24,637 research outputs found
Zeta measures and Thermodynamic Formalism for temperature zero
We address the analysis of the following problem: given a real H\"older
potential defined on the Bernoulli space and its equilibrium state,
it is known that this shift-invariant probability can be weakly approximated by
probabilities in periodic orbits associated to certain zeta functions. Given a
H\"older function and a value such that , we can associate a
shift-invariant probability such that for each continuous function
we have where is the pressure of , is
the set of solutions of , for any , and
We
call a zeta probability for and . It is known that , when . We consider for each value the potential
and the corresponding equilibrium state . What happens with
when goes to infinity and goes to one? This question is
related to the problem of how to approximate the maximizing probability for
by probabilities on periodic orbits. We study this question and also present
here the deviation function and Large Deviation Principle for this limit
. We will make an assumption: . We do not assume here the maximizing probability for is
unique
Pseudo-Supersymmetry and the Domain-Wall/Cosmology Correspondence
The correspondence between domain-wall and cosmological solutions of gravity
coupled to scalar fields is explained. Any domain wall solution that admits a
Killing spinor is shown to correspond to a cosmology that admits a
pseudo-Killing spinor: whereas the Killing spinor obeys a Dirac-type equation
with hermitian `mass'-matrix, the corresponding pseudo-Killing spinor obeys a
Dirac-type equation with a anti-hermitian `mass'-matrix. We comment on some
implications of (pseudo)supersymmetry.Comment: 11 pages, contribution to the proceedings of IRGAC 2006;v3: minor
change
SourcererCC: Scaling Code Clone Detection to Big Code
Despite a decade of active research, there is a marked lack in clone
detectors that scale to very large repositories of source code, in particular
for detecting near-miss clones where significant editing activities may take
place in the cloned code. We present SourcererCC, a token-based clone detector
that targets three clone types, and exploits an index to achieve scalability to
large inter-project repositories using a standard workstation. SourcererCC uses
an optimized inverted-index to quickly query the potential clones of a given
code block. Filtering heuristics based on token ordering are used to
significantly reduce the size of the index, the number of code-block
comparisons needed to detect the clones, as well as the number of required
token-comparisons needed to judge a potential clone.
We evaluate the scalability, execution time, recall and precision of
SourcererCC, and compare it to four publicly available and state-of-the-art
tools. To measure recall, we use two recent benchmarks, (1) a large benchmark
of real clones, BigCloneBench, and (2) a Mutation/Injection-based framework of
thousands of fine-grained artificial clones. We find SourcererCC has both high
recall and precision, and is able to scale to a large inter-project repository
(250MLOC) using a standard workstation.Comment: Accepted for publication at ICSE'16 (preprint, unrevised
Neural networks with dynamical synapses: from mixed-mode oscillations and spindles to chaos
Understanding of short-term synaptic depression (STSD) and other forms of
synaptic plasticity is a topical problem in neuroscience. Here we study the
role of STSD in the formation of complex patterns of brain rhythms. We use a
cortical circuit model of neural networks composed of irregular spiking
excitatory and inhibitory neurons having type 1 and 2 excitability and
stochastic dynamics. In the model, neurons form a sparsely connected network
and their spontaneous activity is driven by random spikes representing synaptic
noise. Using simulations and analytical calculations, we found that if the STSD
is absent, the neural network shows either asynchronous behavior or regular
network oscillations depending on the noise level. In networks with STSD,
changing parameters of synaptic plasticity and the noise level, we observed
transitions to complex patters of collective activity: mixed-mode and spindle
oscillations, bursts of collective activity, and chaotic behaviour.
Interestingly, these patterns are stable in a certain range of the parameters
and separated by critical boundaries. Thus, the parameters of synaptic
plasticity can play a role of control parameters or switchers between different
network states. However, changes of the parameters caused by a disease may lead
to dramatic impairment of ongoing neural activity. We analyze the chaotic
neural activity by use of the 0-1 test for chaos (Gottwald, G. & Melbourne, I.,
2004) and show that it has a collective nature.Comment: 7 pages, Proceedings of 12th Granada Seminar, September 17-21, 201
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