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NISQ reality
Decoherence, gate errors and readout errors: the three ways a real device disagrees with the simulator.
- Define T1, T2, gate error and readout error.
- Estimate the success probability of a circuit from its gate counts.
- Read the calibration panel of a backend.
| Quantity | Meaning | Heron r2, typical |
|---|---|---|
| T1 | time for |1⟩ to decay toward |0⟩ | ≈ 150–300 µs |
| T2 | time for a superposition's phase to randomise | ≈ 100–250 µs |
| 1q gate error | probability one single-qubit gate goes wrong | ≈ 2–5 × 10⁻⁴ |
| 2q gate error | same for CZ / ECR | ≈ 2–5 × 10⁻³ |
| Readout error | probability a 0 is read as 1 or vice versa | ≈ 1 % |
Ideal versus noisy twin
Run Simulate with the preset 'Ideal + noisy twin'. The GHZ state should be 50/50 on 0000 and 1111; the fake backend leaks probability into the other 14 strings. The Metrics tab reports the Hellinger fidelity between the two.
OPENQASM 3.0; include "stdgates.inc"; qubit[4] q; bit[4] c; h q[0]; cx q[0], q[1]; cx q[1], q[2]; cx q[2], q[3]; c = measure q;
NISQ stands for noisy intermediate-scale quantum: hundreds of qubits, no error correction, circuits limited to a few hundred two-qubit gates before the signal drowns. Everything in this track is about getting useful answers inside that budget.
A circuit has 40 CZ gates at 0.4% error each and negligible other errors. Roughly what fraction of shots is error-free?
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T2 ≤ 2·T1 always. Which process limits T2 but not T1?
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Real devices lose signal through decoherence, gate errors and readout errors. Budget them with the gate counts, and always compare against the ideal reference.
Up next: Noise models and fake backends