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juliensimon/4xmm-dr14-xray-sources

4XMM-DR14 Serendipitous X-ray Source Catalog Credit: NASA/DOE/Fermi LAT Collaboration Part of the Astronomy Datasets collection on Hugging Face. The 4XMM catalog is the largest X-ray source catalog ever produced, containing 630,347 unique X-ray sources detected serendipitously by the European Space Agency's XMM-Newton observatory. This dataset provides the unique-source "slim" version of the catalog (currently DR12s from VizieR), where multiple detections of the same… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/4xmm-dr14-xray-sources.

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4XMM-DR14 Serendipitous X-ray Source Catalog

<div align="center"> <img src="banner.jpg" alt="The gamma-ray sky as seen by NASA's Fermi telescope" width="400"> <p><em>Credit: NASA/DOE/Fermi LAT Collaboration</em></p> </div>

Part of the [Astronomy Datasets](https://huggingface.co/collections/juliensimon/astronomy-datasets-69c24caf2f17e36128946743) collection on Hugging Face.

Updated

The 4XMM catalog is the largest X-ray source catalog ever produced, containing 630,347 unique X-ray sources detected serendipitously by the European Space Agency's XMM-Newton observatory. This dataset provides the unique-source "slim" version of the catalog (currently DR12s from VizieR), where multiple detections of the same source have been combined into a single entry with averaged parameters.

Dataset description

XMM-Newton is ESA's flagship X-ray observatory, launched in 1999 and carrying three co-aligned European Photon Imaging Cameras (EPIC) that simultaneously observe the same field. Because the EPIC field of view spans approximately 30 arcminutes, every pointed observation serendipitously detects dozens to hundreds of X-ray sources beyond the intended target. Over more than two decades of operations, this serendipitous survey has built up the most comprehensive census of the X-ray sky ever assembled.

The 4XMM-DR14 catalog is the fourteenth data release of this serendipitous source catalog, compiled by the XMM-Newton Survey Science Centre (SSC) consortium. It covers over 13,000 observations and spans the full 0.2-12 keV energy range of the EPIC cameras. For each unique source, the catalog provides positions, fluxes in five standard energy bands, hardness ratios that encode spectral shape, variability indicators, extent measurements for non-point sources, and quality flags.

The scientific reach of 4XMM is extraordinary. X-ray emission traces the most energetic processes in the universe: accretion onto black holes and neutron stars, million-degree gas in galaxy clusters, coronal activity on stars, and shock-heated plasma in supernova remnants. The catalog contains everything from nearby active stars to distant quasars at cosmological redshifts. It is a primary resource for identifying counterparts to sources detected at other wavelengths, for constructing X-ray luminosity functions, and for discovering rare objects such as tidal disruption events, changing-look AGN, and ultra-luminous X-ray sources.

The five standard energy bands are: band 1 (0.2-0.5 keV), band 2 (0.5-1.0 keV), band 3 (1.0-2.0 keV), band 4 (2.0-4.5 keV), and band 5 (4.5-12.0 keV). Hardness ratios between adjacent bands provide a coarse spectral characterisation without requiring full spectral fitting. Sources detected multiple times have their parameters averaged, and variability between observations is flagged, enabling time-domain studies on timescales from hours to decades.

