- Richard Feynman emphasized the power of quantum computers over 30 years ago.
- Quantum computers can simulate quantum systems more effectively than classical computers.
- Quantum error correction is a theory developed in the mid-90s to protect quantum states from environmental interactions.
- Entanglement is a key characteristic of quantum physics, where information is stored in correlations between particles.
- Quantum error correction takes advantage of entanglement to protect information from being disturbed by the environment.
- Grover's algorithm is a way to speed up exhaustive searches in quantum computing.
- Quantum computing utilizes interference, where probabilities add based on the squares of amplitudes.

- In quantum physics, the interference phenomenon occurs when different alternatives can interfere with each other, leading to wiggles in graphs and the ability to enhance the probability of getting the right answer.
- Quantum computers have the potential to outperform classical computers and have transformative effects on society, particularly in areas such as understanding and inventing new materials and chemical compounds.
- Quantum computers excel at solving quantum physics problems and predicting the behavior of quantum systems, which is difficult for ordinary digital computers.
- The exponential speedups offered by quantum computing, such as Shor's algorithm for factoring large numbers, are particularly exciting.
- The pressing problems in physics related to quantum computing include determining the best approach to building quantum hardware and increasing the number of qubits to achieve better control.

- In the next few years, quantum computers with 50 to 100 qubits will be developed, which is already too many for digital computers to simulate.
- The reliability of qubits and the error rate of quantum gates are important factors in quantum computing.
- Hybrid classical-quantum methods with classical feedback are expected to be used for optimization problems.
- Different approaches to quantum computing include trapped ions, superconductivity circuits, and topological quantum computing.
- Microsoft is working on topological quantum computing, which aims to create better qubits with improved control.
- The progress in quantum computing has been driven by advancements in coherence time and reducing interactions with the outside world.

- Coherence time of qubits in superconducting circuits is crucial for quantum computers
- Coherence times have been increasing by a factor of 10 every 3 years
- Control of qubits is critical for progress in quantum computing
- Superconducting circuits and trapped ions are the most advanced technologies currently
- Other technologies like topologically protected qubits have potential but are not expected to surpass superconducting circuits and trapped ions in the next 5-10 years
- Companies like IBM, Google, Microsoft, and Intel, as well as startups, are working on quantum technology
- Quantum computers are likely to be accessed through cloud-based interfaces in the near term
- Nuclear spins offer a potential approach for quantum information storage at room temperature
- Quantum computers pose a threat to current encryption schemes and alternative cryptographic protocols are being developed for post-quantum cryptography

- There is currently no proposed cryptosystem that is considered quantum resistant or unbreakable by quantum computers.
- The US government wants a system that can stay secure for 50 years and be used for 20 years, with intercepted traffic protected for another 30 years.
- Quantum key distribution allows for secure communication by sending qubits instead of bits, with the ability to detect if the key has been tampered with.
- Quantum cryptography requires a different infrastructure, such as sending qubits through optical fiber, and the development of quantum repeaters for long-distance communication.
- Quantum technology has potential for improved sensing, particularly in biological and medical applications.
- The speaker's research interests include quantum computing and the exploration of quantum information as a new frontier in the physical sciences.

- Quantum information is a new frontier in the physical sciences, referred to as the entanglement frontier.
- The entanglement frontier involves scaling up quantum systems to larger complexity, making it harder to simulate with existing digital tools.
- Quantum information is connected to fundamental questions about gravitation and the nature of space-time.
- Quantum error correction is a key concept in understanding how space-time geometry works.
- Entanglement holds space together and prevents it from falling apart into separate pieces.
- Experimentation and the development of quantum computers may provide guidance in understanding the quantum structure of space-time.
- Quantum entanglement allows for correlations among quantum systems that are different from classical correlations.
- Entanglement is unique because there are complementary ways of measuring qubits, unlike classical coins.
- The impression that quantum entanglement allows for instantaneous communication over long distances is not accurate.

