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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

THE INFLUENCE OF NEUTRON-IRRADIATION AT LOW TEMPERATURES ON THE DIELECTRIC PARAMETERS OF 3C-SiC

3C-SiC wafers were irradiated with neutrons of various fluences and at low (200 - 400 ?C) irradiation temperatures. Fourier Transform infrared (FTIR) reflectance spectra were obtained for the samples, and the spectra used to extract the dielectric parameters for each specimen, using statistical curve-fitting procedures. Analysis of all data revealed trends in reflectance peak heights as well as in the dielectric parameters. The surface roughness of the irradiated samples was measured by atomic force spectroscopy (AFM) and certain trends could be ascribed to surface roughness.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

EXAMINING THE RADIO-LOUD/RADIO-QUIET DICHOTOMY WITH NEW CHANDRA AND VLA OBSERVATIONS OF 13 UGC GALAXIES

We present the results from new {approx}15 ks Chandra-ACIS and 4.9 GHz Very Large Array (VLA) observations of 13 galaxies hosting low-luminosity active galactic nuclei (AGNs). This completes the multiwavelength study of a sample of 51 nearby early-type galaxies described in Capetti and Balmaverde and Balmaverde and Capetti. The aim of the three previous papers was to explore the connection between the host galaxies and AGN activity in a radio-selected sample. We detect nuclear X-ray emission in eight sources and radio emission in all but one (viz., UGC 6985). The new VLA observations improve the spatial resolution by a factor of 10: the presence of nuclear radio sources in 12 of the 13 galaxies confirms their AGN nature. As previously indicated, the behavior of the X-ray and radio emission in these sources depends strongly on the form of their optical surface brightness profiles derived from Hubble Space Telescope imaging, i.e., on their classification as 'core', 'power-law', or 'intermediate' galaxies. With more than twice the number of 'power-law' and 'intermediate' galaxies compared to previous work, we confirm with a much higher statistical significance that these galaxies lie well above the radio-X-ray correlation established in Fanaroff-Riley type I radio galaxies and the low-luminosity 'core' galaxies. This result highlights the fact that the 'radio-loud/radio-quiet' dichotomy is a function of the host galaxy's optical surface brightness profile. We present radio-optical-X-ray spectral indices for all 51 sample galaxies. Survival statistics point to significant differences in the radio-to-optical and radio-to-X-ray spectral indices between the 'core' and 'power-law galaxies (Gehan's Generalized Wilcoxon test probability p for the two classes being statistically similar is <10{sup -5}), but not in the optical-to-X-ray spectral indices (p = 0.25). Therefore, the primary difference between the 'core' and 'power-law' galaxies is in their ability to launch powerful radio outflows. This result is consistent with the hypothesis of different formation processes and evolution histories in 'core' and 'power-law' galaxies: major mergers are likely to have created 'core' galaxies, while minor mergers were instrumental in the creation of 'power-law' galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Classification of Malaysia aromatic rice using multivariate statistical analysis

Aromatic rice (Oryza sativa L.) is considered as the best quality premium rice. The varieties are preferred by consumers because of its preference criteria such as shape, colour, distinctive aroma and flavour. The price of aromatic rice is higher than ordinary rice due to its special needed growth condition for instance specific climate and soil. Presently, the aromatic rice quality is identified by using its key elements and isotopic variables. The rice can also be classified via Gas Chromatography Mass Spectrometry (GC-MS) or human sensory panels. However, the uses of human sensory panels have significant drawbacks such as lengthy training time, and prone to fatigue as the number of sample increased and inconsistent. The GC–MS analysis techniques on the other hand, require detailed procedures, lengthy analysis and quite costly. This paper presents the application of in-house developed Electronic Nose (e-nose) to classify new aromatic rice varieties. The e-nose is used to classify the variety of aromatic rice based on the samples odour. The samples were taken from the variety of rice. The instrument utilizes multivariate statistical data analysis, including Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and K-Nearest Neighbours (KNN) to classify the unknown rice samples. The Leave-One-Out (LOO) validation approach is applied to evaluate the ability of KNN to perform recognition and classification of the unspecified samples. The visual observation of the PCA and LDA plots of the rice proves that the instrument was able to separate the samples into different clusters accordingly. The results of LDA and KNN with low misclassification error support the above findings and we may conclude that the e-nose is successfully applied to the classification of the aromatic rice varieties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Comparison between mirror Langmuir probe and gas-puff imaging measurements of intermittent fluctuations in the Alcator C-Mod scrape-off layer

