Cosmic chronometers with galaxy clusters: a new avenue for multi-probe cosmology

TL;DR

The paper introduces cosmic chronometers based on massive passive galaxies in three galaxy clusters to measure the expansion history $H(z)$ at $z\sim0.54$ and to enable a self-consistent CC+TDC cosmology in overlapping fields. Using VLT/MUSE spectroscopy and HST photometry, it performs full-spectrum fitting with Bagpipes without cosmological age priors, selecting 37–38 CCs and deriving their physical properties, including ages, metallicities, and dust content. From the age–redshift relation, it reports $H(z=0.542)=66_{-29}^{+81}$ (stat) $\pm 13$ (syst) km s$^{-1}$ Mpc$^{-1}$, with a bootstrap approach across two mass bins, highlighting a mass-downsizing trend and an ageing population. Forecasts indicate that larger samples (≈100 CCs) and extended redshift coverage could reduce uncertainties by up to a factor of ~4, underscoring the role of cluster CCs in strengthening joint cosmological constraints alongside time-delay cosmography in future surveys such as Euclid and LSST.

Abstract

We provide a new measurement of the expansion history of the Universe at $z=0.54$ with the cosmic chronometers (CC) method, exploiting the high-quality spectroscopic VLT/MUSE data for three galaxy clusters in close-by redshift bins: SDSS J2222+2745 ($z=0.49$), MACS J1149.5+2223 ($z=0.54$), and SDSS J1029+2623 ($z=0.59$). The central one, MACS J1149.5+2223, hosts the well-known supernova 'Refsdal', which allowed for $H_0$ measurements via time delay cosmography (TDC). This represents the first step for a self-consistent probe combination, where different methods are applied to the same data sample. After selecting the most passive and massive cluster members (38 CCs), we derive their age and physical parameters via full spectrum fitting. We use the code Bagpipes, specifically modified to remove the cosmological prior on ages. On average, the CC sample shows super-solar metallicities $Z/Z_{\odot} = 1.3 \pm 0.7$, low dust extinction $A_{\rm{V}} = 0.3 \pm 0.3$ mag and to have formed in short bursts $τ= 0.6 \pm 0.2$ Gyr. We also observe both an ageing trend in redshift and a mass-downsizing pattern. From the age-redshift trend, implementing the CC method through a bootstrap approach, we derive a new $H(z)$ measurement: $H$($z$=0.542) = $66_{-29}^{+81}$ (stat) $\pm$13 (syst) km/s/Mpc. We also simulate the impact of increased statistics and extended redshift coverage, finding that $H$($z$) uncertainties can be reduced by up to a factor of 4 with $\sim$100 CCs and a slightly broader redshift range (d$z\sim$0.2).

Figures (6)

• Figure 1: Fit of the spectrum (left) and photometry (right) of an example galaxy for each cluster. In blue, the observed spectrum and photometry are shown, in red the corresponding best fit. The shaded regions mark potential emission or telluric lines that are masked in the fit.
• Figure 2: Trends in redshift for the main physical parameters, colour-coded by the measured velocity dispersion. In the top left panel, the solid line shows the age of the Universe computed in a flat $\Lambda$CDM with $\Omega_m=0.3$.
• Figure 3: Collection of all $H(z)$ measurements obtained to date simon_constraints_2005stern_cosmic_2010Moresco2012zhang_four_2014Moresco2015Moresco2016ratsimbazafy_age-dating_2017Borghi2022bJiao2023Tomasetti2023Jiao2023loubser_independent_2025loubser_measuring_2025, including the result of this work. For comparison, the dashed line represents the flat $\Lambda$CDM trend from Planck18. The red shaded box shows the forecast on the precision achievable with a sample of 100 CCs (see Sect. \ref{['sec:future_persp']} for details).
• Figure 4: Results of the simulations. The left column shows, for each setting, an example of age--redshift both for the HM (red) and LM (blue) samples, randomly extracted from a Gaussian distribution centred on the seed, in black. The right column shows the resulting $H(z)$ distribution and the derived measurement (yellow star, also reported in the title), in comparison with the assumed cosmology PlanckCollaboration2020.
• Figure 5: Example showing the effect of the aperture sizes on the extraction of a 1D spectrum from a MUSE data cube. The top panel shows the spectrum of the same member of the cluster SDSS 2222, extracted using circular apertures of radius $1.4"$ (blue), $0.6"$ (orange), and $0.3"$ (red). The bottom panel shows the ratio between each spectrum and the one extracted with the $0.3"$ aperture. A bigger extraction aperture produces a relatively bluer spectrum (namely, the spectrum shows a larger flux at lower wavelengths).