JWST characterization of the JADES-ID1 protocluster
Here we overview several key aspects of the JWST analysis. Specifically, we summarize the method used to define the JADES-ID1 centroid, quantify the statistical significance of its galaxy overdensity and present tests that rule out the presence of any substantial low-redshift foreground structures.
To define the centre of JADES-ID1 (ref. 8), we construct two-dimensional galaxy overdensity maps in narrow-redshift slices using the DETECTIFz algorithm59, which uses Monte Carlo realizations of the redshift probability distribution function of each galaxy. We then identify the slice with the highest overdensity peak, z = 5.68 for JADES-ID1, and use the coordinates of that peak as the protocluster centre.
Next we quantify the rarity of the JWST-identified overdensity around JADES-ID1 by comparing it with field fluctuations. Within a projected radius of 42″ (≈250 kpc) around the JADES-ID1 centroid, the local galaxy overdensity is measured as δ gal = 3.9 relative to the mean density across the JADES field in the same redshift slice8. Focusing on the inner 21″ (≈125 kpc) region, which is coincident with our X-ray aperture, the overdensity rises to δ gal = 4.5. This is comparable with or exceeds those of previously confirmed protoclusters at similar redshifts7. To assess the statistical significance of this overdensity, we compared these values to the mean field density over 5.44 < z < 6.08 within a spherical volume of radius 410 kpc. Accounting for an approximately 30% cosmic variance, which is appropriate for the typical ultraviolet luminosities of candidate members8,60, we performed 106 Monte Carlo realizations. The chance of obtaining the observed overdensity of the observed galaxies by random fluctuation is 1.4 × 10−5, corresponding to a roughly 4.2σ detection. We note that our field baseline includes cluster members, so both δ gal and its significance are slight underestimates relative to a purely field reference. This confirms that, at z ≈ 5.7, such a strong overdensity is exceptionally rare.
Although ref. 8 identifies a clear overdensity at z ≈ 5.68, we further verify that no other substantial structures exist at lower redshifts. To do this, we investigated the photometric galaxy catalogues based on JWST and Hubble Space Telescope (HST) observations in the JADES field. We measured the galaxy surface density within a 40″ × 40″ box centred on the X-ray emission peak, corresponding to the extent of the detected emission from the JADES-ID1 protocluster. We binned galaxies in redshift slices with width of Δz = 0.3 in the redshift range z = 0–6.6 and derived the surface density in each bin. To correct for redshift-dependent selection biases (most notably the increased completeness at lower redshifts), we carried out the same measurement in a large background region within the JADES footprint, while excluding the 40″ × 40″ region with the X-ray detection. The difference between the galaxy surface density at the position of the X-ray excess and the field average exhibits a single significant peak in the z = 5.25–6.23 redshift bin. There are no comparable galaxy overdensities at any other redshift bins. This result demonstrates the absence of any substantial foreground structure along the line of sight of the JADES-ID1 protocluster.
The halo detection probabilities presented in the main part of this paper are based on the cosmic mean density field. To estimate how local density fluctuations could bias these results, we estimate the variance of the matter density over a JADES-sized volume. We find σ(R) ≈ 0.059, which corresponds to a 6% typical fluctuation between different patches of this size. Although a 6% overdense field would allow structure to grow more rapidly, the chance of finding a 1013 M ⊙ halo would increase only from about 4 × 10−5 to about 3 × 10−4.
Chandra data analysis
To examine the presence and physical properties of the hot ICM associated with the protocluster JADES-ID1, we analysed 99 Chandra ACIS-I observations that cover the CDFS. The CDFS represents the deepest X-ray field ever observed. The list of analysed Chandra observations is given in Extended Data Table 1. We performed most of the data analysis using standard CIAO tools, specifically, we used the latest version of CIAO (4.17) and the Calibration Database (CALDB 4.11.6). The main steps of the X-ray data analysis followed those outlined in our previous studies61,62. Below, we outline the main steps of the X-ray analysis.
The first step of the analysis was to reprocess each individual observation using the chandra_repro tool, thereby applying the latest calibration products. Next we identified and filtered high-background periods from the observations using the lc_clean routine by applying a 3σ threshold to remove fluctuations in the light curves. Because ACIS-I observations are not highly sensitive to solar flares, this step only reduced the exposure time by approximately 2%. The total cleaned exposure time of the dataset was 6.55 Ms.
Because we analyse and combine a large set of observations, small differences exist in the alignment between the individual Chandra observations. To account for this effect, we correct the absolute astrometry using the wcs_match and wcs_update tools. This step ensures that point sources are accurately aligned and exhibit a sharp point spread function, thereby minimizing contamination of the extended emission. To perform the astrometry correction, we cross-matched the positions of X-ray point sources in individual observations with the coordinates of guide stars in the same field. Using the coordinates of the X-ray–optical source pairs, we applied frame transformations for each Chandra observation, including transformations for rotation, scale and translation. We set the deepest observation, ObsID 8594, as the reference coordinate system. For the subsequent analysis, we used these astrometry-corrected event files.
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