> I can't even imagine why I should bother trying to understand it.

Well, maybe you should just try for the hell of it and see how far you get? Becoming fit seems impossible to a morbidly obese 45 y.o, and it is if that person's expectation is unreasonable, but if they just change it to be more reasonable, break it down into manageable routines, then they can get somewhere eventually.

Find some papers, fill many gaps, dedicate a few years in your spare time, in 6 months you'll be 6 months closer than you were.

Whether there's a reason or not, idk, it's something to do, be curious. Don't forget that by dedicating their life to something, they're naturally not dedicating their life to other things, things that you might be able to do, like climbing mountains, making pizza, or coming up with witty banter in social situations.

Same, but kind of; I'm so far removed from higher up engineering stuff like quantum stuff, nuclear fusion stuff, LHC stuff, astronomy stuff, AI stuff that I just scan it, grab a coffee, raise an eyebrow and go "Interesting", then go about my day and wonder what the fuck I'm supposed to be doing at work again. Oh right, implement a component, same thing I've been doing for the past decade or so.

Thing is, I don't know how to get out without on the one side giving up my comfort zone (well paid, doable work), and on the other side gaining responsibility / being looked at as an expert in any field (that's where impostor syndrome and responsibility aversion comes in). I really need a holiday lol.

This was me yesterday after reading the official Willow release.

Spent yesterday afternoon and this morning learning what I could. I'm now superficially familiar with quantum coherence, superposition, and phase relationships.

In other words, you got this. Now I gotta learn linear algebra. brb.

We are all small in every domain in which we are not an expert, which is approximately all of them. The "computer" domain has expanded wildly over the last 50 years to include so many specialties that even within it one cannot possibly acquire expertise in everything. And of course "computers" do not include (although they do impact!) the vast majority of domains.

If you want to go deeper into quantum computing, I can highly recommend Scott Aaronson's own book, "Quantum Computing since Democritus"[0]. Although I have a background in physics and math, I found his style lively and engaging with truly unique and compact recapitulations of things I already knew (two come to mind: his description of Cantor's diagnalization argument, and the assertion that QM is the natural consequence of "negative probabilities" being real. The later is a marvelous insight that I've personally gotten a lot of use out of).

It's also useful to understand the boundary of what quantum computing is. At the end of the day what we'll see are "QaaS" apis that give us the ability to, for example, factor large primes. You won't need to know Shor's algorithm or the implementation details, you'll just get your answer exponentially faster than the classical method. I would not expect desktop quantum computers, languages designed for them, or general user software designed to run on them. (Of course, eventually someone will make Doom run on one, but that's decades in the future.)

https://www.alibris.com/booksearch?mtype=B&keyword=quantum+c...

Also good starting places (but still, only understood a tiny bit of what was there).

https://podcast.clearerthinking.org/episode/208/scott-aarons...

https://quantum.country

I’d urge you to not feel small.

First of all, the formalism/practice gap is real: taking API calls and updating a database correctly has a mountain of formalism around it. And it is not easy to get right! Concurrent sequential processes and distributed systems theory and a bunch of topics have a huge formalism. It is also the case that many (most?) working software engineers have internalized much of that formalism: they “play by ear” rather than read sheet music, but what matters is if it sounds good.

Second, whether it’s quantum computing or frontier machine learning or any other formalism-heavy topic? It’s eminently possible to learn this stuff. There’s a certain lingering credentialism around “you need a PhD” or whatever, I call BS: this stuff is learnable.

Keep hacking, keep pushing yourself on topics you’re passionate about, but don’t consign yourself to some inferior caste. You’re just as likely as the next person to be the next self-taught superstar.

The theory of quantum computation is accessible with a good understanding of linear algebra. Anyone working in machine learning or computer graphics should feel encouraged by that, and take a look at the theory.

Quantum error correction is one of those “wow” moments like euler’s identity, it is worth making the effort to get there.

A few years ago I made peace with the fact that my space of ignorance is humongous and will only get exponentially bigger. Even in the domain of my work which is software engineering. It liberated me from the pressure or burden of having to learn or know everything and enabled me to focus on things that I truly like to pursue.

I’ve made a list of 4-5 things at which I want to be extremely good at in 10 years compared to where I’m today. Now I just spend time on those. I occasionally wander into something new just for the sake of diversion.

