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We present measurements of galaxy clustering from the Baryon Oscillation Spectroscopic Survey (BOSS), which is part of the Sloan Digital Sky Survey III (SDSS‐III). These use the Data Release 9 (DR9) CMASS sample, which contains 264 283 massive galaxies covering 3275 square degrees with an effective redshift z = 0.57 and redshift range 0.43 < z < 0.7. Assuming a concordance ΛCDM cosmological model, this sample covers an effective volume of 2.2 Gpc3, and represents the largest sample of the Universe ever surveyed at this density, n¯≈3×10−4h−3 Mpc 3. We measure the angle‐averaged galaxy correlation function and power spectrum, including density‐field reconstruction of the baryon acoustic oscillation (BAO) feature. The acoustic features are detected at a significance of 5σ in both the correlation function and power spectrum. Combining with the SDSS‐II luminous red galaxy sample, the detection significance increases to 6.7σ. Fitting for the position of the acoustic features measures the distance to z = 0.57 relative to the sound horizon DV/rs = 13.67 ± 0.22 at z = 0.57. Assuming a fiducial sound horizon of 153.19 Mpc, which matches cosmic microwave background constraints, this corresponds to a distance DV (z = 0.57) = 2094 ± 34 Mpc. At 1.7 per cent, this is the most precise distance constraint ever obtained from a galaxy survey. We place this result alongside previous BAO measurements in a cosmological distance ladder and find excellent agreement with the current supernova measurements. We use these distance measurements to constrain various cosmological models, finding continuing support for a flat Universe with a cosmological constant.

We present the first application to density field reconstruction to a galaxy survey to undo the smoothing of the baryon acoustic oscillation (BAO) feature due to non-linear gravitational evolution and thereby improve the precision of the distance measurements possible. We apply the reconstruction technique to the clustering of galaxies from the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) luminous red galaxy (LRG) sample, sharpening the BAO feature and achieving a 1.9 per cent measurement of the distance to z = 0.35. We update the reconstruction algorithm of Eisenstein et al. to account for the effects of survey geometry as well as redshift-space distortions and validate it on 160 LasDamas simulations. We demonstrate that reconstruction sharpens the BAO feature in the angle averaged galaxy correlation function, reducing the non-linear smoothing scale nl from 8.1 to 4.4 Mpc h −1 . Reconstruction also significantly reduces the effects of redshift-space distortions at the BAO scale, isotropizing the correlation function. This sharpened BAO feature yields an unbiased distance estimate (<0.2 per cent) and reduces the scatter from 3.3 to 2.1 per cent. We demonstrate the robustness of these results to the various reconstruction parameters, including the smoothing scale, the galaxy bias and the linear growth rate. Applying this reconstruction algorithm to the SDSS LRG DR7 sample improves the significance of the BAO feature in these data from 3.3σ for the unreconstructed correlation function to 4.2σ after reconstruction. We estimate a relative distance scale D V /r s to z = 0.35 of 8.88 ± 0.17, where r s is the sound horizon and D V ≡ (D 2 A H −1 ) 1/3 is a combination of the angular diameter distance D A and Hubble parameter H. Assuming a sound horizon of 154.25 Mpc, this translates into a distance measurement D V (z = 0.35) = 1.356 ± 0.025 Gpc. We find that reconstruction reduces the distance error in the DR7 sample from 3.5 to 1.9 per cent, equivalent to a survey with three times the volume of SDSS.

We present a fast method of producing mock galaxy catalogues that can be used to compute covariance matrices of large-scale clustering measurements and test the methods of analysis. Our method populates a 2nd-order Lagrangian Perturbation Theory (2LPT) matter field, where we calibrate masses of dark matter halos by detailed comparisons with N-body simulations. We demonstrate the clustering of halos is recovered at ∼10 per cent accuracy. We populate halos with mock galaxies using a Halo Occupation Distribution (HOD) prescription, which has been calibrated to reproduce the clustering measurements on scales between 30 and 80 h −1 Mpc. We compare the sample covariance matrix from our mocks with analytic estimates, and discuss differences. We have used this method to make catalogues corresponding to Data Release 9 of the Baryon Oscillation Spectroscopic Survey (BOSS), producing 600 mock catalogues of the "CMASS" galaxy sample. These mocks enabled detailed tests of methods and errors that formed an integral part of companion analyses of these galaxy data.

We analyse the density field of galaxies observed by the Sloan Digital Sky Survey (SDSS)‐III Baryon Oscillation Spectroscopic Survey (BOSS) included in the SDSS Data Release Nine (DR9). DR9 includes spectroscopic redshifts for over 400 000 galaxies spread over a footprint of 3275 deg2. We identify, characterize and mitigate the impact of sources of systematic uncertainty on large‐scale clustering measurements, both for angular moments of the redshift‐space correlation function, ξℓ(s), and the spherically averaged power spectrum, P(k), in order to ensure that robust cosmological constraints will be obtained from these data. A correlation between the projected density of stars and the higher redshift (0.43 < z < 0.7) galaxy sample (the approximately constant stellar mass threshold ‘CMASS’ sample) due to imaging systematics imparts a systematic error that is larger than the statistical error of the clustering measurements at scales s > 120 h−1 Mpc or k < 0.01 h Mpc−1. We find that these errors can be ameliorated by weighting galaxies based on their surface brightness and the local stellar density. The clustering of CMASS galaxies found in the Northern and Southern Galactic footprints of the survey generally agrees to within 2σ. We use mock galaxy catalogues that simulate the CMASS selection function to determine that randomly selecting galaxy redshifts in order to simulate the radial selection function of a random sample imparts the least systematic error on ξℓ(s) measurements and that this systematic error is negligible for the spherically averaged correlation function, ξ0. We find a peak in ξ0 at s∼ 200 h−1 Mpc, with a corresponding feature with period ∼0.03 h Mpc−1 in P(k), and find features at least as strong in 4.8 per cent of the mock galaxy catalogues, concluding this feature is likely to be a consequence of cosmic variance. The methods we recommend for the calculation of clustering measurements using the CMASS sample are adopted in companion papers that locate the position of the baryon acoustic oscillation feature, constrain cosmological models using the full shape of ξ0 and measure the rate of structure growth.

