The Experts below are selected from a list of 249 Experts worldwide ranked by ideXlab platform
Yiping Shu - One of the best experts on this subject based on the ideXlab platform.
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a direct measurement of the high mass end of the velocity Dispersion Function at z 0 55 from sdss iii boss
Monthly Notices of the Royal Astronomical Society, 2017Co-Authors: Antonio D Monterodorta, A Bolton, Yiping ShuAbstract:We report the first direct spectroscopic measurement of the velocity Dispersion Function (VDF) for the high-mass red sequence (RS) galaxy population at redshift $z\sim0.55$. We achieve high precision by using a sample of 600,000 massive galaxies with spectra from the Baryon Oscillation Spectroscopic Survey (BOSS) of the third Sloan Digital Sky Survey (SDSS-III), covering stellar masses $M_*\gtrsim10^{11}~M_{\odot}$. We determine the VDF by projecting the joint probability-density Function (PDF) of luminosity $L$ and velocity Dispersion $\sigma$, i.e. $p(L,\sigma)$, defined by our previous measurements of the RS luminosity Function and $L-\sigma$ relation for this sample. These measurements were corrected from red--blue galaxy population confusion, photometric blurring, incompleteness and selection effects within a forward-modeling framework that furthermore correctly accommodates the low spectroscopic signal-to-noise ratio of individual BOSS spectra. Our $z\sim0.55$ RS VDF is in overall agreement with the $z\sim0$ early-type galaxy (ETG) VDF at $\log_{10}\sigma\gtrsim2.47$, however the number density of $z=0.55$ RS galaxies that we report is larger than that of $z=0$ ETG galaxies at $2.35\gtrsim\log_{10}\sigma\gtrsim 2.47$. The extrapolation of an intermediate-mass L-$\sigma$ relation towards the high-mass end in previous low-z works may be responsible for this disagreement. Evolutionary interpretation of this comparison is also subject to differences in the way the respective samples are selected; these differences can be mitigated in future work by analyzing $z=0$ SDSS data using the same framework presented in this paper. We also provide the sample PDF for the RS population (i.e. uncorrected for incompleteness), which is a key ingredient for gravitational lensing analyses using BOSS.
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A direct measurement of the high-mass end of the velocity Dispersion Function at z ∼ 0.55 from SDSS-III/BOSS
Monthly Notices of the Royal Astronomical Society, 2017Co-Authors: Antonio D. Montero-dorta, Adam S. Bolton, Yiping ShuAbstract:We report the first direct spectroscopic measurement of the velocity Dispersion Function (VDF) for the high-mass red sequence (RS) galaxy population at redshift $z\sim0.55$. We achieve high precision by using a sample of 600,000 massive galaxies with spectra from the Baryon Oscillation Spectroscopic Survey (BOSS) of the third Sloan Digital Sky Survey (SDSS-III), covering stellar masses $M_*\gtrsim10^{11}~M_{\odot}$. We determine the VDF by projecting the joint probability-density Function (PDF) of luminosity $L$ and velocity Dispersion $\sigma$, i.e. $p(L,\sigma)$, defined by our previous measurements of the RS luminosity Function and $L-\sigma$ relation for this sample. These measurements were corrected from red--blue galaxy population confusion, photometric blurring, incompleteness and selection effects within a forward-modeling framework that furthermore correctly accommodates the low spectroscopic signal-to-noise ratio of individual BOSS spectra. Our $z\sim0.55$ RS VDF is in overall agreement with the $z\sim0$ early-type galaxy (ETG) VDF at $\log_{10}\sigma\gtrsim2.47$, however the number density of $z=0.55$ RS galaxies that we report is larger than that of $z=0$ ETG galaxies at $2.35\gtrsim\log_{10}\sigma\gtrsim 2.47$. The extrapolation of an intermediate-mass L-$\sigma$ relation towards the high-mass end in previous low-z works may be responsible for this disagreement. Evolutionary interpretation of this comparison is also subject to differences in the way the respective samples are selected; these differences can be mitigated in future work by analyzing $z=0$ SDSS data using the same framework presented in this paper. We also provide the sample PDF for the RS population (i.e. uncorrected for incompleteness), which is a key ingredient for gravitational lensing analyses using BOSS.