- Entanglement does not mean that actions on one qubit instantaneously affect another qubit, but rather that they are correlated in a certain way.
- Quantum computers are not more powerful because they can perform multiple computations at once, but because they can utilize interference to enhance the correct answer.
- Richard Feynman was a physicist who loved physics and enjoyed discussing and drumming. He was dismissive of relying on the knowledge of others and preferred to find his own approach to problems. He also enjoyed telling stories and served on the Challenger Commission after the space shuttle explosion.

- Quantum computers have the potential to outperform classical computers and have transformative effects on society.
- Quantum error correction and entanglement are key concepts in protecting and utilizing quantum information.
- Grover's algorithm and interference are important elements in quantum computing.
- The development of quantum hardware and increasing the number of qubits are pressing challenges.
- Different approaches to quantum computing are being explored, with trapped ions and superconducting circuits being the most advanced.
- Companies like IBM, Google, Microsoft, and Intel are actively working on quantum technology.
- Quantum computers pose a threat to current encryption schemes, and alternative cryptographic protocols are being developed.
- Quantum technology has potential applications in sensing, communication, and understanding the quantum structure of space-time.

- The speaker discusses Richard Feynman's interest in various subjects, including biology and computation.
- They mention the possibility of quantum computing becoming more accessible and simple in the future, even for those without a deep understanding of physics.
- The speaker suggests that experimenting and "fooling around" with quantum computers could lead to the discovery of new applications.
- In terms of STEM education, the speaker emphasizes the importance of teaching reasoning skills and critical thinking, as well as the ability to evaluate evidence.
- They mention the need for more scientifically trained individuals in government, both in elected positions and within agencies dealing with technical issues.
- The Department of Energy under the Obama administration supported startup companies and technologies related to battery and solar power advancements.

- The Department of Energy has supported startup companies to improve battery technology and solar power.
- The Bay Area is a hub for quantum startups due to the concentration of tech industry and potential investors.
- Communication across different areas of expertise is valuable in entrepreneurial activities related to physics.
- Teaching and explaining concepts helps deepen knowledge and gain new insights.
- Leonard Susskind, a physicist at Stanford, is recommended for learning about quantum computing and physics through his lectures and books.

- The speaker learned about quantum computing and information science through teaching a quantum information class at Caltech.
- Teaching the class helped the speaker synthesize and understand concepts in information theory, computational complexity, and algorithms.
- The experience expanded the speaker's knowledge and made them feel more confident in their understanding of the subject.
- The speaker also had a similar experience in particle physics when teaching a comprehensive class on elementary particles.
- Teaching these classes continues to influence the speaker's thinking and gives them new ideas.

The speaker discusses Richard Feynman's interests, the future accessibility of quantum computing, the importance of STEM education and scientifically trained individuals in government, the Department of Energy's support for battery and solar power advancements, the concentration of quantum startups in the Bay Area, the value of communication across expertise, the benefits of teaching and explaining concepts, and the speaker's personal experiences teaching quantum information and particle physics classes.

John Preskill - https://twitter.com/preskill - is a theoretical physicist and the Richard P. Feynman Professor of Theoretical Physics at Caltech - http://www.theory.caltech.edu/people/preskill/

Read the transcript here - https://blog.ycombinator.com/john-preskill-on-quantum-computing

He once won a bet with Steven Hawking - http://www.theory.caltech.edu/people/preskill/bets.html - which as he writes made him “briefly almost famous.” John and Kip Thorne - https://en.wikipedia.org/wiki/Kip_Thorne - bet that singularities could exist outside of black holes and after six years Hawking conceded that they were possible in very special, “nongeneric” conditions.

In this episode we cover what John’s been focusing on for years: quantum information, quantum computing, and quantum error correction.

The YC podcast is hosted by Craig Cannon - https://twitter.com/craigcannon

And what was the revelation that made scientists and physicists think that a quantum computer could exist?

