Sabine Hossenfelder: Backreaction: Quantum Winter Is Coming

[This is a transcript of the video embedded below. Some of the explanations may not make sense without the animations in the video.]Quantum technology current attracts a lot of attention and money, which might explain why they’re missing on my end. But it’s not just governments who think quantum everything is where your taxes should go, business investors and companies are willing to putting in big money, too. This has had a dramatic impact on quantum physics research in the past decade. It’s also created a lot of hype, especially around quantum computing. But if so much of quantum computing is hype then why are companies like Google and IBM pouring so much money into it, what’ll happen when the investment bubble bursts, what’s the “quantum winter”, and what does it mean for all of us? That’s what we’ll talk about today. There are several different quantum technologies, and as a rule of thumb, the fewer headlines they make, the more promising they are. Take for example, quantum metrology. That’s not a mispronunciation of meteorology, that’s making better measurements with quantum effects. You basically never read anything about this. But it’s really promising and already being used by scientists to improve their own experiments. You can learn more about this in my earlier video.

The quantum internet is one of those things that you read a lot about but don't need or want. According to many headlines, quantum computing will change the world. Nuclear fusion and quantum computers are both promising technologies, but how did they work out?

A lot of physicists, me included, have warned that quantum computing is being oversold. It’s not going to change the world, it’ll have some niche applications at best, and it’s going to take much longer than many start-ups want you to believe.

I like the optimism of the quantum computing believers. Multiverse is a startup that works with customers in more than 10 different industries. Some of them don't return from the bathroom.

There is a universal quantum that helps everyone find a "super position" and has afault tolerant team. Do they collapse if you stare at them?

According to the company, quantum computers are suited to modelling complex systems, making them better at forecasting both near term weather patterns and the long-term effects of climate change.

Last time I looked, no one had any idea how to do a weather forecast on a quantum computer. It’s not just that no one has done it, no one knows if it’s even possible, because weather is a non-linear system whereas quantum mechanics is a linear theory.

An article titled "Quantum computing: a new industrial revolution" can be found on the website "Investors Chronicle". When problem-solving power can be applied to real world issues, which makes it much more interesting, they explain that quantum computers are close to showing "quantum advantage" and that "Quantum advantage, therefore, can be interpreted as being when problem-solving power can be applied to real world

That’s just wrong. Quantum advantage has indeed been demonstrated for some quantum computers but that just means the quantum computer did something faster than a conventional computer, not that this was of any use for real world issues. They just produced a random distribution that would take a really long time to calculate by any other means. It’s like this this guy stapling 5 M&M. That’s a world record, hurray, but what are you going to do with it?

A lot of CEOs in industry and the financial sector can't tell from a ket that quantum computing is going to be relevant for their business, and that it's going to be relevant soon The managing director of research at Bank of America said that quantum computing will be bigger than fire. I think it will produce more carbon emissions.

This bubble of inflated promises will eventually burst. It’s just a matter of time. This’ll cause a sudden decline of investment in quantum tech overall and be the start of a difficult time for research and development. This scenario has been dubbed the “quantum winter”. And winter is coming. But before we get to the quantum winter, let me briefly summarize how quantum computers work and what their problems are. A conventional computer works with bits that take on one of two discrete values. A quantum computer instead uses qubits that can be in arbitrary *superpositions of two states. A quantum computer then works by entangling the qubits and shifting this entanglement around. Entanglement is a type of correlation, but it has no analogy in conventional computers. This is why quantum computers can do things that standard computers can’t do. For some mathematical problems, a quantum computer can give you an answer much faster than any conventional computer possibly could. This is called “quantum advantage”. Those problems include things like factorizing large numbers into prime factors. But also calculating properties of molecules and materials without having to chemically synthesize them first. Putting these questions on a quantum computer could speed up material design and drug discovery. Quantum computers can also solve certain logistic problems or optimize financial systems. This is why, if you’re Bank of America, you think it's bigger than fire. And like fire, quantum computing is not magic, it’s an application of standard quantum mechanics. There is no speculative new physics involved. It’s rather to the contrary. Claims that quantum computers will *not work rest on speculative new physics. But it’s one thing to say if you could build them, they’d be useful. It’s another thing entirely to actually build them. So what does it take to build a quantum computer? First of all you need qubits. Then you have to find a way of entangling many of those qubits. And, like a conventional computer, a quantum computer needs an algorithm, that tells it how to move the entanglement around. Eventually, you make a measurement which collapses the wave-function and you read out the final state. This final state should be one that answers your question correctly with high probability. This means most importantly, a quantum computer isn’t a stand-alone device, it needs other devices for the programming and the readout. The quantum part is really just a small piece of the whole thing. Now let’s talk about the problems. First there’s the qubits. Producing them is not the problem, indeed there are many different ways to produce qubits. I went through the advantages and disadvantages of each approach in an earlier video, so check this out if you want to know more. But a general problem with qubits is decoherence, which means they lose their quantum properties quickly. The currently most widely developed systems are superconducting qubits and ion traps. Superconducting qbits are used for example by IBM and Google. For them to work, they have to be cooled to 10-20 milli Kelvin, that’s colder than outer space. Even so, they decoherence within 10s of micro-seconds.