As with most novel hardware since the dawn of computing, there are ways to emulate it.

https://www.ibm.com/quantum/qiskit

they buried the lede. google doesn't have 2 qubits to rub together 100%. 105 "qubits" make a "single" qubit after coalescing or whatever. I'm really annoyed because i've kinda followed this since the mid-90s and this is the first time i am hearing that "it'll probably take millions of physical qubits to crack 256 bit"

to me the whole endeavor smells like a bait and switch or something. I remember about 10 years ago canada or someone had at least a few hundred qubits if not close to 1000 of them, but these were physical qubits, and don't represent anything, really. Google's 105 finally makes a "fast enough" single qubit or at best half of a pair.

As hard it may seem to you to tackle that, it's harder to convince others like you that tackling it can be like child play. Not just QM/QC (which btw it's beeing successfully taught to highschoolers) but any "advanced" topic. I hope we'll be able to look back and laugh at how backwards education was "back in the day" and how dumb people were to think that some were "elite few", while the reality is that the "elite few" were the "lucky few" to not be deprived of learning to think either by having the right people around them or the right context to find it by themselves.

When Corridor Digital was analyzing the really impressive time spaghetti effect in Loki season 2 they said "there are two kinds of CGI artists. The kind that use the buttons and the kind the program the buttons."

You captured very well my sentiment. Also same feelings for AI.

I'm wondering if it's time for me to switch professions and give up compsci / software altogether.

It's also way harder to make money doing "not laughably childish" stuffs. The more accessible and human-connected it gets, the more likely people recognize and pays you. People criticize yes-men getting rewarded but you have to be nearly clinically insane to recognize value of a no-machine like a partial prototype quantum supercomputer.

> I can't even imagine why I should bother trying to understand it

Why should you? I agree with your sentiment, super advanced quantum physics is probably out of reach for 99% of the population (I'm estimating here but I think it's reasonable to assume that's the average IQ of the physics PHDs who can actually understand this stuff to a deep level). You can probably make the effort to understand something about what's going on there, but it will be very superficial. Going advanced quantum physics takes a huge amount of effort and an incredible capacity for learning complex things. And even the advanced physics guys don't and can't understand a bunch of very elementary things about reality, so it's not as if the feeling of not understanding stuff ever goes away.

We recently launched of our self-paced, mathematically rigorous course on quantum computing! This comprehensive introduction is designed to help you grasp foundational concepts like superposition and entanglement with mathematical clarity and depth.

Here’s a sneak peek from Lecture 6: https://youtu.be/6rf-hjyNl4U

You can sign up via: https://quantumformalism.academy/mathematical-foundations-fo...

> Being a "software engineer" consuming APIs and updating database rows ...

> Only an elite few get to touch these machines.

But lately many can run quite a lot of AI models at home. Doesn't require too crazy of a setup.

Why not build something software fun at home that doesn't involve a DB? Maybe using some free AI model?

I did experiment lately: automatically "screenshot" a browser and ask an AI to find the URL and ask if the URL and site looked like a phishing attempt or not. Fun stuff (and it works).

I tried installing one of these "photo gallery" in a Docker container (where you can put all your family/travel pics and let anyone on your LAN [or on the net] browse them). I saw some of these have "similarity" searches features. I also saw that SAM / SAM2 (Meta's Segment Anything Model) was plenty quick: some people are using these to analyze video frames in real-time. So I was thinking about sending all my family pictures through SAM2 (or a similar model: I saw some modified SAM2 to make it even faster) and then augmenting the "similarity search" by using the results of SAM2. For example finding all the pictures about "pool", etc.

And why limit myself to pictures? I could do family vids too: "Find all the vids where that item can be seen".

Possibilities at the moment seems endless: times are exciting if you ask me.

I haven't tried this yet myself, but have you tried plugging it into GPT or Claude or Perplexity and asking Qs? I've made some progress on thongs this way, much faster than I would have the usual way. Apply the usual precautions about hallucinations etc (and maybe do the "ask multiple AIs the same thing" thing). We don't yet have a perfect tutor in these machines, but on balance I've gained from talking to them about deep topics.

Some people say higher education is a privilege, but a few times during college while grinding out difficult classes it felt more like a huge burden.

Being part of a highly educated elite group like that has some huge benefits, but they have also shackled themselves to an insanely specialized and highly difficult niche. I can't imagine the stress they are under and the potential for despair when dedicating years to something with so much uncertainty.

Start with the handy precis that Mr A leaves at the top in yellow. You can drop that into conversation right now with some confidence! Mr A has quite some clout hereabouts let alone elsewhere, so that seems reasonable.

