Relationships Among PL, #L, and the Determinant

Recent results by Toda, Vinay, Damm, and Valiant have shown that the complexity of the determinant is characterized by the complexity of counting the number of accepting computations of a nondeterministic logspace-bounded machine. (This class of functions is known as #L.) By using that characterization and by establishing a few elementary closure properties, we give a very simple proof of a theorem of Jung, showing that probabilistic logspace-bounded (PL) machines lose none of their computational power if they are restricted to run in polynomial time. We also present new results comparing and contrasting the classes of functions reducible to PL, #L, and the determinant, using various notions of reducibility. 1 Introduction One of the most important and influential early results of complexity theory is the theorem of [47] showing that the complexity of computing the permanent of an integer matrix is characterized by the complexity class #P of functions that count the number of acceptin..