You know, a lot of people thought it couldn't.

The idea that a quantum computer would be powerful was emphasized over 30 years ago by Richard Feynman, the Caltech physicist.

And it was interesting how he came to that realization.

Feynman was interested in computation his whole life.

He had been involved during the war in Los Alamos.

He was the head of the computation group.

He was the guy who fixed the little mechanical calculators and he had a whole crew of people who were calculating and he figured out how to flow the work from 1 computer to another, all that kind of stuff.

And as computing technology started to evolve, he followed that.

And in the 1970s, particle physicists like Feynman, that's my background too, got really interested in using computers to study the properties of elementary particles, like the quarks inside a nucleus.

We know a proton isn't really a fundamental object.

It's got little beans rattling around inside, but they're quantum.

And Gell-Mann, who's good at names, called them quarks.

And now we've had a theory since the 1970s of how quarks behave.

And so in principle, you know everything about the theory, you can compute everything, but you can't because it's just too hard.

And people started to simulate that physics with digital computers in the 70s.

And there were some things that they could successfully compute and some things they couldn't, because it was just too hard.

The resources required, the memory, the time were out of reach.

And so Feynman in the early 80s said, you know, nature is quantum mechanical, damn it.

want a simulation of nature, it should be quantum mechanical.

You should use a quantum system to behave like another quantum system.

At the time, he called it a universal quantum simulator.

And the idea caught on about 10 years later when Peter Shore made the suggestion that we could solve problems which don't seem to have anything to do with physics, which are really things about numbers, like finding the prime factors of a big integer.

And that caused a lot of excitement, in part because the implications for cryptography are a bit disturbing.

But then physicists, good physicists, started to consider, can we really build this thing?

And some concluded and argued fairly cogently that no, you couldn't because of this difficulty that it's so hard to isolate systems from the environment well enough for them to behave quantumly.

And so it took a few years for that to sort out sort of at the theoretical level.

In the mid-90s we developed a theory called quantum error correction.

It's about how to encode the quantum state that you'd like to protect in such a clever way that even if there are some interactions with the environment that you can't control, it still stays robust.

But at first that was just kind of a theorist's fantasy.

It was a little too far ahead of the technology.

But you know, 20 years later, the technology is catching up.

So now this idea of quantum error correction has become something you can do in the lab.

And how does quantum error correction work?

I've seen a bunch of diagrams, so maybe this is difficult to explain, but how would you explain it?

I don't think I've said the word entanglement yet.

No, I have been checking off all the bingo words yet.

Okay, so let's talk about entanglement because it's part of the answer to your question, which I'm still not done answering.

It's really the characteristic way, maybe the most important way that we know, in which quantum is different from ordinary stuff and classical.

It means that you can have a physical system which has many parts which have interacted with 1 another so it's in kind of a complex correlated state of all those parts.

And when you look at the parts 1 at a time, it doesn't tell you anything about the state of the whole thing.

The whole thing's in some definite state.

So, if it's an ordinary book, 100 people could each take a page and read it.

They'd know what's on that page and then they could get together and talk and now they'd know everything that's in the book, right?

But if it's a quantum book written in cupids where these pages are very highly entangled, There's still a lot of information in the book, but you can't read it the way I just described.

You can look at the pages 1 at a time, but a single page, when you look at it, just gives you random gibberish.

It doesn't reveal anything about the content of the book.

There's information in the book, but it's not stored in the individual pages.

It's encoded almost entirely in how those pages are correlated with 1 another.

That's what we mean by quantum entanglement.

Information stored in those correlations, which you can't see when you look at the parts 1 at a time.

So you asked about quantum error correction.

It's to take advantage of that property of entanglement.

Because let's say you have a system of many particles and the environment is kind of kicking them around, it's interacting with them.

Because you can't really completely turn off those interactions no matter how hard you try.

