346 research outputs found
Hierarchies of turing machines with restricted tape alphabet size
It is shown that for any real constants b>a≥0, multitape Turing machines operating in space L1(n)=[bnr] can accept more sets than those operating in space L2(n)=[anr] provided the number of work tapes and tape alphabet size are held fixed. It is also shown that Turing machines with k+1 work tapes are more powerful than those with k work tapes if the tape alphabet size and the amount of work space are held constant
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
The Reachability Problem for Petri Nets is Not Elementary
Petri nets, also known as vector addition systems, are a long established
model of concurrency with extensive applications in modelling and analysis of
hardware, software and database systems, as well as chemical, biological and
business processes. The central algorithmic problem for Petri nets is
reachability: whether from the given initial configuration there exists a
sequence of valid execution steps that reaches the given final configuration.
The complexity of the problem has remained unsettled since the 1960s, and it is
one of the most prominent open questions in the theory of verification.
Decidability was proved by Mayr in his seminal STOC 1981 work, and the
currently best published upper bound is non-primitive recursive Ackermannian of
Leroux and Schmitz from LICS 2019. We establish a non-elementary lower bound,
i.e. that the reachability problem needs a tower of exponentials of time and
space. Until this work, the best lower bound has been exponential space, due to
Lipton in 1976. The new lower bound is a major breakthrough for several
reasons. Firstly, it shows that the reachability problem is much harder than
the coverability (i.e., state reachability) problem, which is also ubiquitous
but has been known to be complete for exponential space since the late 1970s.
Secondly, it implies that a plethora of problems from formal languages, logic,
concurrent systems, process calculi and other areas, that are known to admit
reductions from the Petri nets reachability problem, are also not elementary.
Thirdly, it makes obsolete the currently best lower bounds for the reachability
problems for two key extensions of Petri nets: with branching and with a
pushdown stack.Comment: Final version of STOC'1
Complexity Hierarchies Beyond Elementary
We introduce a hierarchy of fast-growing complexity classes and show its
suitability for completeness statements of many non elementary problems. This
hierarchy allows the classification of many decision problems with a
non-elementary complexity, which occur naturally in logic, combinatorics,
formal languages, verification, etc., with complexities ranging from simple
towers of exponentials to Ackermannian and beyond.Comment: Version 3 is the published version in TOCT 8(1:3), 2016. I will keep
updating the catalogue of problems from Section 6 in future revision
Refinement sensitive formal semantics of state machines with persistent choice
Modeling languages usually support two kinds of nondeterminism, an external one for interactions of a system with its environment, and one that stems from under-specification as familiar in models of behavioral requirements. Both forms of nondeterminism are resolvable by composing a system with an environment model and by refining under-specified behavior (respectively). Modeling languages usually dont support nondeterminism that is persistent in that neither the composition with an environment nor refinements of under-specification will resolve it. Persistent nondeterminism is used, e.g., for modeling faulty systems. We present a formal semantics for UML state machines enriched with an operator persistent choice that models persistent nondeterminism. This semantics is based on abstract models - μ-automata with a novel refinement relation - and a sound three-valued satisfaction relation for properties expressed in the μ-calculus. © 2009 Elsevier B.V. All rights reserved
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