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Nobel Prize in Physics Winner: John Martinis on the State of Quantum Podcast Episode Description
(0:00) David Friedberg intros John Martinis, the 2025 recipient of the Nobel Prize in Physics
(0:43) John’s history, how he got into physics
(4:54) Explainer on quantum mechanics
(22:57) Quantum tunneling and the 1985 paper that led to this Nobel Prize
(30:37) Understanding qubits, the state of quantum computing, and the impact of AI
(40:56) US vs China in quantum, reactions to winning the Nobel Prize
Learn more about the 2025 Nobel Prize in Physics:
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Nobel Prize in Physics Winner: John Martinis on the State of Quantum Podcast Episode Summary
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Nobel Prize in Physics Winner: John Martinis on the State of Quantum Podcast Episode Transcript (Unedited)
Speaker: 0
00:00
Welcome today. I’m very excited for this all in interview with this week’s Nobel Laureate, winner of the Nobel Ai in Physics in 2025, John Martinis. John, welcome to the all in interview.
Speaker: 1
00:14
Yeah. Thanks for inviting me. I’m quite excited about this, this talk and, you know, love to explain to people about, you know, what this prize is all about.
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Speaker: 0
00:24
All of you. Ai, besties. I think that was another epic discussion. People love the interviews. I could hear him talk for hours. Absolutely.
Speaker: 1
00:32
We crushed your questions a minute.
Speaker: 0
00:34
We are giving people ground truth data to underwrite your own opinion. What’d you guys say? That was fun. I’m doing
Speaker: 1
00:40
all in.
Speaker: 0
00:43
Well, the Nobel Ai is the most prestigious honor and particularly in physics that I think can be awarded. You’re in the record books. It’s gonna be an incredible ceremony coming up for you. Maybe we could go back to the beginning in your history. I’d love to hear a little bit about, you know, where’d you grow up and how do you get started with your interest in physics?
Speaker: 1
01:04
Well, so I, I grew up in San Pedro, California and, you know, grew up there my whole time. My, my father is a fireman, and my mom stayed at home, took care of us. And, you know, through the years, I was always interested in science, technology. I’m gonna say one of the things is you know, my my dad, you know, actually didn’t have a high school education, but very smart person.
Speaker: 1
01:30
He was always building things in the garage, various projects. So I grew up kinda knowing how to build things, which also kinda tells you how things work, you know, kind of empirical view, you know, tactical view of how physics works. So, when I took physics in high school, I actually loved it because there was actually some math behind it and concepts and, you know, really made sense to meh.
Speaker: 1
01:54
And, you know, I I just really, you know, fell in love with the subject and then went to UC Berkeley and and did pretty well there and enjoyed it, enjoyed it a lot. And then in ai, senior year at UC Berkeley, I had a class from John Clark, who was my advisor, and, found out what he was doing.
Speaker: 1
02:15
He was just starting to look at these quantum mechanics and electrical devices stuff, and it sounded really interesting for me. I guess I have, you know, I guess I could see maybe when when something maybe would would take off. So I started to, to to do the graduate school work with him.
Speaker: 0
02:34
You went to Berkeley for graduate school. Right?
Speaker: 1
02:36
I went to Gertrude for bachelor school, which you’re not supposed to do.
Speaker: 0
02:39
I was originally a physics and math undergrad at Cal.
Speaker: 1
02:42
Okay.
Speaker: 0
02:43
I changed my major later and and actually got my degree in astrophysics. There was some upper division math class that really turned me off to math as a major. There were just so many proofs. It drove me nuts.
Speaker: 1
02:54
Right. Right.
Speaker: 0
02:55
And then physics was always sai, but I liked, working in the astrolab. And I worked actually at Lawrence Berkeley Lab.
Speaker: 1
03:03
Oh, okay. Yeah.
Speaker: 0
03:03
But then you you stayed at Berkeley and went to grad school. Right?
Speaker: 1
03:06
Yeah. I stayed at Berkeley, went to grad school. We started this project a couple years into grad school. I forget exact date. And what was interesting is this was a question that was actually posed by, Professor Anthony Leggett who won the Nobel Ai for, you know, Helium three, you know, physics, in, I think, ’20 02/2003.
Speaker: 0
03:28
Was that superfluid
Speaker: 1
03:29
or Superfluid helium three. Yeah. That’s right.
Speaker: 0
03:32
So he showed, like, if you put helium three cold enough, it kind of almost has this new sort of characteristics with the physics and how it moves and how it works.
Speaker: 1
03:40
Well, it has this superfluid behavior, but it has a very complicated behavior because of the more complicated nuclei of the Helium three.
Speaker: 0
03:50
And
Speaker: 1
03:50
this had been discovered, and people worked for a while to figure that out, and he, you know, helped develop the theory for that. So, he is quite well known, very, very smart person. And although he won the Nobel Ai for that, okay, there’s not much helium three physics going on.
Speaker: 1
04:09
But for the question that led to our experiment, okay, there’s a huge field. And the question was, do macroscopic objects behave quantum mechanically? Okay? And this is a macroscopic object, might be a small ball, in our case it’s sai electrical circuit with billions of electrons in it, billions of atom, and is the collective motion of, say, the ball, ai mechanical.
