Analytic Detection Thresholds for Measurements of Linearly Polarized Intensity Using Rotation Measure Synthesis

A fully analytic statistical formalism does not yet exist to describe radio-wavelength measurements of linearly polarized intensity that are produced using rotation measure synthesis. In this work we extend the analytic formalism for standard linear polarization, namely that describing measurements of the quadrature sum of Stokes Q and U intensities, to the rotation measure synthesis environment. We derive the probability density function and expectation value for Faraday-space polarization measurements for both the case where true underlying polarized emission is present within unresolved Faraday components, and for the limiting case where no such emission is present. We then derive relationships to quantify the statistical significance of linear polarization measurements in terms of standard Gaussian statistics. The formalism developed in this work will be useful for setting signal-to-noise ratio detection thresholds for measurements of linear polarization, for the analysis of polarized sources potentially exhibiting multiple Faraday components, and for the development of polarization debiasing schemes.Comment: 14 pages, 6 figures, accepted for publication in MNRA

Improved orbit predictions using two-line elements

The density of orbital space debris constitutes an increasing environmental challenge. There are three ways to alleviate the problem: debris mitigation, debris removal and collision avoidance. This paper addresses collision avoidance, by describing a method that contributes to achieving a requisite increase in orbit prediction accuracy. Batch least-squares differential correction is applied to the publicly available two-line element (TLE) catalog of space objects. Using a high-precision numerical propagator, we fit an orbit to state vectors derived from successive TLEs. We then propagate the fitted orbit further forward in time. These predictions are compared to precision ephemeris data derived from the International Laser Ranging Service (ILRS) for several satellites, including objects in the congested sun-synchronous orbital region. The method leads to a predicted range error that increases at a typical rate of 100 meters per day, approximately a 10-fold improvement over TLE's propagated with their associated analytic propagator (SGP4). Corresponding improvements for debris trajectories could potentially provide initial conjunction analysis sufficiently accurate for an operationally viable collision avoidance system. We discuss additional optimization and the computational requirements for applying all-on-all conjunction analysis to the whole TLE catalog, present and near future. Finally, we outline a scheme for debris-debris collision avoidance that may become practicable given these developments.Comment: Submitted to Advances in Space Research. 13 pages, 4 figure

Photometric redshifts and clustering of emission line galaxies selected jointly by DES and eBOSS

We present the results of the first test plates of the extended Baryon Oscillation Spectroscopic Survey. This paper focuses on the emission line galaxies (ELG) population targetted from the Dark Energy Survey (DES) photometry. We analyse the success rate, efficiency, redshift distribution, and clustering properties of the targets. From the 9000 spectroscopic redshifts targetted, 4600 have been selected from the DES photometry. The total success rate for redshifts between 0.6 and 1.2 is 71\% and 68\% respectively for a bright and faint, on average more distant, samples including redshifts measured from a single strong emission line. We find a mean redshift of 0.8 and 0.87, with 15 and 13\% of unknown redshifts respectively for the bright and faint samples. In the redshift range 0.6<z<1.2, for the most secure spectroscopic redshifts, the mean redshift for the bright and faint sample is 0.85 and 0.9 respectively. Star contamination is lower than 2\%. We measure a galaxy bias averaged on scales of 1 and 10~Mpc/h of 1.72 \pm 0.1 for the bright sample and of 1.78 \pm 0.12 for the faint sample. The error on the galaxy bias have been obtained propagating the errors in the correlation function to the fitted parameters. This redshift evolution for the galaxy bias is in agreement with theoretical expectations for a galaxy population with MB-5\log h < -21.0. We note that biasing is derived from the galaxy clustering relative to a model for the mass fluctuations. We investigate the quality of the DES photometric redshifts and find that the outlier fraction can be reduced using a comparison between template fitting and neural network, or using a random forest algorithm

