scholarly journals barry and the BAO model comparison

2020 ◽  
Vol 493 (3) ◽  
pp. 4078-4093 ◽  
Author(s):  
Samuel R Hinton ◽  
Cullan Howlett ◽  
Tamara M Davis
Keyword(s):  
Model Comparison ◽  
State Of The Art ◽  
Model Fitting ◽  
Power Spectra ◽  
Acoustic Oscillation ◽  
Effective Field ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
New Public ◽  
Sky Survey

ABSTRACT We compare the performance of four state-of-the-art models for extracting isotropic measurements of the baryon acoustic oscillation (BAO) scale. To do this, we created a new, public, modular code barry, which contains data sets, model fitting tools, and model implementations incorporating different descriptions of non-linear physics and algorithms for isolating the BAO feature. These are then evaluated for bias, correlation, and fitting strength using mock power spectra and correlation functions developed for the Sloan Digital Sky Survey Data Release 12. Our main findings are as follows: (1) all of the models can recover unbiased constraints when fit to the pre- and post-reconstruction simulations. (2) Models that provide physical descriptions of the damping of the BAO feature (using e.g. standard perturbation or effective-field theory arguments) report smaller errors on average, although the distribution of mock χ2 values indicates these are underestimated. (3) Allowing the BAO damping scale to vary can provide tighter constraints for some mocks, but is an artificial improvement that only arises when noise randomly sharpens the BAO peak. (4) Unlike recent claims in the literature when utilizing a BAO Extractor technique, we find no improvement in the accuracy of the recovered BAO scale. (5) We implement a procedure for combining all models into a single consensus result that improves over the standard method without obviously underestimating the uncertainties. Overall, barry provides a framework for performing the cosmological analyses for upcoming surveys, and for rapidly testing and validating new models.

scholarly journals A study on the statistical significance of mutual information between morphology of a galaxy and its large-scale environment

2020 ◽  
Vol 497 (4) ◽  
pp. 4077-4090 ◽  
Author(s):  
Suman Sarkar ◽  
Biswajit Pandey
Keyword(s):  
Mutual Information ◽  
Large Scale ◽  
Statistical Significance ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Information Theoretic ◽  
Galaxy Distribution ◽  
Sky Survey ◽  
The Galaxy ◽  
Physical Correlations

ABSTRACT A non-zero mutual information between morphology of a galaxy and its large-scale environment is known to exist in Sloan Digital Sky Survey (SDSS) upto a few tens of Mpc. It is important to test the statistical significance of these mutual information if any. We propose three different methods to test the statistical significance of these non-zero mutual information and apply them to SDSS and Millennium run simulation. We randomize the morphological information of SDSS galaxies without affecting their spatial distribution and compare the mutual information in the original and randomized data sets. We also divide the galaxy distribution into smaller subcubes and randomly shuffle them many times keeping the morphological information of galaxies intact. We compare the mutual information in the original SDSS data and its shuffled realizations for different shuffling lengths. Using a t-test, we find that a small but statistically significant (at $99.9{{\ \rm per\ cent}}$ confidence level) mutual information between morphology and environment exists upto the entire length-scale probed. We also conduct another experiment using mock data sets from a semi-analytic galaxy catalogue where we assign morphology to galaxies in a controlled manner based on the density at their locations. The experiment clearly demonstrates that mutual information can effectively capture the physical correlations between morphology and environment. Our analysis suggests that physical association between morphology and environment may extend to much larger length-scales than currently believed, and the information theoretic framework presented here can serve as a sensitive and useful probe of the assembly bias and large-scale environmental dependence of galaxy properties.

scholarly journals The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: N-body mock challenge for the quasar sample

2020 ◽  
Vol 499 (1) ◽  
pp. 269-291 ◽  
Author(s):  
Alex Smith ◽  
Etienne Burtin ◽  
Jiamin Hou ◽  
Richard Neveux ◽  
Ashley J Ross ◽  
...  
Keyword(s):  
Final Analysis ◽  
Systematic Errors ◽  
Acoustic Oscillation ◽  
Sloan Digital Sky Survey ◽  
Fourier Space ◽  
Redshift Surveys ◽  
Sky Survey ◽  
History Of ◽  
Space Distortion ◽  
Halo Occupation Distribution

