506 research outputs found
The inner dark matter distribution of the Cosmic Horseshoe (J1148+1930) with gravitational lensing and dynamics
We present a detailed analysis of the inner mass structure of the Cosmic
Horseshoe (J1148+1930) strong gravitational lens system observed with the
Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3). In addition to the
spectacular Einstein ring, this systems shows a radial arc. We obtained the
redshift of the radial arc counter image from
Gemini observations. To disentangle the dark and luminous matter, we consider
three different profiles for the dark matter distribution: a power-law profile,
the NFW, and a generalized version of the NFW profile. For the luminous matter
distribution, we base it on the observed light distribution that is fitted with
three components: a point mass for the central light component resembling an
active galactic nucleus, and the remaining two extended light components scaled
by a constant M/L. To constrain the model further, we include published
velocity dispersion measurements of the lens galaxy and perform a
self-consistent lensing and axisymmetric Jeans dynamical modeling. Our model
fits well to the observations including the radial arc, independent of the dark
matter profile. Depending on the dark matter profile, we get a dark matter
fraction between 60 % and 70 %. With our composite mass model we find that the
radial arc helps to constrain the inner dark matter distribution of the Cosmic
Hoseshoe independently of the dark matter profile.Comment: 19 pages, 14 figures, 8 tables, submitted to A&
Silicon-on ceramic process: Silicon sheet growth and device development for the large-area silicon sheet task of the low-cost solar array project
The technical feasibility of producing solar-cell-quality sheet silicon to meet the Department of Energy (DOE) 1986 overall price goal of $0.70/watt was investigated. With the silicon-on-ceramic (SOC) approach, a low-cost ceramic substrate is coated with large-grain polycrystalline silicon by unidirectional solidification of molten silicon. This effort was divided into several areas of investigation in order to most efficiently meet the goals of the program. These areas include: (1) dip-coating; (2) continuous coating designated SCIM-coating, and acronym for Silicon Coating by an Inverted Meniscus (SCIM); (3) material characterization; (4) cell fabrication and evaluation; and (5) theoretical analysis. Both coating approaches were successful in producing thin layers of large grain, solar-cell-quality silicon. The dip-coating approach was initially investigated and considerable effort was given to this technique. The SCIM technique was adopted because of its scale-up potential and its capability to produce more conventiently large areas of SOC
Silicon on ceramic process. Silicon sheet growth development for the large-area silicon sheet task of the low-cost silicon solar array project
The technical and economic feasibility of producing solar-cell-quality sheet silicon was investigated. The sheets were made by coating one surface of carbonized ceramic substrates with a thin layer of large-grain polycrystalline silicon from the melt. Significant progress was made in all areas of the program
Dip-coating process: Silicon sheet growth development for the large-area silicon sheet task of the low-cost silicon solar array project
The objective of this research program is to investigate the technical and economic feasibility of producing solar-cell-quality sheet silicon by coating one surface of carbonized ceramic substrates with a thin layer of large-grain polycrystalline silicon from the melt. The past quarter demonstrated significant progress in several areas. Seeded growth of silicon-on-ceramic (SOC) with an EFG ribbon seed was demonstrated. Different types of mullite were successfully coated with silicon. A new method of deriving minority carrier diffusion length, L sub n from spectral response measurements was evaluated. ECOMOD cost projections were found to be in good agreement with the interim SAMIS method proposed by JPL. On the less positive side, there was a decrease in cell performance which we believe to be due to an unidentified source of impurities
HOLISMOKES -- X. Comparison between neural network and semi-automated traditional modeling of strong lenses
Modeling of strongly gravitationally lensed galaxies is often required in
order to use them as astrophysical or cosmological probes. With current and
upcoming wide-field imaging surveys, the number of detected lenses is
increasing significantly such that automated and fast modeling procedures for
ground-based data are urgently needed. This is especially pertinent to
short-lived lensed transients in order to plan follow-up observations.