Statistical properties of the scrape-off layer plasma fluctuations are studied in ohmically heated plasmas in the Alcator C-Mod tokamak. For the first time, plasma fluctuations as well as parameters that describe the fluctuations are compared across measurements from a mirror Langmuir probe (MLP) and from gas-puff imaging (GPI) that sample the same plasma discharge. This comparison is complemented by an analysis of line emission time-series data, synthesized from the MLP electron density and temperature measurements. The fluctuations observed by the MLP and GPI typically display relative fluctuation amplitudes of order unity together with positively skewed and flattened probability density functions. Such data time series are well described by an established stochastic framework that models the data as a superposition of uncorrelated, two-sided exponential pulses. The most important parameter of the process is the intermittency parameter, $γ=τ_d/τ_w$, where τd denotes the duration time of a single pulse and $τ_w$ gives the average waiting time between consecutive pulses. In this study we show, using a new deconvolution method, that these parameters can be consistently estimated from different statistics of the data. We also show that the statistical properties of the data sampled by the MLP and GPI diagnostic are very similar. Finally, a synthetic GPI signal using only plasma parameters sampled by the MLP shows qualitatively different fluctuation statistics from the measured GPI signal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Multifidelity uncertainty quantification with models based on dissimilar parameters

Multifidelity uncertainty quantification (MF UQ) sampling approaches have been shown to significantly reduce the variance of statistical estimators while preserving the bias of the highest-fidelity model, provided that the low-fidelity models are well correlated. However, maintaining a high level of correlation can be challenging, especially when models depend on different input uncertain parameters, which drastically reduces the correlation. Existing MF UQ approaches do not adequately address this issue. In this work, we propose a new sampling strategy that exploits a shared space to improve the correlation among models with dissimilar parameterization. We achieve this by transforming the original coordinates onto an auxiliary manifold using the adaptive basis (AB) method (Tipireddy and Ghanem, 2014). The AB method has two main benefits: (1) it provides an effective tool to identify the low-dimensional manifold on which each model can be represented, and (2) it enables easy transformation of polynomial chaos representations from high- to low-dimensional spaces. This latter feature is used to identify a shared manifold among models without requiring additional evaluations. Here we present two algorithmic flavors of the new estimator to cover different analysis scenarios, including those with legacy and non-legacy high-fidelity (HF) data. We provide numerical results for analytical examples, a direct field acoustic test, and a finite element model of a nuclear fuel assembly. For all examples, we compare the proposed strategy against both single-fidelity and MF estimators based on the original model parameterization.

42 ENGINEERING↗
DOE OSTI2011

Laboratory Studies on Surface Sampling of Bacillus anthracis Contamination: Summary, Gaps, and Recommendations

This report summarizes previous laboratory studies to characterize the performance of methods for collecting, storing/transporting, processing, and analyzing samples from surfaces contaminated by Bacillus anthracis or related surrogates. The focus is on plate culture and count estimates of surface contamination for swab, wipe, and vacuum samples of porous and nonporous surfaces. Summaries of the previous studies and their results were assessed to identify gaps in information needed as inputs to calculate key parameters critical to risk management in biothreat incidents. One key parameter is the number of samples needed to make characterization or clearance decisions with specified statistical confidence. Other key parameters include the ability to calculate, following contamination incidents, the (1) estimates of Bacillus anthracis contamination, as well as the bias and uncertainties in the estimates, and (2) confidence in characterization and clearance decisions for contaminated or decontaminated buildings. Gaps in knowledge and understanding identified during the summary of the studies are discussed and recommendations are given for future studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterization and differentiation of aluminum powders used in improvised explosive devices – Part 1: Proof of concept of the utility of particle micromorphometry

