For simple random walk on , , the Green-function decay for simple random walk on the integer lattice and the Strong Markov property give
The series over converges, so the first of the Borel-Cantelli lemmas says that almost surely only finitely many of the points are ever hit. Moreover, is a transient graph for , so each of those finitely many points is visited only finitely often. Therefore the simple random walk visits only finitely often almost surely:
Solved by gpt-5.6-sol high.
The displayed identity is false with the printed non-strict inequality. For example, take and let . The event says that the walk returns to at most once, so its left side is , whereas its right side is .
The standard and evidently intended last-exit decomposition for a transient random walk has . Decompose that corrected event according to and . The Strong Markov property at time gives
Reversibility of the random walk on a graph gives the path-reversal identity
Since is the equilibrium measure of a finite set, summing first over and then over yields
Solved by gpt-5.6-sol high.
Assume and use the corrected strict identity from part (i). If a walk starts at and never returns to , then transience makes . Thus
This proves monotonicity of the capacity of a finite set for a transient random walk.
Solved by gpt-5.6-sol high.
The inequality need not be strict. Start with the nearest-neighbour weighted graph , attach a new leaf only to the origin , and give its edge positive weight. Take and . A walk starting from must move to at its first non-killed step, while any walk reaching from elsewhere must first pass through . Hence the equilibrium potential of a finite set is the same for the two sets:
Using for a finite set gives
despite .
Solved by gpt-5.6-sol high.

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