Speaker: 1
04:38
Now, you know, if you think about throwing a ball against the wall it’s sana to bounce off. But if you make the wall thin enough and the ball light enough, it’ll then every once in a while tunnel through because of the, you know, laws of quantum mechanics. So,
Speaker: 0
04:54
Hold on. Let’s just pause on that for a second. I think that’s really worth spending a moment on.
Speaker: 1
04:58
Yeah. Great.
Speaker: 0
04:59
So when we talk about quantum mechanics, when we talk about the relative position or energy or movement of a particle at the atomic scale as small as an atom or smaller than an atom, we have to use ai of probabilities to describe where things are going to be. That was what was really kind of the big of quantum mechanics in the early twentieth century. Right? Is that there’s Yeah.
Speaker: 0
05:26
And probability of things being where they are and moving as they’re moving. There it’s not, like like, deterministic, like, we can see with the ball that we throw around. I think when you get very, very small, things get very fuzzy, and it’s very hard to get
Speaker: 1
05:40
over there. Upon upon the key idea here, maybe by accident, but it’s very important. Quantum mechanics was developed for the theory of small things, you know, electrons, atoms, you know, things shah are the fundamental constituents of it, but very small. And, you know, if you take an atom, it’s made from electron in the nucleus. You know, classically they attract each other and they would just, you know, combine together.
Speaker: 1
06:12
And then atoms basically would have no size. Why do atoms have size? Okay. That, you know, that was one of the strange things. And it’s because this atom is kind of not a a point particle. I used to say to my kids that the electrons were fuzzy. Okay?
Speaker: 1
06:31
And and ai mechanically, it has some wave function and extended. You can think of the electrons being all around the nucleus at the same time. So, it it’s just a very strange behavior, but of small things, and, of course, very important as how atoms work and how we describe nature.
Speaker: 0
06:52
So quantum mechanics ultimately became a field that people say is very nonintuitive in terms of understanding where small small particles are, the energy they have, where they’re moving to. And and, basically, we resolved to figuring out that we had to use these functions. It’s not just a single point, but it’s a distribution.
Speaker: 0
07:13
It’s a whole bunch of places, and there’s a probability of where the atom could be or where the electron could be. It’s also a probability of how fast it might be moving. All of these things become probability functions.
Speaker: 1
07:24
And you develop a mathematical theory for doing this that, you know, takes you until your third year in university to really know enough math to understand that. But basically, these are forming waves, elective waves of the electron. So you have kind of a wave, an electron around the nucleus describing what the, the electrons are.
Speaker: 1
07:48
And these are kind of like standing waves, you know, it’s like hitting the string, you know, at at different length strings, different tension strings form different notes. These vibrations of the electrons around the atom can vibrate at different frequencies.
Speaker: 0
08:04
So rather than think about an electron moving around an atom in a predescribed ai, and I can know where it is at any point in ai. The right way to think about an electron around an atom is it’s in a wave. It’s a and it’s it’s a long there’s a wave that describes kind of where it is and what it’s doing.
Speaker: 1
08:23
And you have the electron and you have the proton, attracting it. So the whole waves theory combines all those two and, you know, gives you a description of how the the atom works and quite accurate description too.
Speaker: 0
08:37
And so one of the other kind of features that arises from the fact that everything at a micro scale is described by wave functions is that there’s a small probability of something kind of extreme or extraordinary happening. Like, the one example is, Stephen Hawking figured out that you could have a particle and antiparticle come out of nowhere in speak, and the antiparticle goes into the black hole.
Speaker: 0
09:01
The particle shoots off. Yeah. And that the probability of that happening is so low, but it happens enough that the antiparticle actually starts to delete part of a black hole. And that’s how black holes evaporate in the end of this theory, all these interesting things. But can you tell us how what quantum tunneling is?
Speaker: 0
09:17
So this is another one of these sort of features of quantum mechanics that arises from the fact that these things are kind of waves and probability functions.
Speaker: 1
09:25
Yeah. So if you have, if you have an electron just traveling through space hitting hitting a wall, let’s say, there’s a little wave wave packet, wave function to it. So it’s not a single particle. It has some extent to it. And what happens is that when that particle hits the wall, quantum mechanics say there is some amount, small amount of this wave function, or if you ai, the particle going through the wall and then to the other side.
Speaker: 1
09:56
Now most of the time it, it bounces off, but everyday devices. This is not, and if you build very small meh circuit, you have to worry about electrons tunneling and, charge leaking off your capacitor. They have magnetic memories that depend on these tunnel junctions. So this is a very well known phenomenon.
Speaker: 1
10:26
If you make this barrier, this insulator, just the, you know, ten twenty atoms thick, then that’s thin enough for it to go through.
Speaker: 0
10:35
To go through. So this is what’s so interesting. You can actually predict the number of electrons that might tunnel through one of these barriers, one of these insulating barriers as they’re called, over to the other side, which really is crazy to think about. It’s just like walking through walls. Right? I mean, like, what is this?
Speaker: 1
10:53
Yeah. That’s that’s the idea.
Speaker: 0
10:55
Yeah. So going back to the story you were sharing, you’re in grad school.
Speaker: 1
10:58
Right.