Ion traps are used by many companies. They need to be cooled to a few zeros. They have longer coherence times, up to some minutes, but they are also slower to respond to operations, so it is not clear which approach is better. They're both bad. It is difficult to scale to larger quantum computers due to the high cost and energy intensive cooling. IBM is attempting to break world records by building large containers. If quantum computing doesn't work out, they can rent them out for people to freeze their heads.

There are some qubits that operate at room temperature, the most promising ones of those are currently nitrogen vacancy systems and photonics on a chip. However, for both of those, no working quantum computer exists to date and it’s unclear even what the challenges may be, let alone how to overcome them. The next biggest problem is combining these qubits. Again, the issue is that quantum effects are fragile, so the quantum computer is extremely sensitive to noise. The noise brings in errors. You can correct for those to some extent, but this error correction requires more qubits. More qubits bring problems by themselves, for example, they tend to be not as independent as they should be, an issue known as “crosstalk”. It’s kind of like if you’re trying to write while moving your feet in circles. It gets really difficult. The qubits states are also drifting if you leave them unattended. Indeed it’s somewhat of a mystery at the moment what a quantum computer does if you don’t calculate with it. It’s like it’s difficult to calculate what a big quantum system does. Maybe we can put it on a quantum computer? And finally there’s the issue of the algorithms: Few algorithms for quantum computers are known, an issue that goes often unmentioned because everyone is focused on the technology. Wikipedia helpfully has a list of quantum algorithms. It’s short. Several of those algorithms don’t compute anything of practical use, and for some it's not known if they lead to any speedup. As this brief summary makes clear, the challenges are enormous. But how far along is the technology? The largest current quantum computers have somewhere between 50 and 100 qubits, though IBM has a roadmap saying they want to make it to a thousand next year. Two different approaches have demonstrated a “quantum advantage”, that is, they have performed a calculation faster than the currently fastest conventional computer could have done. However in those demonstrations of quantum advantage, the devices were executing algorithms that did not calculate anything of use.

The prime number factorization of 21 is the most useful calculation for quantum computers. The number isn't the number of digits. If you do it on a quantum computer, it can be published in Nature. If you are impressed by this achievement, please be aware that doing this calculation with the standard algorithm and error correction is way past the capacity of current quantum computers. They used a simplified method for this number.

To be fair, there have been some cute applications of quantum algorithms for simple examples in quantum chemistry and machine learning, but none of this is anywhere even close to being commercially interesting. How many qubits do you need for a quantum computer to do something commercially interesting? Current estimates say it’s several hundred thousand to a few millions qubits, depending on what you want to calculate and how large your tolerance for errors is. A lot of quantum computing enthusiasts claim that we’ll get there quickly because of Moore’s law. Unfortunately, I have to inform you that Moore’s law isn’t a law of nature. It worked for conventional computers because those could be miniaturized. However, you can’t miniaturize ions or the Compton wavelength of electrons. They’re already as small as it gets. Nature’s a bitch sometimes. In the past years there’s been some noise around Noisy intermediate scale quantum computers, or NISQs for short. Those are small quantum computers in which you just accept the noise, kind of like YouTube comment sections. But no one seems to have found anything useful to do with them and the hype around them has noticeably died down recently. I guess you understand now why I am extremely skeptical that we are anywhere close to commercially relevant applications of quantum computers. But let’s hear what some other people say.

