A fixed asymmetric assignment matrix biases the observed budget the same direction for every true state it is applied to. Exact arithmetic here means exact results for the stated model inputs; measured inputs still carry uncertainty and significant-figure limits.
highlighted = computed this step
The same asymmetric matrix starts from a balanced state
Chapter six's matrix-quality scan fixed the true state and varied the matrix. Here the matrix stays fixed at the mild asymmetric row from this chapter's first lesson, and the true state changes instead.
ptrue=(21,21)
A fixed asymmetric matrix skews every true state the same way
Each row's observed zero probability sits above the true zero probability, because the matrix under-reports prepared one more than it under-reports prepared zero, regardless of which true state is checked.
A nearly-certain true state still carries the same bias
Even when the true state is already 9/10 toward zero, the asymmetric matrix still pushes the observed zero count above the true count: 88 expected zero reads out of 100 shots.