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A machine learning classifier for microlensing in wide-field surveys
Bachelet, E.; Street, R. A.; Narayan, G. +1 more
While microlensing is very rare, occurring on average once per million stars observed, current and near-future surveys are coming online with the capability of providing photometry of almost the entire visible sky to depths up to R ∼22 mag or fainter every few days, which will contribute to the detection of black holes and exoplanets through follo…
Identifying transient and variable sources in radio images
Eislöffel, J.; Wijers, R. A. M. J.; Fender, R. +16 more
With the arrival of a number of wide-field snapshot image-plane radio transient surveys, there will be a huge influx of images in the coming years making it impossible to manually analyse the datasets. Automated pipelines to process the information stored in the images are being developed, such as the LOFAR Transients Pipeline, outputting light cu…
The ssos pipeline: Identification of Solar System objects in astronomical images
Bertin, E.; Bouy, H.; Carry, B. +3 more
Observatories and satellites around the globe produce tremendous amounts of imaging data to study many different astrophysical phenomena. The serendipitous observations of Solar System objects are a fortunate by-product which have often been neglected due to the lack of a simple yet efficient identification algorithm. Meanwhile, the determination …
The data processing pipeline for the Herschel1- HIFI instrument
Shipman, R. F.; Edwards, K.; Kester, D. +2 more
The HIFI data processing pipeline was developed to systematically process diagnostic, calibration and astronomical observations taken with the HIFI science instrument as part of the Herschel mission. The HIFI pipeline processed data from all HIFI observing modes within the Herschel automated processing environment, as well as, within an interactiv…