相关论文: Beyond the best-fit parameter: new insight on gala…

Precise analyses of the statistical and scaling properties of galaxy distribution are essential to elucidate the large-scale structure of the universe. Given the ongoing debate on its statistical features, the development of statistical…

In this work we develop a new propagation model for the Galactic cosmic rays based on the GALPROP code, including contributions from dark matter annihilation. The model predicts compatible Galactic diffuse $\gamma$ ray spectra with EGRET…

The GLAST satellite mission will study the gamma ray sky with considerably greater exposure than its predecessor EGRET. In addition, it will be capable of measuring the arrival directions of gamma rays with much greater precision. These…

In the field of multi-messenger astronomy, Bayesian inference is commonly adopted to compare the compatibility of models given the observed data. However, to describe a physical system like neutron star mergers and their associated…

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…

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 study a family of parametric statistical models based on gamma distributions, which do give realistic descriptions for other stochastic porous media. Gamma distributions contain as a special case the exponential distributions, which…

Various programs aimed at exploring the still largely unknown low surface brightness Universe with deep imaging optical surveys have recently started. They open a new window for studies of galaxy evolution, pushing the technique of galactic…

We introduce EXOFIT, a Bayesian tool for estimating orbital parameters of extrasolar planets from radial velocity measurements. EXOFIT can search for either one or two planets at present. EXOFIT employs Markov Chain Monte Carlo method…

We describe application of the `shapelet' linear decomposition of galaxy images to morphological classification using images of $\sim$ 3000 galaxies from the Sloan Digital Sky Survey. After decomposing the galaxies we perform a principal…

Gaussian processes are the gold standard for many real-world modeling problems, especially in cases where a model's success hinges upon its ability to faithfully represent predictive uncertainty. These problems typically exist as parts of…

[abridged] We present a statistical exploration of the parameter space of the De Lucia and Blaizot version of the Munich semi-analytic model built upon the millennium dark matter simulation. This is achieved by applying a Monte Carlo Markov…

Current methods for learning graphical models with latent variables and a fixed structure estimate optimal values for the model parameters. Whereas this approach usually produces overfitting and suboptimal generalization performance,…

In the gravitational-wave analysis of pulsar-timing-array datasets, parameter estimation is usually performed using Markov Chain Monte Carlo methods to explore posterior probability densities. We introduce an alternative procedure that…

Measurements of the galaxy power spectrum contain a wealth of information about the Universe. Its optimal extraction is vital if we are to truly understand the micro-physical nature of dark matter and dark energy. In Smith & Marian (2015)…

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…

We present a percent-level accurate model of the line-of-sight velocity distribution of galaxies around dark matter halos as a function of projected radius and halo mass. The model is developed and tested using synthetic galaxy catalogs…

Cross-correlating the gamma-ray background with local galaxy catalogs potentially gives stringent constraints on dark matter annihilation. We provide updated theoretical estimates of sensitivities to the annihilation cross section from…

We use the GALPROP model for cosmic-ray propagation to obtain a new estimate 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 in the energy…

The advantages of sequential Monte Carlo (SMC) are exploited to develop parameter estimation and model selection methods for GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) style models. It provides an alternative method…