相关论文: Identifying Potential Exomoon Signals with Convolu…

In this paper we investigate the detectability of a habitable-zone exomoon around various configurations of exoplanetary systems with the Kepler Mission or photometry of approximately equal quality. We calculate both the predicted transit…

Despite their successes in the field of self-learning AI, Convolutional Neural Networks (CNNs) suffer from having too many trainable parameters, impacting computational performance. Several approaches have been proposed to reduce the number…

The Transiting Exoplanet Survey Satellite (TESS) is surveying a large fraction of the sky, generating a vast database of photometric time series data that requires thorough analysis to identify exoplanetary transit signals. Automated…

Despite the ever-growing number of exoplanets discovered and the extensive analyses carried out to find their potential satellites, only two exomoon candidates, Kepler-1625b-i and Kepler-1708 b-i, have been discovered to date. A…

The TESS mission produces a large amount of time series data, only a small fraction of which contain detectable exoplanetary transit signals. Deep learning techniques such as neural networks have proved effective at differentiating…

Recently Kipping (2021) identified the so-called "exomoon corridor", a potentially powerful new tool for identifying possible exomoon hosts, enabled by the observation that fully half of all planets hosting an exomoon will exhibit transit…

The high-precision photometry from NASA's Kepler and TESS missions has revolutionized exoplanet detection, enabling the discovery of over 5500 confirmed exoplanets via the transit method and around 10000 additional candidates awaiting…

Directly imaging exoplanets is a formidable challenge due to extreme contrast ratios and quasi-static speckle noise, motivating the exploration of advanced post-processing methods. While Convolutional Neural Networks (CNNs) have shown…

Despite the discovery of thousands of exoplanets, no exomoons have been detected so far. We test a recently developed method for exomoon search, the orbital sampling effect (OSE), using the full exoplanet photometry from the Kepler Space…

If a transiting exoplanet has a moon, that moon could be detected directly from the transit it produces itself, or indirectly via the transit timing variations it produces in its parent planet. There is a range of parameter space where the…

The search for extrasolar planets is strongly motivated by the goal of characterizing how frequent habitable worlds and life may be within the Galaxy. Whilst much effort has been spent on searching for Earth-like planets, large moons may…

NASA's Kepler Space Telescope was designed to determine the frequency of Earth-sized planets orbiting Sun-like stars, but these planets are on the very edge of the mission's detection sensitivity. Accurately determining the occurrence rate…

Recent developments in computational power and machine learning techniques motivate their use in many different astrophysical research areas. Consequently, many machine learning models have been trained to classify exoplanet transit signals…

Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential…

Many attempts have already been made for detecting exomoons around transiting exoplanets but the first confirmed discovery is still pending. The experience that have been gathered so far allow us to better optimize future space telescopes…

It has recently been demonstrated that deep learning has significant potential to automate parts of the exoplanet detection pipeline using light curve data from satellites such as Kepler \cite{borucki2010kepler} \cite{koch2010kepler} and…

Never before has the detection and characterization of exoplanets via transit photometry been as promising and feasible as it is now, due to the increasing breadth and sensitivity of time domain optical surveys. Past works have made use of…

We examined which exo-systems contain moons that may be detected in transit. We numerically modeled transit light curves of Earth-like and giant planets that cointain moons with 0.005--0.4 Earth-mass. The orbital parameters were randomly…

We describe a new metric that uses machine learning to determine if a periodic signal found in a photometric time series appears to be shaped like the signature of a transiting exoplanet. This metric uses dimensionality reduction and…

We introduce a new machine learning based technique to detect exoplanets using the transit method. Machine learning and deep learning techniques have proven to be broadly applicable in various scientific research areas. We aim to exploit…