相关论文: Detrending Exoplanetary Transit Light Curves with …

We develop a novel human trajectory prediction system that incorporates the scene information (Scene-LSTM) as well as individual pedestrian movement (Pedestrian-LSTM) trained simultaneously within static crowded scenes. We superimpose a…

Knowledge of an exoplanet's oblateness and obliquity would give clues about its formation and internal structure. In principle, a light curve of a transiting planet bears information about the planet's shape, but previous work has shown…

The ability to observe extrasolar planets transiting their stars has profoundly changed our understanding of these planetary systems. However, these measurements depend on how well we understand the properties of the host star, such as…

In the new era of very large telescopes, where data is crucial to expand scientific knowledge, we have witnessed many deep learning applications for the automatic classification of lightcurves. Recurrent neural networks (RNNs) are one of…

Automated planetary transit detection has become vital to prioritize candidates for expert analysis given the scale of modern telescopic surveys. While current methods for short-period exoplanet detection work effectively due to periodicity…

A significant fraction of an exoplanet transit model evaluation time is spent calculating projected distances between the planet and its host star. This is a relatively fast operation for a circular orbit, but slower for an eccentric one.…

Public transportation system commuters are often interested in getting accurate travel time information to plan their daily activities. However, this information is often difficult to predict accurately due to the irregularities of road…

Transit timing variations (TTVs) of exoplanets are normally interpreted as the consequence of gravitational interaction with additional bodies in the system. However, TTVs can also be caused by deformations of the system transits by…

Making accurate motion prediction of surrounding agents such as pedestrians and vehicles is a critical task when robots are trying to perform autonomous navigation tasks. Recent research on multi-modal trajectory prediction, including…

We present Latent Diffeomorphic Dynamic Mode Decomposition (LDDMD), a new data reduction approach for the analysis of non-linear systems that combines the interpretability of Dynamic Mode Decomposition (DMD) with the predictive power of…

Out of the known transiting extrasolar planets, the majority are gas giants orbiting their host star at close proximity. Both theoretical and observational studies support the hypothesis that such bodies emit significant amounts of flux…

We present a direct method for isolating the component of the starlight blocked by a planet as it transits its host star, and apply it to spectra of the bright transiting planet HD 189733b. We model the global shape of the stellar…

Various studies that address the compressed sensing problem with Multiple Measurement Vectors (MMVs) have been recently carried. These studies assume the vectors of the different channels to be jointly sparse. In this paper, we relax this…

We present photometry of HD 189733 during eight transits of its close-in giant planet, and out-of-transit photometry spanning two years. Using the transit photometry, we determine the stellar and planetary radii and the photometric…

The properties of a transiting planet's host star are written in its transit light curve. The light curve can reveal the stellar density and the limb darkening profile in addition to the characteristics of the planet and its orbit. For…

Long Short-Term Memory (LSTM) is a special class of recurrent neural network, which has shown remarkable successes in processing sequential data. The typical architecture of an LSTM involves a set of states and gates: the states retain…

Short-term traffic forecasting based on deep learning methods, especially long short-term memory (LSTM) neural networks, has received much attention in recent years. However, the potential of deep learning methods in traffic forecasting has…

We present a method that employs the secondary eclipse light curves of transiting extrasolar planets to probe the spatial variation of their thermal emission. This technique permits an observer to resolve the surface of the planet without…

Context. Correlated noise in exoplanet light curves, such as noise from stellar activity, convection noise, and instrumental noise, distorts the exoplanet transit light curves and leads to biases in the best-fit transit parameters. An…

We present a technique for verifying or refuting exoplanet candidates from the Transiting Exoplanet Survey Satellite (TESS) mission by searching for nearby eclipsing binary stars using higher-resolution archival images from ground-based…