at datacentre scale and also what a fundamental barrier to anything remotely "at home" that is. I've worked with dil fridges a lot. They're neither cheap nor commonplace and famously most of the world's helium has a nasty habit of leaving at the top of the atmosphere (very marginally cooling it!) as it is so light, and the sources of helium are mostly underground and collected by machines blown up in the middle east or russia recently, as a byproduct of oil and gas extraction.
Very cool technology though.
[1] https://www.ibm.com/quantum/blog/goldeneye-cryogenic-concept...
I recommend people read the Ars Technica article [1] too, better written than this press release.
https://arstechnica.com/science/2026/11/ibm-to-offer-access-...
I keep wondering how long before funding for quantum computer development dries up due to lack of significant progress. I mean, we've been hearing stories about "breakthroughs" in the field for over three decades now and still these machines can't do anything useful. Some companies are even selling quantum machines (D-Wave) and its customers are still trying to figure out what to do with them.
I will repeat the comment I made in another quantum-related discussion on HN:
Every single discussion thread about any announcement in quantum feels exactly the same:
1. this is not what you think it is, there are caveats and the title is misleading.
2. I feel there is so much hype around quantum computing.
3. It's like nuclear fusion, always 10 years away.
4. Nuclear fusion is at least practical. QC is not.
5. Did they manage to find prime factorization of 17 already? LOL
6. Cryptography will be dead, RIP bitcoin and https.
7. No, actually quantum computers are useless.
It's tiring. I recommend this recent post by Scott Aaronson https://scottaaronson.blog/?p=9668
Is this a complaint about Hacker News users being lazy when commenting or an argument to ban Quantum as a topic in HN?
IMHO RSA-4096 will be secure for the foreseeable future, but governments and intelligence agencies are so spooked about their secret communications possibly leaking out that they're mandating "quantum proof" encryption now.
HN can be quite shallow sometimes. Such a waste of energy, mentally and physically.
But they don't actually seem to have any good use case except for breaking cryptography? And by the time they're actually able to do it (if ever), most of the stuff will be probably migrated to quantum resistant algorithms.
Can it run Shor?
Perhaps, but it's highly unlikely it can outperform classical machines. If it actually had that capability, it would be front and center in the announcement.
Can it run Doom?
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It plays Quantum Civ II.
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It can only run up your IBM bill.
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Is this new processor capable of achieving reliable and practically useful results beyond the capabilities of classical machines? The answer is almost certainly, no.
Yes, and this was true starting with IBM Boston. I think anything before Dec 2025 could be picked apart as too noisy in particular due to crosstalk problems, for example on Pittsburgh. From the IBM Boston QPU build to the R2s, the fidelity allows for compute beyond what classical computers can do for quantum applications.
IBM has an advantage tracker that needs more submissions https://quantum-advantage-tracker.github.io/
As a pure research project with possible implications in the indefinite future, this is very interesting.
The problem is that the US approach to funding research has backed itself into a corner. Every research advance in a technologically relevant industry has to be presented as though a commercial product is just around the corner, because no-one will pay for the research otherwise.
Eventually, though, the market will get tired of the endless unfulfilled projections and you'll get a "quantum winter".
in terms of progress quantum winter most likely already happened during COVID and there will no longer be any pause in progress.
between 2021-2024 technical progress was not impressive, and companies failed to build what they were trying to at the pace they wanted to. Since the end of 2024 this is no longer the case and progress is constant. To me it seems increasingly likely that by 2030 we'll have fault tolerant compute across multiple modalities including IBM's superconductors.
“Winter” in this case refers to drying up of investor interest and confidence, due to promises and expectations not being lived up to. The classic example is “AI winter”, of which there were two major ones. The result of that is lack of funding and a dramatic reduction in research.