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For a nonempty finite vertex set $A$ in a degree-$k$ regular tree, its induced forest has $|A|-c(A)$ edges, where $c(A)$ counts its components. Summing degrees and subtracting twice the internal edge count gives the displayed number of edges with exactly one endpoint in $A$. In particular it is at least $(k-2)|A|+2$.

For the contact process with per-edge infection rate $\lambda$ and recovery rate one on a degree-$(d+1)$ regular tree, the infinitesimal generator gives $L{\nu }_{\rho }(A)=(1-\rho ){\nu }_{\rho }(A)(|A|/\rho -\lambda |{\partial }_{E}A|)$. The edge boundary of a finite forest in a regular tree implies $L{\nu }_{\rho }\le 0$ whenever $\rho \lambda (d-1)\ge 1$, including the absorbing empty state where the generator is zero. Thus the displayed functional is a bounded supermartingale, and the extinction probability from $A$ is at most ${\rho }^{|A|}$.

Orient a degree-$(d+1)$ regular tree towards one end, and let height $g$ decrease along the unique parent edge and increase along the $d$ child edges. For $w_{\rho }(A)={\sum }_{x\in A}{\rho }^{g(x)}$, suppressing the occupied-target constraint only increases births, so its infinitesimal generator satisfies $L{w}_{\rho }\le [-1+\lambda ({\rho }^{-1}+d\rho )]w_{\rho }$. For $d>1$, choose $\rho =d^{-1/2}$. If $\lambda <1/(2\sqrt{d})$, the expected weight and the infection probability at each fixed site decay exponentially. The expected number of recoveries there equals its expected total occupation time, which is finite. Each infection episode ends almost surely at a recovery, so infinitely late infection is impossible. For $d=1$, take $\rho <1$ sufficiently close to one for each $\lambda <1/2$.

For this radial random walk on a regular tree, the drawing is an infinite regular tree of degree $z$, not a planar lattice with closed loops. The radial coordinate is the number of edges in the unique path to the root. A non-root vertex has one neighbour inward and $z-1$ neighbours outward, so equal probabilities for its $z$ edges giveLet $r$ be radial distance measured in edge units. For $r>1$, probability arriving in shell $r$ comes from shell $r-1$ by an outward step or from shell $r+1$ by an inward step:This has precisely the same bulk master equation as the one-dimensional biased random walk, withThe outward bias is geometric: beyond the first shell, the number of vertices is $M_r=z(z-1{)}^{r-1}$, so there are more outward than inward choices even though no edge direction is dynamically preferred. $P(r,N)$ is the probability summed over an entire shell, not the probability at one specified vertex; no additional shell-size factor belongs in the boxed recurrence.

The equality concerns the evolution equation away from the root, not equality to the unrestricted full-line binomial distribution at all positions. The root imposes a different boundary rule.

For a simple random walk on an infinite regular tree of degree $z\ge 2$, every vertex other than the chosen root has one neighbour closer to the root and $z-1$ farther away. The graph distance from the root is therefore a nearest-neighbour Markov chain on the nonnegative integers, with the displayed bulk transition probabilities and a certain outward step from zero. For shell probabilities $P_r(N)$,Shell probabilities include all vertices at the given distance. They differ from single-vertex probabilities by the shell size, $1$ at the root and $z(z-1{)}^{r-1}$ for $r\ge 1$.

Inside a rooted $d$-ary subtree of a degree-$(d+1)$ regular tree, pair each cell root with one distinguished child. Keep reinfection inside each pair, suppress infection back into its parent cell, and allow each child cell to be activated only once. Offspring counts of different cells are independent and identically distributed, so cell genealogies form a Galton-Watson process. A cell root has $d-1$ outgoing child-cell edges and its paired vertex has $d$. Starting at the root, the probabilities to send an arrow along one specified outgoing edge from these two vertices before internal extinction are respectivelyThey follow by first-step equations on the three nonempty pair states. The offspring mean is $M=(d-1)a+db$, andContinuity makes $M>1$ at some strictly smaller positive rate. The branching-process extinction criterion then gives positive survival probability for the suppressed process, hence for the original contact process.