You can't know everything but knowing what you don't know and when to rely on someone else to know what you don't know and to confidently quote or use what they know that you don't know, is a skill too.

"Critical thinking", and I suspect you do know how to do that and whilst this blog post might be somewhat impenetrable it is still might be useful to you, even as just general knowledge. Use your skills to determine - for you and you alone - whether it is truth, false or somewhere in between.

Besides, a mental work out is good for you!

For what it’s worth, Scott spent the last few years working for OpenAI because he wanted to do something much more applied than quantum information theory. As an applied scientist I’m aghast: he’s one of the few people who actually gets to “touch the firmament of the Universe,” why would you ever give that up for mere applied science (even science as interesting as whatever goes on inside OpenAI) :) But as a human being I understand it. The grass is always greener somewhere else, and doing tangible things is sometimes more fun.

TL;DR: whatever you’re doing, there’s probably someone who wishes they were doing it instead.

People feel like this about domains they don't know all the time. Don't allow your ignorance of an area to trick you into thinking you can't learn that area. It's just new to you!

Source: teaching beginners piano for years. Of course sheet music looks like gobbledygook, until you've spent a bit of time learning the basic rules!

To be fair, probably everyone who "touches these things" had extensive graduate work on the topic, or put in a lot of long years toiling away at far less exciting and remunerative grunt work. They weren't just super bright CS undergrads who got entry level jobs you couldn't.

I know absolutely nothing about quantum, but I did watch this Bloomberg video this week which was very helpful to understand it in layman’s term.

https://youtu.be/1_gJp2uAjO0?si=--XzbVlAT3w9hw2L

Thank you. Seeing this as the top comment actually makes me feel better as I now know that I am not alone.

> Only an elite few get to touch these machines.

For now, people were saying the same thing about mainframes in the 60s

I think the jargon makes it seem scarier/less approachable than it is. There's tons of jargon in every new branch of anything interesting that you first notice, but it's not as impenetrable as it appears (at least for a high level understanding imo).

I had exactly the same thought. I read it after struggling for hours, making notes, etc, with a very hard (to me) part of my code and it made it seem pretty trivial.

if it makes you feel any better, it is almost impossible to do anything practically useful at all with quantum computation at the moment. this is a field for researchers, people who are okay with not seeing the fruits of their work materialize for decades, if ever. by not understanding it, you're not missing anything more than what you're missing by not understanding e.g. string theory.

Not even Einstein got it, you're fine

The machines you program today were once only accessible by "elites" too though?

Anything that someone else does that you don't understand or can't do always sounds super important, impressive, and enviable. Usually. But you have to realize that he spends his life doing and thinking about this. And will stipulate he's gifted in this area. I've never heard of him but managed to download his CV.

I will also note that sometimes when I read HN links and think one thing then read the comments and people know enough to take issue with what is being said and even call it out.

AWS Bracket is on AWS Free Tier.

And yet it pays the bills and runs the world, doesn't it.

React 19 is out and it's time to hit the docs eh to solve the same exact problem we've had for the last 30 years in a slightly better (or NOT) way.

but no one other than a quantum researcher cares about that problem.

The better question may be why the rest of us don’t care about the same things. If we sat here in 2014 and pondered why neural net folks cared about particular problems, I’m not sure where we’d be. Faith and Vision are truly spiritual things, even in tech.

Google says the next step is to find a problem with real life application. From https://blog.google/technology/research/google-willow-quantu...

> The next challenge for the field is to demonstrate a first "useful, beyond-classical" computation on today's quantum chips that is relevant to a real-world application.

This will never be relevant for solving travelling salesmen problems.

More relevantly, that line of experimentation is specifically to refute the notion that something unexpected will happen with the physics to break the computational scaling.

Nobody with any credibility is claiming that the current experiments are useful for anything practical.

> The problem it solved would take a septillion years to do on a conventional computer

And more importantly, the solution is not actually verified in any way. It might be wrong.

I don't understand (as a complete laymen) why the milestone isn't something classically hard but easily verified (in line with you). I feel like it's weird because people have spent a lot of time telling me how trivially quantum computing will break encryption that defeats normal computers.

I feel like the problems airlines face when not running a hub-and-spoke model would be a good market for quantum computing? Could be totally wrong though. Lots and lots of variables and permutations and options to sift through.

>Until then quantum computers are in the same category as commercial fusion.