Speaker: 0
10:58
And then Leggett proposes this idea. Maybe you can share a little bit more now that we’ve got, I think, a bit of the basics on what was discussed, which was zooming out a bit. Like, rather than just think about all of this happening at a microscopic scale, is it possible for it to happen at a bigger scale?
Speaker: 1
11:13
Yeah. And again, we’ve been talking about quantum mechanics sai the physics nature at this microscopic atomic scale. But the question was, if you made a macroscopic object, would it obey quantum mechanics also? Okay? And then, you know, that was the basic question. And it turns out that there’s a very natural system to look vatsal looking at an electrical system and looking for quantum mechanics and electrical system where the currents and voltages of essentially electrical oscillator, does it behave like a classical physics bryden it behave with this quantum mechanical nature to it?
Speaker: 1
11:57
And that was the question. Now, it turns out that when you think about quantum mechanics and thinking about, well, there’s the quantum behavior, but then at some point you have to measure it, which then turns it into a probability. There’s something called the Schrodinger cat paradox, where, in the paradox you have a radioactive decay, and then you you let it happen for, let’s say, half of the radioactive decay ai, and then you sai, and then you have already detected decay, a detector, and then a bottle of cyanide, which will kill a cat.
Speaker: 1
12:36
And then do you say, you know, after some amount of ai, is the cat in the dead and alive state? Okay. And, you know, physicists, you know, and this is sai good question. Einstein brought it brought it up, Schoelander brought it up. A lot of people, discussed it.
Speaker: 1
12:53
But Elegat pointed out that the reason this is a paradox is you can believe that a macroscopic object like a cat could be in a quantum superposition state. And, in fact, there was no experimental evidence that this could happen, and that was his point. So, so he said, well, you know, people should be testing this and let’s see if it’s true.
Speaker: 1
13:18
And, as a young graduate student who just, you know, learned about quantum mechanics, it’s like, oh, that’s a really great, great question. That’s something that we should try to do and we should try to do an experiment, you know, on the suggested system, to look for quantum mechanics.
Speaker: 1
13:38
And the the original proposal was looking for the tunneling. Well, it turned out to be more than that, but, the it looked for tunneling.
Speaker: 0
13:47
Let me just kind of describe another way is, you know, the macroscopic system could be my entire body. Could I walk through a wall?
Speaker: 1
13:56
That’s right. And then
Speaker: 0
13:57
The probability of all of my atoms being in the perfect moment, perfect position, you know, to to be able to kind of cross through the wall is so low. It would never happen in this or many other universes
Speaker: 1
14:10
of electrical And and that’s the problem is that most macroscopic objects, when you try to think about the quantum mechanics, that won’t happen. Okay.
Speaker: 0
14:19
Sai So there’s a small probability one electron can cross over a sai barrier.
Speaker: 1
14:24
Right.
Speaker: 0
14:24
But the probability that many crossover at once is lower and lower and lower, and that makes it very difficult to see at scale.
Speaker: 1
14:31
And what what happens is if you look vatsal electrical circuit, then the parameters become favorable for seeing this kind of macroscopic behavior. And, okay, it’s hard to go into the whole physics of all that, but it’s basically because you can make a circuit that operates at microwave frequencies.
Speaker: 1
14:52
So instead of you trying to go through the wall once a second, it tries to go through the wall 5,000,000,000 times a second. Okay? And so then it’s it’s a lot, you know, more, you know, you have more chances to go through. And, the other thing is just the various parameters that involved in quantum mechanics, you know, are favorable for seeing this kind of phenomena.
Speaker: 1
15:15
You have to do the experiment right, but, it’s favorable for doing that.
Speaker: 0
15:19
So one of the parts of your experiment you created what’s called the Josephson junction. Is that is that correct? Sai this is two superconductors with a barrier between them. Right? I got really fascinated by superconductors when I was maybe 12 years old. I I went and bought a superconducting disk, yttrium barium copper oxide.
Speaker: 1
15:40
Oh, yes. Yes. That’s right.
Speaker: 0
15:41
Yeah. From the back of popular science. And then I went to UCLA and I got a a jug of liquid ai, and then I floated a magnet above the disk Yeah. Yeah. Yeah. Because of the Meissner effect. And I had it at the science fair, and I and I did very well with the science fair that year because I showed this really far.
Speaker: 1
15:57
What year was that? Was that when it was discovered?
Speaker: 0
15:59
It must have been ’91, ai.
Speaker: 1
16:01
Okay. Yeah. That was close enough that that was
Speaker: 0
16:04
good. Yeah.
Speaker: 1
16:04
Yeah. The hard part’s giving meh the liquid ai. But
Speaker: 0
16:07
Yeah. And I had a friend whose dad was, like, a doctor at UCLA or something like that. So he was able to get the liquid nitrogen for our demonstration.
Speaker: 1
16:15
Right. Yeah. That that was the hard part. Okay.
Speaker: 0
16:17
I’ve always been fascinated by the physics of superconductors. And maybe you can just explain one of these important features of the of superconductors as it relates to kind of resistance and current flow, and then we can talk about your experiment.
