106,520 research outputs found
Approximating Optimal Bounds in Prompt-LTL Realizability in Doubly-exponential Time
We consider the optimization variant of the realizability problem for Prompt
Linear Temporal Logic, an extension of Linear Temporal Logic (LTL) by the
prompt eventually operator whose scope is bounded by some parameter. In the
realizability optimization problem, one is interested in computing the minimal
such bound that allows to realize a given specification. It is known that this
problem is solvable in triply-exponential time, but not whether it can be done
in doubly-exponential time, i.e., whether it is just as hard as solving LTL
realizability.
We take a step towards resolving this problem by showing that the optimum can
be approximated within a factor of two in doubly-exponential time. Also, we
report on a proof-of-concept implementation of the algorithm based on bounded
LTL synthesis, which computes the smallest implementation of a given
specification. In our experiments, we observe a tradeoff between the size of
the implementation and the bound it realizes. We investigate this tradeoff in
the general case and prove upper bounds, which reduce the search space for the
algorithm, and matching lower bounds.Comment: In Proceedings GandALF 2016, arXiv:1609.0364
The lid method for exhaustive exploration of metastable states of complex systems
The `lid' algorithm performs an exhaustive exploration of neighborhoods of
local energy minima of energy landscapes. This paper describes an
implementation of the algorithm, including issues of parallel performance and
scalability. To illustrate the versatility of the approach and to stress the
common features present in landscapes of quite different systems, we present
selected results for 1) a spin glass, 2) a ferromagnet, 3) a covalent network
model for glassy systems, and 4) a polymer. The exponential nature of the local
density of states found in these systems and its relation to the ordering
transition is briefly commented upon.Comment: RevTeX, 11 pages, 1 figur
SlowFuzz: Automated Domain-Independent Detection of Algorithmic Complexity Vulnerabilities
Algorithmic complexity vulnerabilities occur when the worst-case time/space
complexity of an application is significantly higher than the respective
average case for particular user-controlled inputs. When such conditions are
met, an attacker can launch Denial-of-Service attacks against a vulnerable
application by providing inputs that trigger the worst-case behavior. Such
attacks have been known to have serious effects on production systems, take
down entire websites, or lead to bypasses of Web Application Firewalls.
Unfortunately, existing detection mechanisms for algorithmic complexity
vulnerabilities are domain-specific and often require significant manual
effort. In this paper, we design, implement, and evaluate SlowFuzz, a
domain-independent framework for automatically finding algorithmic complexity
vulnerabilities. SlowFuzz automatically finds inputs that trigger worst-case
algorithmic behavior in the tested binary. SlowFuzz uses resource-usage-guided
evolutionary search techniques to automatically find inputs that maximize
computational resource utilization for a given application.Comment: ACM CCS '17, October 30-November 3, 2017, Dallas, TX, US
An Introduction to Quantum Computing for Non-Physicists
Richard Feynman's observation that quantum mechanical effects could not be
simulated efficiently on a computer led to speculation that computation in
general could be done more efficiently if it used quantum effects. This
speculation appeared justified when Peter Shor described a polynomial time
quantum algorithm for factoring integers.
In quantum systems, the computational space increases exponentially with the
size of the system which enables exponential parallelism. This parallelism
could lead to exponentially faster quantum algorithms than possible
classically. The catch is that accessing the results, which requires
measurement, proves tricky and requires new non-traditional programming
techniques.
The aim of this paper is to guide computer scientists and other
non-physicists through the conceptual and notational barriers that separate
quantum computing from conventional computing. We introduce basic principles of
quantum mechanics to explain where the power of quantum computers comes from
and why it is difficult to harness. We describe quantum cryptography,
teleportation, and dense coding. Various approaches to harnessing the power of
quantum parallelism are explained, including Shor's algorithm, Grover's
algorithm, and Hogg's algorithms. We conclude with a discussion of quantum
error correction.Comment: 45 pages. To appear in ACM Computing Surveys. LATEX file. Exposition
improved throughout thanks to reviewers' comment
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