We measure shifts of the acoustic scale due to nonlinear growth and redshift distortions to a high precision using a very large volume of high-force-resolution simulations. We compare results from various sets of simulations that differ in their force, volume, and mass resolution. We find a consistency within 1.5 − σ for shift values from different simulations and derive shift α(z) − 1 = (0.300 ± 0.015)%[D(z)/D(0)] 2 using our fiducial set. We find a strong correlation with a non-unity slope between shifts in real space and in redshift space and a weak correlation between the initial redshift and low redshift. Density-field reconstruction not only removes the mean shifts and reduces errors on the mean, but also tightens the correlations. After reconstruction, we recover a slope of near unity for the correlation between the real and redshift space and restore a strong correlation between the initial and the low redshifts. We derive propagators and mode-coupling terms from our N-body simulations and compare with the Zel'dovich approximation and the shifts measured from the χ 2 fitting, respectively. We interpret the propagator and the mode-coupling term of a nonlinear density field in the context of an average and a dispersion of its complex Fourier coefficients relative to those of the linear density field; from these two terms, we derive a signal-to-noise ratio of the acoustic peak measurement. We attempt to improve our reconstruction method by implementing 2LPT and iterative operations, but we obtain little improvement. The Fisher matrix estimates of uncertainty in the acoustic scale is tested using 5000h −3 Gpc 3 of cosmological PM simulations from Takahashi et al. (2009a). At an expected sample variance level of 1%, the agreement between the Fisher matrix estimates based on and the N-body results is better than 10 %. Subject headings: distance scale-large-scale structure of universe -methods: numerical

We present measurements of the angular diameter distance D A (z) and the Hubble parameter H(z) at z = 0.35 using the anisotropy of the baryon acoustic oscillation (BAO) signal measured in the galaxy clustering distribution of the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) Luminous Red Galaxies (LRG) sample. Our work is the first to apply density-field reconstruction to an anisotropic analysis of the acoustic peak. Reconstruction partially removes the effects of non-linear evolution and redshift-space distortions in order to sharpen the acoustic signal. We present the theoretical framework behind the anisotropic BAO signal and give a detailed account of the fitting model we use to extract this signal from the data. Our method focuses only on the acoustic peak anisotropy, rather than the more model-dependent anisotropic information from the broadband power. We test the robustness of our analysis methods on 160 LasDamas DR7 mock catalogues and find that our models are unbiased at the ∼ 0.2% level in measuring the BAO anisotropy. After reconstruction we measure D A (z = 0.35) = 1050 ± 38 Mpc and H(z = 0.35) = 84.4 ± 7.0 km/s/Mpc assuming a sound horizon of r s = 152.76 Mpc. Note that these measurements are correlated with a correlation coefficient of 0.57. This represents a factor of 1.4 improvement in the error on D A relative to the pre-reconstruction case; a factor of 1.2 improvement is seen for H.

A ssessment is an essential component of education. Results from assessments serve diverse functions for diagnosis, placement, prediction, and so forth. Course instructors rely on tests, for example, to obtain information on students' mastery of content knowledge and other contextual variables, such as problem solving and creativity. At another level, most colleges use SAT or ACT test scores for college admissions, and GRE test scores for graduate admissions. Test scores allow comparisons, although a long and vigorous debate has taken place among education stakeholders regarding how to interpret test scores and create education policy. The debate has developed into a national concern since the passage in 2001 of the No Child Left Behind Act (NCLB), which includes a strong focus on assessment. Critics focus on the limitations of tests, potential misinterpretations of test scores, and the unintended consequences of a testing program. It is often difficult for an educator to evaluate the arguments for and against a particular approach.While there are no easy answers, a better understanding of educational measurement theory can provide necessary nuance to discussions of education policy. The full assortment of measurement theories and practices is beyond the scope of this paper, but the basics are pertinent for all of us who teach chemistry and are aware of the need to improve science, technology, engineering, and mathematics (STEM) education outcomes at the national level. For the purpose of assessing both academic achievement and noncognitive variables such as attitude, the first and most important thing is to find "good" assessments. This study will present one way to proceed with this task. ' WHY ATTITUDE?The term "attitude" falls within the purview of "scientific literacy", which is a central goal of science education. Usually, scientific literacy focuses on the cognitive knowledge dimension, as highlighted by the proposition "the scientifically literate person accurately applies appropriate science concepts, principles, laws, and theories in interacting with his [sic] universe". 1 However, many science educators emphasize that noncognitive factors such as values and attitudes are important components of science literacy. According to the American Association for the Advancement of Science, 2 spelling out the "knowledge, skills, and attitudes all students should acquire as a consequence of their total school experience" is a requirement for a curriculum to be considered as promoting scientific literacy. Here AAAS places attitudes on an equal footing with knowledge and skills.Appropriately, many research studies have investigated students' attitudes toward learning science. 3À7 The last thing educators want to see is students scoring high on standard tests, but thinking that science is depressing, boring, or otherwise unpleasant, and never again using their scientific knowledge after it is no longer compulsory to do so. High-quality science courses that promote both content knowledge and a positive attitude towa...