Why Spin Qubits Will Win the Quantum Race (Part 2)
EP 55
·1:57:22

Atom loss and post-selection

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This chapter, from the episode video's captions · 951 words

1:57:22You read the fine print. What's actually happening is the following. Um during their experiment, they will lose atoms because the atoms are in this like this this tractor beam. Sometimes they'll leave, sometimes the photon will come in, they'll leave, another atom from the vacuum will come in, they'll leave. They're going to lose atoms. every time they lose atoms, they just throw away that experiment. >> That doesn't count. >> Yeah. They're just like, uh uh, you know, we have so many of them. >> Let's do it again. Let's just do it again. And then so the the there's this post selection >> and many of the published fidelity figures calculate on calculate

1:58:04conditioned on atom survival. They throw away the trials where the atoms died, >> which doesn't count, >> which is like I mean there's a reason there. Okay, there there might be a good reason for for you to do that, but then at the same time, I should be able to say, "Ah, is that the same as the numbers that other people are reporting? If I'm running a 100 meter dash and I can run it a 100 times >> and just throw out the ones I don't like [laughter] does it still count?" >> Yeah. Yeah. >> I'm I I don't know. >> I don't know. >> I'm a layman. I'm just asking the question cuz that's what it sounds like. >> That's what it sounds like to me, right? But but please convince I can be dissuaded from this perspective. Yeah. Anyway, so that's cubid quality, right? [laughter] The quality of the cubit. All

1:58:45right. What about control? Um control like the fact that you can use these laser beams. You can create you can bring any two atoms together. >> Um and you you can make the tweezers sort of grab this atom and this atom and bring them together. Grab this atom and this atom. This is a experiment where they showed like using these tractor beams they can create like a 3D sculpture. Yeah, that's cool. >> of stuff, which is which is kind of cool. >> That's very cool, >> right? Um, and so this is to show you that you can physically move them across the array. You can park them right next to new orbits midcircuit. So you can have like this all to all connectivity type of thing. And because you have all toall connectivity, you can now um >> not limited by two. >> Not limited by trapped ion.

1:59:25>> Exactly. Yeah. Yeah. So now you can um you can you can do error codes that are like way more efficient, >> right? Um because you can harness this all toall connectivity. Yep. Um the readout however is kind of destructive because you do it by shining a laser and capturing the fluorescent photons, but the light pressure from this readout can heat up the atoms and then again they'll like leave. But then I guess you can just throw it out. >> Yeah. >> Would would this then sort of mean like the idea is that we're solving for lack of coherence time in this kind of system which was great in trapped ions but is not necessarily as great here by just saying we can scale this so much. We can just have so many that coherence time is

2:00:05not no longer as important of a variable. >> Yeah. It's like I mean coherence time is might not be the correct idea but I think what like survival cubit survival is like yeah it might not be because because maybe the gates are a little bit more faster and they I mean the the community is saying that they are working on it. >> Okay. >> Okay. They're working on this problem and they've got like they've got these ideas where they've got a reservoir where they can take the atom from the reservoir and put it in where the where it was missing. The key thing is it's it gets pretty obvious to know where the atom left, right? >> Yeah. Yeah. >> Right. Because you've got a grid or whatever right? >> And because you know exactly where the atom left, the error codes where you know where the error happened are really

2:00:45efficient. >> Yeah. And that makes sense. And and again, these systems sort of have optimizations for different things uh or are successful in different arenas that >> you know maybe other methodologies don't do as well. But the idea again going back to our initial original original analogy of like the transistor versus vacuum tube versus electric relays it's still unclear right now you'll make the argument otherwise right now >> which path is going to be cuz there's there's going to be maybe there are use cases for some niche areas for some of these if there's not an outright winner that's just good for everything like maybe that's true >> but it's also very possible that one of

2:01:27these is just going to solve each of these layers >> and just be the best for everything. >> Um, and the architecture for this neutral atoms >> is really nice because you have a lot of fine grain control. >> Yeah. And that's why I think a lot of people think that this is the current sort of front runner. >> Okay. >> Okay. Because it's out there. Yeah. You've got all these nice little knobs that you can like tune, right? [laughter] >> Um, and then to to scale them like how how scalability? Well, to scale them, you've got an, you know,

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.