Abstract Aluminum (Al) powders are commonly used in improvised explosive devices as metallic fuels, a component of explosive mixtures. These powders can be obtained readily from industrial‐scale and consumer products, and produced using unsophisticated “kitchen chemistry” techniques. This research demonstrates the potential of automated particle micromorphometry for comparisons between known source and questioned Al powders recovered from IEDs, as well as for insight into the method of Al powder manufacture. Al powder samples were obtained from legitimate manufacturers, and 56 samples were produced “in‐house” from Al‐containing spray paints and ball‐milled Al foils. Transmitted light microscope images of Al powder particles were acquired using an automated stage with automated z‐focus; 17 size and shape parameters were measured for all particles. Approximately 37,000–2,500,000 particles/sample were analyzed using an open‐source statistical package with customized code. Dimensionality reduction was required for processing the large datasets: eight of the 17 measured variables were selected based on inspection of the correlation matrix. Data from four subsamples from each of the 56 samples produced using “in‐house” methods were analyzed using ANOVA to assess the within‐ and between‐sample variation. High within‐sample variation was noted; however, ANOVA and post‐hoc Tukey's honestly significant difference (HSD) tests demonstrated that the between‐sample variation was substantially larger than the within‐sample variation. Each sample could be differentiated from all other samples in the test set. Future experiments will focus on ways to reduce the within‐sample variation, and additional statistical and microanalytical methods to classify sources and confidently constrain the method of Al powder manufacture.

Baldaino, JenaMarie↗
DOE OSTI2015

On the origin of nonlinear elasticity in disparate rocks

Dynamic acousto-elastic (DAE) studies are performed on a set of 6 rock samples (four sandstones, one soapstone, and one granite). From these studies, at 20 strain levels 10 -7 < ϵ < 10 -5 , four measures characterizing the nonlinear elastic response of each sample are found. Additionally, each sample is tested with nonlinear resonant ultrasonic spectroscopy (NRUS) and a fth measure of nonlinear elastic response is found. The ve measures of the nonlinear elastic response of the samples (approximately 3 x 6 x 20 x 5 numbers as each measurement is repeated 3 times) are subjected to careful analysis using model independent statistical methods, principal component analysis and fuzzy clustering. This analysis reveals di erences among the samples and di erences among the nonlinear measures. Four of the nonlinear measures are sensing much the same physical mechanism in the samples. The fth is seeing something di erent. This is the case for all samples. Although the same physical mechanisms (two) are operating in all samples there are distinctive features in the way the physical mechanisms present themselves from sample to sample. This suggests classi cation of the samples into two groups. The numbers in this study and the classi cation of the measures/samples constitute an empirical characterization of rock nonlinear elastic properties that can serve as a valuable testing ground for physically based theories that relate rock nonlinear elastic properties to microscopic elastic features.

36 MATERIALS SCIENCE↗
NASA NTRS1992

BATSE analysis techniques for probing the GRB spatial and luminosity distributions

The Burst And Transient Source Experiment (BATSE) has measured homogeneity and isotropy parameters from an increasingly large sample of observed gamma-ray bursts (GRBs), while also maintaining a summary of the way in which the sky has been sampled. Measurement of both of these are necessary for any study of the BATSE data statistically, as they take into account the most serious observational selection effects known in the study of GRBs: beam-smearing and inhomogeneous, anisotropic sky sampling. Knowledge of these effects is important to analysis of GRB angular and intensity distributions. In addition to determining that the bursts are local, it is hoped that analysis of such distributions will allow boundaries to be placed on the true GRB spatial distribution and luminosity function. The technique for studying GRB spatial and luminosity distributions is direct. Results of BATSE analyses are compared to Monte Carlo models parameterized by a variety of spatial and luminosity characteristics.