Speaker: 1
16:30
So so what happens is, when a a material goes superconducting, all the electrons condense into one state. Okay? Now, to just to give you saloni of how it’s not a perfect analogy, it’s close analogy. If you have a normal metal, any metal we have at room temperature, it’s like a gas of electrons. It’s like, you know, gas in the air.
Speaker: 1
16:56
And then when you get below the superconducting temperature
Speaker: 0
17:00
Sorry. I think we should just explain that. So so when you have a metal, all the electrons are kinda moving around. They’re they’re perturbed. They’re Yeah.
Speaker: 1
17:07
In in their own
Speaker: 0
17:08
energies, different states.
Speaker: 1
17:09
That’s right. They’re different energies, different states. You know there’s some Fermi statistics, Ai not go into that, but it’s more or less looks like a gas. You think of a sai and then when you cool it below, you know, a certain temperature it then coalesces into, let’s say, a solid like like atoms will, and the electrons coalesce into something Cooper pair, BCS condensate, it’s the name, where all the electrons are kind of locked together and doing the same thing.
Speaker: 1
17:42
Now the nice thing about that, it’s not like they’re frozen in place, but they have a free parameter that allows them all the currents, all the electrons to flow in some direction, which is the super current.
Speaker: 0
17:57
In a superconductor, meaning a material that’s cool enough that it reaches its superconducting critical temperature. Right? So suddenly, all the electrons can still move. They can still create a current, but
Speaker: 1
18:08
But they’re they’re moving together like they’re in, ai, in my analogy, like they’re in a solid instead of the gas. And because they’re moving together, okay, then then when you work through all the physics, they are not, they, you know, they aren’t randomly scattering off things.
Speaker: 1
18:25
They’re just moving together, and then you get a super current. Where, for example, if you made a ring a superconductor superconductor, that current would basically flow for forever around the ring. This is what you saw with the floating magnet.
Speaker: 0
18:39
Right. That’s so interesting. I’ve always, thought and there’s obviously been companies started around the idea of creating an infinite battery where you could store technically forever electricity because the electrons are just moving around. If it’s superconducting, it can they can just spin forever around the If it’s superconducting, it can they can just spin forever around that circuit. Yeah.
Speaker: 1
18:56
And people actually do use big superconducting magnets to, store energy. And when you get an MRI, that you’re in a you’re in a liquid helium machine with a superconducting magnet. They charge it up and that magnetic field is basically there forever, you know, waiting for people to go inside it.
Speaker: 1
19:16
It’s kind of strange to be in if you’re inside this super cold magnet there, but they’ve designed it very well. It works well.
Speaker: 0
19:24
So this Josephson junction is two superconductors. They’re on either side of a barrier that you create, an insulating barrier. And then maybe just explain the
Speaker: 1
19:35
Ai pairs have to tunnel through it, but they kind of tunnel through it together without any loss, this this actually forms what’s called an electrical inductor in circuit in circuits. So inductor is normally a coil of wire that stores energy in this magnetic field. Here this just stores energy of electrons tunneling through here.
Speaker: 1
20:09
And so it’s something called we call a kinetic inductance, and it happens with this. But that forms a nonlinear inductance, and with a capacitor in the circuit that forms an inductor capacitance resonance circuit, which is in your old, which is like in your radios you have filters of LC resonant circuits to filter your signal and do anything.
Speaker: 1
20:34
So this is a very common microwave and, you know, radio frequency, element that you use all the time to make electrical circuits.
Speaker: 0
20:44
So I just wanna simplify that you have these two superconductors split by this barrier. There’s some tunneling. Some of these electrons are actually going through the barrier to the other ai, and then you can effectively measure all of these different changes as you change the temperature.
Speaker: 0
20:59
You guys were putting different voltage states into the circuit that you built. And what you saw and what you measured and what you demonstrated was that there were these very ai of discrete or specific changes that happened that basically demonstrated quantum mechanics at scale.
Speaker: 1
21:17
That’s right. So so this inductor capacitor resonator, which you just treat as a, you know, is a charge and a current going through. But because it’s quantum mechanics there’s this wave function to it, so there’s some uncertainty in these. And then given just the way that the simple electrical circuit works, you can then demonstrate the quantum mechanics.
Speaker: 1
21:42
One of the tunneling, which is a little bit hard to describe here, but you can see tunneling. But I think the little bit easier thing, maybe easier, is to look at the energy levels of this. And let me kind of explain that. When people discovered, you know, atomic physics and started doing any doing this, they excited a gas of, you know, some sai, and the light coming out of that gas would be at certain colors of frequency.
Speaker: 1
22:15
So if you go outside and you have the sodium lamps on, these are kind of the yellow ram, you have, you know, kind of a single frequency coming out of that lamp. Or nowadays you look at LEDs, there are certain frequencies that come out of that. And, this is a quantum mechanical effect that sai how the electrons travel around the atom, there’s only certain kind of frequencies that they oscillate at.
Speaker: 1
22:44
Now classically you would expect there to be all different frequencies that spirals around or spirals into the nucleus. So that’s what you speak, but we we saw these discrete frequencies.
Speaker: 0
22:57
And so by measuring those discrete frequencies, you now had proof
Speaker: 1
23:01
Right.
Speaker: 0
23:01
That there was quantum mechanics happening at a macro scale.
