Robust Simulations and Significant Separations

We define and study a new notion of "robust simulations" between complexity classes which is intermediate between the traditional notions of infinitely-often and almost-everywhere, as well as a corresponding notion of "significant separations". A language L has a robust simulation in a complexity class C if there is a language in C which agrees with L on arbitrarily large polynomial stretches of input lengths. There is a significant separation of L from C if there is no robust simulation of L in C. The new notion of simulation is a cleaner and more natural notion of simulation than the infinitely-often notion. We show that various implications in complexity theory such as the collapse of PH if NP = P and the Karp-Lipton theorem have analogues for robust simulations. We then use these results to prove that most known separations in complexity theory, such as hierarchy theorems, fixed polynomial circuit lower bounds, time-space tradeoffs, and the theorems of Allender and Williams, can be strengthened to significant separations, though in each case, an almost everywhere separation is unknown. Proving our results requires several new ideas, including a completely different proof of the hierarchy theorem for non-deterministic polynomial time than the ones previously known

A Generic Time Hierarchy for Semantic Models With One Bit of Advice

We show that for any reasonable semantic model of computation and for any positive integer a and rationals 1 ≤ c < d, there exists a language computable in time n d with a bits of advice but not in time n c with a bits of advice. A semantic model is one for which there exists a computable enumeration that contains all machines in the model but may also contain others. We call such a model reasonable if it has an efficient universal machine that can be complemented within the model in exponential time and if it is efficiently closed under deterministic transducers. Our result implies the first such hierarchy theorem for randomized machines with zero-sided error, quantum machines with one- or zero-sided error, unambiguous machines, symmetric alternation, Arthur-Merlin games of any signature, interactive proof protocols with one or multiple provers, etc. Our argument yields considerably simpler proofs of known hierarchy theorems with one bit of advice for randomized or quantum machines with two-sided error and randomized machines with one-sided error. Our paradigm also allows us to derive stronger separation results in a unified way. For models that have an efficient universal machine that can be simulated deterministically in exponential time and that are efficiently closed under randomized reductions with two-sided error, we establish the following: For any constants a and c, there exists a language computable in polynomial time with one bit of advice but not in time n c with a log n bits of advice. In particular, we obtain such separation for randomized and quantum machines with two-sided error. For randomized machines with one-sided error, we get that for any constants a and c there exists a language computable in polynomial time with one bit of advice but not in time n c with a(log n) 1/c bits of advice.