53 research outputs found
Fast and Reliable Time Delay Estimation of Strong Lens Systems Using Method of Smoothing and Cross-Correlation
The observable time delays between the multiple images of strong lensing
systems with time variable sources can provide us with some valuable
information to probe the expansion history of the Universe. Estimation of these
time delays can be very challenging due to complexities of the observed data
where there are seasonal gaps, various noises and systematics such as unknown
microlensing effects. In this paper we introduce a novel approach to estimate
the time delays for strong lensing systems implementing various statistical
methods of data analysis including the method of smoothing and
cross-correlation. The method we introduce in this paper has been recently used
in TDC0 and TDC1 Strong Lens Time Delay Challenges and has shown its power in
reliable and precise estimation of time delays dealing with data with different
complexities.Comment: 23 pages, 9 figures, 3 tables, discussions extended, references
added, results unchanged, matches final version published in Ap
Unveiling acoustic physics of the CMB using nonparametric estimation of the temperature angular power spectrum for Planck
Estimation of the angular power spectrum is one of the important steps in
Cosmic Microwave Background (CMB) data analysis. Here, we present a
nonparametric estimate of the temperature angular power spectrum for the Planck
2013 CMB data. The method implemented in this work is model-independent, and
allows the data, rather than the model, to dictate the fit. Since one of the
main targets of our analysis is to test the consistency of the CDM
model with Planck 2013 data, we use the nuisance parameters associated with the
best-fit CDM angular power spectrum to remove foreground contributions
from the data at multipoles . We thus obtain a combined angular
power spectrum data set together with the full covariance matrix, appropriately
weighted over frequency channels. Our subsequent nonparametric analysis
resolves six peaks (and five dips) up to in the temperature
angular power spectrum. We present uncertainties in the peak/dip locations and
heights at the confidence level. We further show how these reflect the
harmonicity of acoustic peaks, and can be used for acoustic scale estimation.
Based on this nonparametric formalism, we found the best-fit CDM model
to be at confidence distance from the center of the nonparametric
confidence set -- this is considerably larger than the confidence distance
() derived earlier from a similar analysis of the WMAP 7-year data.
Another interesting result of our analysis is that at low multipoles, the
Planck data do not suggest any upturn, contrary to the expectation based on the
integrated Sachs-Wolfe contribution in the best-fit CDM cosmology.Comment: 15 pages, 8 figures, 2 table
Evolution of the Cosmic Microwave Background power spectrum across Wilkinson Microwave Anisotropy Probe data releases: A nonparametric analysis
Using a nonparametric function estimation methodology, we present a comparative analysis of the Wilkinson Microwave Anisotropy Probe (WMAP) 1-, 3-, 5-, and 7-year data releases for the cosmic microwave background (CMB) angular power spectrum with respect to the following key questions. (1) How well is the power spectrum determined by the data alone? (2) How well is the ÎCDM model supported by a model-independent, data-driven analysis? (3) What are the realistic uncertainties on peak/dip locations and heights? Our results show that the height of the power spectrum is well determined by data alone for multipole l approximately less than 546 (1-year), 667 (3-year), 804 (5-year), and 842 (7-year data). We show that parametric fits based on the ÎCDM model are remarkably close to our nonparametric fits in l-regions where data are sufficiently precise. In contrast, the power spectrum for an HÎCDM model is progressively pushed away from our nonparametric fit as data quality improves with successive data realizations, suggesting incompatibility of this particular cosmological model with respect to the WMAP data sets. We present uncertainties on peak/dip locations and heights at the 95% (2Ï) level of confidence and show how these uncertainties translate into hyperbolic "bands" on the acoustic scale (lA ) and peak shift (Φ
m ) parameters. Based on the confidence set for the 7-year data, we argue that the low-l upturn in the CMB power spectrum cannot be ruled out at any confidence level in excess of about 10% (â0.12Ï). Additional outcomes of this work are a numerical formulation for minimization of a noise-weighted risk function subject to monotonicity constraints, a prescription for obtaining nonparametric fits that are closer to cosmological expectations on smoothness, and a method for sampling cosmologically meaningful power spectrum variations from the confidence set of a nonparametric fit
Examining the role of export competitive advantages on export performance
This paper investigates the role of export competitive advantage on export performance in food industry. The proposed study designs a questionnaire in Likert scale and distributes it among 280 randomly selected experts in food industry and Cronbach alpha has been calculated as 0.827. The study has applied factor analysis to find important factors influencing export performance. Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Bartlett's Test of Sphericity have been performed to validate the results and they both validated the questionnaire. The results of the survey have determined six effective groups including product development, e-commerce, marketing planning, organizational performance, competitiveness and supply chain management
Evolution of the CMB Power Spectrum Across WMAP Data Releases: A Nonparametric Analysis
Using a nonparametric function estimation methodology, we present a
comparative analysis of the WMAP 1-, 3-, 5-, and 7-year data releases for the
CMB angular power spectrum with respect to the following key questions: (a) How
well is the power spectrum determined by the data alone? (b) How well is the
CDM model supported by a model-independent, data-driven analysis? (c)
What are the realistic uncertainties on peak/dip locations and heights? Our
results show that the height of the power spectrum is well determined by data
alone for multipole l approximately less than 546 (1-year), 667 (3-year), 804
(5-year), and 842 (7-year data). We show that parametric fits based on the
CDM model are remarkably close to our nonparametric fits in
-regions where data are sufficiently precise. In contrast, the power
spectrum for an HCDM model gets progressively pushed away from our
nonparametric fit as data quality improves with successive data realizations,
suggesting incompatibility of this particular cosmological model with respect
to the WMAP data sets. We present uncertainties on peak/dip locations and
heights at the 95% () level of confidence, and show how these
uncertainties translate into hyperbolic "bands" on the acoustic scale ()
and peak shift () parameters. Based on the confidence set for the
7-year data, we argue that the low-l up-turn in the CMB power spectrum cannot
be ruled out at any confidence level in excess of about 10% (). Additional outcomes of this work are a numerical formulation for
minimization of a noise-weighted risk function subject to monotonicity
constraints, a prescription for obtaining nonparametric fits that are closer to
cosmological expectations on smoothness, and a method for sampling
cosmologically meaningful power spectrum variations from the confidence set of
a nonparametric fit
The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment
The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014â2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V
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