B (3:27)

They show up at the smallest of scales. The reason you don't see them on A day to day basis is you don't have senses that can perceive atoms and electrons. It's just as weird that when you let go of something, it falls to the ground. Why should gravity exist at all? You don't question it because you're used to it. Quantum mechanics is kind of the same way, except scientists only first started observing these phenomena 100 years ago.

A (3:54)

And what was the first quantum result that made scientists themselves say, wait, that can't be right.

B (4:02)

There were a number of things that shocked people. I would say most famously, Einstein objected to this idea of entanglement, that is, that particles could be linked over distances because relativity says information can't travel faster than the speed of light. That's still true. Entanglement doesn't let information travel instantaneously. And yet there is some instantaneous linkage between particles.

A (4:31)

And that instantaneous linkage between particles can be across vast distances, even across galaxies.

B (4:40)

In principle, yes, you could have that over arbitrarily large distances. And that's one of the key pieces for building interesting quantum technologies.

A (4:49)

What are the other key pieces?

B (4:52)

The other is, are called superposition. This is the idea that an object can be more than one thing at the same time. For a computer, we store information as zeros or ones. But a quantum computer could store information as 0 and ones@ the same time. And that allows you to explore a much larger space in your algorithms. When you observe a system, you only ever get one outcome. So if I ask just the right question, then the system, which could have been sort of in a superposition of everything that ever could happen, suddenly becomes only a subset of those things. And that allows you to sort of search for patterns in data periods where something repeats over and over again. These kinds of things are often the things we're looking for when we run some kind of algorithm. It's also important for error correction. In quantum computing. Information is very fragile, and you can get these very small analog errors that are very hard to correct. But you can ask the question, did an error occur? And as a result, you get the answer either yes or no. And if you get a yes, it makes the error much worse, but also something that we can fix.

A (6:07)

So quantum allows many different possibilities at once. The famous case of Schrodinger's cat being both potentially alive and dead at the same time.

B (6:20)

That's right. So stranger's cat can be both alive and dead at the same time. But when you look at the cat, you only ever see a cat that's alive or dead. But until you look it can be both. And that's different from not knowing. Maybe it was alive or maybe it's dead. It's actually something different, that it has some elements of both.

A (6:41)

So how does this quantum rule that things that can be in multiple states at once until they're observed help to create incredibly powerful computers?

B (6:54)

Often when you're using a computer, running an algorithm, one of the things you're trying to do is search for a needle in a haystack to explore some vast possible set of numbers that might be the solution to your problem. If you have a quantum computer, you can start by putting in the computer in the superposition of every possible input you could ever want to put into that algorithm. And that allows you, in some way to get every possible answer in some state. The problem is, as soon as you look at it, you only get one answer, and it's randomly picked, and that's not very useful. But this sort of large, before you look, the cat is still alive in dead state contains information. And if you look at it in just the right way and ask just the right question for certain problems, something very interesting can pop out.

A (7:49)

So interesting. And, Andrew, you're not just studying these strange behaviors. You're using them to build computers. What makes these weird quantum computers so powerful?

B (8:01)

Quantum computers are the only different kind of computer that's ever been invented. For a long time, everybody thought every computer that existed was the equivalent of a Turing machine. This is the way computer scientists think of computing. And that means they can all solve some problems and find other problems very hard. Quantum computers work differently. They don't just make each step of a problem go faster. A faster processor, more memory. They can solve problems that we don't know how to solve in any other way because they're fundamentally different.

A (8:39)

You've said that quantum computers don't just work faster, they work differently. Can you explain a little more about what that actually means?

B (8:49)

Sure. One way that we think about how hard a problem is is how many steps it takes to solve. If I have a regular computer that gets better, it still takes the same number of steps to solve, but it can do each step faster. But if the number of steps to solve is some enormous number, like the number of atoms in the universe, and each step is a little bit faster, it's still not going to be able to be solved. It's just never going to happen. In the age of our universe, the way quantum computers work is by shortening that list of steps. They work differently. And so problems that can only be solved one way on Classical computers take just fewer steps. And so that is what makes it possible to solve things in relatively short timescales that we just don't know how to solve in any other way.

A (9:39)

Some exciting potential ideas are using quantum computers to discover new drugs or new materials or more efficient ways to create energy. Why can't normal computers do that? And how could quantum computers completely change the game?

B (9:56)

A lot of times we're thinking about simulating systems that involve atoms and molecules and electrons, and those themselves are quantum mechanical objects. And so you're usually trying to use classical things to represent this vast quantum superposition space. And that's incredibly inefficient. The idea of simulating systems that are themselves quantum mechanical with a quantum computer is essentially trying to use something that can natively think in a quantum way and therefore might be able to more efficiently get to the kinds of solutions we need.

A (10:34)

Because it can look at a much wider range of possibilities.

B (10:38)

It can look at a much wider range of possibilities. And for those problems, in particular for things involving drugs and materials, it just speaks natively in the right language. Right. Those are quantum systems, and it's very inefficient to describe a quantum system without using a quantum system to represent it.