That category being: "Technologies We Will Have Unlocked Within 10 Years"

Note there's a caveat: problems in CS can be reduced to other problems in CS. If we solved SAT, well, no one cares about SAT, but traveling salesman obviously reduces to that.

(disclaimer: I don't think that's what is going on here, I'd have to dig into it more)

I don't think they're building them for people like you, yet. Why does everyone think of anything that's announced or shown as if it's a commercial product on a shelf and marketed at them.

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That's not really how MWI works. There isn't some fixed number of universes; actually, there aren't really distinct universes (or timelines) at all. Attempting to count them is about like trying to measure the length of a coastline; they blend together once you zoom far enough in.

Running the quantum computer causes 'new timelines' to be created. Though so would ordinary atoms just sitting there; the tricky thing about quantum computers is making it so the split is temporary.

So the quantum computer gets split into multiple versions of itself, does some computation in each, and merges the results. This isn't map-reduce; there's a strictly limited set of ways in which you can do the merger, all of which are weird from a classical perspective.

You can argue for MWI based on this, because the computations that got merged still had to happen somewhere. It's incompatible with Copenhagen, more so the bigger and longer-lasting the computation gets. It's not, strictly speaking, incompatible with pilot wave theory; but pilot wave theory is MWI plus an additional declaration that "Here, you see this timeline here? That's the real one, all the others are fake. Yes, all the computation needed to instantiate them still happens, but they lack the attribute of being real."

Though that makes PWT incompatible with computationalism, and hence with concepts such as mind-uploading. Which is a bullet you can choose to bite, of course...

> “where else could the computation have happened, if it wasn’t being farmed out to parallel universes?”

Right. I’m definitely a layman here but as a CS generalist this rings out as narrow-minded to me, biased towards the way we designed physically and then mathematically formalized “computation”.

Not that I have anything against multiverses but.. if I had to choose between “Turing-style computation happened, but needed parallel universes to do so” and “what happened is something counter-intuitive and insufficiently understood about the universe we inhabit” I would bet on the latter.

But to emphasize one quote from the blog: "the new experiment doesn’t add anything new to this old debate" about multiverse interpretations vs. something else. An equally viable and perhaps conceptually simpler interpretation of the experiment is that the qubits are temporarily put in a 'superposition' of many different bitstrings, some operations are performed, and then measurement collapses this superposition back into a single definite bitstring. No multiverse required.

You just need to devise a system where the vast majority of universes give the right answer for this to work.

Start by at least having a universe for each possibility so that every code path is computed. Then add a mechanism to create many more universes when a correct result is hit.

So each wrong result has 1 universe and the correct result alone has 2^300 a universes. Run this. You now end up with the correct result 99.99999% of the time.

I’m not arguing on the above take or not fwiw, it’s just that it easy to see how this could happen in many worlds. Effectively error correction just becomes a mechanism to create more universes for correct answers than incorrect answers and it all works. In fact it’s very reasonable to think of quantum error correction this way (it really is a mechanism to favour correct answers being observed and in many worlds that means it creates more correct answer universes).

> Aren't these parallel universes running the same computation at the same time, and thus also "farming out" part of their computations to us? If so, it's a zero-sum game, so how could there be an overall performance gain for all the universes?

The result is the same in all universes. There's a kind of scatter-gather/map-reduce feel - each universe computes part of the problem, then you add up all their results to get the final one (in all universes).

The argument works for me, although I already believed the conclusion so I'm biased.

The main issue with this line of argument is that you don't see people who like other interpretations claiming quantum computers won't work. Saying quantum computers imply many worlds is the classic mistake of wanting to show A=>B and arguing B=>A instead of ~B=>~A. If quantum computers were inconsistent with collapse interpretations, you'd expect people who think collapse interpretations are correct to be confidently predicting quantum computers will never work. But they don't; they just think the state inside the computer isn't collapsing.

I'm often tempted to argue quantum computers at least clearly favor ontic interpretations (ones where quantum states are real). Because good luck computing things by subjectively having a computer instead of actually having a computer. But, as far as I know, you don't see quantum-bayesianism-ists having any qualms with quantum computers. I think because if you're already biting the bullet of interpreting diagonally polarized light as subjective, and Bell tests as subjective, then interpreting a computation as subjective isn't fundamentally different. It's just more in your face about it.

I’m not sure the sibling comment is correct, so I’ll take another stab at it.

