Paper detail

HEIDI: An Automated Process for the Identification and Extraction of Photometric Light Curves from Astronomical Images

The production of photometric light curves from astronomical images is a very time-consuming task. Larger data sets improve the resolution of the light curve, however, the time requirement scales with data volume. The data analysis is often made more difficult by factors such as a lack of suitable calibration sources and the need to correct for variations in observing conditions from one image to another. Often these variations are unpredictable and corrections are based on experience and intuition. The High Efficiency Image Detection & Identification (HEIDI) pipeline software rapidly processes sets of astronomical images. HEIDI automatically selects multiple sources for calibrating the images using an algorithm that provides a reliable means of correcting for variations between images in a time series. The algorithm takes into account that some sources may intrinsically vary on short time scales and excludes these from being used as calibration sources. HEIDI processes a set of images from an entire night of observation, analyses the variations in brightness of the target objects and produces a light curve all in a matter of minutes. HEIDI has been tested on three different time series of asteroid 939 Isberga and has produced consistent high quality photometric light curves in a fraction of the usual processing time. The software can also be used for other transient sources, e.g. gamma-ray burst optical afterglows. HEIDI is implemented in Python and processes time series astronomical images with minimal user interaction. HEIDI processes up to 1000 images per run in the standard configuration. This limit can be easily increased. HEIDI is not telescope-dependent and will process images even in the case that no telescope specifications are provided. HEIDI has been tested on various Linux . HEIDI is very portable and extremely versatile with minimal hardware requirements.