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EVOLUTION OF THE VELOCITY-Dispersion Function OF LUMINOUS RED GALAXIES: A HIERARCHICAL BAYESIAN MEASUREMENT
The Astronomical Journal, 2012Co-Authors: Yiping Shu, Adam S. Bolton, David J. Schlegel, Kyle S. Dawson, David A. Wake, Joel R. Brownstein, Jon Brinkmann, Benjamin A. WeaverAbstract:We present a hierarchical Bayesian determination of the velocity-Dispersion Function of approximately 430,000 massive luminous red galaxies observed at relatively low spectroscopic signal-to-noise ratio (S/N ∼ 3–5 per 69 km s −1 ) by the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. We marginalize over spectroscopic redshift errors, and use the full velocity-Dispersion likelihood Function for each galaxy to make a self-consistent determination of the velocity-Dispersion distribution parameters as a Function of absolute magnitude and redshift, correcting as well for the effects of broadband magnitude errors on our binning. Parameterizing the distribution at each point in the luminosity–redshift plane with a log-normal form, we detect significant evolution in the width of the distribution toward higher intrinsic scatter at higher redshifts. Using a subset of deep re-observations of BOSS galaxies, we demonstrate that our distribution-parameter estimates are unbiased regardless of spectroscopic S/N. We also show through simulation that our method introduces no systematic parameter bias with redshift. We highlight the advantage of the hierarchical Bayesian method over frequentist “stacking” of spectra, and illustrate how our measured distribution parameters can be adopted as informative priors for velocity-Dispersion measurements from individual noisy spectra.
M. A. Hellberg - One of the best experts on this subject based on the ideXlab platform.
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A new formulation and simplified derivation of the Dispersion Function for a plasma with a kappa velocity distribution
Physics of Plasmas, 2009Co-Authors: R. L. Mace, M. A. HellbergAbstract:A simplified derivation of the relationship between the Dispersion Function for a plasma with a kappa velocity distribution and the Gauss hypergeometric Function is presented. This derivation relies on only a few standard integrals. It naturally leads to a new integral representation for the Dispersion Function, which readily yields the power and Laurent series for it. The new integral representation is shown to be closely related to the Gordeyev integral for a kappa distribution.
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generalized plasma Dispersion Function for a plasma with a kappa maxwellian velocity distribution
Physics of Plasmas, 2002Co-Authors: M. A. Hellberg, R. L. MaceAbstract:A generalized plasma Dispersion Function has previously been obtained for waves in plasmas with isotropic kappa distributions for arbitrary real kappa [Mace and Hellberg, Phys. Plasmas 2, 2098 (1995)]. In many instances plasmas are found to have anisotropic power-law distributions, and hence a similar Dispersion Function for electrostatic waves in plasmas having a one-dimensional kappa distribution along a preferred direction in space, and a Maxwellian distribution perpendicular to it has now been developed. It is used to study the effect of superthermal electrons and ions on ion-acoustic waves propagating at an angle to a magnetic field. This Dispersion Function should find application to wave studies both in space plasmas, where the magnetic field defines a preferred direction, and in dusty plasma crystal studies, where the ion flow direction is unique.
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A Dispersion Function for plasmas containing superthermal particles
Physics of Plasmas, 1995Co-Authors: R. L. Mace, M. A. HellbergAbstract:It is now well known that space plasmas frequently contain particle components that exhibit high, or superthermal, energy tails with approximate power law distributions in velocity space. Such nonthermal distributions, with overabundances of fast particles, can be better fitted, for supra‐ and superthermal velocities, by generalized Lorentzian or kappa distributions, than by Maxwellians or one of their variants. Employing the kappa distribution, with real values of the spectral index κ, in place of the Maxwellian we introduce a new plasma Dispersion Function expected to be of significant importance in kinetic theoretical studies of waves in space plasmas. It is demonstrated that this Function is proportional to Gauss’ hypergeometric Function 2F1[1,2κ+2;κ+2;z] enabling the well‐established theory of the hypergeometric Function to be used to manipulate Dispersion relations. The reduction, for integer values of κ, to the less general so‐called modified plasma Dispersion Function [Phys. Fluids B 3, 1835 (1991...
R. L. Mace - One of the best experts on this subject based on the ideXlab platform.
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A new formulation and simplified derivation of the Dispersion Function for a plasma with a kappa velocity distribution
Physics of Plasmas, 2009Co-Authors: R. L. Mace, M. A. HellbergAbstract:A simplified derivation of the relationship between the Dispersion Function for a plasma with a kappa velocity distribution and the Gauss hypergeometric Function is presented. This derivation relies on only a few standard integrals. It naturally leads to a new integral representation for the Dispersion Function, which readily yields the power and Laurent series for it. The new integral representation is shown to be closely related to the Gordeyev integral for a kappa distribution.
