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How can a simulation be more accurate than what it's simulating?

Physical quantum computers have noise. Let's take a (simplified) scenario. You've set up your quantum circuit with one qubit, and put it in a position where it will measure as either 0 or 1 with equal chance. In the simulation it'll come out as 0 or 1 with actual equal chance. In the real world, other factors will create a bias one way or the other (this may not be consistent, either) so that it comes out more like 60% 0 to 40% 1, even over 1000s of trials.

If you set up a circuit where you've entangled two qubits so that they should come out as the same value (00 or 11) and the configuration says they should come out with 50% chance of either, the simulation will show that. The outputs of 01 and 10 will never show up in the simulation. But in the real world, there's still a chance that you get those. You'll likely (on IBM's quantum computers) get something like 1-5% 01, 1-5% 10, 45-50% 11, 45-50% 00 (again, over thousands of runs).

If you want to see how this plays out with simulations and real quantum computers, IBM [0] has free access (constrained by credits when you want to run on real quantum computers, they reset each day).

[0] https://quantum-computing.ibm.com/

As far as I understand, it's because what it's simulating is a logical qubit which is different from the very noisy, almost instantaneously collapsing physical qubits present in current quantum computers.

Software simulates what's supposed to happen while the hardware only approaches it through many repeated trials.

Current quantum computers are noisy. Gates aren’t perfectly implemented. Qubits are prone to dephasing and decoherence.

I think he means returns correct results to known problems more reliably.

Quantum computers are used to simulate digital computers, so a digital computer simulating a quantum computer simulating a digital computer can cheat.

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