First, I also think the “this favors the Everett interpretation” argument is incoherent, but for different reasons. I won’t be defending that view. But I can try to answer your question about the nature of computation and “where” that computation is taking place.

A quantum computer is essentially a random number generator, but with a non-uniform distribution that can be programmatically controlled.

Let’s start with the random part: a qubit can be either a 1 or a 0. When first initialized, when you then read it you will get either a zero or a one with 50% probability. (I am oversimplifying to the point of error! This is technically incorrect, but please excuse me for the purpose of a simplified explanation that makes sense to computer scientists rather than quantum physicists.) In the Copenhagen interpretation the wave function randomly collapsed in a way that can be measured as a 0 or as a 1 with 50% probability for either outcome. In the Everett interpretation there are two universes (really, two disjoint sets of universes): one where you see a 0, and the other where you see a 1, and your likelihood of ending up in either is 50%.

For example, with three qubits you can read a random value between 0 to 7, where each qubit provides a 0 or 1 of a classical 3-bit binary value. If you're making a D&D simulator, you can take three of these registers (9 qubits total) and read them to get three values between 0 to 7, then increment each and add together to get the simulated value of three 8-sided dice, for the attack value of some game weapon.

But so far we're assuming even and independent odds for a 0 or 1 in each qubit. A quantum gate operation lets you modify that probability distribution in interesting ways. Specifically you can take multiple qubits and entangle their state such that the eventual outcome (still random) is constrained to a non-uniform probability distribution. (The details don't matter, but it has to do with the fact that you can add wave amplitude, which is complex-valued and therefore can constructively or destructively interfere.)

So instead of reading three separate 1d8 registers and adding them together, we can use quantum gate operations to perform the addition: entangling the state of a new 4 qubit register (large enough to hold the sum of two 3 qubit registers) such that it represents the sum of two separate, randomly chosen with independent probability values between 0..7. The combined sum will be a random value between 0 and 14, but with the value 7 being most likely, 6 or 8 next most likely, etc. (You can see the probabilities here: https://anydice.com) We then add in the third 3-bit register, getting a 5-qubit result. For good measure, we then add a constant 3 value using quantum gate operations so the result will be what we expect for adding 3 dice rolls, which start counting at 1 rather than 0. Now we have a great random number generator for D&D games. It's a 5-bit register that when you read it will give you a value between 3 and 24, with exactly the probabilities you would expect of three rolls of a fair 8-sided die.

You can interpret what this means in Copenhagen vs Everett, but there isn't a way in which it makes material difference. I will say that the Everett interpretation is easier to think about: you setup the entangled operations such that there simply isn't a universe in which the register reads 31, or some value not representative of a 3d8 dice roll, and if you count the number of possible universes under the born rules and holding the rest of the multiverse constant, the counts match the 3d8 dice probability distribution. So you don't know which universe you will end up in when you finally read the register and, under the many worlds interpretation, split off into one of many possibilities. But you know it will be a good 3d8 dice roll for your D&D game.

Now imagine you have two 1,024 qubit registers (each with random probability for each bit), and you run a full set of shift-adders to multiply them together into a 2,048 qubit register. If you read the result, it'll be a random non-prime number. Why? Because it's necessarily the product of two 1,024 composites. What's interesting is that you can kinda do the reverse, as Peter Shor figured out how to do in the 90's: start with a 2,048 bit register, run the shift-adder in reverse (really, the method of continued fractions, but I'm going for an intuition pump here), then read the two 1,024 registers. What you will get is two values that when multiplied together will result in the input, the factors. If you put "60" in the input, you will maybe get the outputs (15, 4), or (5, 12), or (2, 30), or (1, 60). It's random which will pop out, but what you get WILL be a factorization of 60.

Now put your bank's SSL public key in the register, and read the factors out. The factors are the private key.

I don't think any talk of multiverses is needed to understand this. It's simply mucking around with the probability distribution of a random number generator in clever enough ways that the random number generated, whatever it is, will be A solution (perhaps one of many) to your problem. You do this by destructively interfering the register with wave functions that represent non-solutions, and keep doing this until only solutions are left as possible values. Then you read your random number register and know the result is drawn from the solution set.

I think the "parallel universe" analogies are misleading at best. I actually think most "narrative" explanations of quantum physics are as well. For a long time I used to imagine quantum physics with the same language we talk about superheroes and time travel and consciousness and whatever.

But then I actually saw some of the math (very basic Hisenberg uncertainty equations) and good comparisons to classical wave mechanics and wave interference. Everything made more sense.