Speaker: 1
23:07
That that’s right.
Speaker: 0
23:08
And you published this work. And was there a lot of attention when you published this work?
Speaker: 1
23:14
No. Yeah.
Speaker: 0
23:14
’80 This was in 1985, ’86?
Speaker: 1
23:17
’85 or ‘8. I actually forget, but ’85 or ’86.
Speaker: 0
23:21
And so was there much attention on this work at the time? ’80 yeah.
Speaker: 1
23:25
This was a big question, and people wanted to, you know, understand that. And, you know, we published it in physical review letters, and it got a lot of attention. And I think, we had a little article in Scientific Meh that I was very proud of
Speaker: 0
23:41
Yeah.
Speaker: 1
23:41
That wrote about that. And, yeah, it it was, you know, it was kind of a a kind of a big deal.
Speaker: 0
23:48
What did you go on to do? At that point, was it considered groundbreaking Nobel ai winning work? And what was the story at that time when this came out?
Speaker: 1
23:57
Yeah. So, you know, it was an it was an important piece of work and people noticed it. But, you know, it it it you know, we we shah that quantum mechanics worked and quantum mechanics worked on the macro scale, which was ai, but one could still, you know, argue, well, what is it good for?
Speaker: 1
24:15
What are you sana do? And the the fact the secret of an important scientific breakthrough is, does it lead to other experiments and other papers and other inventions and the ai? And, that ai took, you know, many decades to happen because it was so new, and people had to do do that.
Speaker: 1
24:37
So I would say it was noteworthy at the ai, but, you know, not necessarily, you know, something for a Nobel Prize because it was just kind of, you know, weird and went off and, you know, what are you sana to do with it? Ram what happened at the time was very interesting. And at the end of my thesis ai, there was a conference in, UC Santa Barbara where I came here for the first ai.
Speaker: 0
25:05
Yeah.
Speaker: 1
25:05
And, they they were talking about this experiment. But the very last day, the last talk, was by Richard Feynman, very well known physicist. Of
Speaker: 0
25:16
course. The greatest. Yeah.
Speaker: 1
25:18
The great. Yeah. Ai. You know, I Ai kind of idolized him and Right. And read his his his books and whatever. And he was talking about using quantum mechanics for computation, which is building a quantum computer.
Speaker: 0
25:34
Yeah.
Speaker: 1
25:34
So he gave a talk that was, you know, really kind of amazing. I’m gonna be honest, as a student, I I didn’t quite catch everything. And, ai Michel Devoret, my dear friend, said, yeah, maybe some of the things wasn’t quite figured out at the time. But afterwards, he was absolutely mobbed by people asking him questions because it’s so interesting to think about taking this this, you know, basic law and actually doing computation with it.
Speaker: 1
26:04
Right. And I was a graduate student, so I was kind of at the outside ring. You know, you have the professors in close and whatever. I’m just a lowly graduate student. So I could hear a little bit.
Speaker: 1
26:16
But what I what I learned from this, it was a great question and and something that would be ai worth doing, you know, for your ai work because it’s so deep and so interesting and maybe practical and the like. So that really motivated me.
Speaker: 0
26:35
Yeah. So that big idea is to use quantum mechanics and these properties of quantum mechanics to do computing.
Speaker: 1
26:44
Yeah. That’s right. And and I would say, soon after that, other people in the field got a little bit more specific and showed how you would how you would do it. And then it was in the early 1990s, maybe five years later, that Peter Shor came up with this factoring algorithm to solve a, you know, a real world problem with it.
Speaker: 0
27:07
Yeah.
Speaker: 1
27:07
Yeah. And it took a while to people figure out. It was very abstract and, you know, people would point which what to do. But but ai I said, I could see that in all of the crowd around Feynman asking him questions, that this was the most, you know, most interesting fundamental question, you know, how to combine quantum mechanics with doing computation.
Speaker: 1
27:28
It’s it’s really amazing.
Speaker: 0
27:31
And so you started to do that with your life’s work pretty much. You go on to a very good career.
Speaker: 1
27:39
Yeah. So my career path, was of course, quantum computing was getting developed and and it took me a while to really get go all in on it. Okay? Yeah. So, what happened is Michel Devoret was was from France, from CEA France, went to Berkeley, went back. I went there as a postdoc and, worked with them.
Speaker: 1
28:02
And they were young and unknown at the tyler, and people was like, well, you’re gonna go to Europe, and you’re not gonna get connected to US science. But I knew Michelle and Daniela Stebb and Christian Urbino, the people I was working with, were absolutely brilliant. Okay? And they’ve had a very illustrious, career.
Speaker: 1
28:21
So I went over there because I knew that was great. And we continued to do experiments on this. Yeah. And then after that, I came back to The US, and I worked for the National Institute of Standards and Technology. And it turns out just down the hall from Dave Ai and his group who went a Nobel Ai for atomic physics for, you know, doing quantum computation.
Speaker: 1
28:43
And I worked on some with doing experiments on counting electrons and working for metrology, and then did other experiments. And then in late, the late nineties, I I just, again, went all in on building a quantum computer. There was funding available at that time. It had progressed enough theoretically that the US government started, you know, funding this to see if people can do it.
