10,486 research outputs found
Global persistence exponent of the double-exchange model
We obtained the global persistence exponent for a continuous spin
model on the simple cubic lattice with double-exchange interaction by using two
different methods. First, we estimated the exponent by following the
time evolution of probability that the order parameter of the model does
not change its sign up to time . Afterwards,
that exponent was estimated through the scaling collapse of the universal
function for different lattice sizes. Our results for
both approaches are in very good agreement each other.Comment: 4 pages, 3 figures, and 3 tables. To appear in Physical Review
Short-time behavior of a classical ferromagnet with double-exchange interaction
We investigate the critical dynamics of a classical ferromagnet on the simple
cubic lattice with double-exchange interaction. Estimates for the dynamic
critical exponents and are obtained using short-time Monte Carlo
simulations. We also estimate the static critical exponents and
studying the behavior of the samples at an early time. Our results are in good
agreement with available estimates and support the assertion that this model
and the classical Heisenberg model belong to the same universality class
Recording from two neurons: second order stimulus reconstruction from spike trains and population coding
We study the reconstruction of visual stimuli from spike trains, recording
simultaneously from the two H1 neurons located in the lobula plate of the fly
Chrysomya megacephala. The fly views two types of stimuli, corresponding to
rotational and translational displacements. If the reconstructed stimulus is to
be represented by a Volterra series and correlations between spikes are to be
taken into account, first order expansions are insufficient and we have to go
to second order, at least. In this case higher order correlation functions have
to be manipulated, whose size may become prohibitively large. We therefore
develop a Gaussian-like representation for fourth order correlation functions,
which works exceedingly well in the case of the fly. The reconstructions using
this Gaussian-like representation are very similar to the reconstructions using
the experimental correlation functions. The overall contribution to rotational
stimulus reconstruction of the second order kernels - measured by a chi-squared
averaged over the whole experiment - is only about 8% of the first order
contribution. Yet if we introduce an instant-dependent chi-square to measure
the contribution of second order kernels at special events, we observe an up to
100% improvement. As may be expected, for translational stimuli the
reconstructions are rather poor. The Gaussian-like representation could be a
valuable aid in population coding with large number of neurons
Long Term Variability of SDSS Quasars
We use a sample of 3791 quasars from the Sloan Digital Sky Survey (SDSS)
Early Data Release (EDR), and compare their photometry to historic plate
material for the same set of quasars in order to study their variability
properties. The time base-line we attain this way ranges from a few months to
up to 50 years. In contrast to monitoring programs, where relatively few
quasars are photometrically measured over shorter time periods, we utilize
existing databases to extend this base-line as much as possible, at the cost of
sampling per quasar. Our method, however, can easily be extended to much larger
samples. We construct variability Structure Functions and compare these to the
literature and model functions. From our modeling we conclude that 1) quasars
are more variable toward shorter wavelengths, 2) their variability is
consistent with an exponentially decaying light-curve with a typical time-scale
of ~2 years, 3) these outbursts occur on typical time-scales of ~200 years.
With the upcoming first data release of the SDSS, a much larger quasar sample
can be used to put these conclusions on a more secure footing.Comment: 16 pages, accepted for publication in AJ, Sept issu
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