As a layman with some very rudimentary understanding of the math, I would ignore ALL talk about "farming out" and "parallel universrs" and similar concepts. I think thise ideas are charged with too many interesting but fantastical elements which you probably don't find in actual quantum mechanics.

I am also curious if Mark Everett, Hugh’s son, has an account here.

It’s not necessary for there to be parallel universes when all possible paths are already taken within this universe.

The Everettian multiverse is a bit like seeing some bubbles and foam in the surf and concluding that there are "many oceans." Yes, there are many surfaces of water, but calling each bubble an ocean is a bit disingenuous.

Like the bubble analogy, new Everettian universes are local, small, and the total amount of probability density (water in this analogy) is conserved.

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This computation is... handwaves, most handwaving I've done in a while...initializing a random state, and it's well-understood whether this state was randomly initialized isn't computable in a reasonable timeframe on classical computers. ends extreme handwaving

This nerd sniped a bunch of us, because it sounds like "oh we proved P!=NP", the keys to understanding are A) hanging onto the this in "this computation" (this is easier when you're familiar with the computation and it's contextual history in the field) B) remembering prime factors as a plausible application of QC.

Then faced with the contradiction of B, it's neatly resolved by "yes, but the quantum computer isn't big enough to do prime factorization yet"

As noted somewhat sideways in the blog, if someone has a computation that is A) not classically computable in a reasonable timeframe B) is computable on a miniscule quantum computer C) can be verified on a classic computer in a reasonable timeframe, a lot of researchers will be excited.

> Oh yes, Zapata Computing, the best funded company in quantum algorithms just went under this year.

It's kinda hard to make money by developing algorithms for imaginary magic computers.

For one, we could just start simulating quantum chemistry, though at that point it's more like "actually running quantum chemistry" rather than simulating.

Sorry but you need to cite some sources... The fact that random adtech devs on HN have no algorithms useful to them to run on a QC does not mean much to me.

This is not true.

There are plenty of quantum algorithms.

https://en.wikipedia.org/wiki/Quantum_algorithm

you're mixing up 2 different results

a) error-correction needs small level of errors to begin with to amplify signal - we finally got to that point, and larger correction setup deals with more errors

b) "standard" benchmark problem now 100% computes something uncomputable with classic chips (in practice) - the problem is that it's so quantum, neither it is verifiable with classic chips anymore

Literally none of this is correct.

> - Google’s Willow quantum chip significantly outpaces current supercomputers, solving tasks in minutes that would otherwise take billions of years.

billions of years you say? Just what kinds of "computing tasks" we talkin about here?

> Let's talk about things that actually matter

I'm all ears

> where to invest

and like that, you lost me

Somehow the universe knows how to organise the sand in an egg timer to form an orderly pile. Simulating that with a classical computer seems impossible - yet the universe "computes" the correct result in real time. It feels like there is a huge gap between what actually happens and what can be done with a computer (even a quantum one).

> I wonder why, the chip had 105 qubits and the error correction experiment used 101 qubits.

I wonder why, byte has 8 bits and the Hamming error correction code uses 7 bits.

oh right - that's because *the scheme* requires 3-7-15-... bits [0] and 7 is the largest that fits

Same with surface error correction - it's just the largest number in a list. No need for conspiracies. And no connection to manufacturing capabilities, which determine qubits on a single chip

[0] https://en.wikipedia.org/wiki/Hamming_code

That's what the author is saying. Researchers in this field should, for credibility reasons, be solving test problems that can be quickly verified. As to why this isn't done:

(1) They're picking problems domains that are maximally close to the substrate of the computation device, so they can hit maximum problem sizes (like 10^25). For many (all?) fast-verifiable problems they can't currently handle impressively large problem sizes. In the same way that GPUs are only really good at "embarrassingly parallel" algorithms like computer graphics and linear algebra, these quantum chips are only really good at certain classes of algorithms that don't require too much coherence.

(2) A lot of potential use cases are NOT easy to validate, but are still very useful and interesting. Weather and climate prediction, for example. Quantum chemistry simulations is another. Nuclear simulations for the department of energy. Cryptography is kinda exceptional in that it provides easily verifiable results.

I think he was making that exact point in this blog.

Because we don't currently know a problem like this that both has a quantum algorithm we can run on this type of device with expected exponential speedup and has a fast classical verification algorithm. That's exactly the author's point/he has been advocating for quite a while the importance of researching such an example that would be better to use.

