Related papers: A Machine Learning approach for correcting radial …
One of the main obstacles in exoplanet detection when using the radial velocity (RV) technique is the presence of stellar activity signal induced by magnetic regions. In this context, a realistic simulated dataset that can provide…
The radial velocity method is one of the most successful techniques for detecting exoplanets. It works by detecting the velocity of a host star induced by the gravitational effect of an orbiting planet, specifically the velocity along our…
Twenty-four years after the discoveries of the first exoplanets, the radial-velocity (RV) method is still one of the most productive techniques to detect and confirm exoplanets. But stellar magnetic activity can induce RV variations large…
The goal of this paper is to investigate the optimal parameters space for using the reloaded Rossiter-McLaughlin technique to detect differential rotation (DR) and centre-to-limb convective variations. We simulated a star-planet system with…
The intrinsic variability of stars, due to acoustic oscillations, surface granulation, and magnetic activity, introduces radial velocity (RV) jitter in spectral lines, obscuring true planetary signals and hindering the detection of…
The direct imaging of Earth-like planets in solar neighbors is challenging. Both transit and radial velocity (RV) methods suffer from noise due to stellar activity. By choosing a typical configuration of an X array interferometer, we used…
The Rossiter-McLaughlin (RM) effect has been widely used to estimate the sky-projected spin-orbit angle, $\lambda$, of transiting planetary systems. Most of the previous analysis assume that the host stars are rigid rotators in which the…
Accurate knowledge of the state variables in a dynamical system is critical for effective control, diagnosis, and supervision, especially when direct measurements of all states are infeasible. This paper presents a novel approach to…
Artificial Neural Network computation relies on intensive vector-matrix multiplications. Recently, the emerging nonvolatile memory (NVM) crossbar array showed a feasibility of implementing such operations with high energy efficiency, thus…
Magnetic activity in stars manifests as dark spots on their surfaces that modulate the brightness observed by telescopes. These light curves contain important information on stellar rotation. However, the accurate estimation of rotation…
Wi-Fi sensing detects human motions and activities by analysing the channel state information (CSI) derived from Wi-Fi transmissions. However, the impact of variable transmission traffic, which dictates the effective sampling rate and…
In recent decades, the use of optical detection systems for meteor studies has increased dramatically, resulting in huge amounts of data being analyzed. Automated meteor detection tools are essential for studying the continuous meteoroid…
At wavelengths longwards of the sensitivity of silicon, hybrid structured mercury-cadmium-telluride (HgCdTe) detectors show promise to enable extremely precise radial velocity (RV) measurements of late-type stars. The most advanced near…
We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…
Change detection in satellite imagery seeks to find occurrences of targeted changes in a given scene taken at different instants. This task has several applications ranging from land-cover mapping, to anthropogenic activity monitory as well…
Radar sensors are gradually becoming a wide-spread equipment for road vehicles, playing a crucial role in autonomous driving and road safety. The broad adoption of radar sensors increases the chance of interference among sensors from…
Many phenomena taking place in the solar photosphere are controlled by plasma motions. Although the line-of-sight component of the velocity can be estimated using the Doppler effect, we do not have direct spectroscopic access to the…
A new apodized Keplerian (AK) model is proposed for the analysis of precision radial velocity (RV) data to model both planetary and stellar activity (SA) induced RV signals. A symmetrical Gaussian apodization function with unknown width and…
The sensitivity of radial velocity (RV) surveys for exoplanet detection are extending to increasingly long orbital periods, where companions with periods of several years are now being regularly discovered. Companions with orbital periods…
Uncertainty estimation for unlabeled data is crucial to active learning. With a deep neural network employed as the backbone model, the data selection process is highly challenging due to the potential over-confidence of the model…