Preprocessing Among the Infalling Galaxy Population of EDisCS Clusters

We present results from a low-resolution spectroscopic survey for 21 galaxy clusters at $0.4 < z < 0.8$ selected from the ESO Distant Cluster Survey. We measured spectra using the low-dispersion prism in IMACS on the Magellan Baade telescope and calculate redshifts with an accuracy of $\sigma_z = 0.007$. We find 1763 galaxies that are brighter than $R = 22.9$ in the large-scale cluster environs. We identify the galaxies expected to be accreted by the clusters as they evolve to $z = 0$ using spherical infall models and find that $\sim30\%$ to $\sim70\%$ of the $z = 0$ cluster population lies outside the virial radius at $z \sim 0.6$. For analogous clusters at $z = 0$, we calculate that the ratio of galaxies that have fallen into the clusters since $z \sim 0.6$ to those that were already in the core at that redshift is typically between $\sim0.3$ and $1.5$. This wide range of ratios is due to intrinsic scatter and is not a function of velocity dispersion, so a variety of infall histories is to be expected for clusters with current velocity dispersions of $300 \lesssim\sigma\lesssim 1200$ km s$^{-1}$. Within the infall regions of $z \sim 0.6$ clusters, we find a larger red fraction of galaxies than in the field and greater clustering among red galaxies than blue. We interpret these findings as evidence of "preprocessing", where galaxies in denser local environments have their star formation rates affected prior to their aggregation into massive clusters, although the possibility of backsplash galaxies complicates the interpretation.Comment: Accepted for publication in Ap

Effect of influential cases on factor analysis results etkili vakaların faktör analizi sonuçları üzerindeki etkisi

When performing regression analysis, one way to examine the normality of data is to screen outliers. Outliers, on the other hand, do not always have an effect on regression results. In reality, cases with a large amount of residuals that affect regression analysis results are referred to as influential cases. It is important to detect them in the dataset because they can lead to erroneous conclusions. The influence of influential cases has already gotten a lot of attention in the regression literature, while it has gotten a lot less attention in factor analysis. The aim of this paper is to show how influential cases affect factor analysis results when they are detected using the Forward Search algorithm. The data was collected from 686 university students ranging in age from 17 to 30. The data was gathered using the Self-Regulation Scale (SRS). The results revealed that the removal of influential cases had an effect on the observed correlation matrice for the SRS items, the factorability results, the number of dimensions extracted, CFA fit indices, and the amount of factor loadings and associated errors. Later, in light of related literature, these results were discussed and the researchers were recommended to consider the effect of influential when applying factor analysis.Regresyon analizi gerçekleştirirken verilerin normalliğini araştırmak için uç değerlerin incelenmesi kullanılan yaklaşımlardan bir tanesidir. Gerçekte ise, uç değerlerin regresyon sonuçları üzerinde etkili olması bir gereklilik değildir. Aslında, regresyon analizi sonuçlarını etkileyen gözlemler, büyük miktarda artık barındıran etkili vakalar olarak adlandırılır. Veri setinde yanıltıcı sonuçlara yol açabilecek yüksek artık içeren gözlemleri tespit etmek önemlidir. Etkili vakaların etkisi, regresyon alan yazını hâlihazırda dikkat çekmişken faktör analizinde ise daha az vurgulanmıştır. Gerçekleştirilen bu çalışmanın amacı, ileri arama algoritması kullanılarak etkili durumlar belirlendiğinde bu vakaların faktör analizi sonuçları üzerindeki etkilerini göstermektir. Veriler, yaşları 17 ile 30 arasında değişen 686 üniversite öğrencisinden toplanmıştır. Çalışmada veri toplama aracı olarak Öz Düzenleme Ölçeği (ÖDÖ) kullanılmıştır. Sonuçlar, etkili vakaların veri setinden kaldırılmasının ÖDÖ maddeleri için gözlemlenen korelasyon matrisini, faktörlenebilirlik sonuçlarını, çıkarılan boyutların sayısını, doğrulayıcı faktör analizi uyum indekslerini ve faktör yüklerinin miktarını ve yüklere ait hataları etkilediğini ortaya koymuştur. Bu bulgular daha sonra ilgili alanyazın kapsamında tartışılmış ve araştırmacılar faktör analizi gerçekleştirirken etkili vakaların etkilerini dikkate almaları önerilmiştir

