A biased random walk between zero and N reaches N with a probability satisfying a two-point recurrence. This is a compact note, but the quantifiers and hypotheses stay on the page.
Objects and notation
A discrete-time Markov chain has transition matrix \(P=(p_{ij})\) and forgets the past after conditioning on the present. Matrix powers \(P^n\) give multi-step transition probabilities.
A reliable calculation names domain and codomain. The notation \(\mathsf{data}\mapsto\mathsf{claim}\) is harmless only after both \(\operatorname{dom}\) and \(\operatorname{cod}\) have been fixed.
Push the symbols
An explicit case prevents the notation from becoming ceremonial. Every subscript and superscript in the display contributes to the value.
Structural reading
The formula is reusable precisely because it says which pieces are structural and which belong only to the worked example.
A hypothesis worth keeping
A stationary distribution need not be unique without irreducibility, and convergence to it can fail without aperiodicity.
This is enough machinery for one note: an exact object, a worked case, a structural law, and a clearly marked boundary. Each layer can now be tested independently.