Why Spin Qubits Will Win the Quantum Race (Part 2)
EP 55
·3:07:32

The fidelity breakthrough

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3:07:3499.9%, what that really means is the error rate is 0.1%. Right? It's just one minus that. So, um, one in 1,000 operations are going to result in the wrong state. And because quantum algorithms string together a bunch of gates, it compounds. >> And so, you really need that fidelity to be really, really high. >> That makes sense. >> Okay. >> Now, this is kind of a interesting little part of this current paper. The fidelity has gone down gone up by a lot. The error rate has gone from that previous 2022 2023 performance 3.7% error >> down to nice 0.09%. >> So just under that.1%.

3:08:15>> Right? So the performance has really really gone up >> and this makes it possible to now really start doing error correction algorithms and things like that because now I can reliably >> do gates. >> Yes. Yes. Okay. And also the your pace of improvement if you were extrapolate moving forward >> that does we've not necessarily reached the ceiling yet on that performance improvement. Actually it's kind of interesting that you bring that point up. >> So how do they reduce this error? Right. What is the ceiling for example? >> Yes. >> Well there could be two sources to error. There could be an intrinsic and an exttrinsic source. Intrinsic means it's the stuff that we've talked about. It's the charge noise. It's the magnetic noise. It's this valley nonsense. This is stuff that is intrinsic to the

3:08:56physics. Um, exttrinsic noise is stuff from the engineering, [clears throat] >> right? This is stuff like, um, how good are my controls pulses? Are they are they squares? Are they calibrated correctly? Um, how good is it to go from room temperature down to there and then from the cryocontroller through the ribbon cable down to this thing? Am I losing am I losing like electricity and stuff as I move through there? So, that's the exttrinsic part. Okay. >> Yes. Here's [snorts] the kicker. This is a a quote from the paper. It says um errors resulting from the mean values of NOS and T2 star. These are two different measurements that you can do to qualify how good your cubid chip is. And you can

3:09:38use those measurements to then qualify how much of the error is because of exttrinsic sources and intrinsic sources. It shows that collectively those things only contribute to 0.02% of the absolute C not error absolute error in these gates. So the intrinsic part of things only contributes to 0.02% of the error. >> The >> this is a subtle way of them saying the physics problems have been solved. >> Yeah. Yeah. >> Kind of. >> Yeah. Yeah. Yeah. >> Okay. >> And then when you go into the into the methods where they talk about the cubit chip, right? Because anyone

3:10:19who's in spin cubits is going to look at this or anyone outside who's like how did they do that? The last sentence just says the sigy the silicon germanmanium heterroructure it was enriched with 28 silicon and depleted with 73 germanmanium. It was engineered to increase valleys splitting energy. That's it. >> Mhm. >> Okay. >> Mhm.

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.