The X-ray Observatory Athena (Nandra et al. 2013) was proposed in April 2014 as the mission to implement the science theme "The Hot and Energetic Universe" selected by ESA for L2 (the second Large-class mission in ESA’s Cosmic Vision science programme). One of the two X-ray detectors designed to be onboard Athena is the X-IFU (Barret et al. 2016), a cryogenic microcalorimeter based on Transition Edge Sensor (TES) technology that will provide spatially resolved high-resolution spectroscopy. X-IFU will be developed by an international consortium led by IRAP (PI), SRON (co-PI) and IAPS/INAF (co-PI) and involving ESA Member States, Japan and the United States.

The X-ray photons absorbed in X-IFU generate intensity pulses that must be detected and reconstructed on-board to recover their energy, position and arrival time. The software prototype package (SIRENA 1) in development as an anticipated contribution of IFCA/Spain to X-IFU through the Digital Readout Electronics (DRE) unit (Ravera et al. 2014), is currently testing a set of processing algorithms with the aim of finding the best compromise between performance and availability of on-board computing resources.

The optimal filtering has recently been chosen as the baseline algorithm but other techniques are still under study in an effort to get the better results at the lower computing cost. In particular at IFCA, we are currently investigating the performance of the Extreme Learning Machine (ELM) algorithm for single-hidden layer feedforward neural networks (SLFNs) for the reconstruction of the pulses in the X-IFU data signal.

Trabajo presentado a la XXVII Astronomical Data Analysis Software and Systems Conference, celebrada del 22 al 26 de octubre de 2017 en Santiago de Chile, Chile.

This work has been funded by the Spanish Ministry MINECO under project ESP2014-53672-C3-1-P, co-funded by FEDER funds.

Peer reviewed