641 research outputs found
Heavy Quarkonium Potential Model and the State of Charmonium
A theoretical explanation of the observed splittings among the P~states of
charmonium is given with the use of a nonsingular potential model for heavy
quarkonia. We also show that the recently observed mass difference between the
center of gravity of the states and the state of
does not provide a direct test of the color hyperfine interaction in heavy
quarkonia. Our theoretical value for the mass of the state is in
agreement with the experimental result, and its E1 transition width is
341.8~keV. The mass of the state is predicted to be 3622.3~MeV.Comment: 15 page REVTEX documen
Observation of Coherent Elastic Neutrino-Nucleus Scattering
The coherent elastic scattering of neutrinos off nuclei has eluded detection
for four decades, even though its predicted cross-section is the largest by far
of all low-energy neutrino couplings. This mode of interaction provides new
opportunities to study neutrino properties, and leads to a miniaturization of
detector size, with potential technological applications. We observe this
process at a 6.7-sigma confidence level, using a low-background, 14.6-kg
CsI[Na] scintillator exposed to the neutrino emissions from the Spallation
Neutron Source (SNS) at Oak Ridge National Laboratory. Characteristic
signatures in energy and time, predicted by the Standard Model for this
process, are observed in high signal-to-background conditions. Improved
constraints on non-standard neutrino interactions with quarks are derived from
this initial dataset
Transfer learning for galaxy morphology from one survey to another
© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of 5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ( 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies (500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio
Photometric redshifts and clustering of emission line galaxies selected jointly by DES and eBOSS
We present the results of the first test plates of the extended Baryon
Oscillation Spectroscopic Survey. This paper focuses on the emission line
galaxies (ELG) population targetted from the Dark Energy Survey (DES)
photometry. We analyse the success rate, efficiency, redshift distribution, and
clustering properties of the targets. From the 9000 spectroscopic redshifts
targetted, 4600 have been selected from the DES photometry. The total success
rate for redshifts between 0.6 and 1.2 is 71\% and 68\% respectively for a
bright and faint, on average more distant, samples including redshifts measured
from a single strong emission line. We find a mean redshift of 0.8 and 0.87,
with 15 and 13\% of unknown redshifts respectively for the bright and faint
samples. In the redshift range 0.6<z<1.2, for the most secure spectroscopic
redshifts, the mean redshift for the bright and faint sample is 0.85 and 0.9
respectively. Star contamination is lower than 2\%. We measure a galaxy bias
averaged on scales of 1 and 10~Mpc/h of 1.72 \pm 0.1 for the bright sample and
of 1.78 \pm 0.12 for the faint sample. The error on the galaxy bias have been
obtained propagating the errors in the correlation function to the fitted
parameters. This redshift evolution for the galaxy bias is in agreement with
theoretical expectations for a galaxy population with MB-5\log h < -21.0. We
note that biasing is derived from the galaxy clustering relative to a model for
the mass fluctuations. We investigate the quality of the DES photometric
redshifts and find that the outlier fraction can be reduced using a comparison
between template fitting and neural network, or using a random forest
algorithm
Astrometric calibration and performance of the Dark Energy Camera
We characterize the ability of the Dark Energy Camera (DECam) to perform
relative astrometry across its 500~Mpix, 3 deg^2 science field of view, and
across 4 years of operation. This is done using internal comparisons of ~4x10^7
measurements of high-S/N stellar images obtained in repeat visits to fields of
moderate stellar density, with the telescope dithered to move the sources
around the array. An empirical astrometric model includes terms for: optical
distortions; stray electric fields in the CCD detectors; chromatic terms in the
instrumental and atmospheric optics; shifts in CCD relative positions of up to
~10 um when the DECam temperature cycles; and low-order distortions to each
exposure from changes in atmospheric refraction and telescope alignment. Errors
in this astrometric model are dominated by stochastic variations with typical
amplitudes of 10-30 mas (in a 30 s exposure) and 5-10 arcmin coherence length,
plausibly attributed to Kolmogorov-spectrum atmospheric turbulence. The size of
these atmospheric distortions is not closely related to the seeing. Given an
astrometric reference catalog at density ~0.7 arcmin^{-2}, e.g. from Gaia, the
typical atmospheric distortions can be interpolated to 7 mas RMS accuracy (for
30 s exposures) with 1 arcmin coherence length for residual errors. Remaining
detectable error contributors are 2-4 mas RMS from unmodelled stray electric
fields in the devices, and another 2-4 mas RMS from focal plane shifts between
camera thermal cycles. Thus the astrometric solution for a single DECam
exposure is accurate to 3-6 mas (0.02 pixels, or 300 nm) on the focal plane,
plus the stochastic atmospheric distortion.Comment: Submitted to PAS
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