Decoherence time — why qubits “forget” so quickly

1:14:42makes total sense. The the point is you don't actually have like a workspace that is active for long enough for you to do like yeah >> like valuable computation to get an output because the decoherence time is so short. similar to our first story because we're at a scale now where the little stuff >> changes in very very very small things >> that might not have mattered in a classical system matter a lot in this uh quantum system in the same way that like under five mock you don't have to worry about the little stuff but above five mock you have to worry about stuff in a in a different way or the details matter and so >> if you can increase the decoherence time

1:15:24that means I can run a longunning algorithm. It's like a context window in AI. Yeah. Like exactly like like you you have more time to do the thing you want to do before >> forgets. Yeah. Before before it forgets, right? And Yeah. Yeah. And there and there's ways to do this to get around it. There's stuff called error correction where what you do is you like replicate the cubit multiple times and then you have like a bunch of cubits retain that information. So if one of them forgets, you can have like the other guys. But like at the end of the day, a hardware solution is >> is king. >> It's not it's not clean. It's not >> clean. >> It's not clean. Right. Right. You have to do all of these contingencies. If you have a hardware solution, well then you can implement that software solution

1:16:05with the hardware solution and even multiply. Correct. Beyond >> beyond like what you were. So the hardware is always king. >> The king. The biggest fundamental limit is still at the hardware level. >> It's still at the hardware level. Exactly. And so there's different kinds of cubits. I just gave an illusion of the electron being a single cubit, right? Where it's like spinning one way or the other way. The one that we're talking about is actually pioneered by the 2025 Nobel Prize in physics by these three gentlemen's um John Clark, Michelle Devay, and John Martinez back in UC Berkeley. They came up with this idea of macroscopic quantum tunneling. Right. The idea was to make a quantum circuit, a tiny little circuit that had

1:16:45something called um a Josephson junction. Yes. And then you have on the order of billions of electrons that behave like a single quantum unit that are tunneling from one to the other from one to the other. Right? We had a great deep dive on this during the Nobel Prizes. So it it is a phenomenally well done deep dive. Yeah. So, please go check out our our Nobel Prize episode on this because if you're curious about this concept of the superconducting circuits with Joseph and junctions and macroscopic quantum tunneling, it is really fascinating and we have I think one of the best explainer videos out that's available.

1:17:25>> We won an award from Tik Tok. >> We we did Tik Tok did give us second place for our science content because it was so good. Um, and I just was so fascinated by please watch that video. >> Exactly. So, so these guys sort of, >> you know, went and created that thing, >> right? >> And IBM and Google now use something called a transmon design, which is a charge cubit. It's basically their design, but they've attached a large capacitor on on the side, and they've made it insensitive to charge noise. But this is this is basically the cubit that they're using to make the um the quantum computers that they talk about. So