[HN Gopher] Artificial Intelligence for Quantum Computing
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Artificial Intelligence for Quantum Computing
Author : jimminyx
Score : 55 points
Date : 2024-11-16 11:44 UTC (11 hours ago)
(HTM) web link (arxiv.org)
(TXT) w3m dump (arxiv.org)
| itchyjunk wrote:
| Petition to add AI to HN so it lists out the gist of papers and
| articles posted xD . I also always thought AI would overlap with
| Q Annealing in some way vaguely because both are optimization
| process. But maybe this is where QC helps AI and not the other
| way around.
| l33tbro wrote:
| People can deploy that personally if they wish. The abstract
| captures the gist in most cases.
| mg wrote:
| Is there a metric which lets us track how far/close we are to do
| something useful with quantum computers?
|
| And when we look at that metric and extrapolate its progression
| over the last years, when do we expect QCs to hit datacenters?
| foresttony wrote:
| QCs are in all major data centers already. Although there is
| not much you can do with them, but you can use them. IONQ is
| considered the leader right now in QC. Look them up, very
| interesting stuff they are doing. They just partnered with
| astrazeneca to start developing useful applications. They will
| also demonstrate hybrid algorithms next week where they offload
| some stuff to QPUs to speed up models. I would say within two
| years QCs will start being useful.
| almostgotcaught wrote:
| > QCs are in all major data centers already
|
| Citation needed
| bawolff wrote:
| I think https://xkcd.com/678/ is relavent.
|
| Basically we are far enough out from "useful" QC that its
| anyone's guess (except for the people trying to convince you to
| invest in their startup). That said relavent metrics include
| number of qubits and their error rate (once you get past a
| certain number with a low enough error rate you can start to
| use error correction which is when things really start to
| become interesting)
|
| It does depend a bit on what you mean by "useful" though see
| also https://en.wikipedia.org/wiki/Noisy_intermediate-
| scale_quant...
| foresttony wrote:
| Good job commenting on something you know nothing about...
| vtomole wrote:
| 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.
| wzeng wrote:
| You can track resource estimates for different problems against
| QC performance here: https://metriq.info/progress
|
| It crowdsources new submissions to the chart if there are ones
| you see missing (just open a PR)
| dr_dshiv wrote:
| The most remarkable thing is using frontier models to write and
| then run code on quantum computers (eg IBM's). It's amazing --
| you can even teach with a "creative coding" approach (without the
| multiple courses in quantum physics).
|
| It's not even the code that is the hardest part. In general, it
| is very difficult to frame a given problem domain (ie, any other
| field of science or optimization problem) as a problem
| addressable with a quantum computer. Quantum computer scientists
| have not made this easy--with LLMs, it still isn't trivial, but
| it is a huge leap in accessibility.
|
| Warning: LLMs hallucinate a ton within this area. Many things can
| go wrong. But the fact that sometimes they are correct is amazing
| to me.
|
| We've run some studies showing the importance of expertise in
| this area: participants with quantum background and coding skills
| were much more effective at solving quantum problems with LLMs
| than novices, for instance.
| Escapado wrote:
| My master thesis was on using machine learning techniques to
| synthesise quantum circuits. Since any operation on a QC can be
| represented as a unitary matrix my research topic was that, using
| ML, given a set of gates, how many and in what arrangement of
| them you could generate or at least approximate this matrix.
| Another aspect was, given a unitary matrix, could a neural
| network predict a number of gates needed to simulate that matrix
| as a QC and thereby give us a measure of complexity. It was a lot
| of fun to test different algorithms from genetic algorithms to
| neural network architectures. Back then NNs were a lot smaller
| and I trained them mostly on one GPU and since the matrices get
| exponentially bigger with the amount of qbits in the circuit it
| was only possible for me to investigate small circuits with less
| than a dozen qubits but it was still nice to see that in
| principle this worked quite well.
| sigmoid10 wrote:
| At which university? I literally know a guy who did exactly the
| same thing for his master thesis. I'm wondering if the world is
| so small or this specific topic is so common.
| IIAOPSW wrote:
| How did it do compared to the baseline of the solvoy kitaev
| algorithm (and the more advanced algorithms that experts have
| come up with since)?
|
| How (if at all) can the ML approach come up with a circuit when
| the unitary is too big to explicitly represent it as all the
| terms in the matrix but the general form of it is known? Eg it
| is known what the quantum fourier transform on N qubits is
| defined to be, and consequently any particular element within
| its matrix is easy to calculate, but you don't need (and
| shouldn't try) to write it out as a 2^n x 2^n matrix to figure
| out its implementation.
| westurner wrote:
| Solvay-Kiteav theorem:
| https://en.wikipedia.org/wiki/Solovay%E2%80%93Kitaev_theorem
|
| /? Solvay-Kiteav theorem Cirq QISkit:
| https://www.google.com/search?q=Solvay-
| Kiteav+theorem+cirq+q...