Therefore, we present in a companion paper (submitted) a neural network
predicting the parameter values with corresponding uncertainties of a Singular
Isothermal Ellipsoid (SIE) mass profile with external shear. In this work, we
present a newly-developed pipeline glee_auto.py to model consistently any
galaxy-scale lensing system. In contrast to previous automated modeling
pipelines that require high-resolution images, glee_auto.py is optimized for
ground-based images such as those from the Hyper-Suprime-Cam (HSC) or the
upcoming Rubin Observatory Legacy Survey of Space and Time. We further present
glee_tools.py, a flexible automation code for individual modeling that has no
direct decisions and assumptions implemented. Both pipelines, in addition to
our modeling network, minimize the user input time drastically and thus are
important for future modeling efforts. We apply the network to 31 real
galaxy-scale lenses of HSC and compare the results to the traditional models.
In the direct comparison, we find a very good match for the Einstein radius
especially for systems with ". The lens mass center and
ellipticity show reasonable agreement. The main discrepancies are on the
external shear as expected from our tests on mock systems. In general, our
study demonstrates that neural networks are a viable and ultra fast approach
for measuring the lens-galaxy masses from ground-based data in the upcoming era
with lenses expected.Comment: 17+28 pages, 7+31 figures, 2+5 tables, submitted to A&
Silicon on Ceramic Process: Silicon Sheet Growth and Device Development for the Large-area Silicon Sheet and Cell Development Tasks of the Low-cost Solar Array Project
The technical and economic feasibility of producing solar cell quality sheet silicon was investigated. It was hoped this could be done by coating one surface of carbonized ceramic substrates with a thin layer of large-grain polycrystalline silicon from the melt. Work was directed towards the solution of unique cell processing/design problems encountered with the silicon-ceramic (SOC) material due to its intimate contact with the ceramic substrate. Significant progress was demonstrated in the following areas; (1) the continuous coater succeeded in producing small-area coatings exhibiting unidirectional solidification and substatial grain size; (2) dip coater succeeded in producing thick (more than 500 micron) dendritic layers at coating speeds of 0.2-0.3 cm/sec; and (3) a standard for producing total area SOC solar cells using slotted ceramic substrates was developed
Silicon-on-ceramic process: Silicon sheet growth and device development for the large-area silicon sheet task of the low-cost solar array project
The technical feasibility of producing solar cell quality sheet silicon to meet the DOE 1986 cost goal of 70 cents/watt was investigated. The silicon on ceramic approach is to coat a low cost ceramic substrate with large grain polycrystalline silicon by unidirectional solidification of molten silicon. Results and accomplishments are summarized
HOLISMOKES -- IV. Efficient mass modeling of strong lenses through deep learning
Modelling the mass distributions of strong gravitational lenses is often
necessary to use them as astrophysical and cosmological probes. With the high
number of lens systems () expected from upcoming surveys, it is timely
to explore efficient modeling approaches beyond traditional MCMC techniques
that are time consuming. We train a CNN on images of galaxy-scale lenses to
predict the parameters of the SIE mass model (, and ).
To train the network, we simulate images based on real observations from the
HSC Survey for the lens galaxies and from the HUDF as lensed galaxies. We
tested different network architectures, the effect of different data sets, and
using different input distributions of . We find that the CNN
performs well and obtain with the network trained with a uniform distribution
of the following median values with scatter:
, ,
,
and . The bias in is driven by
systems with small . Therefore, when we further predict the multiple
lensed image positions and time delays based on the network output, we apply
the network to the sample limited to . In this case, the offset
between the predicted and input lensed image positions is
and for and ,
respectively. For the fractional difference between the predicted and true time
delay, we obtain . Our CNN is able to predict the SIE
parameters in fractions of a second on a single CPU and with the output we can
predict the image positions and time delays in an automated way, such that we
are able to process efficiently the huge amount of expected lens detections in
the near future.Comment: 17 pages, 14 Figure
Ready Student One: Exploring the predictors of student learning in virtual reality
Immersive virtual reality (VR) has enormous potential for education, but
classroom resources are limited. Thus, it is important to identify whether and
when VR provides sufficient advantages over other modes of learning to justify
its deployment. In a between-subjects experiment, we compared three methods of
teaching Moon phases (a hands-on activity, VR, and a desktop simulation) and
measured student improvement on existing learning and attitudinal measures.
While a substantial majority of students preferred the VR experience, we found
no significant differences in learning between conditions. However, we found
differences between conditions based on gender, which was highly correlated
with experience with video games. These differences may indicate certain groups
have an advantage in the VR setting.Comment: 28 pages, 7 figures, 4 tables. Published in PLOS ONE March 25, 202
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