相关论文: Beyond the best-fit parameter: new insight on gala…
In this paper we discuss the possibility to measure the Hubble parameter and the slope of galaxy density profiles using future supernova data. With future supernova surveys such as SNAP, large numbers of core collapse supernovae will be…
We investigate in detail the effects of sampling on our ability to accurately reconstruct the distribution of galaxies from galaxy surveys. We use a simple probability theory approach, Bayesian classifier theory and Bayesian transition…
Gravitational lensing has now become a popular tool to measure the mass distribution of structures in the Universe on various scales. Here we focus on the study of galaxy's scale dark matter halos with galaxy-galaxy lensing techniques:…
Accurate analyses of present and next-generation galaxy surveys require new ways to handle effects of non-linear gravitational structure formation in data. To address these needs we present an extension of our previously developed algorithm…
A high accuracy photometric reduction method is needed to take full advantage of the potential of the transit method for the detection and characterization of exoplanets, especially in deep crowded fields. In this context, we present…
Research in many areas of modern physics such as, e.g., indirect searches for dark matter and particle acceleration in SNR shocks, rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays,…
Luminosity profiles of galaxies acting as strong gravitational lenses can be tricky to study. Indeed, strong gravitational lensing images display several lensed components, both point-like and diffuse, around the lensing galaxy. Those…
We describe the development of a new toolkit for data analysis. The analysis package is based on Bayes' Theorem, and is realized with the use of Markov Chain Monte Carlo. This gives access to the full posterior probability distribution.…
Based on the most complete sample of Galactic open star clusters up to 1.8 kpc, we performed statistical analysis of the distribution of open cluster parameters in order to understand the Galactic structure. The geometrical characteristics…
We use the GALPROP model for cosmic-ray (CR) propagation to obtain our best prediction of the Galactic component of gamma rays, and show that away from the Galactic plane it gives an accurate prediction of the observed EGRET intensities. On…
In this work we explore the possibility of applying machine learning methods designed for one-dimensional problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly…
Structural properties posses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a…
We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation…
Conventional approaches to cosmology inference from galaxy redshift surveys are based on n-point functions, which are under rigorous perturbative control on sufficiently large scales. Here, we present an alternative approach, which employs…
Dissecting the underlying structure of galaxies is of main importance in the framework of galaxy formation and evolution theories. While a classical bulge+disc decomposition of disc galaxies is usually taken as granted, this is only rarely…
We present a novel approach to photometric redshifts, one that merges the advantages of both the template fitting and empirical fitting algorithms, without any of their disadvantages. This technique derives a set of templates, describing…
We present a Bayesian inference approach to estimating the cumulative mass profile and mean squared velocity profile of a globular cluster given the spatial and kinematic information of its stars. Mock globular clusters with a range of…
Image decomposition of galaxies is now routinely used to estimate the structural parameters of galactic components. In this work, I address questions on the reliability of this technique. In particular, do bars and AGN need to be taken into…
We demonstrate a new multi-wavelength technique for two-dimensional parametric modelling of galaxy surface-brightness profiles, which we have incorporated into the widely used software GALFIT. Our new method, named GALFITM, extends…
In this paper, we propose a path following replicator dynamic, and investigate its potentials in uncovering the underlying cluster structure of a graph. The proposed dynamic is a generalization of the discrete replicator dynamic. The…