3,582 research outputs found
A conjugate gradient algorithm for the astrometric core solution of Gaia
The ESA space astrometry mission Gaia, planned to be launched in 2013, has
been designed to make angular measurements on a global scale with
micro-arcsecond accuracy. A key component of the data processing for Gaia is
the astrometric core solution, which must implement an efficient and accurate
numerical algorithm to solve the resulting, extremely large least-squares
problem. The Astrometric Global Iterative Solution (AGIS) is a framework that
allows to implement a range of different iterative solution schemes suitable
for a scanning astrometric satellite. In order to find a computationally
efficient and numerically accurate iteration scheme for the astrometric
solution, compatible with the AGIS framework, we study an adaptation of the
classical conjugate gradient (CG) algorithm, and compare it to the so-called
simple iteration (SI) scheme that was previously known to converge for this
problem, although very slowly. The different schemes are implemented within a
software test bed for AGIS known as AGISLab, which allows to define, simulate
and study scaled astrometric core solutions. After successful testing in
AGISLab, the CG scheme has been implemented also in AGIS. The two algorithms CG
and SI eventually converge to identical solutions, to within the numerical
noise (of the order of 0.00001 micro-arcsec). These solutions are independent
of the starting values (initial star catalogue), and we conclude that they are
equivalent to a rigorous least-squares estimation of the astrometric
parameters. The CG scheme converges up to a factor four faster than SI in the
tested cases, and in particular spatially correlated truncation errors are much
more efficiently damped out with the CG scheme.Comment: 24 pages, 16 figures. Accepted for publication in Astronomy &
Astrophysic
A census of Oph candidate members from Gaia DR2
The Ophiuchus cloud complex is one of the best laboratories to study the
earlier stages of the stellar and protoplanetary disc evolution. The wealth of
accurate astrometric measurements contained in the Gaia Data Release 2 can be
used to update the census of Ophiuchus member candidates. We seek to find
potential new members of Ophiuchus and identify those surrounded by a
circumstellar disc. We constructed a control sample composed of 188 bona fide
Ophiuchus members. Using this sample as a reference we applied three different
density-based machine learning clustering algorithms (DBSCAN, OPTICS, and
HDBSCAN) to a sample drawn from the Gaia catalogue centred on the Ophiuchus
cloud. The clustering analysis was applied in the five astrometric dimensions
defined by the three-dimensional Cartesian space and the proper motions in
right ascension and declination. The three clustering algorithms systematically
identify a similar set of candidate members in a main cluster with astrometric
properties consistent with those of the control sample. The increased
flexibility of the OPTICS and HDBSCAN algorithms enable these methods to
identify a secondary cluster. We constructed a common sample containing 391
member candidates including 166 new objects, which have not yet been discussed
in the literature. By combining the Gaia data with 2MASS and WISE photometry,
we built the spectral energy distributions from 0.5 to 22\microm for a subset
of 48 objects and found a total of 41 discs, including 11 Class II and 1 Class
III new discs. Density-based clustering algorithms are a promising tool to
identify candidate members of star forming regions in large astrometric
databases. If confirmed, the candidate members discussed in this work would
represent an increment of roughly 40% of the current census of Ophiuchus.Comment: A&A, Accepted. Abridged abstrac
Inhomogeneous contraction of interatomic distances in metallic clusters: Calculations for Csn and OCsn
The equilibrium geometrical structures of Csn and OCsn clusters have been obtained by a method
that, in the framework of density-functional theory, describes the ion-electron interaction by means of a
pseudopotential that is spherically averaged about the cluster center. In the size range studied (up to
n =78 and 70, respectively) the clusters present well-separated atomic layers for which the distances to
the two closest neighbors of each atom have been analyzed, showing that there is an inhomogeneous
shrinking of the geometrical structure, in the sense that the distances obtained for atoms in the inner layers
are lower than those for the outer ones. The analysis of the growing of the clusters suggests that the
equilibrium geometries are those for which any atom of the aggregate has its closest neighbor at a distance
lower than the nearest-neighbor distance of the pure bulk metal. For small (n †20) pure clusters,
geometries of high symmetry have been found, which are completely modified by the presence of the oxygen
impurity. A regular octahedron is formed around the oxygen atom in most cases
Gaia Data Processing Architecture
Gaia is ESA's ambitious space astrometry mission the main objective of which
is to astrometrically and spectro-photometrically map 1000 Million celestial
objects (mostly in our galaxy) with unprecedented accuracy. The announcement of
opportunity for the data processing will be issued by ESA late in 2006. The
Gaia Data Processing and Analysis Consortium (DPAC) has been formed recently
and is preparing an answer. The satellite will downlink close to 100 TB of raw
telemetry data over 5 years. To achieve its required accuracy of a few 10s of
Microarcsecond astrometry, a highly involved processing of this data is
required.
