Can trapped ions scale?

1:45:10are not great to work with. >> Laser beam >> laser beams are not great to work with. I'm gonna be honest. Okay. Um, if you want to do arbitrary grates, uh, arbitrary gates on millions of ions, you're going to need like a bunch of really perfectly aligned laser beams. Okay. Um, there's going to be these like spatial light modulators. There's going to be massive lenses that are all going to be pointing inside this vacuum chamber. If now that's going to heat stuff up first, >> you're you're pumping in lasers into a thing that's supposed to be cold. you're heating stuff up. >> It's like the more lasers you add, it changes the the economics of the equation, right? It just it's not like a

1:45:52linear where it's like, oh, one additional laser means just like one additional >> it it becomes more comp anyway. >> Exactly. Um and you know if if let's say like some random thermal expansion changes the lens shape. >> Right. Right. Right. Then everything else >> then like the laser is not pointing somewhere. Right. Now you got to deal with that. Lasers are just tough. >> Yeah. >> Okay. Lasers are tough. Um the other the other thing about the economics part of things, right? Um with superconducting circuits, I told you that you know it's going to be big. These things are going to be massive. >> Yeah. >> Well, with this, the algorithms are going to take a really, really long time. >> Because the gate times are so long,

1:46:32>> right? They're like a thousand times longer than the superconducting circuits. There have been estimates that show and obviously these are biased estimates but this is a biased show so we're [laughter] gonna we're going to talk about the biased estimates um it shows that like a superconducting arrays if they want to crack 20 48 bit RSA encryption >> it's going to take them about 8 hours >> okay with like a scalable fall tolerant quantum computer >> here even if we achieve scale >> because the gate times are so slow it might take like on the order of a year to to decrypt >> 248 RSA >> which defeats the purpose of why we want these. >> Yeah. Yeah. Yeah. I mean you say that

1:47:12Yeah. Yeah. It's one of the reasons, right? You could say there are other uses for quantum computing, but as I >> as I um talked about last episode, >> um the one that's like clear to me is Shor's algorithm. >> Yeah. >> Right. Yeah. >> It's like everyone wants to decrypt stuff >> and that's also the um geopolitical incentive. >> Exactly. >> Which is a driver of the investment. Yeah. >> Into the space. >> Yeah. I mean the So Quant continuum they have a lot of private funding. Um I think Honeywell is one of the big like computer chip uh technology firms is I think one of the big sponsors. Also, um JP Morgan, I think they want to do like

1:47:54financial algorithms and like portfolio management with quantum computers. More power to them. >> I'm not convinced. Um but you know, so there are there are use cases for it. Um and there they obviously have the like the backing, private backing, and now public backing with the IPO. And I'm I'm actually excited to see what they're going to come up with for their next iteration after Helios because um one of the things that we're going to get into later is like the fact that algorithms are getting more and more efficient. So maybe you don't need that many cubits and that many gates to do that. >> It could be irrelevant. >> So it's an open problem, right? But um

1:48:34in any case, as of now with all of the optical engineering, like if it takes a year for you to do RSA, like in that year, your lasers have to be perfect, right, for a whole year, like it's it's tough, right? So, um again, opinions are all my own. Final verdict, um the same as superconducting. If you say that I copied the slide and just replaced it, that is actually exactly what I did. [laughter] Um but again proprietary >> the standards for by which we uh judge things is proprietary. Cubid quality 5 out of 10 cubic control 5 out of 10 scalability and economics 1 out of 10 to get 11 out of 30.

1:49:14>> What I would say just as a brief side note is that being said with the same score the lever in which superconducting cubits versus trapped ions could change uh the levers they would pull are different. >> Mhm. Um yeah right like with with trapped ions if the algorithm problem goes away the scalability in economics very quickly >> is a solved problem >> as an example and so while they're they're similarly scored the levers of changing are fundamentally different. >> Yes. Yeah. And as as time goes on there's a there's an interesting plot. Oh I wish I had this overlay you know but maybe I'll put it up uh in the clips later. Go on go on Instagram. Um there's

1:49:55a plot that shows um on the on the x-axis time and on the y- axis like the efficiency of the algorithm effectively like how many cubits do you need or how many gate how many clifford gates do you need to or whatever gates that you need to implement and like it's steadily decreasing as time goes on. People are finding more and more efficient ways to to implement this kind of stuff. >> It's like the uh not quite but it's like the inverse of Moors law. Um not quite because Moors law is a little bit the numbers. >> Yeah. Well, it depends. I mean if you do Mors law size of transistor >> oh >> that's going down right >> that's going okay >> MOS law is traditionally number of transistors in a chip and that goes up but you could do it one way or the other so that's trapped ions >> so we we've covered superconducting

1:50:36cubits we've covered trapped ions and then uh the next thing we're going to look at >> neutral atoms >> neutral atoms >> I didn't even want to do this >> but >> but we got it >> for our audience we're always going to give you >> the best you can get anywhere. This is the best. This is the best. >> So, we're finally going to do neutral atoms. Um, there's a bunch of companies