There is a physics professor who has been working on quantum things for a long time. He wrote a book titled " Will we ever have a quantum computer?" in 2020. If you agree to write a book but then want to do something else, it only has 49 pages. Heanswers his own question.

“No, we will never have a quantum computer. Instead, we might have some special-task (and outrageously expensive) quantum devices operating at millikelvin temperatures. The saga of quantum computing is waiting for a profound sociological analysis, and some lessons for the future should be learnt from this fascinating adventure.”

The brevity of Dyakonov’s book is balanced by another book “Law and Policy for the Quantum Age” by Chris Hoofnagle and Simson Garfinkle, who make it to a whooping 602 pages. Their book was just published earlier this year, it’s freely available online, and it has an adorable cat pic on the cover, so definitely go check it out. Hoofnagle is a professor for law and Garfinkle is a data scientist, but their book has been heavily informed by people who work in quantum computing. They look at the possible future scenarios. The most likely scenario, they say, is the “Quantum Winter” which they describe as follows:

“In this scenario (call it “Quantum Winter”), quantum computing devices remain noisy and never scale to a meaningful quantum advantage… After a tremendous amount of public and private monies are spent pursuing quantum technologies, businesses in the field are limited to research applications or simply fail, and career paths wither. If that happens, funding eventually dries up for quantum computing. Academics and scientists in the field either retool and shift, or simply appear irrelevant, even embarrassing.”

Then there is Victor Galitski, Professor at the Joint Quantum Institute at the University of Maryland who wrote in a 2021 post on LinkedIn:

“The number of known quantum algorithms, which promise advantage over classical computation, is just a few (and none of them will "solve global warming" for sure). More importantly, exactly zero such algorithms have been demonstrated in practice so far and the gap between what’s needed to realize them and the currently available hardware is huge, and it's not just a question of numbers. There are qualitative challenges with scaling up, which will likely take decades to resolve (if ever).”

Most recently, there was an opinion piece by Nikita Gourianov in the Financial Times. Nikita works on computational quantum physics at the University of Oxford. He writes:

“As more money flowed [into quantum computing], the field grew, and it became progressively more tempting for scientists to oversell their results… After a few years of this, a highly exaggerated perspective on the promise of quantum computing reached the mainstream, leading to… the formation of a classical bubble.”

He then points out that no quantum computing company is currently making profit and that:

“The little revenue they generate mostly comes from consulting missions aimed at teaching other companies about “how quantum computers will help their business”.”

I have to disagree on the final point because big companies have another way to make money from quantum computers, namely by renting them out to universities. And since governments are pouring money into research, that’s quite a promising way to funnel tax money into your business. Imagine the LHC was owned by Google and particle physicists had to pay to use it. That’s how I think it’ll go with quantum computing: First all the smaller startups will falter because they don’t reach their milestones, venture capital will evaporate, and all the overeducated quantum computists in academia will use grant money to pay a few large companies who own the only workable devices. And while those devices are interesting research objects, they’ll not be useful for commercial applications. I might be totally wrong of course. Maybe one of those start-ups will actually come up with a scalable quantum computing platform. I don’t know, I’m guessing as much as everyone else. But if quantum winter is coming, what does it mean for you and me? Well, some people will lose a lot of money but that just means they had too much of it to begin with, so can’t say it bothers me all that much. There’ll also be fewer headlines about how quantum computing is supposedly going to revolutionize something or other, which I’d say is a good development. And we’ll see many people who worked in quantum computing going into other professions. Chances are in ten years you can have a nice chat about the finer details of multi-particle entanglement with your taxi driver. I don’t know about you, but I’m looking forward to quantum winter.