Schema

ColumnTypeDescription
source_idint64Unique source identifier in the 4XMM catalog
iau_namestringIAU source name (e.g. 4XMM J000001.2+635739)
ra_degfloat64Right ascension J2000 (degrees)
dec_degfloat64Declination J2000 (degrees)
pos_error_arcsecfloat64Positional uncertainty (arcsec, 1-sigma)
src_det_mlfloat64Src Det Ml
flux_band1float64Mean flux in band 1: 0.2-0.5 keV (erg/cm2/s)
flux_band1_errfloat64Flux uncertainty in band 1
flux_band2float64Mean flux in band 2: 0.5-1.0 keV (erg/cm2/s)
flux_band2_errfloat64Flux uncertainty in band 2
flux_band3float64Mean flux in band 3: 1.0-2.0 keV (erg/cm2/s)
flux_band3_errfloat64Flux uncertainty in band 3
flux_band4float64Mean flux in band 4: 2.0-4.5 keV (erg/cm2/s)
flux_band4_errfloat64Flux uncertainty in band 4
flux_band5float64Mean flux in band 5: 4.5-12.0 keV (erg/cm2/s)
flux_band5_errfloat64Flux uncertainty in band 5
flux_totalfloat64Mean total-band flux: 0.2-12.0 keV (erg/cm2/s)
flux_total_errfloat64Total-band flux uncertainty
flux_band9float64Mean flux in band 9: 0.5-4.5 keV (erg/cm2/s)
flux_band9_errfloat64Flux uncertainty in band 9
hardness_ratio_1float64Hardness ratio HR1 (bands 1-2)
hardness_ratio_1_errfloat64HR1 uncertainty
hardness_ratio_2float64Hardness ratio HR2 (bands 2-3)
hardness_ratio_2_errfloat64HR2 uncertainty
hardness_ratio_3float64Hardness ratio HR3 (bands 3-4)
hardness_ratio_3_errfloat64HR3 uncertainty
hardness_ratio_4float64Hardness ratio HR4 (bands 4-5)
hardness_ratio_4_errfloat64HR4 uncertainty
extent_arcsecfloat64Extent Arcsec
extent_arcsec_errfloat64Extent Arcsec Err
extent_mlfloat64Maximum likelihood of source extent
chi2_constancyfloat64Chi2 Constancy
fractional_variabilityfloat64Fractional Variability
fractional_variability_errfloat64Fractional Variability Err
variability_flagint64Variability flag (True if variable)
summary_flagint64Summary quality flag (0=good, higher=worse)
flux_total_minfloat64Flux Total Min
flux_total_min_errfloat64Flux Total Min Err
flux_total_maxfloat64Flux Total Max
flux_total_max_errfloat64Flux Total Max Err
mjd_firstfloat64Mjd First
mjd_lastfloat64Mjd Last
n_detectionsint64Number of detections across all observations
confusion_flagint64Confusion Flag
irap_flagstringIrap Flag

Quick stats

  • —630,347 unique X-ray sources
  • —45 columns after cleanup
  • —123,037 sources with multiple detections
  • —RA range: 0.00 to 360.00 degrees
  • —Dec range: -88.19 to 89.40 degrees

Usage

python
from datasets import load_dataset

ds = load_dataset("juliensimon/4xmm-dr14-xray-sources", split="train")
df = ds.to_pandas()

# Brightest sources by total-band flux
if "flux_total" in df.columns:
    brightest = df.nlargest(10, "flux_total")[["iau_name", "ra_deg", "dec_deg", "flux_total"]]
    print(brightest)

# Sources detected multiple times (variability studies)
multi = df[df["n_detections"] > 5]
print(f"{len(multi):,} sources with >5 detections")

# Sky distribution
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(14, 7))
ax.scatter(df["ra_deg"], df["dec_deg"], s=0.1, alpha=0.1, c="navy")
ax.set_xlabel("RA (deg)")
ax.set_ylabel("Dec (deg)")
ax.set_title("4XMM-DR14 Sky Coverage")

Data source

4XMM-DR14 Serendipitous Source Catalog (Webb N.A. et al., 2020, A&A, 641, A136), compiled by the XMM-Newton Survey Science Centre consortium. Accessed via VizieR (catalog IX/68), CDS Strasbourg.

Update schedule

Static dataset — based on 4XMM-DR14 catalog release.

Related datasets

Pipeline

Source code: juliensimon/space-datasets

Support

If you find this dataset useful, please give it a ❤️ on the dataset page and share feedback in the Community tab! Also consider giving a ⭐️ to the space-datasets repo.

Citation

bibtex
@dataset{xmm_4xmm_dr14,
  author = {Simon, Julien},
  title = {4XMM-DR14 Serendipitous X-ray Source Catalog},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/juliensimon/4xmm-dr14-xray-sources},
  note = {Based on 4XMM-DR14 (Webb et al. 2020) via VizieR CDS Strasbourg}
}

License

CC-BY-NC-3.0-IGO