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Enabling Multi Messenger Astronomy with a low-latency LISA data pipeline

CORDIS · observation · Publication date unknown

h our knowledge boundaries in astronomy, astrophysics, and cosmology. With EMILIA, we aspire to enable multi-messenger astronomy with LISA, by developing a low-latency data analysis pipeline based on Machine Learning techniques. Our proposed methodology will take into account the source confusion problem of LISA, where monochromatic signals and noise artefacts are going to be classified as such and subtracted from the data. We will then apply a fast semi-analytical algorithm on the residual data, in order to swiftly estimate the sky position and time of coalescence of chirping signals. Such a scheme will enable the synergy of LISA and optical observatories on Earth and in space. A prime example is that of the LISA-Athena missions synergy, which would probe the existence of electromagnetic counterpart of massive black hole mergers and extreme mass ratio inspirals, or phenomena like X-ray flares, disk re-brightening, and relativistic jet formations. LISA Gravitational Waves Multimessenger astronomy data analysis machine learning

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recordType

award

status

CLOSED

region

EU

value

169326.72

unit

EUR