🔭 astrophysics

Identification of low redshift groups and clusters of galaxies in the X-CLASS survey and the X-ray luminosity-temperature relation

Using a spectroscopically complete sample of 155 low-redshift galaxy groups and clusters from the X-CLASS survey, this study establishes a steep X-ray luminosity-temperature relation ( $L_X \propto T^{3.2}$ ) that deviates from self-similar predictions, suggesting that strong feedback mechanisms efficiently expel gas from the shallower potential wells of lower-mass systems.

Original authors: Q. Moysan, F. Sarron, N. Clerc, G. Soucail, C. Adami, B. Altieri, R. Cabanac, M. Chira, J. Comparat, D. Coia, E. Drigga, E. Gaynullina, A. Khalikova, E. Koulouridis, K. Migkas, M. Molham, L. Paquereau

Published 2026-03-25

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Q. Moysan, F. Sarron, N. Clerc, G. Soucail, C. Adami, B. Altieri, R. Cabanac, M. Chira, J. Comparat, D. Coia, E. Drigga, E. Gaynullina, A. Khalikova, E. Koulouridis, K. Migkas, M. Molham, L. Paquereau, T. Sadibekova, I. Valtchanov

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the universe as a giant, cosmic city. In this city, the "buildings" are galaxies, and sometimes these galaxies huddle together in massive neighborhoods called clusters or smaller, cozy communities called groups.

Between these galaxies, there isn't empty space. Instead, it's filled with a super-heated, invisible fog of gas. This gas is so hot it glows with X-rays, like a neon sign that only special cameras can see.

This paper is like a detective story where astronomers try to understand the rules of this cosmic city. Specifically, they wanted to answer a big question: How does the brightness of this hot gas relate to how hot the gas is?

Here is the breakdown of their adventure, explained simply:

1. The Problem: The "Self-Similar" Rulebook

For a long time, scientists had a simple rulebook (called the "self-similar model") for how these cosmic neighborhoods work. It was based on gravity alone.

The Rule: If you have a bigger neighborhood (more mass), the gas should be hotter and brighter in a very predictable, gentle way. Think of it like a campfire: if you add more wood (mass), the fire gets hotter and brighter, but the relationship is steady.

However, real life is messy. In these cosmic neighborhoods, there are "angry neighbors" (like supermassive black holes in the center of galaxies) that shoot out jets of energy, blowing gas away. This messes up the simple rulebook. Scientists knew the rulebook was wrong, but they didn't have enough data on the smaller neighborhoods (groups) to know exactly how wrong it was.

2. The Mission: Finding the Small Neighborhoods

Most previous studies focused on the giant, massive clusters (the skyscrapers of the universe). But the authors of this paper wanted to study the small groups (the suburban neighborhoods).

Why? Because in small neighborhoods, the "gravity fence" is weaker. It's much easier for the "angry neighbors" (black holes) to blow the gas out of the neighborhood. This makes the gas dimmer and cooler than the simple rulebook predicts.

To do this, they used a massive database called X-CLASS, which is a list of thousands of galaxy groups and clusters found by the XMM-Newton space telescope.

3. The Detective Work: Fixing the Addresses

A major problem with the database was that many of these cosmic neighborhoods didn't have a confirmed "address" (redshift). Without an address, you don't know how far away they are, so you can't tell how bright or hot they actually are.

The Solution: The team acted like a team of detectives.
1. Digital Sleuthing: They used powerful computer algorithms to estimate the distance of thousands of clusters based on how their colors looked (photometric redshifts).
2. The Field Trip: For the most important, nearby clusters, they went to the Observatoire de Haute-Provence in France. They used a telescope with a special instrument called MISTRAL to take actual spectra (fingerprints) of the light from these galaxies. This gave them the exact distance.
3. The Result: They updated the addresses for hundreds of clusters, creating a clean, reliable list of 155 nearby groups and clusters.

