相关论文: A Gaussian process model for stellar activity in 2…
[Abridged] Context. Stellar activity is an important source of systematic errors and uncertainties in the characterization of exoplanets. Most of the techniques used to correct for this activity focus on an ad hoc data reduction. Aims. We…
We introduce graph gamma process (GGP) linear dynamical systems to model real-valued multivariate time series. For temporal pattern discovery, the latent representation under the model is used to decompose the time series into a…
The detection and characterisation of Earth-like planets with Doppler signals of the order of 1 m/s currently represent one of the greatest challenge for extrasolar-planet hunters. As results for such findings are often controversial, it is…
A Gaussian process (GP)-based methodology is proposed to emulate complex dynamical computer models (or simulators). The method relies on emulating the numerical flow map of the system over an initial (short) time step, where the flow map is…
In G dwarfs, the surface distribution, coverage and lifetimes of starspots deviate from solar-like patterns as the rotation rate increases. We set up a numerical platform which includes the large-scale rotational and surface flow effects,…
Aims. We observed the $\tau$ Boo system with the HARPS-N spectrograph to test a new observational strategy aimed at jointly studying asteroseismology, the planetary orbit, and star-planet magnetic interaction. Methods. We collected…
The HARPS/HARPS-N Data Reduction Software (DRS) relies on the cross-correlation between the observed spectra and a suitable stellar mask to compute a cross-correlation function (CCF) to be used both for the radial velocity (RV) computation…
Aims: We investigate whether bisectors derived from cross-correlation functions (CCF) of single-exposure spectra can be used to provide information on stellar atmospheres, and whether they can be used to discriminate between radial velocity…
Dynamic behavior of traffic adversely affect the performance of the prediction models in intelligent transportation applications. This study applies Gaussian processes (GPs) to traffic speed prediction. Such predictions can be used by…
Investigating the relationship, particularly the lead-lag effect, between time series is a common question across various disciplines, especially when uncovering biological process. However, analyzing time series presents several…
Gaussian process (GP) modulated Cox processes are widely used to model point patterns. Existing approaches require a mapping (link function) between the unconstrained GP and the positive intensity function. This commonly yields solutions…
In this work we review the application of the theory of Gaussian processes to the modeling of noise in pulsar-timing data analysis, and we derive various useful and optimized representations for the likelihood expressions that are needed in…
In this paper, we explore the application of Gaussian Processes (GPs) for predicting mean-reverting time series with an underlying structure, using relatively unexplored functional and augmented data structures. While many conventional…
Context: Chromospheric activity produces both photometric and spectroscopic variations that can be mistaken as planets. Large spots crossing the stellar disc can produce planet-like periodic variations in the light curve of a star. These…
Stellar activity is the major roadblock on the path to finding true Earth-analogue planets with the Doppler technique. Thus, identifying new indicators that better trace magnetic activity (i.e. faculae and spots) is crucial to aid in…
Estimating causal effects in quasi-experiments with spatio-temporal panel data often requires adjusting for unmeasured confounding that varies across space and time. Gaussian Processes (GPs) offer a flexible, nonparametric modeling approach…
Transits of exoplanets across cool stars contain blended information about structures on the stellar surface and about the planetary body and atmosphere. To advance understanding of how this information is entangled, a surface-flux…
Astrophysical data, in the domains of time, involve a wide range of stellar variability phenomena, among them the magnetic activity of the order of a few hours until the signature of an extra-solar planet which can cover a scale of time of…
Continuous-time state estimation is gaining in popularity due to its abilities to provide smooth solutions, handle asynchronous sensors, and interpolate between data points. While there are two main paradigms, parametric (e.g., temporal…
Sharp structural variations induce specific signatures on stellar pulsations that can be studied to infer localised information on the stratification of the star. This information is key to improve our understanding of the physical…