XMM2ATHENA, the H2020 project to improve XMM-Newton analysis software and prepare for Athena

XMM-Newton, a European Space Agency observatory, has been observing the X-ray, ultra-violet, and optical sky for 23 years. During this time, astronomy has evolved from mainly studying single sources to populations and from a single wavelength, to multi-wavelength/messenger data. We are also moving into an era of time domain astronomy. New software and methods are required to accompany evolving astronomy and prepare for the next-generation X-ray observatory, Athena. Here we present XMM2ATHENA, a program funded by the European Union's Horizon 2020 research and innovation program. XMM2ATHENA builds on foundations laid by the XMM-Newton Survey Science Centre (XMM-SSC), including key members of this consortium and the Athena Science ground segment, along with members of the X-ray community. The project is developing and testing new methods and software to allow the community to follow the X-ray transient sky in quasi-real time, identify multi-wavelength/messenger counterparts of XMM-Newton sources and determine their nature using machine learning. We detail here the first milestone delivery of the project, a new online, sensitivity estimator. We also outline other products, including the forthcoming innovative stacking procedure and detection algorithms, to detect the faintest sources. These tools will then be adapted for Athena and the newly detected/identified sources will enhance preparation for observing the Athena X-ray sky

XMM2ATHENA, the H2020 project to improve XMM-Newton analysis software and prepare for Athena

International audienceXMM-Newton, a European Space Agency observatory, has been observing the X-ray, ultra-violet and optical sky for 23 years. During this time, astronomy has evolved from mainly studying single sources to populations and from a single wavelength, to multi-wavelength or messenger data. We are also moving into an era of time domain astronomy. New software and methods are required to accompany evolving astronomy and prepare for the next generation X-ray observatory, Athena. Here we present XMM2ATHENA, a programme funded by the European Union's Horizon 2020 research and innovation programme. XMM2ATHENA builds on foundations laid by the XMM-Newton Survey Science Centre (XMM-SSC), including key members of this consortium and the Athena Science ground segment, along with members of the X-ray community. The project is developing and testing new methods and software to allow the community to follow the X-ray transient sky in quasi-real time, identify multi-wavelength or messenger counterparts of XMM-Newton sources and determine their nature using machine learning. We detail here the first milestone delivery of the project, a new online, sensitivity estimator. We also outline other products, including the forthcoming innovative stacking procedure and detection algorithms to detect the faintest sources. These tools will then be adapted for Athena and the newly detected or identified sources will enhance preparation for observing the Athena X-ray sky

XMM2ATHENA, the H2020 project to improve XMM-Newton analysis software and prepare for Athena

International audienceXMM-Newton, a European Space Agency observatory, has been observing the X-ray, ultra-violet and optical sky for 23 years. During this time, astronomy has evolved from mainly studying single sources to populations and from a single wavelength, to multi-wavelength or messenger data. We are also moving into an era of time domain astronomy. New software and methods are required to accompany evolving astronomy and prepare for the next generation X-ray observatory, Athena. Here we present XMM2ATHENA, a programme funded by the European Union's Horizon 2020 research and innovation programme. XMM2ATHENA builds on foundations laid by the XMM-Newton Survey Science Centre (XMM-SSC), including key members of this consortium and the Athena Science ground segment, along with members of the X-ray community. The project is developing and testing new methods and software to allow the community to follow the X-ray transient sky in quasi-real time, identify multi-wavelength or messenger counterparts of XMM-Newton sources and determine their nature using machine learning. We detail here the first milestone delivery of the project, a new online, sensitivity estimator. We also outline other products, including the forthcoming innovative stacking procedure and detection algorithms to detect the faintest sources. These tools will then be adapted for Athena and the newly detected or identified sources will enhance preparation for observing the Athena X-ray sky