1. Introduction
Galaxy clusters have been extensively used to study galaxy evolution because they allow us to discern between nature and nurture galaxy evolutionary processes [
1,
2]. For simplicity, hereafter, we refer to the intra-cluster medium (ICM) as the hot medium of both groups and clusters of galaxies. As galaxies plunge into the ICM, they experience different effects from their surrounding environment, including ram pressure (RP) and tidal stripping. These can produce a range of changes on the galaxy properties from gas loss to enhanced star formation (SF) activity due to the increased pressure acting on the disc of the galaxy. In observations, the effect of RP is studied in galaxies that are being stripped in clusters, identified via their distorted morphologies [
3,
4]. This proceeding presents an alternative method that uses all the galaxies that are identified as cluster members to detect RP stripping in a statistical way. The simplest way to detect this effect is by studying asymmetries in the galaxy properties by dividing each satellite in two halves: the one that faces the medium as it moves through the ICM, to which we will refer to as the leading half; and the one facing the opposite way, the trailing half of the galaxy. If the timescale of the effect of RP stripping on the SF activity is shorter than the dynamical timescale of the disc, the enhancement of the SF could be more prominent in the leading half, which is exposed directly to the RP effect. If this is the case, we would expect to find different SF properties/colours in the leading half with respect to the trailing one.
In this article, the results using the EAGLE simulation to detect these effects are presented. We measure the properties in the leading and trailing halves and study their differences using large samples of
galaxies in clusters and groups. We use the largest box of the EAGLE simulations in order to identify enough massive groups/clusters, in the range of
, and concentrate on large satellites, with more than 100 particles, to avoid resolution problems.
refers to the total mass of the halo, calculated as the sum of the mass of all particles. For the mass scale of the clusters and groups, we have used an overdensity of
as stated in the EAGLE collaboration website. In
Section 2, the dataset used is described in detail. In
Section 3, the results are presented. In
Section 4, we discuss our results and further prospects. Our conclusions are given in
Section 5.
2. Materials and Methods
2.1. EAGLE Simulation
The EAGLE project is a suite of hydrodynamic simulations immersed in a
cosmology. It uses up to seven billion particles per individual simulation to follow the physics of the galaxy processes, considering dark matter and gas particles. The gas particles fall into the centres of dark matter haloes, depending on how they have cooled and whether they reach a density greater than a certain threshold, they can be converted into star particles or not. The rate at which stars are formed is determined by the thermodynamic conditions of the medium. The simulations follow different feedback mechanisms, such as core collapse supernovae, exploding massive stars and AGN (Active Galactic Nuclei), via bursting supermassive black holes, etc. For further details please refer to [
5].
2.2. Halving the Galaxies
We analyse all
galaxies of the largest box simulation RefL0100N1504 that reside within one virial radius of groups of mass greater than
. These groups are found using the multistage procedure, based on a friends of friends algorithm, described in [
6].
We investigate two cases, first halving the galaxy with respect to the plane normal to its position vector and secondly to its velocity vector, both with respect to the centre of the mass of the host group. Hereafter, the former is dubbed the observational case; it refers to the measurements that can be performed in typical observations, while the second is dubbed simulation case which can only be measured when the velocity of the centre of the mass is known. These vectors and planes are shown in the cartoon representation of the problem, in the left panel of
Figure 1.
The right panel of
Figure 1 shows a three-dimensional view of an EAGLE galaxy cut in two halves, according to the plane perpendicular to the velocity vector, with respect to the centre of mass of its host. The left panel schematizes the vectors and planes used to halve the galaxies.
The falling angle is defined as the angle between the position and the velocity vector of the galaxy, both relative to the brightest cluster galaxy (BCG) of each cluster,
The EAGLE consortium provides a diversity of physical properties for each gas, dark matter, and stellar particle. We introduce a new quantity estimated with the star formation rate (SFR) and mass of the gas particles, hereafter dubbed SFR enhancement
This corresponds to the mass-weighted SFR that avoids effects from intrinsic asymmetries between the two halves, such as different number of particles, gas masses, etc., which could dominate the SFR difference. The normalization term
corresponds to the mass-weighted SFR of all gas particles. Within the sample analysed, the leading half of the galaxy that is shown in
Figure 1 presents a typical SFR enhancement of 10% with respect to its trailing half.
3. Results
In what follows, we study the SFR enhancement for the two cases described previously. Eighty galaxies are analysed in total, with typically 500 gas particles per galaxy.
