The XMM-Newton Survey Science Catalogues

The XMM-Newton Survey Science Centre produces catalogues of all X-ray sources detected with XMM-Newton. All catalogues up to 3XMM-DR4 were produced by the University of Leicester in collaboration with the other SSC institutes. Links to all the catalogues can be found on these pages. Ulterior catalogues are produced at the Institut de Recherche en Astrophysique et Planétologie in Toulouse, in collaboration with the other SSC institutes and the XMM-Newton Science Operations Centre (SOC). Catalogues based on a reprocessing of all the data used are named 1XMM, 2XMM, 3XMM, 4XMM, etc. Incremental versions of these catalogues are also released on a regular basis and these include data that has become public since the release of the previous catalogue and processed with a similar, but not necessarily identical, version of the SAS. For the 3XMM-DR7, 4XMM-DR9, 4XMM-DR10, 4XMM-DR11, 4XMM-DR12 and 4XMM-DR13 versions we also provide a stacked version of the catalogue known as 3XMM-DR7s, 4XMM-DR9s, 4XMM-DR10s, 4XMM-DR11s, 4XMM-DR12s and 4XMM-DR13s. All information concerning the data reduction steps can be found on the web pages provided for each catalogue version. Complementary information is provided in the 2XMM paper (The XMM-Newton serendipitous survey. V. The Second XMM-Newton serendipitous source catalogue Watson et al. (2009)), the 3XMM paper (Rosen, Webb, Watson et al., 2016, A&A, 590, 1) and the 4XMM paper Webb et al., (2020). For the stacked catalogue, complementary information is available in Traulsen et al. (2019) and Traulsen et al., (2020). Should you use the catalogue for your research and publish the results, please use the acknowledgement below and cite the paper describing the catalogue Webb et al., (2020) or Traulsen et al., (2020).

The XMM-Newton Survey Science Catalogues

• 4XMM-DR14s
• 4XMM-DR14
• 4XMM-DR13s
• 4XMM-DR13
• 4XMM-DR12s
• 4XMM-DR12
• 4XMM-DR11s
• 4XMM-DR11
• 4XMM-DR10s
• 4XMM-DR10
• 4XMM-DR9s
• 4XMM-DR9
• 3XMM-DR8
• 3XMM-DR7s
• 3XMM-DR7
• 3XMM-DR6
• 3XMM-DR5
• 3XMM DR4
• 2XMMi - DR3
• 2XMMi - DR2
• 2XMM - DR1
• 2XMMp - Data pre-Release 0
• 1XMM - Original catalogue

The catalogue can also be queried via:

• The XMM-Newton Science Archive (XSA)
• The classical XCATDB interface
• The VO sky explorer XCATDB interface
• HEASARC
• IRAP catalogue server
• Vizier
• See also the upper limit server if the source has not been detected

The stacked catalogue is also browsable via the web-based interfaces

• XSA at ESA's XMM-Newton SOC
• Browse at HEASARC NASA GSFC

The XSA provides access to the auxiliary data products per source: a broad-band X-ray image, a colour-coded three-band X-ray image, an optical finding chart, and a long-term X-ray light curve.

We also produce and distribute the XMM-Newton slew survey catalogue as of version 3. The XMMSL3 version is available here:

XMMSL3

• XSA at ESA's XMM-Newton SOC
• ESASky
• Browse at HEASARC NASA GSFC

Should you have any issues that you wish to raise concerning the X-ray catalogue, please send an email to Natalie Webb with the title '4XMM catalogue issues'.

Many other complementary catalogues produced in the framework of the XMM2ATHENA project can be found on this page, such as spectral-fit database that proposes both spectral fits for 4XMM-DR11 detections with spectra and stacked spectra, along with simple spectral fits for all detections. All of these catalogues and other data will be included in the upcoming version of the XMM-Newton catalogue, 5XMM for publication in 2025/2026.

We also help produce the XMM-Newton Optical Monitor (OM) Serendipitous Ultra-violet Source Survey Catalogue (XMM-SUSS, Page et al. (2012)). The latest version, XMM-SUSS6 contains 9.92 million detections (6.66 million unique sources). It can be queried at:

• The XMM-Newton Science Archive (XSA)
• HEASARC

We also provide Multi-Order-Coverage maps (MOCs) for each filter for the SUSS v5 catalogue. They are available here: White filter, UVW2 filter, UVM2 filter, UVW1 filter, U filter, B filter, V filter. Amongst other ways to use the MOCs, we recommend the python tool MOCpy.