Related papers: The Luminous Convolution Model
Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and…
Rotation information for spiral galaxies can be obtained through the observation of different spectral lines. While the Halpha(6563 A) line is often used for galaxies with low to moderate redshifts, it is redshifted into the near-infrared…
We obtain cosmological constraints from a measurement of the spherically averaged power spectrum (PS) of the distribution of about 90000 luminous red galaxies (LRGs) across 7646 deg2 in the Northern Galactic Cap from the DR7 of the SDSS.…
New analysis confirms our earlier claim [1], [7] of circles of notably low temperature variance, often in concentric sets, in the cosmic microwave background (CMB), discernable in WMAP data. Their reality can be interpreted as evidence of…
The rich statistics of galaxy rotations as captured by the velocity function (VF) provides invaluable constraints on galactic baryon physics and the nature of dark matter (DM). However, the comparison of observed galaxy rotations against…
Estimating a reliable covariance matrix for correlation functions of galaxies is a crucial task to obtain accurate cosmological constraints from galaxy surveys. We generate 2,000 independent lightcone mock luminous red galaxy (LRGs)…
We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for…
Galactic rotation curve is a powerful indicator of the state of the gravitational field within a galaxy. The flatness of these curves indicates the presence of dark matter in galaxies and their clusters. In this paper, we focus on the…
This paper advances a general proposal for testing non-standard cosmological models by means of observational relations of cosmological point sources in some specific waveband, and their use in the context of the data provided by the galaxy…
We propose a Multimodal Machine Learning method for estimating the Photometric Redshifts of quasars (PhotoRedshift-MML for short), which has long been the subject of many investigations. Our method includes two main models, i.e. the feature…
We make a detailed investigation of the properties of Lyman-break galaxies (LBGs) in the LambdaCDM model. We present predictions for two published variants of the GALFORM semi-analytical model: the Baugh et al. (2005) model, which has star…
We use the Millennium Simulation to measure the cross-correlation between halo centres and mass (or equivalently the average density profiles of dark haloes) in a LCDM cosmology. We present results for radii in the range 10 kpc/h < r < 30…
We present predictions for the evolution of the galaxy luminosity function, number counts and redshift distributions in the IR based on the Lambda-CDM cosmological model. We use the combined GALFORM semi-analytical galaxy formation model…
We follow the evolution of the galaxy population in a Lambda-CDM cosmology by means of high-resolution N-body simulations in which the formation of galaxies and their observable properties are calculated using a semi-analytic model. We…
We present a new version of the GALFORM semi-analytical model of galaxy formation. This brings together several previous developments of GALFORM into a single unified model, including a different initial mass function (IMF) in quiescent…
We introduce a novel technique for empirically understanding galaxy evolution. We use empirically determined stellar evolution models to predict the past evolution of the Sloan Digital Sky Survey (SDSS-II) Luminous Red Galaxy (LRG) sample…
Weak gravitational lensing is a powerful probe of the dark sector, once measurement systematic errors can be controlled. In Refregier & Amara (2014), a calibration method based on forward modeling, called MCCL, was proposed. This relies on…
We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…
Predicting the colors of Luminous Red Galaxies (LRGs) in the Sloan Digital Sky Survey (SDSS) has been a long-standing problem. The g,r,i colors of LRGs are inconsistent with stellar population models over the redshift range 0.1<z<0.7. The…
This work presents a methodological approach to generate realistic $\gamma$-ray light curves of pulsars, resembling reasonably well the observational ones observed by the Fermi-Large Area Telescope instrument, fitting at the same time their…