Speaker: 0
29:12
And so then couple years after 2014, I think you ended up at at Google’s quantum lab in Santa Barbara. Is that right?
Speaker: 1
29:18
I was at UCSB for, ten years or so, which was wonderful, and built up the lab to go from very basic things to building a five and a nine qubit quantum computer. And then during that time, Google got interested. And I I kinda decided that although academia was great, it would be hard to get the team together and keep them together for a long time to build this complicated machine, and Google had the money.
Speaker: 1
29:48
Okay? Yeah. So so we went there, and we started off fairly small, mostly from people coming from UCSB group. And then in, 2019, we published this quantum supremacy experiment with 53 qubits, where we made a lot of qubits, and we made them really good and, you know, fast and whatever sai that we could run some algorithm, mathematical algorithm that, produced some output, that was took, you know, much much longer on a classical computer to to emulate and do that.
Speaker: 1
30:29
It was not practical, but it was a demonstration of the power of a quantum computer That it were
Speaker: 0
30:36
Well, just maybe give your description of a qubit, and maybe we can relate, you know, how do we build these quantum computers from qubits to the Josephson junction and some of the early work you had done that you ended up winning the prize for?
Speaker: 1
30:52
So very simply, we have a metal wire and a metal wire that gets put together on this Josephson junction, which represents a a an inductor flowing through here. And then from this wire to this wire we have a capacitor, and then we set that up to oscillate at about five GHz cell phone frequencies, you know, to form the qubit.
Speaker: 1
31:19
Okay? This oscillating thing. And then there’s at low temperatures, superconductors, you know, all this magic, we can we can get quantum mechanical behavior out of that.
Speaker: 0
31:30
And then you can measure that quantum mechanical behavior, create a representation, and use that to run your computing.
Speaker: 1
31:37
That’s right. What you can do is you put on ai pulses to change the state of the quantum computer, change the way it oscillates, and then we connect it to, it’s a complicated readout circuitry, to, you know, in the end, figure out what state it’s in. Okay? And then and then you you connect just an array of these, and you just use capacitive coupling from, you know, one one wire to the to the next one to to couple them together.
Speaker: 1
32:10
And it’s more complicated than that, but that gives you a good idea.
Speaker: 0
32:13
And then just to understand your work that you won this Nobel Ai for that demonstrated this quantum mechanical phenomena at scale, is that part of the design of a qubit and the circuitry? Did that inform that design work or explain it rather? Yeah.
Speaker: 1
32:32
Yeah. It was the very basic simplest circuit. You know, and we were using analog simulators at the time, not even the com I I took data with a computer, but this is sai back enough that, you know, it was very rudimentary. And then over the years, we just got more sophisticated design by the whole field, you know, many, many people.
Speaker: 1
32:55
And, and we were able to put things together in a way to actually build a computer. Now Right. The the I would say the reason why it’s interesting from the Nobel Prize thing is what it led to. And what it led to right now is a thousand, maybe several thousand people around the world doing research to build this superconducting quantum computer.
Speaker: 1
33:23
And and it just turned into enormous field, large number of papers, large number of people, people that’s selling quantum computers. IBM is selling quantum computers. People are selling time on the quantum computers. And the fact that it was a it was a useful idea, okay, that led and and and brought into form, all all these different experiments, ai.
Speaker: 1
33:47
And many, many people contributed this.
Speaker: 0
33:50
I mean, it’s very interesting. And I think just this broad question or observation that sometimes inquisitive minds leads to research that leads to some set of discoveries that are completely not apparent until forty years later, the effect or the impact it may have had Yeah.
Speaker: 0
34:10
On building an industrial field. Like, there’s now quantum computing, everyone feels, is on the brink of actually achieving what people have talked about in theory for decades, but seems to be getting very close to doing it. And Yeah.
Speaker: 1
34:23
I I can talk on that. But I would say, you know, this field, many other, ideas on how to build a quantum computer has been generated. And, it is very exciting field, ai large field. And I would say that the science was very, very deep too. To get these things to work, you have to invent lots of different ai. You have to think about materials. You have to fabricate it, build complex control systems.
Speaker: 1
34:53
Engineering and physics is, to me, quite beautiful. And just to tell you a little bit about me, you know, I grew up building things and as an experimentalist, you know, I like to build instruments, you know, build experiments to show this. And this was kind of the ideal project for me because, you know, from very early on it was ai, well let’s, you know, do this great physics but let’s also build something.
Speaker: 1
35:21
And by saying, well, what do we have to do to build a quantum computer? That ai of led me to know what physics we have to test sana what are the kinds of things we have to build. And that’s just the way my mind works. I’m I’m much more practically oriented. So it was a perfect field for me to get in, and that’s kinda what, you know, intuitively led me to, you know, ai on to do this in graduate school.
Speaker: 1
35:44
And I think it’s just so fascinating the amount of engineering and technology you have to do to make this work.
Speaker: 0
35:52
Where are we in quantum computing evolution today? So what’s the state? At what point will we have call it generally accessible and generally useful quantum computers that can do all of the amazing things everyone’s kind of talked about for decades that one would be able to do with quantum computers.
