Why silicon qubits were doubted
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2:37:23unlike for example trapped ions on neutral atoms, you can create like small cubits, small numbers of cubits using bespoke physics machinery that is found in the lab. Lasers are very common in labs. um superconducting circuits also you can kind of just like PhD students can make their own because it's it's the size of a millimeter you can like use a light microscope and like make stuff with this you need a fab it >> you need a fab that's like willing to >> you know be like okay let's print this thing so that's difficult you can't just make this in grad school >> at least not the big uh at least you can't make like big ones in grad school right um and there's there's certain
2:38:05problems. There are like inherent problems that have to be solved. For one, I told you about the magnetic field problem, which is that a global magnetic field is fine, but local magnetic fields are a problem. Now, silicon, normal silicon, the stuff that's in your computer, has a lot of local magnetic fields because silicon comes in two isotopes. It comes in a 28 and a 29. That's the number of protons and neutrons in its nucleus. Um, with 28, because of the PI exclusion principle, all of the spins are going to cancel each other. That's how they're on top of one another. And so there's going to be no net magnetic field inside every single atom. But for 29, there's an odd number. So there's going to be a tiny
2:38:47magnetic field because of the spin of the nucleus. >> So we want 28. >> We want a lot of 28. We don't want a lot of 29. But naturally occurring silicon has about 92% 28. And for the 29 there's about 5%. Now for normal silicon that doesn't matter. For normal classical computing it doesn't matter. But here >> here it's it's fun. >> Your quantum quantum information is going to be lost. There's too much. >> Yeah. >> Okay. >> Okay. >> So that's one reason. >> Charge noise is a thing, right? If you have like random stray charges, your fab isn't good enough or something, then you're going to have some random electromagnetic fields. That's going to cause a problem. And then finally, there's this demon called the valley
2:39:28splitting. Okay, this is something that I'm going to be honest. I do not understand. I am also going to be honest. A lot of practitioners in spin cubits don't understand. And a lot of the people outside of spin cubits who say that valley splitting is the problem also don't understand. It's kind of just this thing where the real theorists are like, "Yeah, it's clearly a problem." >> Here's from what I gather from from reading about it. Okay, the idea is that silicon has this really weird band structure. Like remember in in previous episodes we talked about the veillance band and the conduction band and how the difference between these two is what gives silicon all of its nice um
2:40:09properties as a semiconductor. Now, part of that band structure means that in bulk silicon, the electrons actually can choose to live in one of six different states that all have the same energy. >> For classical computing, this doesn't matter. But for quantum computing, we only want two states. >> Okay? >> Mhm. [clears throat] >> Which means we only want one of the valley states where the electron can live in either a spin up or a spin down. If there's six and in each of them they can live in a spin up or spin down. Now all of a sudden I've got 12 different things that I need to worry about. I only want two.
2:40:51>> Okay. Yeah. This is this is uh for as us living in the valley. Uh there's six different ways to define what is the valley >> in Los Angeles. And we want one way to define what is the valley. The valley is Los Angeles. Yeah. >> But the problem is part of the valley is in Los Angeles, the city. Part of it's not in the city of Los Angeles. What we're kind of saying is we just want the part of the valley that's in the city of Los Angeles. >> Exactly. [laughter] >> And not the other stuff. >> And not the other stuff. >> Not Burbank, Glendale. >> Right. Right. Not Thousand Oaks and all that. However, it that's not how it physically. >> Yeah. Physically all of these the electrons can't tell the difference between the cities. >> Right. Right. >> We're in the valley. So like
2:41:31>> Oh, it's we're in the valley. Exactly. >> Anyway, now um that's in bulk silicon. You get six. Now if you if you do the heterroructure that we've been talking about that like confines the electrons into this 2D plane you put like I don't know a layer of germanmanium or something um then that lifts the degeneracy and now you're only worried about two things [clears throat] because the two dimensions in x and y are in one state the z dimension which is the one that like has the different symmetries in the other state. So now you're worried about two >> but that's still two. And if the electron lives in a spin up spin down in the top or a spin up spin down in the bottom, >> there's still still >> there's still a problem because now you got four again. I only want two. >> Yeah. >> Okay. >> Okay. And that's been kind of a problem.
2:42:13This is this this is a limiting factor because the um the position uh like this impacts everything else downstream. Yeah. from an accur from a cubit quality and cubit control perspective. Both. Both. You're very correct. Both cubit quality in terms of I don't really have a well- definfined zero and a one and cubit control because if I try to kick my zero >> to a one, how do I know I didn't go to the other zero of the other valley state or some nonsense, right? And when I'm reading it out specifically like and I'm trying to do this poly spin blockade thing where I like shove the like what if the stuff goes into the other valley
2:42:53state, >> right? >> This is like kind of an existential >> it's fundamental. It's a fundamental problem >> because if you don't solve this then you you can't get to sustainability in in cubic quality or cubic control. >> Yeah. Yeah. And then scalability is the matter thing. >> Right. Right. Right. Right. Right. Right. Right. Because we still have this there's a there's a physical it's about the material itself. This this is a problem that arises out of the actual physical manufacturing of the material both in like the the quality of it and then anyway. >> Exactly. This is a big deal. >> So this is a big deal that needs to get solved. Right. I can understand why people are like, "Ah, yeah, cuz it seems like just like a this magic trick that Silken does that first of all, they don't even understand." So then when someone tells them, "Oh, it's
2:43:33impossible." They're like, "Oh, yeah, okay. I'm going to go do my neutral atoms nonsense [laughter] in Munich, Germany." >> Sorry. So anyways, there's that. And then finally, there's also a wiring problem because each of these gates, you know, as I told you, there's a wire that has to go in and control the plus 5 - 5 + 55 - 5. Each of these have to be independent wires that go in. And so you're sort of met with the same wiring problem that you had with superconducting except it's a little bit better because with superconducting cubits you had coax cables that were like semi- rigid. Here at least you've got like just wires, right? So it's a little bit more tractable. Inherently though, there is still a wiring problem. >> Okay. >> Okay. Now let's finally talk about HRL
2:44:14in this particular paper. Yes. >> Cuz that's that's sort of where we landed. >> Yes. >> Right. With why people think spin cubits ain't going to be it. >> Right. >> Okay. Now, HRL um for for those who don't know um it started its life out as Hughes Research Labs after Howard Hughes, who is the um Leonardo DiCaprio character in The Aviator. Yes. >> And if you've seen that movie, there's like this uh >> there's like this gaggle of engineers and scientists that are trying to make him this crazy a this crazy airplane. And he goes to them and he's like, "These rivets are on the airplane. They need to be completely flushed." and they spend their time like
From Why Spin Qubits Will Win the Quantum Race (Part 2)
Part II of our quantum computing deep dive compares the leading hardware architectures, and asks whether silicon’s greatest advantage is not simply making good qubits, but making quantum computers that can actually scale.