42,140 research outputs found
Alternative Restart Strategies for CMA-ES
This paper focuses on the restart strategy of CMA-ES on multi-modal
functions. A first alternative strategy proceeds by decreasing the initial
step-size of the mutation while doubling the population size at each restart. A
second strategy adaptively allocates the computational budget among the restart
settings in the BIPOP scheme. Both restart strategies are validated on the BBOB
benchmark; their generality is also demonstrated on an independent real-world
problem suite related to spacecraft trajectory optimization
Developing of the smart textile for energy expenditure monitoring
Peer ReviewedPostprint (published version
Exploring jet-launching conditions for SFXTs
In the magneto-centrifugal mechanism for jet formation, accreting neutron
stars are assumed to produce relativistic jets only if their surface magnetic
field is weak enough ( G). However, the most common manifestation
of neutron stars are pulsars, whose magnetic field distribution peaks at G. If the neutron star magnetic field has at least this strength
at birth, it must decay considerably before jets can be launched in binary
systems. We study the magnetic field evolution of a neutron star that accretes
matter from the wind of a high-mass stellar companion so that we can constrain
the accretion rate and the impurities in the crust, which are necessary
conditions for jet formation. We solved the induction equation for the
diffusion and convection of the neutron star magnetic field confined to the
crust, assuming spherical accretion in a simpliflied one-dimensional treatment.
We incorporated state-of-the-art microphysics, including consistent thermal
evolution profiles, and assumed two different neutron star cooling scenarios
based on the superfluidity conditions at the core. We find that in this
scenario, magnetic field decay at long timescales is governed mainly by the
accretion rate, while the impurity content and thermal evolution of the neutron
star play a secondary role. For accretion rates
M yr, surface magnetic fields can decay up to four orders of
magnitude in 10 yr, which is the timescale imposed by the evolution
of the high-mass stellar companion in these systems. Based on these results, we
discuss the possibility of transient jet-launching in strong wind-accreting
high-mass binary systems like supergiant fast X-ray transients.Comment: 8 pages, 8 figures. Accepted for publication in A&
Enhancement of the critical temperature in iron-pnictide superconductors by finite size effects
Recent experiments have shown that, in agreement with previous theoretical
predictions, superconductivity in metallic nanostructures can be enhanced with
respect to the bulk limit. Motivated by these results we study finite size
effects (FSE) in an iron-pnictide superconductor. For realistic values of the
bulk critical temperature Tc ~ 20-50K, we find that, in the nanoscale region L
~ 10 nm, Tc(L) has a complicated oscillating pattern as a function of the
system size L. A substantial enhancement of Tc with respect to the bulk limit
is observed for different boundary conditions, geometries and two microscopic
models of superconductivity. Thermal fluctuations, which break long range
order, are still small in this region. Finally we show that the differential
conductance, an experimental observable, is also very sensitive to FSE.Comment: 4 pages, 3 figure
CIXL2: A Crossover Operator for Evolutionary Algorithms Based on Population Features
In this paper we propose a crossover operator for evolutionary algorithms
with real values that is based on the statistical theory of population
distributions. The operator is based on the theoretical distribution of the
values of the genes of the best individuals in the population. The proposed
operator takes into account the localization and dispersion features of the
best individuals of the population with the objective that these features would
be inherited by the offspring. Our aim is the optimization of the balance
between exploration and exploitation in the search process. In order to test
the efficiency and robustness of this crossover, we have used a set of
functions to be optimized with regard to different criteria, such as,
multimodality, separability, regularity and epistasis. With this set of
functions we can extract conclusions in function of the problem at hand. We
analyze the results using ANOVA and multiple comparison statistical tests. As
an example of how our crossover can be used to solve artificial intelligence
problems, we have applied the proposed model to the problem of obtaining the
weight of each network in a ensemble of neural networks. The results obtained
are above the performance of standard methods
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