Speaker: 1
36:10
That’s right. So, right now, we’re we’re about 50 or a 100 qubits for the superconducting case, but they they can be fully controlled and run real algorithms and do very complicated things. They have a lot of other systems that can do that. I think the newcomer on the block, which looks good, is neutral atoms where they made big neutral atom systems, but they’re still working to get the gates controlled really well and the like.
Speaker: 1
36:40
But what’s happened right now is we can run genuine algorithms on that. And people have, you know, have ideas they sana to run. But because these qubits are not perfect, okay, it’s an analog control system, and fundamentally these quantum bits have a little bit of error to it, little bit of noise to it.
Speaker: 1
37:04
You can only run so complicated of a project. And it’s good enough to write scientific papers and try things out. Every once in a while people say they’ve done something, you know, that’s hard to compute and well, that’s ai. But they aren’t really big enough to be useful yet.
Speaker: 1
37:25
They have to get bigger and they have to get better. Less noise.
Speaker: 0
37:29
Do you have a point of view on the ai? This is everyone’s speculation and there’s been more hype than reality.
Speaker: 1
37:34
Yeah. There’s more hype than reality and and, and it’s hard. I used to not wanna speak that, but since I started a company, then I can do that. And what we sana do, and it’s a timeline of many other groups, is to do something in, let’s say, in the next eight, ten years, something like that.
Speaker: 1
37:54
But the problem is, you know, people are predicting ten years, you know, for a while now, so okay, we have to do that. But, I can tell you for what we’re doing is that we’ve identified what are kind of the technology bottlenecks of the current fabric different ways to make a a sana computer.
Speaker: 1
38:17
We’ve written some papers on it, and, you know, we’re working with people in the semiconductor industry to manufacture scale up very rapidly. So in in in that, let’s say, ten year ai scale, something like that.
Speaker: 0
38:42
In a lot of technically difficult fields ai fusion energy, perhaps even quantum computing, they’re seeing profound acceleration in getting to their crazy big goals on these very big technical projects because of AI. Is AI starting to play a role in solving some of the engineering, material ai, scaling, noise issues that we’ve seen historically in quantum computing?
Speaker: 0
39:07
And do you think that there’s an acceleration underway in performance improvements because of AI?
Speaker: 1
39:12
There there may be. My and and and there’s things we can maybe do modeling and the like. We also think what we can do is use the quantum computer and AI together to solve the problems better. So that that that’s what our theory team is proposing. I used to work with Google Quantum Ai, that’s what they’re proposing. So there’s a general feeling of that.
Speaker: 1
39:39
My particular view though is that in terms of this control, if you don’t build your system cleanly enough and, you know, that the control is clear enough, you’re you’re not gonna get the the great performance out of it. So I’m a little bit old school here and and working on, you know, building it that way.
Speaker: 1
40:01
There’s certainly some elements where you can use AI, you know, and decoding circuit for the the error correction and the like. But the one thing to mention to you is that, you know, these qubits are are naturally very noisy. And you can maybe do sometimes a 100 for bad qubits and maybe a thousand, maybe a few thousand operations before they kinda lose their memory.
Speaker: 1
40:28
You know, you can think of it as ai dynamic Ram where you have to refresh it. Well, you have to refresh it with error correction. And because of that, you’re talking about a million qubit quantum computers to be general purpose and solve really hard problems. There might be
Speaker: 0
40:44
Sai million.
Speaker: 1
40:45
A million. Something million is a good round number for it, maybe a little bit more. And right now, we’re at, you know, a 100 or, you know, a little bit more than that. So we have a ways to go.
Speaker: 0
40:56
What is your view on China and the progress that they’re making in this technology versus The US? This is the topic de jure in every field, industrial field, computing, ai. Where’s China at compared to The US? The comparisons, and everyone’s worried about the progress in China versus The US and what that means?
Speaker: 1
41:16
So I can talk about my own field, but when I have read the papers that, duplicated what we did at at Google on the quantum supremacy experiment. You know, they know what they’re doing. I mean, they they go through the theory. They talk about a lot of it is very similar to what we’re doing, but they know what they’re doing, and they’re getting great results.
Speaker: 1
41:40
And the thing that scares me a little bit is, you know, last December, the Google Group published the latest results, which is really much nicer. They made some real improvement. But then China soon afterward published something kinda indicating they were, you know, on par or near par or something to it.
Speaker: 1
42:02
And, you know, I’m worried that the the Chinese government is saying, well, you can’t publish anything until it’s in the Western press, and then you can, you know, then it’s open and you can talk about it.
Speaker: 0
42:13
That’s precisely what I’ve heard.
Speaker: 1
42:14
And so Sai, you know, Ai I’m a I’m a little bit, concerned about that. Now what we’re doing with our our company is we’re doing a new generation of fabrication of the ai, and I would consider in my my my research. We have the simple fabrication with the original papers in ai, and then around 2000 we had more sophisticated fabrication.
Speaker: 1
42:44
And then for the quantum supremacy experiment we did something even more complicated, other groups too, But we sana do a similar jump in the fabrication. And what’s interesting about this is we’re going to be using applied materials and the modern fabrication processes that they have, which on 300 millimeter tools, you know, you can’t get in China, for example.
Speaker: 0
43:12
Right.
