Related papers: Line Profiles from Discrete Kinematic Data
The Gaussian linear model provides a unique way to obtain the posterior probability distribution as well as the Bayesian evidence analytically. Considering the expansion rate data, the Gaussian linear model can be applied for $\Lambda$CDM,…
Model fitting is frequently used to determine the shape of galaxies and the point spread function, for examples, in weak lensing analyses or morphology studies aiming at probing the evolution of galaxies. However, the number of parameters…
We present a generalisation of surface photometry to the higher-order moments of the line-of-sight velocity distribution of galaxies observed with integral-field spectrographs. The generalisation follows the approach of surface photometry…
Location estimation is a central problem in functional data analysis. In this paper, we investigate penalized spline estimators of location for discretely sampled functional data under a broad class of convex loss functions. Our framework…
We forecast parameter uncertainties on the mass profile of a typical Milky Way dwarf spheroidal (dSph) galaxy using the spherical Jeans Equation and Fisher matrix formalism. We show that radial velocity measurements for 1000 individual…
Observed and simulated galaxies exhibit a significant variation in their velocity dispersion profiles. We examine the inner and outer slopes of stellar velocity dispersion profiles using integral field spectroscopy data from two surveys,…
Dynamical self-consistent constraints deduced from the Boltzmann equation are necessary to analyse and interpret kinematic data in the Galaxy. It has been shown that the standard epicycle theory approach, a first order theory to estimate…
We consider large non-Hermitian random matrices $X$ with complex, independent, identically distributed centred entries and show that the linear statistics of their eigenvalues are asymptotically Gaussian for test functions having…
We develop a transfer matrix formalism to visualize the framing of discrete piecewise linear curves in three dimensional space. Our approach is based on the concept of an intrinsically discrete curve, which enables us to more effectively…
Advances in optical astrometry allow us to infer the non-radial kinematic structure of the Universe directly from observations. Here I use a supervised machine learning neural network method to predict 1.57 million redshifts based on…
This paper develops an in-depth treatment concerning the problem of approximating the Gaussian smoothing and Gaussian derivative computations in scale-space theory for application on discrete data. With close connections to previous…
The space of images can be equipped with a Riemannian metric measuring both the cost of transport of image intensities and the variation of image intensities along motion lines. The resulting metamorphosis model was introduced and analyzed…
Numerical simulations within a cold dark matter (DM) cosmology form halos whose density profiles have a steep inner slope (`cusp'), yet observations of galaxies often point towards a flat central `core'. We develop a convolutional mixture…
This paper describes a method for quantitatively comparing an N-body model with a sample of discrete kinematic data. The comparison has two stages: (i) finding the optimum scaling and orientation of the model relative to the data; and (ii)…
In the past several years high resolution kinematic data sets from Milky Way satellite galaxies have confirmed earlier indications that these systems are dark matter dominated objects. Further understanding of what these galaxies reveal…
Studies of strong gravitational lensing in current and upcoming wide and deep photometric surveys, and of stellar kinematics from (integral-field) spectroscopy at increasing redshifts, promise to provide valuable constraints on galaxy…
Measurements of radial velocity variations from the spectroscopic monitoring of stars and their companions are essential for a broad swath of astrophysics, providing access to the fundamental physical properties that dictate all phases of…
A simple algorithm is presented for the calculation of the projected line-of-sight velocity profiles (VPs) of non-rotating anisotropic spherical stellar dynamical models with a phase-space distribution function of the Osipkov-Merritt type.…
The line-of-sight peculiar velocities are good indicators of the gravitational fluctuation of the density field. Techniques have been developed to extract cosmological information from the peculiar velocities in order to test the…
Gauss-Hermite and Gauss-Laguerre ("shapelet") decompositions of images have become important tools in galaxy modeling, particularly for the purpose of extracting ellipticity and morphological information from astronomical data. However, the…