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Google claims to have proved its supremacy with new quantum computer

telegraph.co.uk

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Re: Google claims to have proved its supremacy with new quantum computer

#91

Earlier quoted context omitted.

> I can literally measure those with a ruler and a scale You can’t measure a number of internal stress-strain conditions during the moment of failure. You can’t repeat the experiment with the same stick. The best way to get a fast intuition for why the simulation is superior is to take an entry-level CAD course with a focus on material design.

> The best way to get a fast intuition for why the simulation is superior is to take an entry-level CAD course with a focus on material design. I'm sorry but you're completely missing the point of my question. The question was not "what can simulations do that experiments can't". My background in simulation is not zero, and I've never had that question. The question as something else entirely. > You can’t measure a n…

Are you just asking if these are unrealistic, contrived performance benchmarks? Those have always existed and they're fine: https://news.ycombinator.com/item?id=20231084

Some are more useful than others. There's no strict criteria just as there is no perfect way fully characterize CPU performance.

Re: Google claims to have proved its supremacy with new quantum computer

#92

Earlier quoted context omitted.

Note: that there is good physical reasons why the cost of QC may grow exponentially with qbits. Refrigeration is exponentially inefficient as T=>0 and the gap of a quantum system which sets the temperature you must cool to shrinks as you couple new degrees of freedom. This dynamic has been the basic reason for the sub exponential progress in the area (despite exponential expenditure)

Not for photonic quantum computing. Only detectors require cooling, and it is possible to build adequately sized quantum computers with constant number of detectors using loop based architectures. Even more realistic architectures are very very cost effective on the number of components https://quantumfrontiers.com/2023/06/21/what-is-the-logical-...

Yeah, it always struck me as odd that the main quantum computing research labs went for the "VLSI" approach straight away rather than building room-sized computers with qbits that are known to be more stable and don't require such aggressive refrigeration.

Between the costs of refrigeration/fabrication and the increased speed of decoherence, it's not hard to imagine that the approach of using superconducting qbits may be a dead end, despite quantum ECC.

Re: Google claims to have proved its supremacy with new quantum computer

#93
post #7

Dumb question: Say I have a wooden stick and I break it in half in less than a second. Assume a computer would need several minutes to simulate everything that would've happened in the stick. I clearly got the output faster than a computer (and with more precision), so does this imply I'm doing anything particularly fascinating? I assume the same scenario is possible to concoct for a quantum computer. I assume it wou…

Your wooden stick is dedicated hardware for computing the behavior of wooden sticks. Fascinating? Pretty subjective—but one of the best concrete proxies we have for "fascination" is "economic value" (cf OpenAI's AGI definition). Is it going to make (or save) you a lot of money to quickly find out how that stick broke? Probably not.

Re: Google claims to have proved its supremacy with new quantum computer

#94

Earlier quoted context omitted.

Note: that there is good physical reasons why the cost of QC may grow exponentially with qbits. Refrigeration is exponentially inefficient as T=>0 and the gap of a quantum system which sets the temperature you must cool to shrinks as you couple new degrees of freedom. This dynamic has been the basic reason for the sub exponential progress in the area (despite exponential expenditure)

Not for photonic quantum computing. Only detectors require cooling, and it is possible to build adequately sized quantum computers with constant number of detectors using loop based architectures. Even more realistic architectures are very very cost effective on the number of components https://quantumfrontiers.com/2023/06/21/what-is-the-logical-...

Yes, but all existing photonic platforms use post-selection which is even more clearly exponentially lossy. Although this could be solved with a deterministic single photo source if one can be found. Photonic quantum computing is an especially funny post-transistor paradigm because classical photonic computing is also quite attractive.

Re: Google claims to have proved its supremacy with new quantum computer

#95

Earlier quoted context omitted.

> You don't know, with any precision, the amount of force you used, the rate the stick broke at, how much mass remains in the two pieces and how much was lost to splintering, etc. But I can measure those with a ruler and a scale. Both before and after the breakage. Takes a few seconds, and I'd need to do that before punching those numbers into the simulator anyway. And I can be precise with where I apply the force, e…

You're going to measure every point like this? https://www.researchgate.net/profile/Andrzej-Baier/publicati... Likewise, you can crash a car in a lab and do a simulation of one. Both tell you "fascinating" things and are still done by engineers.

This has nothing to do with the question though.

> You're going to measure every point like this?

Why would I need to? Is "tells you a bunch of answers to questions you never asked along the way" really the distinguishing factor for what constitutes computational supremacy? If all I wanted was just the lengths of the broken pieces, my simulation has to tell me the stress and strain at every point in order to be considered superior to a numerical simulator? Merely telling me the answer to the question I asked doesn't count? So if my prime factorization tool factored 4096-bit integers instantly, that's not enough? It has to factor a bunch of unrelated numbers and maybe solve TSP in the middle before we can consider it superior to classical computation?

