Mass profile and dynamical status of the<i>z</i>~ 0.8 galaxy cluster LCDCS 0504

Guennou, L.; Biviano, A.; Adami, C.; Limousin, M.; Neto, G. B. Lima; Mamon, G. A.; Ulmer, M. P.; Gavazzi, R.; Cypriano, E. S.; Durret, F.; Clowe, Douglas; Lebrun, V.; Allam, S.; Basa, S.; Benoist, Christophe; Cappi, A.; Halliday, C.; Ilbert, O.; Johnston, David; Jullo, Eric; Just, Dennis W.; Kubo, Jeffrey M.; Márquez, I.; Marshall, Phil; Martinet, N.; Maurogordato, S.; Mazure, A.; Murphy, Kellen; Plana, H.; Rostagni, F.; Russeil, D.; Schirmer, M.; Schrabback, T.; Slezak, E.; Tucker, D. L.; Zaritsky, Dennis; Ziegler, B.

doi:10.1051/0004-6361/201322447

Cited by 14 publications

(16 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Biviano et al (2013) analyzed the cluster MACS J1206.2-0847, constraining its mass, velocity-anisotropy, and pseudo-phase-space density profiles, finding a good agreement between the results obtained from cluster kinematics and those derived from lensing. Similarly, Guennou et al (2014) compared the mass profile inferred from lensing with different profiles obtained from three methods based on kinematics, showing that they are consistent among themselves.…”

mentioning

confidence: 74%

See 1 more Smart Citation

Combining strong lensing and dynamics in galaxy clusters: integrating MAMPOSSt within LENSTOOL

Verdugo

Limousin

Motta

et al. 2016

A&A

Self Cite

View full text Add to dashboard Cite

Context. The mass distribution in both galaxy clusters and groups is an important cosmological probe. It has become clear in the last years that mass profiles are best recovered when combining complementary probes of the gravitational potential. Strong lensing (SL) is very accurate in the inner regions, but other probes are required to constrain the mass distribution in the outer regions, such as weak lensing or dynamics studies. Aims. We constrain the mass distribution of a cluster showing gravitational arcs by combining a strong lensing method with a dynamical method using the velocities of its 24 member galaxies. Methods. We present a new framework were we simultaneously fit SL and dynamical data. The SL analysis is based on the LENSTOOL software, and the dynamical analysis uses the MAMPOSSt code, which we have integrated into LENSTOOL. After describing the implementation of this new tool, we apply it on the galaxy group SL2S J02140-0535 (z spec = 0.44), which we have already studied in the past. We use new VLT/FORS2 spectroscopy of multiple images and group members, as well as shallow X-ray data from XMM. Results. We confirm that the observed lensing features in SL2S J02140-0535 belong to different background sources. One of this sources is located at z spec = 1.017 ± 0.001, whereas the other source is located at z spec = 1.628 ± 0.001. With the analysis of our new and our previously reported spectroscopic data, we find 24 secure members for SL2S J02140-0535. Both data sets are well reproduced by a single NFW mass profile: the dark matter halo coincides with the peak of the light distribution, with scale radius, concentration, and mass equal to r s =82 14 M ⊙ respectively. These parameters are better constrained when we fit simultaneously SL and dynamical information. The mass contours of our best model agrees with the direction defined by the luminosity contours and the X-ray emission of SL2S J02140-0535. The simultaneous fit lowers the error in the mass estimate by 0.34 dex, when compared to the SL model, and in 0.15 dex when compared to the dynamical method. Conclusions. The combination of SL and dynamics tools yields a more accurate probe of the mass profile of SL2S J02140-0535 up to r 200 . However, there is tension between the best elliptical SL model and the best spherical dynamical model. The similarities in shape and alignment of the centroids of the total mass, light, and intracluster gas distributions add to the picture of a non disturbed system.

show abstract

mentioning

confidence: 74%

“…The main difference of our work, when compared to previous works (e.g., Biviano et al 2013;Guennou et al 2014) is that we apply a joint analysis, seeking a solution consistent with both the SL and the dynamical methods, maximizing the total likelihood. In the bottom-panels of Fig.…”

Section: Sl+dyn Modelmentioning

confidence: 99%

Combining strong lensing and dynamics in galaxy clusters: integrating MAMPOSSt within LENSTOOL

Verdugo

Limousin

Motta

et al. 2016

A&A

Self Cite

View full text Add to dashboard Cite

show abstract

“…There have been many determinations of the M(r) of clusters of galaxies using cluster galaxies as tracers of the potential, both for individual clusters (e.g., Geller et al 1999;Rines et al 2000Rines et al , 2003Łokas & Mamon 2003;Łokas et al 2006;Rines & Diaferio 2006;Wojtak & Łokas 2010;Biviano et al 2013Biviano et al , 2017aGuennou et al 2014;Munari et al 2014;Balestra et al 2016;Maughan et al 2016;Sartoris et al 2020) and for stacks of several clusters (e.g., Carlberg et al 1997a;van der Marel et al 2000;Biviano & Girardi 2003;Katgert et al 2004). Results from these studies have been used to constrain the concentration-mass relation, in most cases by adopting the NFW model (Groener et al 2016;Biviano et al 2017b).…”