3.1. Simulation Case
Figure 2 shows the SFR enhancement as a function of the falling angle. The median of the SFR enhancement is above zero, with a median value of 0.1 (red line). The positive enhancement shows that
s are higher in the leading half of galaxies in groups. Most of the galaxies (
) present a positive enhancement, with a few reaching up to
. This last case corresponds to the typical jellyfish galaxies (confirmed visually in a few examples).
3.2. Observational Case
In the case of real observed galaxies, it is challenging to obtain the three-dimensional velocity vector of satellites to define the leading and trailing halves. Here, the approach is simplified and the most simple observational case is discussed. The differences between the half of the satellite that points to the centre of the group/cluster, are compared to the other half. As it is shown in
Figure 2, the leading half shows higher
s with respect to the trailing half for falling angles lower than 100°. Although this would not be possible to know from observations, it helps to understand where the signal would be coming from. The median value tends to zero (red line). In this observational approach, the velocity vector is unknown, as well as the falling angle. Hence, the median value of the enhancement is the only value measurable using observations. A strategy to detect this effect in observations still needs to be devised, and we present a few examples in Troncoso et al. (in prep).
3.3. Dynamical State of the Host Clusters
We divide the galaxy sample in equal size according to the dynamical state of its host cluster. To determine the relaxation level of each cluster, we measure the position shift between the centre of mass and potential and normalized to its virial radius. The media of the SFR enhancement is pretty similar for both samples: for galaxies residing in the relax cluster, it is
and for the less relax cluster, it is
. In
Figure 2, the diamonds indicate the galaxies residing in relax clusters, while the crosses show the galaxies of the less relax clusters. Yet, the most extreme orbits with the highest SFR enhancements, with the small falling angles or receding galaxies, are found more frequently on galaxies residing in merging clusters, and relax clusters, respectively.
4. Discussion
We have measured the differences between the leading and trailing halves of cluster galaxies in groups and clusters considering different falling angles. The difference between the simulation and the proposed observational case is striking. By construction, the difference between the observational and simulation case increases with the falling angle. The simulation case shows that there is an enhancement of SFR in the leading half, suggesting that RP compression is boosting its SFR, while the observational case suggests that the RP compression is not producing any measurable change; i.e., the mean value of the enhancement is zero for the observational case, while for the simulation case it is positive. Galaxies with falling angles in the range are receding from the cluster centre. Small falling angles were preferably found in cluster galaxies. In the observational case, galaxies falling with angles above 100° tend to show a negative SFR enhancement. This result provides a caveat for observational works using the simplistic case proposed here aiming to detect RP stripping and it provides motivation to find the proper observable using hydrodynamic simulations. In a forthcoming article, the SFR enhancement will be analysed as a function of the galaxy global properties and redshift.
By dividing the sample according the dynamical state of the host cluster, we do not measure a difference of the media SFR enhancement in relax and less relax clusters. The orbits with small falling angles preferably occur on less relax clusters, while the receding galaxies are observed frequently on relax clusters.
In the EAGLE Universe, the largest differences were measured considering the most massive groups (i.e., ). Yet, the differences in are small, lower than .
Even if the simulation case was applicable in observations, it would be challenging to measure these differences with the available integral field units (IFUs) because, to achieve accurate s it is necessary to detect with a high signal to noise. Typically, this involves integrations that are larger by a factor of three–four times higher than for depending on the galaxy extinction. Since in this work we are proposing to integrate the in each half, and not use the individual spaxels, the signal will increase as , where is the total number of spaxels in the IFU.
5. Conclusions
Using the EAGLE simulation, we find an enhancement of the SFR in the part of the galaxy that is facing the intra-cluster medium (leading half) with respect to the trailing one. The differences between the leading and trailing halves of other physical properties, and their evolution with redshift will be presented in a forthcoming article (Troncoso et al. in prep). To confirm these results with observations, it is necessary to study different observational cases using the simulation as a testbed, because projection effects can mislead the final conclusions, as it was shown in this work. This is a clear example and motivation to find the proper observables using hydrodynamical simulations.
Acknowledgments
Paulina Troncoso Iribarren acknowledges support from FONDECYT-CONICYT 3140542.
Author Contributions
Nelson Padilla, Paulina Troncoso Iribarren, Claudia Del P. Lagos, and Diego García-Lambas conceived and designed the experiments; Paulina Troncoso Iribarren analyzed the data. Sergio Contreras, Silvio Rodriguez, and Claudia Del P. Lagos provided materials and analysis tools. Nelson Padilla and Paulina Troncoso Iribarren wrote the paper.
Conflicts of Interest
The authors declare no conflict of interest.
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