But suppose we've encoded the information in entanglement.

So say if you look at 1 atom, it's not telling you anything about the information you're trying to protect.

So the environment isn't learning anything when it looks at the atoms 1 at a time.

And this is kind of The key thing that what makes quantum information so fragile is that when you look at it, you disturb it.

This ordinary water bottle isn't like that.

Let's say we knew it was either here or here and we didn't know.

I would look at it, I'd find out it's here.

I was ignorant of where it was to start with, and now I know.

But with a quantum system, when you look at it, you really change the state.

So if the environment is looking at it in the sense that information is leaking out to the environment, that's going to mess it up.

So we have to encode the information so the environment, so to speak, can't find out anything about what the information is.

And that's the idea of quantum error correction.

If we encoded an entanglement, The environment is looking at the parts 1 at a time, but it doesn't find out what the protected information is.

Yeah, no, so in other words, it's kind of measuring probability the whole way along, right?

Is it Grover's algorithm that was, like as quantum bits roll through, go through gates, the probability is determined of what information's being passed through, what's being computed?

Yeah, So Grover's algorithm is a way of sort of doing an exhaustive search through many possibilities.

You know, like let's say I'm trying to solve some problem like you know a famous 1 is the traveling salesman problem you know I've told you what the distances are between all the pairs of cities and now I want to find the shortest route I can that visits them all.

And it's still hard for a quantum computer, but not quite as hard, because there's a way of solving it, which is to try all the different routes and measure how long they are and then find the 1 that's shortest and you've solved the problem.

The reason it's still hard to solve is there's such a vast number of possible routes.

What Grover's algorithm does is it speeds up that exhaustive search.

And in practice it's not that big a deal.

What it means is that if you have the same processing speed, you can handle about twice as many cities before the problem becomes too hard to solve as you could if you were using a classical processor.

But as far as what's quantum about Grover, it takes advantage of the property in quantum physics that probabilities, Tell me if I'm getting too inside baseball.

That probabilities are the squares of amplitudes.

Again, this is another part of the answer.

Well, we can spend the whole hour answering the question, what is quantum physics?

Another essential part of it is what we call interference, and this is really crucial for understanding how quantum computing works, and that is that probabilities add.

You know, if you know the probability of 1 alternative and you know the probability of another, then you can add those together and find the probability that 1 or the other occurred.

And it's not like that in quantum physics.

The famous example is the double slit interference experiment.

I'm sending electrons, let's say, it could be basketballs, but it's an easier experiment to do with electrons, at a screen and there are 2 holes in the screen and you can try to detect the electron on the other side of the screen.

And when you do that experiment many times, you can plot a graph showing where the electron was detected, you know, in each run or make a histogram of all the different outcomes and the graph wiggles.

So if you could say there's some probability of going through the first hole and some probability of going through the second and each time you've detected it, it went through either 1 or the other, there'd be no wiggles in that graph.

It's the interference that makes it wiggle.

And the essence of the interference is that nobody can tell you whether it went through the first slit or the second slit.

The question is sort of inadmissible And this interference then occurs when we can add up these different alternatives in a way which is different from what we're used to.

It's not right to say that the electron was detected at this point because it had some probability of going through the first hole and some probability of going through the second and we add those probabilities up, that doesn't give the right answer.

The different alternatives can interfere.

And This is really important for quantum computing because what we're trying to do is enhance the probability or the time it takes to find the solution to a problem.

And this interference can work to our advantage.

We want to have, you know, when we're doing our search, we wanna have a higher chance of getting the right answer and a lower chance of getting the wrong answer.

And if the different wrong answers can interfere, they can cancel 1 another out and that enhances the probability of getting the right answer.

So sorry it's such a long-winded answer, but this is how Grover's algorithm works.

can speed up exhaustive search by taking advantage of that interference phenomenon.

Well, this is kind of 1 of the underlying questions among many of the questions from Twitter.

