A measured shot scan turns exact state probabilities into expected counts by multiplying by the number of trials, auditing the pre-measurement distribution without claiming that any single outcome is predetermined. The three rows give (3/5, 4/5) over 25 shots as (9, 16), (4/5, 3/5) as (16, 9), and (5/13, 12/13) over 169 shots as (25, 144) exactly for the stated toy probability ledger; real experiments have shot noise, readout assignment error, state-preparation drift, and finite-count statistics.

A finite batch of identically prepared systems turns squared amplitudes into expected measurement counts. Exact arithmetic here means exact results for the stated model inputs; measured inputs still carry uncertainty and significant-figure limits.

highlighted = computed this step

Expected counts start with squared amplitudes

The rendered state uses amplitudes 3/5 and 4/5. Squaring gives probabilities 9/25 and 16/25.

Pzero=925,Pone=1625P_{\text{zero}}=\frac{9}{25},\quad P_{\text{one}}=\frac{16}{25}
Measurement count sourceProbability bars are computed before expected counts.9/25zero16/25onestate3/5 zero4/5 onestate1 zero0 oneafter measurement

The first row has exact expected counts

For 25 identically prepared systems, the expected counts are 9 zero outcomes and 16 one outcomes. This is still an expectation, not a random draw.

Nzero=9,None=16N_{\text{zero}}=9,\quad N_{\text{one}}=16
Measurement count rowThe rendered row is the three-five, four-five state.9/25zero16/25onestate3/5 zero4/5 onestate1 zero0 oneafter measurement

Three states give three exact shot ledgers

Each row squares the two amplitudes and multiplies by the trial count. The last row uses more trials because thirteenths need a larger exact square denominator.

abNNzeroNone354525916453525169513121316925144\begin{array}{c|c|c|c|c}a&b&N&N_{\text{zero}}&N_{\text{one}}\\\frac{3}{5}&\frac{4}{5}&25&9&16\\\frac{4}{5}&\frac{3}{5}&25&16&9\\\frac{5}{13}&\frac{12}{13}&169&25&144\end{array}
Measured-shot scanThe diagram is the first exact row.9/25zero16/25onestate3/5 zero4/5 onestate1 zero0 oneafter measurement

Counts do not replace the state update rule

The table audits the pre-measurement distribution. A particular measurement result still updates the next state, so this scan does not pretend that expected counts are hidden prewritten answers.

Nzero+None=N,Pzero+Pone=1N_{\text{zero}}+N_{\text{one}}=N,\quad P_{\text{zero}}+P_{\text{one}}=1
Measurement auditDistribution and update are kept separate.9/25zero16/25onestate3/5 zero4/5 onestate1 zero0 oneafter measurement