826 research outputs found
One-Way Reversible and Quantum Finite Automata with Advice
We examine the characteristic features of reversible and quantum computations
in the presence of supplementary external information, known as advice. In
particular, we present a simple, algebraic characterization of languages
recognized by one-way reversible finite automata augmented with deterministic
advice. With a further elaborate argument, we prove a similar but slightly
weaker result for bounded-error one-way quantum finite automata with advice.
Immediate applications of those properties lead to containments and separations
among various language families when they are assisted by appropriately chosen
advice. We further demonstrate the power and limitation of randomized advice
and quantum advice when they are given to one-way quantum finite automata.Comment: A4, 10pt, 1 figure, 31 pages. This is a complete version of an
extended abstract appeared in the Proceedings of the 6th International
Conference on Language and Automata Theory and Applications (LATA 2012),
March 5-9, 2012, A Coruna, Spain, Lecture Notes in Computer Science,
Springer-Verlag, Vol.7183, pp.526-537, 201
The 2CNF Boolean Formula Satisfiability Problem and the Linear Space Hypothesis
We aim at investigating the solvability/insolvability of nondeterministic
logarithmic-space (NL) decision, search, and optimization problems
parameterized by size parameters using simultaneously polynomial time and
sub-linear space on multi-tape deterministic Turing machines. We are
particularly focused on a special NL-complete problem, 2SAT---the 2CNF Boolean
formula satisfiability problem---parameterized by the number of Boolean
variables. It is shown that 2SAT with variables and clauses can be
solved simultaneously polynomial time and space for an absolute constant . This fact inspires us to
propose a new, practical working hypothesis, called the linear space hypothesis
(LSH), which states that 2SAT---a restricted variant of 2SAT in which each
variable of a given 2CNF formula appears at most 3 times in the form of
literals---cannot be solved simultaneously in polynomial time using strictly
"sub-linear" (i.e., for a certain constant
) space on all instances . An immediate consequence of
this working hypothesis is . Moreover, we use our
hypothesis as a plausible basis to lead to the insolvability of various NL
search problems as well as the nonapproximability of NL optimization problems.
For our investigation, since standard logarithmic-space reductions may no
longer preserve polynomial-time sub-linear-space complexity, we need to
introduce a new, practical notion of "short reduction." It turns out that,
parameterized with the number of variables, is
complete for a syntactically restricted version of NL, called Syntactic
NL, under such short reductions. This fact supports the legitimacy
of our working hypothesis.Comment: (A4, 10pt, 25 pages) This current article extends and corrects its
preliminary report in the Proc. of the 42nd International Symposium on
Mathematical Foundations of Computer Science (MFCS 2017), August 21-25, 2017,
Aalborg, Denmark, Leibniz International Proceedings in Informatics (LIPIcs),
Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik 2017, vol. 83, pp.
62:1-62:14, 201
Approximation Complexity of Complex-Weighted Degree-Two Counting Constraint Satisfaction Problems
Constraint satisfaction problems have been studied in numerous fields with
practical and theoretical interests. In recent years, major breakthroughs have
been made in a study of counting constraint satisfaction problems (or #CSPs).
In particular, a computational complexity classification of bounded-degree
#CSPs has been discovered for all degrees except for two, where the "degree" of
an input instance is the maximal number of times that each input variable
appears in a given set of constraints. Despite the efforts of recent studies,
however, a complexity classification of degree-2 #CSPs has eluded from our
understandings. This paper challenges this open problem and gives its partial
solution by applying two novel proof techniques--T_{2}-constructibility and
parametrized symmetrization--which are specifically designed to handle
"arbitrary" constraints under randomized approximation-preserving reductions.
We partition entire constraints into four sets and we classify the
approximation complexity of all degree-2 #CSPs whose constraints are drawn from
two of the four sets into two categories: problems computable in
polynomial-time or problems that are at least as hard as #SAT. Our proof
exploits a close relationship between complex-weighted degree-2 #CSPs and
Holant problems, which are a natural generalization of complex-weighted #CSPs.Comment: A4, 10pt, 23 pages. This is a complete version of the paper that
appeared in the Proceedings of the 17th Annual International Computing and
Combinatorics Conference (COCOON 2011), Lecture Notes in Computer Science,
vol.6842, pp.122-133, Dallas, Texas, USA, August 14-16, 201
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