You've hit our record for most questions asked.

But basically, many people are wondering what quantum computers really will do if and when it becomes a reality that they outperform classical computers.

What are they going to be really good at?

And I think, you know, if you look at the history of technology, it would be hubris to expect me to know.

It's a whole different way of dealing with information.

This quantum information, it's not just, you know, a quantum computer is not just a faster way of computing.

It deals with information in a completely new way because of this interference phenomenon, because of entanglement that we've talked about.

And I think we have limited vision when it comes to predicting decades out what the impact will be of an entirely new way of doing things, information processing in particular.

I mean, you know this well, if we go back to the 1960s and people are starting to put a few transistors on a chip, where's that going to lead?

JCWan Even early days of the internet, even the first browser, No 1 really knew what anyone was going to do with it.

You know, I think, why are we confident there will be some transformative effect on society?

Of the things we know about, and I emphasize again, probably the most important ones are things we haven't thought of

it comes to applications of quantum computing.

Ones which will affect everyday life, I think, are better methods for understanding and inventing new materials, new chemical compounds.

Things like that can be really important.

You know, if you find a better way of capturing carbon by designing a better catalyst, or you can design pharmaceuticals that have new effects, materials that have unusual properties.

These are quantum physics problems because those properties of the molecule or the material really have to do with the underlying quantum behavior of the particles and we don't have a good way for solving such problems or predicting that behavior using ordinary digital computers.

That's what a quantum computer is good at.

It's good but maybe not the only thing it's good at.

But 1 thing it should certainly be good at is telling us quantitatively how quantum systems behave.

And in the 2 contexts I just mentioned, there's little question that there will be practical impact of that.

So it's not, it's not just doing the traveling salesman problem through the table of elements for like why it can find those compounds.

If it were, that wouldn't be very efficient.

And you know, like I said, the exhaustive search though, conceptually, it's really interesting that quantum can speed it up because of interference.

From a practical point of view, it may not be that big a deal.

It means that, well, like I said, in the same amount of time you can solve an instance which is twice as big of the problem.

So what we really get excited about are the so-called exponential speedups.

And that was why Shor's algorithm was exciting in 1994 because factoring large numbers was a problem that had been studied by smart people for a long time.

And on that basis, the fact that there weren't any fast ways of solving it was pretty good evidence it's a hard problem.

Actually, we don't know how to prove that from first principles.

Maybe somebody will come along 1 day and figure out how to solve factoring very fast on a digital computer.

It doesn't seem very likely because people have been trying for so long to solve problems like that and it's just intractable with ordinary computers.

You could say the same thing about these quantum physics problems.

Maybe some brilliant graduate student is going to drop a paper on the archive tomorrow which will say, here I solved quantum chemistry and I can do it on a digital computer.

But we don't think that's very likely because we've been working pretty hard on these problems for decades and they seem to be really hard.

And so those cases like these number theoretic problems which have cryptological implications and tasks for simulating the behavior of quantum systems, we're pretty sure those are hard problems.

Classically, and we're pretty sure quantum computers, I mean we have algorithms that have been proposed, but which we can't really run currently because our quantum computers aren't big enough, on the scale that's needed to solve problems really, people really care about.

Yeah, so maybe we should jump to 1 of the questions from Twitter which is related to that.

So Travis Sholton asked, what are the most problem pressings in physics, let's say specifically around quantum computers, that you think substantial progress ought to be made in to move the field forward?

So, the problems that we need to solve to make quantum computing closer to realization at the level that would solve problems people care about.

So, people have been working on quantum hardware for, you know, 20 years, working hard.

And there are a number of different approaches to building the hardware and nobody really knows which is going to be the best.

We haven't, I think we're far from collapsing to 1 approach which everybody agrees has the best long-term prospects for scalability.

And so it's important that a lot of different types of hardware are being pursued.

And we can come back to what some of the different approaches are later.