ABSTRACT The growth rate and expansion history of the Universe can be measured from large galaxy redshift surveys using the Alcock–Paczynski effect. We validate the Redshift Space Distortion models used in the final analysis of the Sloan Digital Sky Survey (SDSS) extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 quasar clustering sample, in configuration and Fourier space, using a series of halo occupation distribution mock catalogues generated using the OuterRim N-body simulation. We test three models on a series of non-blind mocks, in the OuterRim cosmology, and blind mocks, which have been rescaled to new cosmologies, and investigate the effects of redshift smearing and catastrophic redshifts. We find that for the non-blind mocks, the models are able to recover fσ8 to within 3 per cent and α∥ and α⊥ to within 1 per cent. The scatter in the measurements is larger for the blind mocks, due to the assumption of an incorrect fiducial cosmology. From this mock challenge, we find that all three models perform well, with similar systematic errors on fσ8, α∥, and α⊥ at the level of $\sigma _{f\sigma _8}=0.013$, $\sigma _{\alpha _\parallel }=0.012$, and $\sigma _{\alpha _\bot }=0.008$. The systematic error on the combined consensus is $\sigma _{f\sigma _8}=0.011$, $\sigma _{\alpha _\parallel }=0.008$, and $\sigma _{\alpha _\bot }=0.005$, which is used in the final DR16 analysis. For baryon acoustic oscillation fits in configuration and Fourier space, we take conservative systematic errors of $\sigma _{\alpha _\parallel }=0.010$ and $\sigma _{\alpha _\bot }=0.007$.

scholarly journals Outlier Detection Based on Residual Histogram Preference for Geometric Multi-Model Fitting

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3037
Author(s):  
Xi Zhao ◽  
Yun Zhang ◽  
Shoulie Xie ◽  
Qianqing Qin ◽  
Shiqian Wu ◽  
...  
Keyword(s):  
Outlier Detection ◽  
State Of The Art ◽  
Geometric Model ◽  
Model Fitting ◽  
Distribution Model ◽  
Data Sets ◽  
Analysis Method ◽  
Detection Scheme ◽  
The Impact ◽  
Better Than

Geometric model fitting is a fundamental issue in computer vision, and the fitting accuracy is affected by outliers. In order to eliminate the impact of the outliers, the inlier threshold or scale estimator is usually adopted. However, a single inlier threshold cannot satisfy multiple models in the data, and scale estimators with a certain noise distribution model work poorly in geometric model fitting. It can be observed that the residuals of outliers are big for all true models in the data, which makes the consensus of the outliers. Based on this observation, we propose a preference analysis method based on residual histograms to study the outlier consensus for outlier detection in this paper. We have found that the outlier consensus makes the outliers gather away from the inliers on the designed residual histogram preference space, which is quite convenient to separate outliers from inliers through linkage clustering. After the outliers are detected and removed, a linkage clustering with permutation preference is introduced to segment the inliers. In addition, in order to make the linkage clustering process stable and robust, an alternative sampling and clustering framework is proposed in both the outlier detection and inlier segmentation processes. The experimental results also show that the outlier detection scheme based on residual histogram preference can detect most of the outliers in the data sets, and the fitting results are better than most of the state-of-the-art methods in geometric multi-model fitting.

scholarly journals Baryon acoustic oscillations from the cross-correlation of Lyα absorption and quasars in eBOSS DR14

2019 ◽  
Vol 629 ◽  
pp. A86 ◽  
Author(s):  
Michael Blomqvist ◽  
Hélion du Mas des Bourboux ◽  
Nicolás G. Busca ◽  
Victoria de Sainte Agathe ◽  
James Rich ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Acoustic Oscillation ◽  
Companion Paper ◽  
Peak Position ◽  
Sloan Digital Sky Survey ◽  
Acoustic Oscillations ◽  
Microwave Background ◽  
Angular Diameter Distance ◽  
Statistical Precision ◽  
Sky Survey

We present a measurement of the baryon acoustic oscillation (BAO) scale at redshift z = 2.35 from the three-dimensional correlation of Lyman-α (Lyα) forest absorption and quasars. The study uses 266 590 quasars in the redshift range 1.77 <  z <  3.5 from the Sloan Digital Sky Survey (SDSS) Data Release 14 (DR14). The sample includes the first two years of observations by the SDSS-IV extended Baryon Oscillation Spectroscopic Survey (eBOSS), providing new quasars and re-observations of BOSS quasars for improved statistical precision. Statistics are further improved by including Lyα absorption occurring in the Lyβ wavelength band of the spectra. From the measured BAO peak position along and across the line of sight, we determined the Hubble distance DH and the comoving angular diameter distance DM relative to the sound horizon at the drag epoch rd: DH(z = 2.35)/rd = 9.20 ± 0.36 and DM(z = 2.35)/rd = 36.3 ± 1.8. These results are consistent at 1.5σ with the prediction of the best-fit spatially-flat cosmological model with the cosmological constant reported for the Planck (2016) analysis of cosmic microwave background anisotropies. Combined with the Lyα auto-correlation measurement presented in a companion paper, the BAO measurements at z = 2.34 are within 1.7σ of the predictions of this model.

