  The notion of Las Vegas algorithms was introduced by Babai (1979) and can be
defined in two ways:
  * In Babai's original definition, a randomized algorithm is called Las Vegas
if it has a finitely bounded running time and certifiable random failure.
  * Another definition widely accepted today is that Las Vegas algorithms refer
to zero-error randomized algorithms with random running times.
  The equivalence between the two definitions is straightforward. Specifically,
for randomized algorithms with certifiable failures, repeatedly running the
algorithm until no failure is encountered allows for faithful simulation of the
correct output when it executes successfully.
  We show that a similar perfect simulation can also be achieved in distributed
local computation. Specifically, in the LOCAL model, with polylogarithmic
overhead in time complexity, any Las Vegas algorithm with finitely bounded
running time and locally certifiable failures can be converted to a zero-error
Las Vegas algorithm. This transformed algorithm faithfully reproduces the
correct output of the original algorithm in successful executions.
