Related papers: DIAMONDS: a new Bayesian Nested Sampling tool. App…
The NASA Kepler mission has been continuously monitoring the same field of the sky since the successful launch in March 2009, providing high-quality stellar lightcurves that are excellent data for asteroseismology, far superior to any other…
High-precision frequencies of acoustic modes in red giant stars are now available thanks to the long observing length and high-quality of the light curves provided by the NASA Kepler mission, thus allowing to probe the interior of evolved…
Metal-poor stars are key to understanding the first stellar generation in the Galaxy. Asteroseismic characterisation of red giants has traditionally relied on global seismic parameters, not the full spectrum of individual oscillation modes.…
We aim to detect and characterise solar-like oscillations in bright naked-eye (V<6) main-sequence (MS) and subgiant stars observed by TESS. We seek to expand the current benchmark sample of oscillators, provide accurate global asteroseismic…
Context: Massive amounts of spectroscopic data obtained by stellar surveys are feeding an ongoing revolution in our knowledge of stellar and Galactic astrophysics. Analysing these data sets to extract the best possible astrophysical…
The Kepler space telescope yielded unprecedented data for the study of solar-like oscillations in other stars. The large samples of multi-year observations posed an enormous data analysis challenge that has only recently been surmounted.…
Star-galaxy classification is one of the most fundamental data-processing tasks in survey astronomy, and a critical starting point for the scientific exploitation of survey data. For bright sources this classification can be done with…
Multi-symplectic diamond schemes proposed by McLachlan and Wilkins (2015) provide a framework for the numerical integration of Hamiltonian partial differential equations, combining local implicitness with high-order accuracy and discrete…
We introduce a new class of sequential Monte Carlo methods which reformulates the essence of the nested sampling method of Skilling (2006) in terms of sequential Monte Carlo techniques. Two new algorithms are proposed, nested sampling via…
Context. The analysis of stellar oscillations is one of the most reliable ways to probe stellar interiors. Recent space missions such as Kepler have provided us with an opportunity to study these oscillations with unprecedented detail. For…
Oxygen-terminated diamond has a wide breadth of applications, which include stabilizing near-surface color centers, semiconductor devices, and biological sensors. Despite the vast literature on characterizing functionalization groups on…
Approximate Markov chain Monte Carlo (MCMC) offers the promise of more rapid sampling at the cost of more biased inference. Since standard MCMC diagnostics fail to detect these biases, researchers have developed computable Stein discrepancy…
Asteroseismic observations are crucial to constrain stellar models with precision. Bayesian Estimation of STellar Parameters (BESTP) is a tool that utilizes Bayesian statistics and nested sampling Monte Carlo algorithm to search for the…
We present a homogeneous catalog of global asteroseismic parameters and derived stellar parameters for 765 Kepler main-sequence and subgiant stars. The catalog was produced by re-analyzing all available Kepler DR25 short-cadence data using…
Systems in which two oscillating stars are observed in the same light curve, so-called asteroseismic binaries (ABs), arise from either chance alignments or gravitationally bound stars. In the latter case, ABs offer a novel way to find…
We present dynesty, a public, open-source, Python package to estimate Bayesian posteriors and evidences (marginal likelihoods) using Dynamic Nested Sampling. By adaptively allocating samples based on posterior structure, Dynamic Nested…
During the survey phase of the Kepler mission, several thousands of stars were observed in short cadence, allowing the detection of solar-like oscillations in more than 500 main-sequence and sub-giant stars. Later, the Kepler Science Office…
Spin squeezed states provide a seminal example of how the structure of quantum mechanical correlations can be controlled to produce metrologically useful entanglement. Such squeezed states have been demonstrated in a wide variety of…
Bayesian inference with nested sampling requires a likelihood-restricted prior sampling method, which draws samples from the prior distribution that exceed a likelihood threshold. For high-dimensional problems, Markov Chain Monte Carlo…
The newly established Heisenberg limit in arbitrary waveform estimation is quite different with parameter estimation and shows a unique characteristic of a future quantum version of oscilloscope. However, it is still a non-trivial challenge…