A (10:58)

And those are quantum systems because they exist at the levels of atoms and molecules, which is the language of quantum.

B (11:07)

That's exactly right. Those systems exist as atoms and molecules, and the language of quantum was developed to describe the world at that level.

A (11:16)

And what could quantum potentially make possible? You mentioned medicine, energy, materials.

B (11:24)

We don't actually know what quantum computing can do with certainty. There are a few things we can prove. We know they have real implications for cybersecurity. We believe that you can simulate quantum systems much more efficiently on them. But a lot of our best algorithms that we run on computers are what we call heuristics. We run them, they give us answers. Those answers are things we didn't know. We can't prove they're optimal, but they're better than anything we had. And there's a lot of reasons to suspect that quantum computers will have vastly more impact in these heuristic kinds of algorithms than in things where I can prove down on pen and paper that it will take exactly this many steps to get an optimal answer.

A (12:07)

What makes quantum computers so hard to build? Why can't we just scale them up?

B (12:13)

Today, there's all kinds of challenges there. You need to start with something that can actually behave in a quantum mechanical way. And the leading platform either use single atoms or single ions trapped floating in vacuum, held in place by lasers or electromagnetic fields or superconducting circuits fabricated like the computer chips we have today. The challenge is in the circuit models where you can build a lot of them. The information is incredibly fragile. The very first superconducting qubit that anybody built, a qubit is a quantum bit, something that can store quantum information. The very first supernovan qubit somebody built lasted for 1Ns. You can't do a lot of computation in a nanosecond. In the 25 years since that time, we've gotten that number up just recently above a millisecond, with work that came out of my lab in collaboration with my colleagues here at Princeton. So it's very exciting to break a millisecond, and that's long enough that you can start to do error correction and think about actually getting real algorithms done. But there are so many things that can come and destroy this very fragile quantum state. So it's hard to get to the point where you can do a lot with it.

A (13:32)

So even an elevator moving in another building can disrupt a quantum computer.

B (13:38)

It depends on what your system is sensitive to. But if you're sensitive to magnetic fields, elevators are a real problem. Vibrations are a challenge for a lot of these systems. You need very carefully vibration isolated systems. You need to make sure the temperature is absolutely controlled. And then we also care very much about materials purity. What are all of the atoms that shouldn't be there that are around your material? All of those things come and hurt you. And every time you make your qubit 10 times better, that means you are more sensitive to all of those things that didn't matter before. And so every time you make it better, every little thing that didn't used to matter now starts to matter. So you just increase the numbers, number of problems we have to worry about.

A (14:23)

Looking ahead, what excites you most about the potential of quantum computing?

B (14:29)

The reason this field is exciting is that you get to play with the mysterious world of quantum physics and the great wondrous way the universe works, and also build something that can be applied, and maybe we'll do something that actually helps humanity. Princeton's motto is Princeton in the service of humanity. And we really care about doing things that matter. So the scientific nerdy part of me just wants to see the physics work and, of course, working to build a new drug or to make a new catalyst that can help with energy and in the environment, something that actually helps mankind would be wonderful.

A (15:06)

Before I ask you for the three takeaways, you'd like to leave the audience with today? Is there anything else you'd like to mention that you have not already talked about? Andrew, what should I have asked you that I have not?

B (15:19)

One thing that I think is really important about the whole field is how the different pieces work together. We have quantum computing companies, we have national labs, we have academics, and they all work on different parts of this problem in ways that spur productivity forward. Industry has these incredibly large scaled systems that I could never build in an academic lab with the size of investment that we make there. We in academia make these breakthroughs that make it so much easier for these systems to scale. We think of the crazy ideas that suddenly, when they work, change the way everybody thinks about the field. And the national labs have these incredible tools that are, you know, billion dollar ways of probing materials that are essential for figuring out all of the problems that exist in the materials layer things. And one thing that's happened under the National Quantum Initiative act over the last five years is that these groups have come together and used their relative strengths collectively to advance quantum science.

A (16:22)

That's wonderful. I think that's one of the themes of our world today, that connectedness leverages all the synergies. Andrew, what are the three takeaways you'd like to leave the audience with today?

B (16:37)

One, quantum mechanics is weird and mind blowing, but also follows a very specific set of rules. Two, these rules allow us to build entirely new kinds of technology that can solve problems that we can't solve in any other way. And three, we are actually getting close to these technologies being a reality and having a practical impact. We're not there yet, but sometime in the next few years, they are actually going to be making a real difference in the world.

A (17:14)

That is so exciting. Thank you, Andrea. This has been a pleasure.

B (17:18)

Thank you so much for having me.

A (17:21)

If you're enjoying the podcast, and I really hope you are, please review us on Apple Podcasts or Spotify or wherever you get your podcasts. It really helps get the word out. If you're interested, you can also sign up for the Three Takeaways newsletter at 3takeaways.com, where you can also listen to previous episodes. You can also follow us on LinkedIn, X Instagram and Facebook. I'm Lynne Thoman and this is three Takeaways. Thanks for listening.