We think in a couple of years we'll have devices with about 50 qubits to 100, and we'll be able to control them pretty well.

And that's an interesting range, because even though it's only 50 to 100 qubits, doesn't sound like that big a deal, but that's already too many to simulate with a digital computer, even with the most powerful supercomputers today.

So from that point of view, these are relatively small, near-term quantum computers, which we'll be fooling around with over the next 5 years or so, are doing something that's kind of super classical.

At least we don't know how to do exactly the same things with ordinary computers.

Now that doesn't mean they'll be able to do anything that's practically important, but we're gonna try.

And there are ideas about things we'll try out, including sort of baby versions of these problems in chemistry and materials and ways of speeding up optimization problems.

Nobody knows how well those things are going to work at these small scales.

Part of the reason is not just that the number of qubits is small, but they're also not perfect.

So we can perform elementary operations on pairs of qubits, which we call quantum gates, like the gates in ordinary logic, But they have an error rate a little bit below, you know, an error every 100 gates.

So that if you have a circuit with 1000 qubits, there's a lot of noise.

So exactly, like does, for instance, a 100 qubit quantum computer really mean a hundred qubit quantum commuter?

Or do you need a certain amount of backup going on?

Well, I think In the near term, we're going to be trying out, and probably we have the best hopes, for kind of hybrid classical quantum methods with some kind of classical feedback.

try to do something on the quantum computer, you make a measurement that gives you some information, then you change the way you did it a little bit and try to converge on some better answer.

That's 1 possible way of addressing optimization that might be faster on a quantum computer, but I just wanted to emphasize that the number of qubits isn't the only metric and how good they are and in particular the reliability of the gates, how well we can perform them.

So anyway, coming back to Travis's question, well there are lots of things that we'd like to be able to do better, but just having much better qubits would be huge, right?

So if you, more or less with the technology we have now, you can have a gate error rate of a few parts in a thousand.

If you can improve that by orders of magnitude, then obviously you could run bigger circuits and that would be very enabling.

Even if you stick with 100 qubits, just by having a circuit with more depth, you know, more layers of gates that increases the range of what you could do.

So that's, and that's always gonna be important.

Because, I mean, look at, that's, look at how crappy that is.

A gate error rate, even if it's 1 part in a thousand, it's pretty lousy compared to if you look at where classical processors are.

has a billion transistors in it, something like that, and

You don't worry about the, it's gotten to the point where there is some error protection built in at the hardware level in a processor because, I mean, we're doing these crazy things like going down to an

11 nanometer scale for features on a chip.

So how are folks trying to deal with interference right now.

And yeah, so that's interesting too because there are a range of different ways to do it.

So I mentioned that We could store information, we can make a qubit out of a single atom, for example.

So you have to control a whole bunch of atoms and get them to interact with 1 another.

1 way of doing that is with what we call trapped ions.

That means the atoms have electrical charges.

That's a good thing because then you can control them with electric fields.

You can hold them in a trap and you can isolate them, like I said, in a very high vacuum, so they're not interacting too much with other things in the laboratory, including stray electric and magnetic fields.

But that's not enough, because you gotta get them to talk to 1 another, you gotta get them to interact.

I mean, we have this set of desiderata, which are kind of in tension with 1 another.

On the 1 hand, we want to isolate the qubits very well.

On the other hand, we want to control them from the outside and get them to do what we want them to do.

You have to be able to read out the result of a computation.

If you want to do, you add 2 of those qubits in your device to interact with 1 another in a specified way and to do that very accurately, you have to have some kind of bus that gets the 2 to talk to 1 another.

way they do that in an ion trap is pretty interesting.

It's by using lasers and controlling how the ions vibrate in the trap.

And with a laser, kind of excite wiggles of the ion.

And then by, you know, determining whether the ions are wiggling or not, you can go address another ion and that way you can do a 2 qubit interaction and you can do that pretty well.

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John Preskill on Quantum Computing