Two-way quantum and classical automata with advice for online minimization problems

Abstract

© Springer Nature Switzerland AG 2020. We consider online algorithms. Typically the model is investigated with respect to competitive ratio. In this paper, we explore two-way automata as a model for online algorithms. We focus on quantum and classical online algorithms. We show that there are problems that can be solved more efficiently by two-way automata with quantum and classical states than classical two-way automata in the case of sublogarithmic memory (sublinear size) even if classical automata get advice bits.