|
| qiskit/transpiler/passes/synthesis/solovay_kitaev_synthesis.p
| y: https://github.com/Qiskit/qiskit/blob/main/qiskit/transpil
| er...
|
| qiskit/synthesis/discrete_basis/solovay_kitaev.py: https://gi
| thub.com/Qiskit/qiskit/blob/stable/1.2/qiskit/synt...
|
| SolovayKitaevDecomposition: https://docs.quantum.ibm.com/api/
| qiskit/qiskit.synthesis.Sol...
|
| What are more current alternatives to the Solvay-Kiteav
| theorem for gate-based quantum computing?
| OscarCunningham wrote:
| I would be interesting if finding quantum circuits was one of
| the things that quantum computers were good at.
| Xcelerate wrote:
| > given a unitary matrix, could a neural network predict a
| number of gates needed to simulate that matrix as a QC and
| thereby give us a measure of complexity
|
| That's really interesting. I'm curious--did you explore whether
| the predictivity of the neural network was influenced by any
| hidden subgroup structure in the unitary matrix? Seems like the
| matrix symmetries could play a significant role in determining
| the gate complexity.
| medo-bear wrote:
| My next paper will be titled
|
| Artificial Intelligence for Quantum Computing with Applications
| to Blockchain ... in Rust
| dghughes wrote:
| Used to find a cure cancer but only on a Friday.
| JanisErdmanis wrote:
| One thing that comes to my mind and reminds me by looking into
| the examples is the fragility of existing implementation
| processes for quantum computers. Pulse optimisation, frequency
| allocation to minimise cross-talk between qubits, and the
| development of custom error correction codes tailored for
| specific quantum computers, circuits, or computations are
| unpredictable in their successes and, hence, inherently
| unscalable. It looks like the primary use for AI here is to
| optimise benchmark results for publishing rather than enable
| practical quantum computations.
| bastloing wrote:
| Throw in some crypto and you've got a recipe for some great word
| salad!
| kaycebasques wrote:
| Blockchain and AI algorithms yield novel insights in
| superconductor quantum computing
| dartos wrote:
| I really believe that the confluence of these paradigm
| shifting technologies will enable even greater gains in
| productivity.
|
| With our new AI enabled smart algorithms, we can meta-analyze
| transactions in systems such as blockchain networks to
| identify areas where resources can be more effectively
| aggregated.
|
| We also gave tight integration with salesforce and Jira,
| enabling next-gen teams to conduct research and ship products
| with much flatter management structure.
|
| I wish word salad artist was a profession
| aithrowawaycomm wrote:
| Outside of a few odd citations in the intro (which is innocuous)
| I don't see anything shady or dishonest in this paper after a
| cursory skimming. But I do worry about 60% of the authors being
| NVIDIA employees, where the corresponding author is not a staff
| scientist, but rather a "technical marketing engineer" whose job
| "focuses on inspiring developers by sharing examples of how
| NVIDIA quantum technologies can accelerate research."[1] So I am
| wondering about what articles _didn 't_ make it to this review,
| where ANN/GPU-accelerated QC research didn't work very well or
| was too expensive to justify. It makes me suspect I am being
| advertised to, and that this paper must be read with an unusually
| high degree of scrutiny.
|
| Like I said: there's nothing obviously shady or dishonest here.
| But this is also an arXiv paper, so no need for authors to
| disclose conflicts of interest. (OpenAI has pioneered the
| technique of using the arXiv to distribute academic infomercials
| with zero scientific value.) And I worry about the distortion
| this stuff has on honest scientific work. Bell Labs was always an
| independent subsidiary: Bell's marketing staff did not take
| ownership of Bell Labs' research. The fact that NVIDIA's marketer
| has a PhD and an "engineer" title doesn't actually mitigate any
| of this.
|
| [1] https://developer.nvidia.com/blog/author/mawolf/
| alw4s wrote:
| meanwhile the 5M prize for the first real application of
| quantum remains open..
|
| quantum computing like string theory remains a scratch waiting
| for an itch - ie, a boondoggle.
|
| to be fair though, it is worth looking at something that has
| the potential to break all of the encryption on the internet.
| Jabbs wrote:
| Aliens for Time Travel (is how I read this)
| bee_rider wrote:
| Well, of course Aliens are for time travel. The universe is far
| too long, we don't get to see anything interesting if we show
| up after everybody is dead.
| vivzkestrel wrote:
| me and my friend used to joke about how to get VC funding a few
| years ago and it's about to be true soon at this rate VC: what
| are you building? me: Decentralized deep learning powered
| vertical farming using quantum computing on the blockchainfor
| onions
| dartos wrote:
| That's always how it works with tech investors
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