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generalized plasma Dispersion Function for a plasma with a kappa maxwellian velocity distribution
Physics of Plasmas, 2002Co-Authors: M. A. Hellberg, R. L. MaceAbstract:A generalized plasma Dispersion Function has previously been obtained for waves in plasmas with isotropic kappa distributions for arbitrary real kappa [Mace and Hellberg, Phys. Plasmas 2, 2098 (1995)]. In many instances plasmas are found to have anisotropic power-law distributions, and hence a similar Dispersion Function for electrostatic waves in plasmas having a one-dimensional kappa distribution along a preferred direction in space, and a Maxwellian distribution perpendicular to it has now been developed. It is used to study the effect of superthermal electrons and ions on ion-acoustic waves propagating at an angle to a magnetic field. This Dispersion Function should find application to wave studies both in space plasmas, where the magnetic field defines a preferred direction, and in dusty plasma crystal studies, where the ion flow direction is unique.
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A Dispersion Function for plasmas containing superthermal particles
Physics of Plasmas, 1995Co-Authors: R. L. Mace, M. A. HellbergAbstract:It is now well known that space plasmas frequently contain particle components that exhibit high, or superthermal, energy tails with approximate power law distributions in velocity space. Such nonthermal distributions, with overabundances of fast particles, can be better fitted, for supra‐ and superthermal velocities, by generalized Lorentzian or kappa distributions, than by Maxwellians or one of their variants. Employing the kappa distribution, with real values of the spectral index κ, in place of the Maxwellian we introduce a new plasma Dispersion Function expected to be of significant importance in kinetic theoretical studies of waves in space plasmas. It is demonstrated that this Function is proportional to Gauss’ hypergeometric Function 2F1[1,2κ+2;κ+2;z] enabling the well‐established theory of the hypergeometric Function to be used to manipulate Dispersion relations. The reduction, for integer values of κ, to the less general so‐called modified plasma Dispersion Function [Phys. Fluids B 3, 1835 (1991...
Ernazar Abdikamalov - One of the best experts on this subject based on the ideXlab platform.
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polarization measurement analysis iii analysis of the polarization angle Dispersion Function with high precision polarization data
Astronomy and Astrophysics, 2016Co-Authors: D Alina, L Montier, I Ristorcelli, J P Bernard, F Levrier, Ernazar AbdikamalovAbstract:High precision polarization measurements, such as those from the Planck satellite, open new opportunities for the study of the magnetic field structure as traced by polarimetric measurements of the interstellar dust emission. The polarization parameters suffer from bias in the presence of measurement noise. It is critical to take into account all the information available in the data in order to accurately derive these parameters. In our previous work, we studied the bias on polarization fraction and angle, various estimators of these quantities, and their associated uncertainties. The goal of this paper is to characterize the bias on the polarization angle Dispersion Function that is used to study the spatial coherence of the polarization angle. We characterize for the first time the bias on the conventional estimator of the polarization angle Dispersion Function and show that it can be positive or negative depending on the true value. Monte Carlo simulations were performed to explore the impact of the noise properties of the polarization data, as well as the impact of the distribution of the true polarization angles on the bias. We show that in the case where the ellipticity of the noise in ( Q, U ) varies by less than 10%, one can use simplified, diagonal approximation of the noise covariance matrix. In other cases, the shape of the noise covariance matrix should be taken into account in the estimation of the polarization angle Dispersion Function. We also study new estimators such as the dichotomic and the polynomial estimators. Though the dichotomic estimator cannot be directly used to estimate the polarization angle Dispersion Function, we show that, on the one hand, it can serve as an indicator of the accuracy of the conventional estimator and, on the other hand, it can be used for deriving the polynomial estimator. We propose a method for determining the upper limit of the bias on the conventional estimator of the polarization angle Dispersion Function. The method is applicable to any linear polarization data set for which the noise covariance matrices are known.
