Classical metric Diophantine approximation revisited: the Khintchine-Groshev theorem
Abstract
Under the assumption that the approximating function is monotonic, the classical Khintchine-Groshev theorem provides an elegant probabilistic criterion for the Lebesgue measure of the set of -approximable matrices in mn. The famous Duffin-Schaeffer counterexample shows that the monotonicity assumption on is absolutely necessary when m=n=1. On the other hand, it is known that monotonicity is not necessary when n > 2 (Sprindzuk) or when n=1 and m>1 (Gallagher). Surprisingly, when n=2 the situation is unresolved. We deal with this remaining case and thereby remove all unnecessary conditions from the classical Khintchine-Groshev theorem. This settles a multi-dimensional analogue of Catlin's Conjecture.
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