The spectral evolution of hot white dwarfs

2019 ◽  
Vol 15 (S357) ◽  
pp. 162-165
Author(s):  
Antoine Bédard ◽  
Pierre Bergeron ◽  
Gilles Fontaine
Keyword(s):  
White Dwarfs ◽  
Spectroscopic Analysis ◽  
State Of The Art ◽  
Sloan Digital Sky Survey ◽  
Atmospheric Composition ◽  
Spectral Evolution ◽  
Sky Survey

AbstractAs they evolve, white dwarfs undergo major changes in their atmospheric composition, a phenomenon known as spectral evolution. In particular, most hot He-rich (DO) stars transform into H-rich (DA) stars as they cool off, most likely as a result of the float-up of residual H. We investigate this DO-to-DA transition by taking advantage of the extensive spectroscopic dataset provided by the Sloan Digital Sky Survey (SDSS). Using our new state-of-the-art non-LTE model atmospheres, we perform a spectroscopic analysis of 1882 hot (Teff >30,000 K) white dwarfs identified in the SDSS. We find that at least 15% of all white dwarfs are born with a He-dominated atmosphere. Among these, ∼2/3 turn into H-rich stars before they reach Teff ∼40,000 K, while the remaining ∼1/3 maintain their He-rich surface throughout their entire evolution. We speculate on the origin of these two groups of objects.

Statistics, Data Mining, and Machine Learning in Astronomy

2014 ◽  
Author(s):  
Željko Ivezic ◽  
Andrew J. Connolly ◽  
Jacob T VanderPlas ◽  
Alexander Gray
Keyword(s):  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Complex Data ◽  
Dark Energy Survey ◽  
Astronomical Surveys ◽  
Sky Survey ◽  
Different Types ◽  
Complex Data Sets ◽  
Coding Standards ◽  
Energy Survey

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. The book presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest.

CONSTRAINT ON THE KINEMATICAL AND DYNAMICAL MODEL FROM THE LATEST OBSERVATIONAL DATA

2010 ◽  
Vol 25 (36) ◽  
pp. 3033-3046 ◽  
Author(s):  
JIANBO LU ◽  
YABO WU ◽  
LIXIN XU
Keyword(s):  
Observational Data ◽  
Acoustic Oscillation ◽  
Sloan Digital Sky Survey ◽  
Dynamical Model ◽  
Sky Survey ◽  
Type Ia ◽  
Redshift Survey ◽  
Galaxy Redshift ◽  
Ia Supernovae ◽  
Field Galaxy

The kinematical model j(z) = j0and dynamical model wde(z) = w0, are constrained from the latest observational data: Union2 data including 557 type Ia supernovae (SNIa), 15 observational Hubble data (OHD), baryon acoustic oscillation (BAO) data from Sloan Digital Sky Survey (SDSS) and Two-degree Field Galaxy Redshift Survey (2dFGRS) and CMB data from seven-year WMAP. We get the current values of deceleration parameter q0, jerk parameter j0, dimensionless matter density Ωm, equation of state for dark energy w0and transition redshift zT. Furthermore, it is shown that for both kinematical and dynamical models, the constraint results support for the cosmic concordance model, ΛCDM.

scholarly journals Beyond model fitting SEDs

2011 ◽  
Vol 7 (S284) ◽  
pp. 38-41
Author(s):  
Ignacio Ferreras
Keyword(s):  
Line Strength ◽  
Model Fitting ◽  
Sloan Digital Sky Survey ◽  
Spectral Fitting ◽  
Sky Survey ◽  
Fitting Procedures ◽  
Definition Of ◽  
Traditional Approaches ◽  
Star Formation Histories

AbstractExtracting star formation histories from spectra is a process plagued by numerous degeneracies among the parameters that contribute to the definition of the underlying stellar populations. Traditional approaches to overcome such degeneracies involve carefully defined line strength or spectral fitting procedures. However, all these methods rely on comparisons with population synthesis models. This paper illustrates alternative approaches based on the statistical properties of the information that can be extracted from uniformly selected samples of observed spectra, without any prior reference to modelling. Such methods are more useful with large datasets, such as surveys, where the information from thousands of spectra can be exploited to classify galaxies. An illustrative example is presented on the classification of early-type galaxies with optical spectra from the Sloan Digital Sky Survey.

scholarly journals Measuring the Baryon Acoustic Oscillation scale using the Sloan Digital Sky Survey and 2dF Galaxy Redshift Survey

2007 ◽  
Vol 381 (3) ◽  
pp. 1053-1066 ◽  
Author(s):  
Will J. Percival ◽  
Shaun Cole ◽  
Daniel J. Eisenstein ◽  
Robert C. Nichol ◽  
John A. Peacock ◽  
...  
Keyword(s):  
Acoustic Oscillation ◽  
Sloan Digital Sky Survey ◽  
Baryon Acoustic Oscillation ◽  
Sky Survey ◽  
Redshift Survey ◽  
Galaxy Redshift
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