Proving the power of postselection

It is a widely believed, though unproven, conjecture that the capability of postselection increases the language recognition power of both probabilistic and quantum polynomial-time computers. It is also unknown whether polynomial-time quantum machines with postselection are more powerful than their probabilistic counterparts with the same resource restrictions. We approach these problems by imposing additional constraints on the resources to be used by the computer, and are able to prove for the first time that postselection does augment the computational power of both classical and quantum computers, and that quantum does outperform probabilistic in this context, under simultaneous time and space bounds in a certain range. We also look at postselected versions of space-bounded classes, as well as those corresponding to error-free and one-sided error recognition, and provide classical characterizations. It is shown that $\mathsf{NL}$ would equal $\mathsf{RL}$ if the randomized machines had the postselection capability.Comment: 26 pages. This is a heavily improved version of arXiv:1102.066

A Uniform Method for Proving Lower Bounds of the Computational Complexity of Logical Theories

https://deepblue.lib.umich.edu/bitstream/2027.42/154178/1/39015100081655.pd

On Time-space Classes and Their Relation to the Theory of Real Addition

A new lower bound on the computational complexity of the theory of real addition and several related theories is established: any decision procedure for these theories requires either space n2 or nondeterministic time 2en2 for some constant E> 0 and infinitely many n