4,060 research outputs found
A novel laser ranging system for measurement of ground-to-satellite distances
A technique was developed for improving the precision of laser ranging measurements of ground-to-satellite distances. The method employs a mode-locked laser transmitter and utilizes an image converter tube equipped with deflection plates in measuring the time of flight of the laser pulse to a distant retroreflector and back. Samples of the outgoing and returning light pulses are focussed on the photocathode of the image converter tube, whose deflection plates are driven by a high-voltage 120 MHz sine wave derived from a very stable oscillator. From the relative positions of the images produced at the output phosphor by the two light pulses, it is possible to make a precise determination of the fractional amount by which the time of flight exceeds some large integral multiple of the period of the deflection sinusoid
Unsupervised machine learning of integrated health and social care data from the Macmillan Improving the Cancer Journey service in Glasgow
Background: Improving the Cancer Journey (ICJ) was launched in 2014 by Glasgow City Council and Macmillan Cancer Support. As part of routine service, data is collected on ICJ users including demographic and health information, results from holistic needs assessments and quality of life scores as measured by EQ-5D health status. There is also data on the number and type of referrals made and feedback from users on the overall service. By applying artificial intelligence and interactive visualization technologies to this data, we seek to improve service provision and optimize resource allocation.Method: An unsupervised machine-learning algorithm was deployed to cluster the data. The classical k-means algorithm was extended with the k-modes technique for categorical data, and the gap heuristic automatically identified the number of clusters. The resulting clusters are used to summarize complex data sets and produce three-dimensional visualizations of the data landscape. Furthermore, the traits of new ICJ clients are predicted by approximately matching their details to the nearest existing cluster center.Results: Cross-validation showed the model’s effectiveness over a wide range of traits. For example, the model can predict marital status, employment status and housing type with an accuracy between 2.4 to 4.8 times greater than random selection. One of the most interesting preliminary findings is that area deprivation (measured through Scottish Index of Multiple Deprivation-SIMD) is a better predictor of an ICJ client’s needs than primary diagnosis (cancer type).Conclusion: A key strength of this system is its ability to rapidly ingest new data on its own and derive new predictions from those data. This means the model can guide service provision by forecasting demand based on actual or hypothesized data. The aim is to provide intelligent person-centered recommendations. The machine-learning model described here is part of a prototype software tool currently under development for use by the cancer support community.Disclosure: Funded by Macmillan Cancer Support</p
Dynamical elastic bodies in Newtonian gravity
Well-posedness for the initial value problem for a self-gravitating elastic
body with free boundary in Newtonian gravity is proved. In the material frame,
the Euler-Lagrange equation becomes, assuming suitable constitutive properties
for the elastic material, a fully non-linear elliptic-hyperbolic system with
boundary conditions of Neumann type. For systems of this type, the initial data
must satisfy compatibility conditions in order to achieve regular solutions.
Given a relaxed reference configuration and a sufficiently small Newton's
constant, a neigborhood of initial data satisfying the compatibility conditions
is constructed
Brown dwarf census with the Dark Energy Survey year 3 data and the thin disc scale height of early L types
27 pages, 18 figuresIn this paper we present a catalogue of 11 745 brown dwarfs with spectral types ranging from L0 to T9, photometrically classified using data from the Dark Energy Survey (DES) year 3 release matched to the Vista Hemisphere Survey (VHS) DR3 and Wide-field Infrared Survey Explorer (WISE) data, covering ≈2400 deg2 up to iAB = 22. The classification method follows the same phototype method previously applied to SDSS-UKIDSS-WISE data. The most significant difference comes from the use of DES data instead of SDSS, which allow us to classify almost an order of magnitude more brown dwarfs than any previous search and reaching distances beyond 400 pc for the earliest types. Next, we also present and validate the GalmodBD simulation, which produces brown dwarf number counts as a function of structural parameters with realistic photometric properties of a given survey. We use this simulation to estimate the completeness and purity of our photometric LT catalogue down to iAB = 22, as well as to compare to the observed number of LT types. We put constraints on the thin disc scale height for the early L (L0–L3) population to be around 450 pc, in agreement with previous findings. For completeness, we also publish in a separate table a catalogue of 20 863 M dwarfs that passed our colour cut with spectral types greater than M6. Both the LT and the late M catalogues are found at DES release page https://des.ncsa.illinois.edu/releases/other/y3-mlt.Peer reviewedFinal Published versio
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
COSMOGRAIL XVI: Time delays for the quadruply imaged quasar DES J0408-5354 with high-cadence photometric monitoring
We present time-delay measurements for the new quadruply imaged quasar DES
J0408-5354, the first quadruply imaged quasar found in the Dark Energy Survey
(DES). Our result is made possible by implementing a new observational strategy
using almost daily observations with the MPIA 2.2m telescope at La Silla
observatory and deep exposures reaching a signal-to-noise ratio of about 1000
per quasar image. This data quality allows us to catch small photometric
variations (a few mmag rms) of the quasar, acting on temporal scales much
shorter than microlensing, hence making the time delay measurement very robust
against microlensing. In only 7 months we measure very accurately one of the
time delays in DES J0408-5354: Dt(AB) = -112.1 +- 2.1 days (1.8%) using only
the MPIA 2.2m data. In combination with data taken with the 1.2m Euler Swiss
telescope, we also measure two delays involving the D component of the system
Dt(AD) = -155.5 +- 12.8 days (8.2%) and Dt(BD) = -42.4 +- 17.6 days (41%),
where all the error bars include systematics. Turning these time delays into
cosmological constraints will require deep HST imaging or ground-based Adaptive
Optics (AO), and information on the velocity field of the lensing galaxy.Comment: 9 pages, 5 figures, accepted for publication in Astronomy &
Astrophysic
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H0LiCOW X: Spectroscopic/imaging survey and galaxy-group identification around the strong gravitational lens system WFI2033-4723
Galaxies and galaxy groups located along the line of sight towards
gravitationally lensed quasars produce high-order perturbations of the
gravitational potential at the lens position. When these perturbation are too
large, they can induce a systematic error on of a few-percent if the lens
system is used for cosmological inference and the perturbers are not explicitly
accounted for in the lens model. In this work, we present a detailed
characterization of the environment of the lens system WFI2033-4723 (, = 0.6575), one of the core targets of the H0LICOW
project for which we present cosmological inferences in a companion paper (Rusu
et al. 2019). We use the Gemini and ESO-Very Large telescopes to measure the
spectroscopic redshifts of the brightest galaxies towards the lens, and use the
ESO-MUSE integral field spectrograph to measure the velocity-dispersion of the
lens ( km/s) and of several nearby
galaxies. In addition, we measure photometric redshifts and stellar masses of
all galaxies down to mag, mainly based on Dark Energy Survey imaging
(DR1). Our new catalog, complemented with literature data, more than doubles
the number of known galaxy spectroscopic redshifts in the direct vicinity of
the lens, expanding to 116 (64) the number of spectroscopic redshifts for
galaxies separated by less than 3 arcmin (2 arcmin) from the lens. Using the
flexion-shift as a measure of the amplitude of the gravitational perturbation,
we identify 2 galaxy groups and 3 galaxies that require specific attention in
the lens models. The ESO MUSE data enable us to measure the
velocity-dispersions of three of these galaxies. These results are essential
for the cosmological inference analysis presented in Rusu et al. (2019).Comment: Matches the version accepted for publication by MNRAS. Note that this
paper previously appeared as H0LICOW X
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