Hakkila, Jon↗
DOE OSTI2017

An exploration of heterogeneity in supernova type Ia samples

We examine three SNe Type Ia datasets: Union2.1, JLA and Panstarrs to check their consistency using cosmology blind statistical analyses as well as cosmological parameter fitting. We find that the Panstarrs dataset is the most stable of the three to changes in the data, although it does not, at the moment, go to high enough redshifts to tightly constrain the equation of state of dark energy, w . The Union2.1, drawn from several different sources, appears to be somewhat susceptible to changes within the dataset. The JLA reconstructs well for a smaller number of cosmological parameters. At higher degrees of freedom, the dependence of its errors on redshift can lead to varying results between subsets. Panstarrs is inconsistent with the other two datasets at about 2σ confidence level, and JLA and Union2.1 are about 1σ away from each other. For the Ω{sub 0} {sub m} − w cosmological reconstruction, with no additional data, the 1σ range of values in w for selected subsets of each dataset is two times larger for JLA and Union2.1 as compared to Panstarrs. The range in Ω{sub 0} {sub m} for the same subsets remains approximately similar for all three datasets. We find that although there are differences in the fitting and correction techniques used in the different samples, the most important criterion is the selection of the SNe, a slightly different SNe selection can lead to noticeably different results both in the purely statistical analysis and in cosmological reconstruction. We note that a single, high quality low redshift sample could help decrease the uncertainties in the result. We also note that lack of homogeneity in the magnitude errors may bias the results and should either be modeled, or its effect neutralized by using other, complementary datasets. A supernova sample with high quality data at both high and low redshifts, constructed from a few surveys to avoid heterogeneity in the sample, and with homogeneous errors, would result in a more robust cosmological reconstruction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Destructive Analysis of TRISO Particles: Crush/Burn/Leach Followed by Davies-Gray Titration and IDMS

The accurate accounting of nuclear materials is a cornerstone of international nuclear safeguards. One emerging challenge in this domain is the fabrication of TRIstructural ISOtropic (TRISO) particle fuels. Although these innovative fuel forms are critical for advanced reactor applications, their robust refractory ceramics and coating compositions present significant obstacles to destructive analysis (DA) methods. Ensuring full and quantitative recovery from these particles is essential for accurate mass accountancy. The current study was initiated to address these challenges, first by validating a previously established destructive method developed by Oak Ridge National Laboratory (ORNL) for the quantitative recovery of uranium from TRISO particles and then following that process with uranium content determination through isotope dilution mass spectrometry (IDMS) and Davies-Gray titration. This study expands on the scope of a digestive method that was developed under the Advanced Gas Reactor Fuel Development and Qualification program and is currently implemented in both the Coated Particle Fuel Development Laboratory and Irradiated Fuels Examination Laboratory at ORNL. The success of the previous Advanced Gas Reactor work relied on developing a DA method to evaluate the fabrication process and reactor experiments. The methodology described in this report was designed to rigorously investigate the efficacy of the crush/burn/leach sample preparation of TRISO particles; it aims to quantify uranium recovery while also assessing the effects of TRISO constituents (e.g., silicon and zirconium) on analytical precision and accuracy. By comparing the results from the titration method and IDMS, we sought to determine whether existing analytical procedures accepted by the International Atomic Energy Agency (IAEA) could be effectively translated to TRISO fuel forms. The team employed an approach that involved processing replicate TRISO samples, optimizing the milling (i.e., crushing) step and performing serial leaches. The elemental composition of the analytical samples was examined to prepare for interference studies in the second year of this project. The integration of gamma spectrometry to verify residual uranium activity further strengthened the validation. Statistical methods were applied to the collected data to evaluate the uncertainties arising from sampling, sample preparation and uranium quantification. These uncertainties were then compared to the IAEA’s international target values (ITVs). Additional data collected in upcoming project work will strengthen the uncertainty estimates. Ultimately, it is hoped that this project will contribute materially to the body of work related to characterization of TRISO based fuels for the purpose of material accountancy and its applications to international safeguards.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2000

Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by the light and heavy rain rates. This is useful in estimating the fraction of rainfall contributed by the rain rates that go undetected by the radar. The results at high rain rates provide a cross-check on the usual attenuation correction methods that are applied at the highest resolution of the instrument.

