The Three Hundred project: Low Gas Fraction Clusters properties and their environment

Galaxy cluster samples based on X-ray and Sunyaev-Zel'dovich observations are affected by selection biases. These catalogs preferentially include systems with high gas content and surface brightness. The new analysis still awaits peer review, but it already lays out the central claim clearly.

It is relevant because cosmology operates at the edge of what current instruments can measure, where systematic errors and model assumptions are never trivial. Small discrepancies between independent measurements have historically pointed toward missing physics rather than simple calibration errors, and the ongoing tension in the Hubble constant is a live example of how a persistent disagreement between methods can reshape the theoretical landscape. Each new dataset that approaches this territory with independent systematics adds real information to a problem that has resisted easy resolution for more than a decade. Galaxy cluster samples based on X-ray and Sunyaev-Zel'dovich (SZ) observations are affected by selection biases. These catalogs preferentially include systems with high gas content and surface brightness.

Excluding objects with depleted gas content, low-gas-fraction clusters (LGFCs), could lead to an incomplete sampling. We aim to investigate the abundance and the properties of the LGFCs population using The Three Hundred hydrodynamical simulations, focusing on the Gadget-X code.

In particular, we study outliers in the $f_{\mathrm{g}, 500} - M_{500}$ relation, environmental influences, and their behavior in key scaling relations, with a focus on the. LGFCs are selected statistically as outliers of the $f_{\mathrm{g}, 500}-M_{500}$ relation.

Finally, we study how the temperature, entropy, and spherical Compton parameter scaling relations are affected by the inclusion of LGFCs. Radial profiles of LGFCs show lower gas concentrations in the core regions and higher temperatures, suggesting a more diffuse and heated ICM.

The relevance goes beyond one dataset because even small shifts in measured parameters can matter when the field is testing the limits of the standard cosmological model. The Lambda-CDM framework describes the observable universe with remarkable economy, but its success rests on two components, dark matter and dark energy, whose physical nature remains entirely unknown. Any credible measurement that tightens or loosens the constraints on those components moves the entire theoretical enterprise forward, regardless of whether the immediate result looks dramatic on its own terms.

Contrary to observations, the $Y_{\mathrm{sph}, 500}$ values of LGFCs show no significant deviation from the general population. Nevertheless, we cannot rule out that these differences are partly driven by the mass incompleteness at the low-mass end and the environmental bias of our simulated sample.

Because this is still a preprint, the result should be read with genuine interest and proportionate caution. Peer review is not a guarantee of correctness, but it is a process that forces authors to respond to technical criticism from specialists who have no stake in a particular outcome. Preprints that survive that process, often with substantive revisions, emerge with a stronger evidential base than the version that first appeared. Until that stage is complete, the responsible reading keeps uncertainty explicitly visible rather than treating the claims as established findings.

The next step is to see whether the effect survives when independent surveys, different calibration strategies and tighter control of systematic uncertainties enter the picture. Programmes such as Euclid, DESI and the Rubin Observatory will deliver datasets over the next several years that cover the same parameter space with largely independent methods. If the current signal persists through those tests, its theoretical implications will become impossible to set aside. Until peer review and independent follow-up address those open questions, skepticism is not a failure of appreciation for the work; it is part of how science decides what to keep.

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