Binomial branching survival correction 2026-10-07
For , the branching survival probability satisfies . If , comparison with a Poisson branching process and expansion of the logarithm giveFor the upper bound use and retain its first nonnegative term. For fixed , the leading term is instead . In particular gives , showing that the uncorrected exact bound is false for small positive .
For and , the uncorrected exact upper bound does hold for the binomial branching process. Here and , so at the first two terms of the nonnegative series give . Monotonicity of that series yields . This recovers the intended large- bracket without claiming it for every finite reproduction law.
In a Galton-Watson process, each individual independently has children with probability . This probability distribution determines its offspring probability generating function, its mean when finite, and the branching extinction probability. A binomial branching process and a Poisson branching process have different offspring distributions even when their means agree.
Past exam of the mathematics course of the University of Cambridge 2012 iii Paper 9 4 i Solution Created 2026-10-03 Updated 2026-10-07
For the binomial branching process, the offspring probability generating function is . The Galton-Watson extinction fixed point gives .
The printed finite-binomial upper bound is false without an additional asymptotic qualification. For and , solving the fixed-point equation exactly givesFor instance gives . More generally, at every fixed the Taylor expansion gives , again contradicting that upper bound for sufficiently small positive .
Here is the corrected binomial branching survival correction. The Poisson branching process of mean has branching survival probability satisfying . Expanding the logarithm givesThus , which implies the requested lower estimate . Since on , iteration of the two offspring probability generating functions gives .
For the actual binomial branching process, expansion of its exact fixed-point equation givesIf , all coefficients are nonnegative. Keeping the first term provesIn particular, for and this gives . The printed bounds also hold for the binomial branching process in an explicit large- regime: and . Indeed these conditions give and . In the preceding nonnegative series, evaluation at givesThe series is increasing, and its value at the actual branching survival probability is , so . Together with the lower bound already proved, this recovers in that regime. In particular it applies eventually to part (ii). The counterexample shows why a regime condition is needed for a literal finite- statement.
Finite-binomial survival exceeds the printed upper bound, while Poisson survival lies between the corrected comparison bounds
. Poisson branching process 2026-10-07
A Galton-Watson process with a Poisson distribution of offspring of mean has this probability generating function. For its branching survival probability satisfies , and . Indeed lies between and . These exact inequalities belong to the Poisson branching process, not to every finite binomial branching process.
Survival probability of a branching process 2026-10-07
For a Galton-Watson process started from one ancestor, this is the probability that every generation is nonempty. It is the complement of the branching extinction probability. The binomial branching survival correction distinguishes finite-binomial reproduction from the Poisson branching process near mean one.