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Polarization measurement analysis III. Analysis of the polarization angle Dispersion Function with high precision polarization data
Astronomy & Astrophysics, 2016Co-Authors: D Alina, L Montier, I Ristorcelli, J P Bernard, F Levrier, Ernazar AbdikamalovAbstract:High precision polarization measurements open new opportunities for the study of the magnetic field structure as traced by polarimetric measurements of the interstellar dust emission. Polarization parameters suffer from bias in the presence of measurement noise. It is critical to take into account all the information available in the data in order to accurately derive these parameters. The goal of this paper is to characterize the bias on the polarization angle Dispersion Function that is used to study the spatial coherence of the polarization angle. We characterize, for the first time, the bias on the conventional estimator of the polarization angle Dispersion Function (S hereafter) and show that it can be positive or negative depending on the true value. Monte Carlo simulations are performed in order to explore the impact of the noise properties of the polarization data, as well as the impact of the distribution of the true polarization angles on the bias. We show that in the case where the ellipticity of the noise in (Q, U) varies by less than 10 percent, one can use simplified, diagonal approximation of the noise covariance matrix. In other cases, the shape of the noise covariance matrix should be taken into account in the estimation of S. We also study new estimators such as the dichotomic and the polynomial estimators. Though the dichotomic estimator cannot be directly used to estimate S, we show that, on the one hand, it can serve as an indicator of the accuracy of the conventional estimator and, on the other hand, it can be used for deriving the polynomial estimator. We propose a method for determining the upper limit of the bias on the conventional estimator of S. The method is applicable to any linear polarization data set for which the noise covariance matrices are known.
D Alina - One of the best experts on this subject based on the ideXlab platform.
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polarization measurement analysis iii analysis of the polarization angle Dispersion Function with high precision polarization data
Astronomy and Astrophysics, 2016Co-Authors: D Alina, L Montier, I Ristorcelli, J P Bernard, F Levrier, Ernazar AbdikamalovAbstract:High precision polarization measurements, such as those from the Planck satellite, open new opportunities for the study of the magnetic field structure as traced by polarimetric measurements of the interstellar dust emission. The polarization parameters suffer from bias in the presence of measurement noise. It is critical to take into account all the information available in the data in order to accurately derive these parameters. In our previous work, we studied the bias on polarization fraction and angle, various estimators of these quantities, and their associated uncertainties. The goal of this paper is to characterize the bias on the polarization angle Dispersion Function that is used to study the spatial coherence of the polarization angle. We characterize for the first time the bias on the conventional estimator of the polarization angle Dispersion Function and show that it can be positive or negative depending on the true value. Monte Carlo simulations were performed to explore the impact of the noise properties of the polarization data, as well as the impact of the distribution of the true polarization angles on the bias. We show that in the case where the ellipticity of the noise in ( Q, U ) varies by less than 10%, one can use simplified, diagonal approximation of the noise covariance matrix. In other cases, the shape of the noise covariance matrix should be taken into account in the estimation of the polarization angle Dispersion Function. We also study new estimators such as the dichotomic and the polynomial estimators. Though the dichotomic estimator cannot be directly used to estimate the polarization angle Dispersion Function, we show that, on the one hand, it can serve as an indicator of the accuracy of the conventional estimator and, on the other hand, it can be used for deriving the polynomial estimator. We propose a method for determining the upper limit of the bias on the conventional estimator of the polarization angle Dispersion Function. The method is applicable to any linear polarization data set for which the noise covariance matrices are known.
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Polarization measurement analysis III. Analysis of the polarization angle Dispersion Function with high precision polarization data
Astronomy & Astrophysics, 2016Co-Authors: D Alina, L Montier, I Ristorcelli, J P Bernard, F Levrier, Ernazar AbdikamalovAbstract:High precision polarization measurements open new opportunities for the study of the magnetic field structure as traced by polarimetric measurements of the interstellar dust emission. Polarization parameters suffer from bias in the presence of measurement noise. It is critical to take into account all the information available in the data in order to accurately derive these parameters. The goal of this paper is to characterize the bias on the polarization angle Dispersion Function that is used to study the spatial coherence of the polarization angle. We characterize, for the first time, the bias on the conventional estimator of the polarization angle Dispersion Function (S hereafter) and show that it can be positive or negative depending on the true value. Monte Carlo simulations are performed in order to explore the impact of the noise properties of the polarization data, as well as the impact of the distribution of the true polarization angles on the bias. We show that in the case where the ellipticity of the noise in (Q, U) varies by less than 10 percent, one can use simplified, diagonal approximation of the noise covariance matrix. In other cases, the shape of the noise covariance matrix should be taken into account in the estimation of S. We also study new estimators such as the dichotomic and the polynomial estimators. Though the dichotomic estimator cannot be directly used to estimate S, we show that, on the one hand, it can serve as an indicator of the accuracy of the conventional estimator and, on the other hand, it can be used for deriving the polynomial estimator. We propose a method for determining the upper limit of the bias on the conventional estimator of S. The method is applicable to any linear polarization data set for which the noise covariance matrices are known.