> Why isn't that approach ever used to validate these quantum computing claims?

Hossenfelder’s linked tweet addresses this head on [1]. We need four orders of magnitude more qubits before a QC can simulate anything real.

In the meantime, we’re stuck with toy problems (absent the sort of intermediate test algorithms Aaronson mentions, though the existence of such algorithms would undermine the feat’s PR value, as it would afford cheap takedowns about the QC lacking supremacy).

[1] https://x.com/skdh/status/1866352680899104960

Could it be that it's not a chance if these kind of problems are chosen? Somehow we can get from a quantum system an amount of computation that goes well beyond what a classical system can perform, but we can't seem to extract any useful information from it. Hmm.

Right, Factoring and discrete logs both come to mind; is Google's quantum computer not able to achieve measurable speedups on those versus classical computation?

For reference, Aaronson is widely regarded as one of the foremost members of the field.

Try "I don't understand this claim"?

The question is not whether a problem is easier to verify than to solve but whether there is a problem that is provably faster (in the complexity sense) on a quantum computer than a classical computer that is easy to verify on a classical computer.

He argues this point exactly.

It’s the implementation of the quantum computer - what are the qubits and gates and things made of?

It is like we are still figuring out whether it’s better to use vacuum tubes or semiconductors or what. Google used superconducting circuits for Willow, which can be fabricated with computer-chip-style lithography etc, but needs to be kept extremely cold and the connectivity is obviously etched permanently into the circuit. Other technologies have different pros and cons.

I think the record for Shor's remains at 15.

Great question. The device is fully programable. Arbitrary one-qubit operations and arbitrary two-qubit operations between adjacent qubits can be performed. Theoretically these are 'universal for computation', meaning that a large enough device could compute anything computable. You can't program Quantum Tetris or whatever on a bouncy ball :).

But nevertheless, many of these 'beyond-classical' demonstrations feel a bit arbitrary in the way you describe, and there's good reason for this. Logical operations are still quite noisy, and the more you apply, the more output quality degrades. To get the most 'beyond-classical,' you run the thing that maps most readily to the physical layout and limitations of the hardware.

As things improve, we'll see more and more demonstrations of actually useful computations. Google and others have already performed lots of quantum simulations. In the long run, you will use quantum error correction, which is the other big announcement this week.

The key difference is that the problem being solved is a math problem. It can be written down on paper.

A ball falling on the ground can be converted into a math problem. To get the conversion exactly right you will need to write down the exact state of the ball. But you will invariably incur small inaccuracies while doing this. For example, maybe the mass you write down is off by 1 part in a trillion. The math problem is the ground truth, so any conversion inaccuracies are now errors in the ball. In practice these inaccuracies will prevent even the original ball from solving the written down problem much better than you could with a computer.

In the case of random circuit sampling, the written down problem is a tensor network [1] (that happens to also be a shallow quantum circuit). Fundamentally, a tensor network just specifies a bunch of matrix multiplications to do. It's not even that big of a problem: only a few kilobytes of information (whereas the exact state of a ball would be gargantuan). All you have to do is perform the specified multiplications, interpret the result as a probability distribution, and sample from it. The obstacle is that these multiplications create intermediate values that are really really large. The quantum computer bypasses this obstacle by executing the tensor network as a circuit.

[1]: https://en.wikipedia.org/wiki/Tensor_network

There are two points. You got the first one, which is controllability. The components are controllable and programmable. But second it's important to appreciate the difference between simulating 10^23 classical billiard balls with a computer (very hard, C * 10^23 work for some C) and simulating 10^23 quantum mechanical atoms (C * d^(10^23) work for some C and some d). Those numbers are very different.

The architecture/design of these quantum computers can do arbitrary computations. The specific machines we are currently able to build don't have enough qubits that remain coherent long enough to solve the problems we care about. We've built the aeolipile, now we need to scale it up to a steam turbine capable of moving ships and trains.

It's hard to say. For example the Google's paper talks about some rare (once an hour) strong errors. Are they fundamental or have some easy fix? We don't know.

One obvious problem is cooling. We can't cool million qubits in a single fridge, so we will need to split them between fridges and communicate. Also, the wiring is really complicated already and hard to scale (one reason IBM has heavy hex is to have more space).

Another problem is connectivity. For transmon qubits connectivity is fixed. Applying gate to two far qubits requires a lot of swaps, which is expensive. This is less of a problem for ions or cold atoms because they can couple any two qubits; but they likely wouldn't be able to for large amount of qubits.

