2024
Lifting query complexity to time-space complexity for two-way finite automata
ZHENG, Shenggen; Yaqiao LI; Minghua PAN; Jozef GRUSKA; Lvzhou LI et. al.Basic information
Original name
Lifting query complexity to time-space complexity for two-way finite automata
Authors
ZHENG, Shenggen (156 China); Yaqiao LI; Minghua PAN; Jozef GRUSKA (703 Slovakia, belonging to the institution) and Lvzhou LI
Edition
Journal of Computer and System Sciences, San Diego, Elsevier, 2024, 0022-0000
Other information
Language
English
Type of outcome
Article in a journal
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
United States of America
Confidentiality degree
is not subject to a state or trade secret
References:
Impact factor
Impact factor: 0.900
RIV identification code
RIV/00216224:14330/24:00139267
Organization unit
Faculty of Informatics
UT WoS
001138384300001
EID Scopus
2-s2.0-85179893976
Keywords in English
Quantum computing; Time-space complexity; Two-way finite automata; Communication complexity; Lifting theorems; Query algorithms
Tags
International impact, Reviewed
Changed: 2/4/2025 00:48, RNDr. Pavel Šmerk, Ph.D.
Abstract
In the original language
Time-space tradeoff has been studied in a variety of models, such as Turing machines, branching programs, and finite automata, etc. While communication complexity as a technique has been applied to study finite automata, it seems it has not been used to study time-space tradeoffs of finite automata. We design a new technique showing that separations of query complexity can be lifted, via communication complexity, to separations of time-space complexity of two-way finite automata. As an application, one of our main results exhibits the first example of a language L such that the time-space complexity of two-way probabilistic finite automata with a bounded error (2PFA) is ⠂⠂(n2), while of exact two-way quantum finite automata with classical states (2QCFA) is O ⠂(n5/3), that is, we demonstrate for the first time that exact quantum computing has an advantage in time-space complexity comparing to classical computing. (c) 2023 Elsevier Inc. All rights reserved.