PointCleanNet: Learning to Denoise and Remove Outliers from Dense Point Clouds

Point clouds obtained with 3D scanners or by image-based reconstruction techniques are often corrupted with significant amount of noise and outliers. Traditional methods for point cloud denoising largely rely on local surface fitting (e.g., jets or MLS surfaces), local or non-local averaging, or on statistical assumptions about the underlying noise model. In contrast, we develop a simple data-driven method for removing outliers and reducing noise in unordered point clouds. We base our approach on a deep learning architecture adapted from PCPNet, which was recently proposed for estimating local 3D shape properties in point clouds. Our method first classifies and discards outlier samples, and then estimates correction vectors that project noisy points onto the original clean surfaces. The approach is efficient and robust to varying amounts of noise and outliers, while being able to handle large densely-sampled point clouds. In our extensive evaluation, both on synthesic and real data, we show an increased robustness to strong noise levels compared to various state-of-the-art methods, enabling accurate surface reconstruction from extremely noisy real data obtained by range scans. Finally, the simplicity and universality of our approach makes it very easy to integrate in any existing geometry processing pipeline

Systematic Effects of Foreground Removal in 21cm Surveys of Reionization

It is well-known that foreground subtraction in 21cm surveys removes large scale power. We investigate associated systematic biases. We show that removing line-of-sight fluctuations on large scales aliases into suppression of the 3D power spectrum across a broad range of scales. This bias can be eliminated by marginalizing over small k in the 1D power spectrum; however, the unbiased estimator will have unavoidably larger variance. We also show that Gaussian realizations of the power spectrum permit accurate and extremely rapid Monte-Carlo simulations for error analysis; repeated realizations of the fully non-Gaussian field are unnecessary. We perform Monte-Carlo maximum-likelihood simulations of foreground removal which yield unbiased, minimum variance estimates of the power spectrum in agreement with Fisher matrix estimates. Foreground removal also distorts the 21cm PDF, reducing the contrast between neutral and ionized regions. We show that it is the subtraction of large-scales modes which is responsible for this distortion, and that it is less severe in the earlier stages of reionization. It can be reduced by using larger bandwidths for foreground removal. In the late stages of reionization, the largest ionized regions (which consist of foreground emission only) provides calibration points which potentially allow recovery of large-scale modes. Finally, we also show that: (i) the broad frequency response of synchrotron and free-free emission will smear out any features in the electron momentum distribution and ensure spectrally smooth foregrounds; (ii) extragalactic radio recombination lines should be negligible foregrounds.Comment: Minor editorial changes (including title) to match published version; conclusions unchanged. 20 pages, 18 figure

The Spitzer c2d Survey of Large, Nearby, Interstellar Clouds. I. Chamaeleon II Observed with MIPS

We present maps of over 1.5 square degrees in Chamaeleon (Cha) II at 24, 70, and 160 micron observed with the Spitzer Space Telescope Multiband Imaging Photometer for Spitzer (MIPS) and a 1.2 square degree millimeter map from SIMBA on the Swedish-ESO Submillimetre Telescope (SEST). The c2d Spitzer Legacy Team's data reduction pipeline is described in detail. Over 1500 24 micron sources and 41 70 micron sources were detected by MIPS with fluxes greater than 10-sigma. More than 40 potential YSOs are identified with a MIPS and 2MASS color-color diagram and by their spectral indices, including two previously unknown sources with 24 micron excesses. Our new SIMBA millimeter map of Cha II shows that only a small fraction of the gas is in compact structures with high column densities. The extended emission seen by MIPS is compared with previous CO observations. Some selected interesting sources, including two detected at 1 mm, associated with Cha II are discussed in detail and their SEDs presented. The classification of these sources using MIPS data is found to be consistent with previous studies.Comment: 44 pages, 12 figures (1 color), to be published in Ap