Past exam of the mathematics course of the University of Cambridge 2009 ib Paper 1 19H Solution Created 2026-09-24 Updated 2026-10-14
Read the maze as two four-cycles: outer vertices , inner vertices for modulo four, edges , , and , together with edges from every to the target . The starting vertex is an outer vertex. Outer degrees are three and inner degrees are four.
For the ordinary random walk on a graph, symmetry gives a common expected hitting time from an outer vertex and from an inner one. First-step conditioning givesThus and , yielding and the requested starting mean moves.
For the non-backtracking random walk, the current vertex alone does not form a Markov chain. Use states recording previous and current vertices. Before hitting , its transitions are with probability for each neighbor . Add a starting state with no preceding vertex, choosing its first neighbor with probability , and an absorbing hit state. This specifies the full Markov chain.
Its directed edges aggregate into types , determined by the two vertex layers. From the next type is or with probability each. From it is with probability and the absorbing state with probability . From it is always . From it is , or the absorbing state with probability each. Every nonabsorbing type has a positive uniformly bounded chance of hitting within at most three more moves, so its mean time is finite.
Transition probabilities between the four directed-edge types of the non-backtracking maze walk and its absorbing target
. Details. Let their remaining mean times be in that order. The first-step equations areSolving gives , , , . The first move from the initial outer vertex reaches type with probability and type with probability , so the intelligent starting mean isThis hitting a hub from two four-cycles calculation reduces the mean from to , saving moves. Excluding immediate reversal removes wasteful two-step returns, although it does not guarantee that the next move is toward the target.