In addition to the main astrometric instrument Gaia will host a Radial
Velocity instrument, two low-resolution dispersers for multi-color photometry
and two Star Mappers. Gaia is a flying Giga Pixel camera. The various
instruments each require relatively complex processing while at the same time
being interdependent. We describe the overall composition of the DPAC and the
envisaged overall architecture of the Gaia data processing system. We shall
delve further into the core processing - one of the nine, so-called,
coordination units comprising the Gaia processing system.Comment: 10 Pages, 2 figures. To appear in ADASS XVI Proceeding
Absorption reconstruction improves biodistribution assessment of fluorescent nanoprobes using hybrid Fluorescence-mediated tomography
Aim: Fluorescence-mediated tomography (FMT) holds potential for accelerating diagnostic and theranostic drug development. However, for proper quantitative fluorescence reconstruction, knowledge on optical scattering and absorption, which are highly heterogeneous in different (mouse) tissues, is required. We here describe methods to assess these parameters using co-registered micro Computed Tomography (”CT) data and nonlinear whole-animal absorption reconstruction, and evaluate their importance for assessment of the biodistribution and target site accumulation of fluorophore-labeled drug delivery systems.\ud
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Methods: Besides phantoms with varying degrees of absorption, mice bearing A431 tumors were imaged 15 min and 48 h after i.v. injection of a fluorophore-labeled polymeric drug carrier (pHPMA-Dy750) using ”CT-FMT. The outer shape of mice and a scattering map were derived using automated segmentation of the ”CT data. Furthermore, a 3D absorption map was reconstructed from the trans-illumination data. We determined the absorption of five interactively segmented regions (heart, liver, kidney, muscle, tumor). Since blood is the main near-infrared absorber in vivo, the absorption was also estimated from the relative blood volume (rBV), determined by contrast-enhanced ”CT. We compared the reconstructed absorption with the rBV-based values and analyzed the effect of using the absorption map on the fluorescence reconstruction.\ud
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Results: Phantom experiments demonstrated that absorption reconstruction is possible and necessary for quantitative fluorescence reconstruction. In vivo, the reconstructed absorption showed high values in strongly blood-perfused organs such as the heart, liver and kidney. The absorption values correlated strongly with the rBV-based absorption values, confirming the accuracy of the absorption reconstruction. Usage of homogenous absorption instead of the reconstructed absorption map resulted in reduced values in the heart, liver and kidney, by factors of 3.5, 2.1 and 1.4, respectively. For muscle and subcutaneous tumors, which have a much lower rBV and absorption, absorption reconstruction was less important.\ud
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Conclusion: Quantitative whole-animal absorption reconstruction is possible and can be validated in vivo using the rBV. Usage of an absorption map is important when quantitatively assessing the biodistribution of fluorescently labeled drugs and drug delivery systems, to avoid a systematic underestimation of fluorescence in strongly absorbing organs, such as the heart, liver and kidney
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