Re: Google claims to have proved its supremacy with new quantum computer

#96
post #7

Dumb question: Say I have a wooden stick and I break it in half in less than a second. Assume a computer would need several minutes to simulate everything that would've happened in the stick. I clearly got the output faster than a computer (and with more precision), so does this imply I'm doing anything particularly fascinating? I assume the same scenario is possible to concoct for a quantum computer. I assume it wou…

Any problems where the configuration space is large, and you want to find some optimal configurations to the problem, would in theory benefit since you can directly map the configurations into the entangled qubits. Entangled qubits give you the ability to physically represent large configuration spaces.

The difficult is ensuring entanglement between qubits, scaling up the qubit count, noise reduction between the qubits and the other physical parts of the quantum computer, error correction, and generating the circuit to represent the optimization problem, formalizing a proof that the total time of quantum computation (computation + preparation) is less than to simulate on high performance computers and what not.

There's several YouTube videos where some company has mapped their problem into a quantum circuit and claim it provided solutions to optimization problems that they couldn't have found classically but dunno, I guess it would really require AB testing between classically computing it on an HPC versus a quantum computer.

Re: Google claims to have proved its supremacy with new quantum computer

#97
The fact that the calculation would take 47 years on a classical computer is only a break through if the calculation is something we actually want to do. Otherwise it just means that we have created an unnecessary problem designed to be solved quickly by a quantum computer.

That isn't to say that this quantum computer isn't impressive and a step forward. Just that the comparison isn't really meaningful unless the problem being calculated transcends computer architecture--meaning it is actually interesting to solve regardless of the architecture being used.

Re: Google claims to have proved its supremacy with new quantum computer

#98
post #7

Dumb question: Say I have a wooden stick and I break it in half in less than a second. Assume a computer would need several minutes to simulate everything that would've happened in the stick. I clearly got the output faster than a computer (and with more precision), so does this imply I'm doing anything particularly fascinating? I assume the same scenario is possible to concoct for a quantum computer. I assume it wou…

You're not modeling or predicting anything though. That's like saying "what if I built a bridge that failed on the first day? A computer would need several days to calculate all the forces that led to the failure, but my bridge failed just fine without any computer help". Well... yes. But try building a bridge that doesn't break. Or to keep with your scenario, try to predict exactly where and how your stick will brea…

Does Google's implementation of quantum computing help with this sort of scenario, or is it a really fancy way of breaking the bridge?

Re: Google claims to have proved its supremacy with new quantum computer

#99

Earlier quoted context omitted.

Not for photonic quantum computing. Only detectors require cooling, and it is possible to build adequately sized quantum computers with constant number of detectors using loop based architectures. Even more realistic architectures are very very cost effective on the number of components https://quantumfrontiers.com/2023/06/21/what-is-the-logical-...

Yeah, it always struck me as odd that the main quantum computing research labs went for the "VLSI" approach straight away rather than building room-sized computers with qbits that are known to be more stable and don't require such aggressive refrigeration. Between the costs of refrigeration/fabrication and the increased speed of decoherence, it's not hard to imagine that the approach of using superconducting qbits ma…

There are very valid reasons for this. Historically, this is what happened.

* People did very basic qubit experiments with NMR in the late 90s. Very noisy experiments.

* Around 2000 they realized photonic quantum computers would be "easiest" because light experiences very little noise. The problem was that its insanely difficult to do non-linear interactions between photons (which is necessary to do any sort of non-trivial classical or quantum computing with photons). In 2001, somebody came up with a clever way of doing non-linear interactions by using fast detectors.

* Huge efforts started to try and build photonic quantum computers. Unfortunately, around 2004-05, people started to do estimates and it turned out that the number of sources and detectors needed with the clever way was humongous. Far more than we could hope to achieve, and there didn't seem to be any way of reducing it. People abandoned photonic quantum computing and started doing ion traps and superconducting.

* Interestingly around the same time in 2005, there emerged an alternate method of building photonic quantum computers, based on "cluster states". However, the method also had the same humongous resource problem, but it had an advantage: the framework could be modified and played with to improve it. Over the next two decades, very slowly people figured out improvement after improvement to this architecture to bring down the resource costs.

* At this point, this cluster-state photonic architecture has improved quite a bit and is starting to become very competitive with ion traps and superconducting qubits. PsiQuantum (whose article I shared above) is the leader in this right now. And they might win the race.

Re: Google claims to have proved its supremacy with new quantum computer

#100
post #9
post #3

"This is a very nice demonstration of quantum advantage. While a great achievement academically, the algorithm used does not really have real world practical applications, though." Not having real world applications is not necessarily damning, of course. Curious to know what implications this has for general algorithms. Reading this, it almost makes it sound like there will be some algorithms that quantum is better a…

My understanding is that quantum computers only have two real use cases, as of today: 1. Breaking crypto. 2. Simulating other quantum systems. For (1) it's basically all downsides. For (2) unless you're a particle phycisist you'll never need quantum computers. But that's now. Maybe there will be a killer app for it some day, changing everything. Or indeed, we could get it indirectly. Maybe simulating quantum systems…

(2) can be very relevant to material science and chemistry. Those things have huge ranges of important practical applications.

For example, people currently struggle to do accurate calculations of the band structures of materials and it doesn't look like there will be much progress there using only classical computers (using more computing power or better approximation tricks). Big enough quantum computers could do this. Band structure calculations are very interesting for pretty much all semiconductor development.

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