Meneghini, R.↗
DOE OSTI2019

Summing Corrections For La-140 On Counter 137 [Slides]

The counting of filters for gamma activity is often done with the sample situated very close or wrapped around the detector. This improves the counting statistics but can increase the probability of summing and affect the calculation of yield. An MCNP model of counter 137 (a 65% HPGe detector) was used to compute the total and peak efficiencies for two sample types, 40 and 20. The type 40 is a long filter strip wrapped in a Marinelli beaker which sits around the detector in an annular fashion. The type 20 is a 8.4 in radius filter, quarter-folded and placed flat on the detector face. A comparison of the peak efficiency computed in MCNP was compared to the measured efficiency to ensure consistency. Using the measured peak efficiency and MCNP-computed total efficiency, the TrueCoinc program was run to estimate the summing values for La-140 peaks. The results showed the summing out of two peaks (487 and 1596 keV) was around 6-8% in for both sample types.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Smart Sampling and HPC-based Probabilistic Look-ahead Contingency Analysis Implementation and its Evaluation with Real-world Data

This paper describes a probabilistic look-ahead contingency analysis application that incorporates smart sampling and high-performance computing (HPC) techniques. Smart sampling techniques are implemented to effectively represent the structure and statistical characteristics of uncertainty introduced by different sources in the power system. They can significantly reduce the data set size required for multiple look-ahead contingency analyses, and therefore reduce the time required to compute them. High-performance-computing (HPC) techniques are used to further reduce computational time. These two techniques enable a predictive capability that forecasts the impact of various uncertainties on potential transmission limit violations. The developed package has been tested with real world data from the Bonneville Power Administration. Case study results are presented to demonstrate the performance of the applications developed.

high performance computing↗
DOE OSTI2017

The Viewing Geometry of Brown Dwarfs Influences Their Observed Colors and Variability Amplitudes

In this paper we study the full sample of known Spitzer [3.6 μm] and J-band variable brown dwarfs. We calculate the rotational velocities, vsin i, of 16 variable brown dwarfs using archival Keck NIRSPEC data and compute the inclination angles of 19 variable brown dwarfs. The results obtained show that all objects in the sample with mid-IR variability detections are inclined at an angle >20{sup ∘}, while all objects in the sample displaying J-band variability have an inclination angle >35{sup ∘}. J-band variability appears to be more affected by inclination than Spitzer [3.6 μm] variability, and is strongly attenuated at lower inclinations. Since J-band observations probe deeper into the atmosphere than mid-IR observations, this effect may be due to the increased atmospheric path length of J-band flux at lower inclinations. We find a statistically significant correlation between the color anomaly and inclination of our sample, where field objects viewed equator-on appear redder than objects viewed at lower inclinations. Considering the full sample of known variable L, T, and Y spectral type objects in the literature, we find that the variability properties of the two bands display notably different trends that are due to both intrinsic differences between bands and the sensitivity of ground-based versus space-based searches. However, in both bands we find that variability amplitude may reach a maximum at ∼7–9 hr periods. Finally, we find a strong correlation between color anomaly and variability amplitude for both the J-band and mid-IR variability detections, where redder objects display higher variability amplitudes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