Section: Introductionmentioning

confidence: 99%

The GOGREEN survey: Internal dynamics of clusters of galaxies at redshift 0.9–1.4

Biviano

Burg

Balogh

et al. 2021

A&A

Self Cite

View full text Add to dashboard Cite

Context. The study of galaxy cluster mass profiles (M(r)) provides constraints on the nature of dark matter and on physical processes affecting the mass distribution. The study of galaxy cluster velocity anisotropy profiles (β(r)) informs the orbits of galaxies in clusters, which are related to their evolution. The combination of mass profiles and velocity anisotropy profiles allows us to determine the pseudo phase-space density profiles (Q(r)); numerical simulations predict that these profiles follow a simple power law in cluster-centric distance. Aims. We determine the mass, velocity anisotropy, and pseudo phase-space density profiles of clusters of galaxies at the highest redshifts investigated in detail to date. Methods. We exploited the combination of the GOGREEN and GCLASS spectroscopic data-sets for 14 clusters with mass M200 ≥ 1014 M⊙ at redshifts 0.9 ≤ z ≤ 1.4. We constructed an ensemble cluster by stacking 581 spectroscopically identified cluster members with stellar mass M⋆ ≥ 109.5 M⊙. We used the MAMPOSSt method to constrain several M(r) and β(r) models, and we then inverted the Jeans equation to determine the ensemble cluster β(r) in a non-parametric way. Finally, we combined the results of the M(r) and β(r) analysis to determine Q(r) for the ensemble cluster. Results. The concentration c200 of the ensemble cluster mass profile is in excellent agreement with predictions from Λ cold dark matter (ΛCDM) cosmological numerical simulations, and with previous determinations for clusters of similar mass and at similar redshifts, obtained from gravitational lensing and X-ray data. We see no significant difference between the total mass density and either the galaxy number density distributions or the stellar mass distribution. Star-forming galaxies are spatially significantly less concentrated than quiescent galaxies. The orbits of cluster galaxies are isotropic near the center and more radial outside. Star-forming galaxies and galaxies of low stellar mass tend to move on more radially elongated orbits than quiescent galaxies and galaxies of high stellar mass. The profile Q(r), determined using either the total mass or the number density profile, is very close to the power-law behavior predicted by numerical simulations. Conclusions. The internal dynamics of clusters at the highest redshift probed in detail to date are very similar to those of lower-redshift clusters, and in excellent agreement with predictions of numerical simulations. The clusters in our sample have already reached a high degree of dynamical relaxation.

show abstract

“…The Caustic method has been extensively used to determine cluster mass profiles (e.g. Biviano & Girardi 2003;Biviano et al 2013;Geller et al 2014;Guennou et al 2014).…”

Section: 3)mentioning

confidence: 99%

The Galaxy Cluster Mass Scale and Its Impact on Cosmological Constraints from the Cluster Population

et al. 2019

Self Cite

View full text Add to dashboard Cite

The total mass of a galaxy cluster is one of its most fundamental properties. Together with the redshift, the mass links observation and theory, allowing us to use the cluster population to test models of structure formation and to constrain cosmological parameters. Building on the rich heritage from X-ray surveys, new results from Sunyaev-Zeldovich and optical surveys have stimulated a resurgence of interest in cluster cosmology. These studies have generally found fewer clusters than predicted by the baseline Planck ΛCDM model, prompting a renewed effort on the part of the commu-nity to obtain a definitive measure of the true cluster mass scale. Here we review recent progress on this front. Our theoretical understanding continues to advance, with numerical simulations being the cornerstone of this effort. On the observational side, new, sophisticated techniques are being deployed in individual mass measurements and to account for selection biases in cluster surveys. We summarise the state of the art in cluster mass estimation methods and the systematic uncertainties and biases inherent in each approach, which are now well identified and understood, and explore how current uncertainties propagate into the cosmological parameter analysis. We discuss the prospects for improvements to the measurement of the mass scale using upcoming multiwavelength data, and the future use of the cluster population as a cosmological probe.

show abstract

Mass profile and dynamical status of thez~ 0.8 galaxy cluster LCDCS 0504

Cited by 14 publications

References 82 publications

Combining strong lensing and dynamics in galaxy clusters: integrating MAMPOSSt within LENSTOOL

Combining strong lensing and dynamics in galaxy clusters: integrating MAMPOSSt within LENSTOOL

The GOGREEN survey: Internal dynamics of clusters of galaxies at redshift 0.9–1.4

The Galaxy Cluster Mass Scale and Its Impact on Cosmological Constraints from the Cluster Population

Contact Info

Product

Resources

About