Holding ensemble weights fixed while population changes separates probability from expected count. Exact arithmetic here means exact results for the stated model inputs; measured inputs still carry uncertainty and significant-figure limits.

highlighted = computed this step

Twenty particles gives five in the moving state

The state weights stay 2 and 6, so the moving probability is 1/4. A population of 20 gives expected moving count 5.

2014=520\cdot\frac{1}{4}=5
Ensemble weight ledgerFinite state weights produce exact probabilities and expected counts.probprobcountcount

Forty particles gives the ten-count audit row

With the same probability 1/4, doubling population to 40 doubles the expected moving count to 10.

4014=1040\cdot\frac{1}{4}=10
Ensemble weight ledgerFinite state weights produce exact probabilities and expected counts.probprobcountcount

Sixty particles keeps the fraction and raises the count

At population 60, the same one-fourth probability gives expected moving count 15. The scan separates probability from population size.

6014=1560\cdot\frac{1}{4}=15
Ensemble weight ledgerFinite state weights produce exact probabilities and expected counts.probprobcountcount