Anytime we introduce any change in temperature, we have higher decoherence. Today, if you look at one of these quantum computers, there’s a great one that Google posted, and I’m not picking on it - it’s a beautiful picture - but if you look at the cryogenic plane where all the computation is happening, what you see is hundreds of wires that are being fed into that quantum computer in order to feed it to the classical computer where we output the data. We might only need something that’s the size of a conference room, and if it’s a conference room, maybe we only need it to be the size of a refrigerator, but that’s the world that we’re heading toward. We don’t need machines that are the size of football fields now. Therefore, when you add five qubits, maybe only 5% of the time, they will fail. We’re proposing that topological qubits will solve this problem of decoherence and therefore make them more stable. If you want a thousand stable qubits, and you have a 99% error ratio - where 99% of the time, the qubits are decohering - you need, if you want a thousand stable ones, a million qubits. In the interim, what’s happening is, because there is no error correction today, people just throw more qubits at the problem. Decoherence goes down greatly, and what we’ve then done is put error corrections in the qubits. Then, if it was open on the other side, you might call it off, but in the interim, it could have been on or off.īy doing that, by putting them in a tube, you don’t get the idea of running into each other. The topological qubit is more like if you could imagine a bunch of these particles where they’re locked arms around each other’s shoulders and they’re sitting in a tube, and if you could imagine that there were three qubits, but there were four chairs, and you would still get this idea that they’re being in an on and off state at the exact same time, but when you would, say, “Freeze!” you would look at the two ends and say which chair is open. When you have those two particles together and then another particle runs into it, and you go to look at them and measure them, and you’re like, “Wait a second - I don’t even see the two particles I was expecting,” that’s called decoherence. That’s one way that we can hold two states in quantum computers at the exact same time, as opposed to a regular binary world where we can only hold one state in our mind, like a light switch. You would expect the one with the electron bound to it to be heavier. When you go to measure the state of that electron, you’re sharing - you have two nuclei and one electron flying between them, and you might occasionally just say, “Freeze!” and measure the weight of the two nuclei. For those not familiar, qubits operate on an electron flying around a nucleus. Well, we’ve been talking about it for quite a while, and we still believe that the topological qubit is the only answer that gets us to true scalability. The issue really comes around factorization, so in order to describe how this works, let’s talk about a bitcoin wallet for a moment. Let me start off with this: Since our project is cryptocurrency based, moving forward, a basic-level understanding of bitcoin will be helpful for your audience. The algorithm will just work in the background, and so almost an asynchronous process, where it’ll say, “Well, we’ll wait until the quantum computer is ready.” Then, when it’s there, it’ll throw the calculation at it, get an answer and then return back to whatever the next step is in the algorithm. Not everybody is going to have access to a quantum computer, so, really, what you’re renting is almost like the equivalent of time, so it’s almost like you’re saying, “I need this for 15 seconds,” or an hour or whatever happens to be. The person won’t have to really worry about that so much - they just want the answer. You might have elements within that ML that are optimized for more of a quantum space versus a classical space. Well, yes, and we’re creating these layers of extraction only now using something like Singular or Python, which is where most machine learning algorithms are written.
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