Another thing is classical control, because the classical data needs to be processed at high speed. Some companies develop specialized hardware for that.

None of these is necessarily fundamental, but these problems need to be solved, in addition to usual scaling (it is hard to manufacture these devices and it becomes harder with each qubit).

I was told by a Microsoft researcher that it will unlock currently unsolvable problems in chemistry, weather modeling, materials science, fusion and plasma physics, drug development… the list went on but it was really long. Most advances he cited would result from improved simulations, iirc.

I don’t recall enough of the conversation (circa 2019) to remember anything about the properties of the problems it helps solve, so I can’t help generalize. Sorry.

I think we are well at the point where it is just time and money. Its not a physics problem its an engineering problem.

I'm sure there are lots of complicated problems ahead, but i don't think we are waiting for someone to discover "new" physics.

What does homeopathy need to move forward? What does perpetual motion machinery need to move forward?

This is not totally fair; it is possible given certain independence assumptions. But they are likely not physically realizable.

It is almost certain that even within our understanding of quantum systems it is simply not possible to have a quantum computer (much less create one). The assumptions necessary to produce a completely uncoupled system are likely invalid; we have yet to produce a compelling experiment to indicate otherwise. [1]

[1] https://arxiv.org/pdf/1908.02499

Isn't instant communication impossible, even with entanglement?

> the big benefit is parallel computing at a massive scale

The problem with this line of reasoning is that, even though a quantum system might have many possible states, we only observe a single one of those states at the time of measurement. If you could somehow prepare a quantum system such that it encoded the N equally-likely solutions to your classical problem, you would still need to rerun that experiment (on average) N times to get the correct answer.

Broadly speaking, quantum computing exploits the fact that states are entangled (and therefore correlated). By tweaking the circuit, you can make it so that incorrect solutions interfere destructively while the correct solution interferes constructively, making it more likely that you will measure the correct answer. (Of course this is all probabilistic, hence the need for quantum error correction.) But developing quantum algorithms is easier said than done, and there's no reason to think a priori that all classical problems can be recast in this manner.

Ahaha! Read the subtitle of the blog, literally at the top: "If you take nothing else from this blog: quantum computers won't solve hard problems instantly by just trying all solutions in parallel."

Even Scott Aaronson doesn't really know what they will be good for. Something something quantum simulation something something material science, perhaps. Yet nothing concrete, no example of a problem that they would actually solve. Apart from cracking RSA, which is the opposite of useful.

It seems the whole quantum computer thing only made people like him excited because it's a different kind of computer, not because there is any strong evidence that it will be practically useful.

It reminds me of nuclear fusion: Sounds cool, but it is highly doubtful whether it could ever compete economically with nuclear fission.

They did a test of pretty much the only thing it can do.

This is an extremely limited system, different in capability but in the grand scheme of things conceptually similar to implementing the quantum equivalent of a single binary digit.

No.

This is progress towards quantum computing but no where near progress towards a real practical quantum computer that could break Bitcoin's algorithms. If progress continues it could be an issue in the future, check back in next time Google publishes a paper.

Asking the real questions here.

I got that ‘Google has been talking about Willow for ages, this isn’t new’ blah blah blah. The problem is the public only started talking about it yesterday.

No, won’t all your stocks and financial information be gone also?

Also Willow can’t even factor 15=5x3 you are good for a very long time.

no

not for the next 5 years for sure.

quantum computing is entering "middle-late 1930s" - it's still quite some time away from Turing&Enigma moment

but it already passed "1920s" with "only radios" - analog, non-digital devices

stability tech is almost here (check quanta magazine), next is the scaling up

Nothing, yet.

Unless your job involves factoring numbers into primes (or a few other limited math problems) probably never.

I don't think it has crazy math skills at all. That's what classical computing is really good at - give it a problem of arbitrary length and a computer should be able to string together instructions to yield you a sum.

Quantum computing, especially right now, is simply focused on getting reliable input/output idempotency. It will be a really long time before it has insane and crazy math skills, and when it does, traditional CPU architectures will probably outperform it.

TL:DR - if the Texas Instrument calculator didn't put you out of a job, neither will quantum computers.

There's two great lanes of progress happening in engineering these days: 1. Quantum Computing, and 2. AI.

If they can find some synergies between the two, that could be THE major development. Make better AI by using Quantum Computers, and make better Quantum Computers by applying AI.