LoCuSS: THE MASS DENSITY PROFILE OF MASSIVE GALAXY CLUSTERS AT z = 0.2 {sup ,}

We present a stacked weak-lensing analysis of an approximately mass-selected sample of 50 galaxy clusters at 0.15 < z < 0.3, based on observations with Suprime-Cam on the Subaru Telescope. We develop a new method for selecting lensed background galaxies from which we estimate that our sample of red background galaxies suffers just 1% contamination. We detect the stacked tangential shear signal from the full sample of 50 clusters, based on this red sample of background galaxies, at a total signal-to-noise ratio of 32.7. The Navarro-Frenk-White model is an excellent fit to the data, yielding sub-10% statistical precision on mass and concentration: M{sub vir}=7.19{sup +0.53}{sub -0.50} Multiplication-Sign 10{sup 14} h{sup -1} M{sub sun}, c{sub vir}=5.41{sup +0.49}{sub -0.45} (c{sub 200}=4.22{sup +0.40}{sub -0.36}). Tests of a range of possible systematic errors, including shear calibration and stacking-related issues, indicate that they are subdominant to the statistical errors. The concentration parameter obtained from stacking our approximately mass-selected cluster sample is broadly in line with theoretical predictions. Moreover, the uncertainty on our measurement is comparable with the differences between the different predictions in the literature. Overall, our results highlight the potential for stacked weak-lensing methods to probe the mean mass density profile of cluster-scale dark matter halos with upcoming surveys, including Hyper-Suprime-Cam, Dark Energy Survey, and KIDS.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2002

A geostatistical analysis of small-scale spatial variability in bacterial abundance and community structure in salt marsh creek bank sediments

Small-scale variations in bacterial abundance and community structure were examined in salt marsh sediments from Virginia's eastern shore. Samples were collected at 5 cm intervals (horizontally) along a 50 cm elevation gradient, over a 215 cm horizontal transect. For each sample, bacterial abundance was determined using acridine orange direct counts and community structure was analyzed using randomly amplified polymorphic DNA fingerprinting of whole-community DNA extracts. A geostatistical analysis was used to determine the degree of spatial autocorrelation among the samples, for each variable and each direction (horizontal and vertical). The proportion of variance in bacterial abundance that could be accounted for by the spatial model was quite high (vertical: 60%, horizontal: 73%); significant autocorrelation was found among samples separated by 25 cm in the vertical direction and up to 115 cm horizontally. In contrast, most of the variability in community structure was not accounted for by simply considering the spatial separation of samples (vertical: 11%, horizontal: 22%), and must reflect variability from other parameters (e.g., variation at other spatial scales, experimental error, or environmental heterogeneity). Microbial community patch size based upon overall similarity in community structure varied between 17 cm (vertical) and 35 cm (horizontal). Overall, variability due to horizontal position (distance from the creek bank) was much smaller than that due to vertical position (elevation) for both community properties assayed. This suggests that processes more correlated with elevation (e.g., drainage and redox potential) vary at a smaller scale (therefore producing smaller patch sizes) than processes controlled by distance from the creek bank. c2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Non-NASA Center↗
DOE OSTI2023

First Constraints on Growth Rate from Redshift-space Ellipticity Correlations of SDSS Galaxies at 0.16 < z < 0.70

We report the first constraints on the growth rate of the universe, f(z)σ 8 (z), with intrinsic alignments (IAs) of galaxies. We measure the galaxy density-intrinsic ellipticity cross-correlation and intrinsic ellipticity autocorrelation functions over 0.16 < z < 0.7 from luminous red galaxies (LRGs) and LOWZ and CMASS galaxy samples in the Sloan Digital Sky Survey (SDSS) and SDSS-III BOSS survey. We detect clear anisotropic signals of IA due to redshift-space distortions. By combining measured IA statistics with the conventional galaxy clustering statistics, we obtain tighter constraints on the growth rate. The improvement is particularly prominent for the LRG, which is the brightest galaxy sample and known to be strongly aligned with underlying dark matter distribution; using the measurements on scales above 10 h -1 Mpc, we obtain $f{\sigma }_{8}={0.5196}_{-0.0354}^{+0.0352}$ (68% confidence level) from the clustering-only analysis and $f{\sigma }_{8}={0.5322}_{-0.0291}^{+0.0293}$ with clustering and IA, meaning 19% improvement. The constraint is in good agreement with the prediction of general relativity, f σ 8 = 0.4937 at z = 0.34. For LOWZ and CMASS samples, the improvement of constraints on f σ 8 is found to be 10% and 3.5%, respectively. Our results indicate that the contribution from IA statistics for cosmological constraints can be further enhanced by carefully selecting galaxies for a shape sample.

79 ASTRONOMY AND ASTROPHYSICS↗