Radial Velocity

Radial velocity, the measurement of an object's velocity along the line of sight, is a crucial technique across diverse scientific fields. Current research focuses on improving the accuracy and robustness of radial velocity measurements, particularly by mitigating noise and interference from sources like stellar activity (in astronomy) or environmental factors (in robotics). This involves the application of advanced machine learning techniques, such as convolutional neural networks and mixture density networks, to process and interpret data, often in conjunction with other sensor modalities. Improved radial velocity measurements have significant implications for exoplanet detection, autonomous navigation, and galaxy shape modeling, enabling more precise and reliable scientific inferences and technological advancements.