Speaker: 1
43:13
You can get it for CMOS. And then they’re developing we’re developing standard processes, but, you know, new recipes and new ways to put it together. And we think by doing that, we can do a huge leapfrog and then get there faster and get there in a way that, you know, will protect our lead.
Speaker: 1
43:31
There’s other things we’re doing too. Ai know, that that’s a small part of it. But, you know, we think there’s a way to, you know, really lead the field. And, and we’re happy. We have good industrial partners of, Ai Materials, Synopsys, Design Tools, Hewlett Packard Ai, some startups who do the theory work.
Speaker: 1
43:55
So, you know, we have a good consortium, and we wanna use all that knowledge and expertise of engineering to make this happen.
Speaker: 0
44:04
Where were you when you got the news this week that you won the Nobel Ai, and how surprised were you? Because this is a forty year old research effort. Had anyone given you a call, rumor, gossip mill saying, hey. You’re on the list this year, potentially being considered.
Speaker: 1
44:19
So let meh, give you a little bit of the ai story. You know, if you we we’ve known that this was a important experiment from the beginning. We’ve attained some other ai that are, you know, much less well known and really appreciative of all that. And you you what happens is the Nobel, system, put together Nobel Symposiums where they get together physicists in a certain field, which is quantum information and this kind of thing, and they they give, have all the scientists give talks and and they sana kind of check on the vitality of the, you know, of the field.
Speaker: 1
45:02
How big is it? And then, you know, also maybe some of the the leaders maybe think about it, you know, can they give a good talk? Would they be a good representative? So, Michelle and John and I have been to these, symposiums before and we kinda knew, you know, what was going on, you know, that at least we were considered.
Speaker: 1
45:24
And Ai just tell you, as a scientist, just to be invited to these and be considered is a fantastic honor, you know. And having getting the prize is just so ai of unbelievable that you shouldn’t think that way. Sai, you know, I’ve known about it for a few years. And in fact, to be very honest, in the past, when the dates have come around, it’s like, oh, is this gonna happen?
Speaker: 1
45:50
And then you wake up in the morning and it’s like, oh, it didn’t happen. And you’re kinda down for a day, you know, it didn’t happen this year. And that’s a very bad attitude. I I don’t like that at all. And, you know, you you should not covet some, you know, insanely difficult prize that, you know, only goes to a few people.
Speaker: 1
46:13
So what happened this year is Ai kind of worked through this over several years, and this year Ai just kind of forgot about it. Okay? So I went to bryden, and then we got the call at three and my wife answered the phone and found out what happened. But shah didn’t wake me up right away because she knew if the day was gonna be hectic and I needed my sleep to not be grumpy.
Speaker: 0
46:38
That was nice of her.
Speaker: 1
46:39
Don’t wanna be grumpy talking it.
Speaker: 0
46:41
That’s right.
Speaker: 1
46:41
So she woke me up at 05:30 as I looked at the computer, oh my God. And then we had some reporters coming over at sai, which interviewed me know, right when I had found out, half hour after Ai found out. And it’s it’s it’s it’s it’s it’s sai great honor and, it’s just been really fun.
Speaker: 1
47:02
And then, you know, I’ve been getting a lot of emails from people I’ve worked with or students I’ve had in the past congratulating me and you exchange old stories and the ai. And it’s it’s it’s ai of a very special time.
Speaker: 0
47:17
That’s great. Any, science or technology fields that you’ve been following outside of your core discipline that you think are really exciting? I always like to hear what major ai of thinkers
Speaker: 1
47:32
and scientists arya doing. Ai just so focused on doing this, especially when you start a company, you better be focused. Right? So I’m doing that. But one of the fields that I find, this is someone, Ben Mazin at UC Santa Barbara, is looking for exoplanets, and they’re using superconducting detectors that are somewhat similar to what we’re doing.
Speaker: 1
47:58
In fact, in the 1990s or so, I helped, you know, helped establish that field with other people and did that for five, six, seven years, to do that. He’s doing it in a different way. And I really like how, you know, this instrumentation, you know, that we’ve been working on, is their quantum devices are are now able to, do these astronomy, detectors and and look for look for these.
Speaker: 1
48:28
And of course, there’s so much going on in astronomy these ways with gravitational detectors and exoplanet searches, and it it it’s just really fascinating to me. Yeah. And, again, it’s it’s very much technology oriented where people are building good detectors. This is what I like. Okay? I like building building instruments.
Speaker: 1
48:48
So that that’s particularly interest me.
Speaker: 0
48:52
Yeah. That’s great. I mean, very exciting field and, hopefully, we’ll develop quantum computers that will help us build materials and technology to help us get there one day.
Speaker: 1
49:04
Sai That’s right.
Speaker: 0
49:05
Many rungs on the ladder of human progress. Well, congratulations again on winning the Nobel Ai in Physics this year. Very well deserved. It’s a fantastic moment. Enjoy it. Enjoy the ceremony. And we’re excited for your continued work in the field of material quantum computing, and thank you.
Speaker: 1
49:23
Yeah. And thank you. I really enjoyed the questions and the flow where you were asking questions to explain it at the right level for people. And, I really appreciate that. This is a great, great podcast.
Speaker: 0
49:37
Great, thank you ai.