4. The Discovery: The "Steep" Relationship

Once they had their clean list, they measured the temperature and brightness of the hot gas in each group. Then, they plotted the data to see the relationship.

The Big Reveal:
The relationship they found was much steeper than the old rulebook predicted.

The Analogy: Imagine the old rulebook said, "If you double the size of the neighborhood, the gas gets a little bit brighter."
What they found: They found that for small groups, if you make the neighborhood even a tiny bit smaller, the gas gets dramatically dimmer.

It's like a house with a weak roof. If you take away just a little bit of the roof (mass), the wind (feedback from black holes) blows all the furniture (gas) out the door. But in a massive skyscraper (a giant cluster), the roof is so strong that even if you take a little bit away, the furniture stays put.

5. Why This Matters

This steep relationship proves that non-gravitational forces (like black holes blowing gas away) are the dominant force in small galaxy groups.

The Takeaway: The universe isn't just a simple gravity machine. In smaller cosmic neighborhoods, the "angry neighbors" (black holes) are very effective at cleaning house, expelling the gas and making these groups much dimmer than we expected.

Summary

The authors took a messy list of cosmic neighborhoods, cleaned up their addresses using both computers and a real telescope, and discovered that small galaxy groups behave very differently from big ones. They found that in these small groups, the gas is much dimmer than gravity alone would predict, likely because black holes are blowing it away. This helps us understand how the universe builds its structures and how energy flows through the cosmos.

1. Problem Statement

The study addresses two primary challenges in the field of galaxy cluster astrophysics:

Redshift Completeness: Large X-ray selected samples, such as the XMM Cluster Archive Super Survey (X-CLASS), often suffer from incomplete or imprecise redshift data. Prior to this work, only 60% of X-CLASS clusters had spectroscopically confirmed redshifts, limiting their utility for cosmological studies and precise physical characterization.
Scaling Relations in Low-Mass Systems: While the scaling relation between X-ray luminosity ( $L_X$ ) and temperature ( $T$ ) is well-studied for massive clusters, there is a scarcity of high-quality data for low-mass systems (groups and low-mass clusters). Understanding this regime is crucial because low-mass halos have shallower gravitational potential wells, making them more susceptible to non-gravitational processes (e.g., AGN feedback, supernovae) that can distort standard self-similar scaling laws. Previous samples were often limited by selection biases ("up-scattering") and lacked the depth to probe the group regime effectively.

2. Methodology

The authors employed a multi-stage approach combining deep photometric data, dedicated spectroscopic follow-up, and rigorous Bayesian modeling:

Redshift Upgrade (Photometric):
- Utilized the DESI Legacy Surveys (DR9/DR10) to obtain deep multi-band photometry ( $g, r, i, z, W1, W2$ ).
- Developed a hybrid photometric redshift ( $z_{phot}$ $z_{p h o t}$ ) estimation strategy combining two codes:
  1. photXclus: A new Bayesian code utilizing individual galaxy photo-zs and the extent of the X-ray signal to inform priors.
  2. RedMaPPer: An established optical cluster finder.
- Strategy: Used photXclus for $z < 0.15$ (where RedMaPPer showed higher outlier fractions) and RedMaPPer for $z \geq 0.15$ . This combination reduced the outlier fraction to 4.62% and the scatter ( $\sigma_{NMAD}$ ) to $0.0044 \times (1+z)$ .
Spectroscopic Follow-up:
- Conducted a dedicated survey using the MISTRAL instrument on the T193 telescope at the Observatoire de Haute-Provence.
- Observed 52 low-redshift X-CLASS systems (prioritizing those with "No redshift," "Photometric," or "Tentative" status).
- Extracted spectra for 144 objects, identifying absorption lines in early-type galaxies to derive precise spectroscopic redshifts ( $\delta z \sim 0.001$ ).
Sample Selection (X-CLASS-LR):
- Defined a clean, low-redshift subsample ( $0.07 \leq z \leq 0.2$ ) in the Northern Hemisphere.
- Applied strict quality cuts: removed sources with uncertain redshifts and those where the X-ray selection function was poorly modeled (using a reduced chi-squared test, $\chi^2/\nu \leq 10$ ).
- Final sample: 104 clusters with robust measurements of $L_X$ , $T$ , and $M_{500}$ .
Physical Property Measurement:
- Temperature ( $T_{500}$ ) & Metallicity ( $Z_{500}$ ): Derived via spectral fitting (XSpec) within an iterative radius determination ( $R_{500}$ ). Metallicity was generally fitted to avoid the "Fe bias" (degeneracy between $T$ and $Z$ ), fixed only for low S/N spectra.
- Luminosity ( $L_X$ ): Calculated by forward-fitting the 2D surface brightness using MBProj2D (a 3D deprojection code) to model the electron density profile ( $\beta$ -model) and integrate emissivity up to $R_{500}$ .
Statistical Modeling:
- Employed a Bayesian framework (MCMC with emcee) to infer the $L_X - T$ relation.
- The model explicitly accounted for the selection function of the X-CLASS survey, measurement uncertainties, intrinsic scatter, and the joint distribution of mass, temperature, and luminosity.
- Assumed a power-law relation for $\langle L_X | M_{500} \rangle$ and fixed the $T - M_{500}$ relation based on previous literature (Lovisari et al. 2015).

