12,744 research outputs found
Statistical Searches for Microlensing Events in Large, Non-Uniformly Sampled Time-Domain Surveys: A Test Using Palomar Transient Factory Data
Many photometric time-domain surveys are driven by specific goals, such as
searches for supernovae or transiting exoplanets, which set the cadence with
which fields are re-imaged. In the case of the Palomar Transient Factory (PTF),
several sub-surveys are conducted in parallel, leading to non-uniform sampling
over its footprint. While the median PTF field has been imaged 40 times in \textit{R}-band,
have been observed 100 times. We use PTF data to
study the trade-off between searching for microlensing events in a survey whose
footprint is much larger than that of typical microlensing searches, but with
far-from-optimal time sampling. To examine the probability that microlensing
events can be recovered in these data, we test statistics used on uniformly
sampled data to identify variables and transients. We find that the von Neumann
ratio performs best for identifying simulated microlensing events in our data.
We develop a selection method using this statistic and apply it to data from
fields with 10 -band observations, light curves,
uncovering three candidate microlensing events. We lack simultaneous,
multi-color photometry to confirm these as microlensing events. However, their
number is consistent with predictions for the event rate in the PTF footprint
over the survey's three years of operations, as estimated from near-field
microlensing models. This work can help constrain all-sky event rate
predictions and tests microlensing signal recovery in large data sets, which
will be useful to future time-domain surveys, such as that planned with the
Large Synoptic Survey Telescope.Comment: 13 pages, 14 figures; accepted for publication in ApJ. fixed author
lis
Detection of leaf structures in close-range hyperspectral images using morphological fusion
Close-range hyperspectral images are a promising source of information in plant biology, in particular, for in vivo study of physiological changes. In this study, we investigate how data fusion can improve the detection of leaf elements by combining pixel reflectance and morphological information. The detection of image regions associated to the leaf structures is the first step toward quantitative analysis on the physical effects that genetic manipulation, disease infections, and environmental conditions have in plants. We tested our fusion approach on Musa acuminata (banana) leaf images and compared its discriminant capability to similar techniques used in remote sensing. Experimental results demonstrate the efficiency of our fusion approach, with significant improvements over some conventional methods
Three-Dimensional Spectral Classification of Low-Metallicity Stars Using Artificial Neural Networks
We explore the application of artificial neural networks (ANNs) for the
estimation of atmospheric parameters (Teff, logg, and [Fe/H]) for Galactic F-
and G-type stars. The ANNs are fed with medium-resolution (~ 1-2 A) non
flux-calibrated spectroscopic observations. From a sample of 279 stars with
previous high-resolution determinations of metallicity, and a set of (external)
estimates of temperature and surface gravity, our ANNs are able to predict Teff
with an accuracy of ~ 135-150 K over the range 4250 <= Teff <= 6500 K, logg
with an accuracy of ~ 0.25-0.30 dex over the range 1.0 <= logg <= 5.0 dex, and
[Fe/H] with an accuracy ~ 0.15-0.20 dex over the range -4.0 <= [Fe/H] <= +0.3.
Such accuracies are competitive with the results obtained by fine analysis of
high-resolution spectra. It is noteworthy that the ANNs are able to obtain
these results without consideration of photometric information for these stars.
We have also explored the impact of the signal-to-noise ratio (S/N) on the
behavior of ANNs, and conclude that, when analyzed with ANNs trained on spectra
of commensurate S/N, it is possible to extract physical parameter estimates of
similar accuracy with stellar spectra having S/N as low as 13. Taken together,
these results indicate that the ANN approach should be of primary importance
for use in present and future large-scale spectroscopic surveys.Comment: 51 pages, 11 eps figures, uses aastex; to appear in Ap
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