Repeated syndrome rounds separate a one-round blip from a data error that deserves correction. This ledger ignores the baseline round, counts later nonbaseline readings, and accepts correction only when the nonbaseline syndrome repeats enough times to reach the threshold. Real stabilizer cycles also include readout mistakes, drifting ancillas, timing limits, finite sampling, and uncertainty.
Syndrome rounds need a repeated nonbaseline reading before data correction. Exact arithmetic here means exact results for the stated model inputs; measured inputs still carry uncertainty and significant-figure limits.
highlighted = computed this step
Data correction needs repeated nonbaseline rounds
The repeat count ignores the baseline round and counts later nonbaseline readings.
m=r−rmin
Three round patterns bracket the data-error threshold
A one-round blip is still below threshold. Two repeated nonbaseline readings meet it.