3. Key Contributions

Redshift Catalog Upgrade: Released an updated redshift catalog for the full X-CLASS sample (1646 sources), increasing the spectroscopic confirmation rate and providing robust photometric redshifts for the remaining objects. The photXclus code is made publicly available.
Spectroscopically Complete Low-Mass Sample: Created the X-CLASS-LR sample, the largest high-quality sample of low-redshift ( $z < 0.2$ ) groups and clusters with precise spectroscopic redshifts and detailed X-ray properties.
Rigorous Selection Modeling: Developed a methodology to correct for selection biases inherent in archival XMM-Newton data, ensuring the derived scaling relations are not distorted by the survey's detection limits.

4. Results

Sample Properties: The final sample of 104 clusters has a median total mass of $\sim 6 \times 10^{13} M_\odot$ , median temperature $T = 1.7$ keV, and median luminosity $L_X = 10^{43}$ erg s $^{-1}$ . Approximately 69% of the sample consists of galaxy groups ( $M < 10^{14} M_\odot$ ).
The $L_X - T$ Scaling Relation:
- The study derived the relation: $\langle L_X | T \rangle = 10^{42.97} (T/2\text{ keV})^{3.2 \pm 0.1}$ .
- Slope: The slope $B = 3.2 \pm 0.1$ is significantly steeper than the self-similar prediction ( $B = 1.5$ ) and steeper than relations derived from massive cluster samples (typically $B \approx 2.5 - 2.7$ ).
- Intrinsic Scatter: The intrinsic scatter in $\ln L_X$ at fixed $T$ is $\approx 0.66$ (0.29 dex).
Mass Dependence: The results confirm a trend where the slope of the $L_X - T$ relation increases as the median halo mass of the sample decreases.

5. Significance and Interpretation

Role of Baryonic Physics: The steep slope observed in low-mass systems is interpreted as evidence of strong non-gravitational feedback processes (likely AGN and supernovae). In low-mass groups with shallow potential wells, this feedback efficiently expels gas, reducing the X-ray luminosity at a given temperature compared to massive clusters where gravity dominates.
Cosmological Implications: The findings highlight the necessity of using mass-selected samples and correcting for selection biases when constraining cosmological parameters (e.g., the mass function). Ignoring the distinct physics of the group regime could lead to systematic errors in cosmological inferences.
Future Outlook: The paper demonstrates that combining deep X-ray archives with modern optical surveys (Legacy Surveys) and targeted spectroscopy is a powerful method for building complete samples of low-mass structures, paving the way for future studies with eROSITA and next-generation spectrographs (e.g., DESI, 4MOST).