Related papers: Bayesian peak-bagging of solar-like oscillators us…
Space observatories such as $\textit{Kepler}$ have provided data that can potentially revolutionise our understanding of stars. Through detailed asteroseismic analyses we are capable of determining fundamental stellar parameters and reveal…
Since the advent of the space-based photometric missions such as CoRoT and NASA's Kepler, asteroseismology has acquired a central role in our understanding about stellar physics. The Kepler spacecraft, especially, is still releasing…
\Kepler has revolutionised our understanding of both exoplanets and their host stars. Asteroseismology is a valuable tool in the characterisation of stars and \Kepler is an excellent observing facility to perform asteroseismology. Here we…
The peak bagging analysis, namely the fitting and identification of single oscillation modes in stars' power spectra, coupled to the very high-quality light curves of red giant stars observed by Kepler, can play a crucial role for studying…
In the context of high-quality asteroseismic data provided by the NASA Kepler mission, we developed a new code, termed Diamonds (high-DImensional And multi-MOdal NesteD Sampling), for fast Bayesian parameter estimation and model comparison…
The currently available Kepler light curves contain an outstanding amount of information but a detailed analysis of the individual oscillation modes in the observed power spectra, also known as peak bagging, is computationally demanding and…
The presence of mixed modes makes subgiants excellent targets for asteroseismology, providing a probe for the internal structure of stars. Here we study 36 \emph{Kepler} subgiants with solar-like oscillations and report their oscillation…
Bayesian methods are becoming more widely used in asteroseismic analysis. In particular, they are being used to determine oscillation frequencies, which are also commonly found by Fourier analysis. It is important to establish whether the…
Stellar oscillations can provide a wealth of information about a star, which can be extracted from observed time series of the star's brightness or radial velocity. In this paper we address the question of how to extract as much information…
To exploit the full potential of Kepler light curves, sophisticated and robust analysis tools are now required more than ever. Characterizing single stars with an unprecedented level of accuracy and subsequently analyzing stellar…
Since the middle of the 1940's scientists have used Monte Carlo (MC) simulations to obtain information about physical processes. This has proved a accurate and and reliable method to obtain this information. Through out resent years…
Determining the physical characteristics of a star is an inverse problem consisting in estimating the parameters of models for the stellar structure and evolution, knowing certain observable quantities. We use a Bayesian approach to solve…
Since the asteroseismic revolution, availability of efficient and reliable methods to extract stellar-oscillation mode parameters has been one of the keystone of modern stellar physics. In the helio- and asteroseismology fields, these…
Bayesian max-margin models have shown superiority in various practical applications, such as text categorization, collaborative prediction, social network link prediction and crowdsourcing, and they conjoin the flexibility of Bayesian…
Context: The detection and identification of oscillation modes (in terms of their $\ell$, $m$ and successive $n$) is a great challenge for present and future asteroseismic space missions. The "peak tagging" is an important step in the…
High precision and long-lasting \emph{Kepler} data enabled us to estimate stellar properties with asteroseismology as an accurate tool. We performed asteroseismic analysis on six solar-like stars observed by the \emph{Kepler} mission: KIC…
With the advance in computational resources, Bayesian inference is increasingly becoming the standard tool of practise in GW astronomy. However, algorithms such as Markov Chain Monte Carlo (MCMC) require a large number of iterations to…
Radial velocity (RV) planet searches are increasingly finding planets with small velocity amplitudes, with long orbital periods, or in multiple planet systems. Bayesian inference has the potential to improve the interpretation of existing…
A Bayesian probability based approach is applied to the problem of detecting and parameterizing oscillations in the upper solar atmosphere for the first time. Due to its statistical origin, this method provides a mechanism for determining…
Markov Chain Monte Carlo (MCMC) methods have revolutionised Bayesian data analysis over the years by making the direct computation of posterior probability densities feasible on modern workstations. However, the calculation of the prior…