ESO Imaging Survey

Scodeggio, M.; Olsen, L. F.; Costa, L. N. da; Slijkhuis, R.; Benoist, Christophe; Deul, E.; Erben, T.; Hook, R. N.; Nonino, M.; Wicenec, A.; Zaggia, S.

doi:10.1051/aas:1999477

Cited by 34 publications

(48 citation statements)

References 1 publication

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“…a density distribution profile and a luminosity function). This last technique has been used to build the Palomar Distant Cluster Survey (PDCS, see P96) catalog and the EIS cluster catalog (Olsen et al 1999;Scodeggio et al 1999). These two catalogs are two of the largest presently available sets of distant clusters, with 79 and 302 candidate clusters respectively.…”

Section: Introductionmentioning

confidence: 99%

Finding galaxy clusters using Voronoi tessellations

Ramella¹,

Boschin²,

Fadda³

et al. 2001

A&A

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Abstract. We present an objective and automated procedure for detecting clusters of galaxies in imaging galaxy surveys . Our Voronoi Galaxy Cluster Finder (VGCF) uses galaxy positions and magnitudes to find clusters and determine their main features: size, richness and contrast above the background. The VGCF uses the Voronoi tessellation to evaluate the local density and to identify clusters as significative density fluctuations above the background. The significance threshold needs to be set by the user, but experimenting with different choices is very easy since it does not require a whole new run of the algorithm. The VGCF is non-parametric and does not smooth the data. As a consequence, clusters are identified irrespective of their shape and their identification is only slightly affected by border effects and by holes in the galaxy distribution on the sky. The algorithm is fast, and automatically assigns members to structures. A test run of the VGCF on the PDCS field centered at α = 13 h 26 m and δ = +29• 52 (J2000) produces 37 clusters. Of these clusters, 12 are VGCF counterparts of the 13 PDCS clusters detected at the 3σ level and with estimated redshifts from z = 0.2 to z = 0.6. Of the remaining 25 systems, 2 are PDCS clusters with confidence level < 3σ and redshift z ≤ 0.6. Inspection of the 23 new VGCF clusters indicates that several of these clusters may have been missed by the matched filter algorithm for one or more of the following reasons: a) they are very poor, b) they are extremely elongated, c) they lie too close to a rich and/or low redshift cluster.

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Section: Introductionmentioning

confidence: 99%

Finding galaxy clusters using Voronoi tessellations

Ramella¹,

Boschin²,

Fadda³

et al. 2001

A&A

Self Cite

163

170

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“…The targeted cluster candidates were selected from patch D with a matched filter estimated redshift z MF = 0.2 (Scodeggio et al 1999). In Table 1 we list the 24 selected cluster candidates.…”

Section: Observations and Data Reductionmentioning

confidence: 99%

“…The requirement for large samples of clusters of galaxies covering a large range in redshift has prompted systematic efforts to assemble catalogues of distant galaxy clusters (e.g. Gunn et al 1986;Postman et al 1996;Scodeggio et al 1999;Gladders & Yee 2001;Gonzalez et al 2001;Bahcall et al 2003). The main goal behind such works is to assemble large samples of clusters with z 0.5 because at these redshifts the evolutionary effects become more significant.…”

Section: Introductionmentioning

confidence: 99%

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Multi-object spectroscopy of low redshift EIS clusters

Olsen¹,

Benoist

Costa

et al. 2005

A&A

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Abstract.We have carried out an investigation of the properties of low redshift EIS clusters using both spectroscopy and imaging data. We present new redshifts for 738 galaxies in 21 ESO Imaging Survey (EIS) Cluster fields. We use the "gap"-technique to search for significant overdensities in redshift space and to identify groups/clusters of galaxies corresponding to the original EIS matched filter cluster candidates. In this way we spectroscopically confirm 20 of the 21 cluster candidates with a matched-filter estimated redshift z MF = 0.2. We have now obtained spectroscopic redshifts for 34 EIS cluster candidates with z MF = 0.2 (see also Hansen et al. 2002, A&A, 388, 1; Olsen et al. 2003, A&A, 409, 439). Of those we spectroscopically confirm 32 with redshifts ranging from z = 0.064 to 0.283. We find that: 1) the velocity dispersions of the systems range from σ v ≤ 130 km s −1 to σ v = 1200 km s −1 , typical of galaxy groups to rich clusters; 2) richnesses corresponding to Abell classes R ≤ 1; and 3) concentration indices ranging from C = 0.2 to C = 1.2. From the analysis of the colours of the galaxy populations we find that 60% of the spectroscopically confirmed systems have a "significant" red sequence. These systems are on average richer and have higher velocity dispersions. We find that the colour of the red sequence galaxies matches passive stellar evolution predictions.

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“…It is clearly important to detect clusters at redshifts as high as possible. To continue these searches to higher redshift, optical surveys have been performed over the last decade: PDCS (Postman et al 1996), EIS (Scodeggio et al 1999), TRCS (Gladders & Yee 2000), LCDCS (Gonzalez et al 2001), and MUNICS (Drory et al 2001). None of these surveys has, however, identified a significant sample of clusters with redshifts well beyond 1 (for a summary see Ramella et al 2000), because only optical and not infrared data (exception Drory et al 2001) were available, and at z = 1.5 the 4000 Å-break, the most important diagnostic feature, is shifted beyond the CCD bandpass into the near-infrared wavelength range.…”

Section: Introductionmentioning

confidence: 99%

The Heidelberg InfraRed Optical Cluster Survey (HIROCS)

Röser¹,

Hippelein²,

Wolf

et al. 2010

A&A

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Aims. We describe a survey for distant clusters of galaxies that identified clusters as local overdensities in the 3D galaxy distribution. Methods. Optical and near-IR imaging in B, R, i, z, and H are used to derive photometric redshifts for objects as faint as m* + 1 at a redshift of 1.5. We outline the astrometric and photometric data reduction. The 3D cluster search, based on the photometric redshifts, is described. Results. On the basis of the first fully reduced 1 square degree of data, we demonstrate that the objectives of HIROCS have been achieved. Four representative clusters from the list of candidates are presented.

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ESO Imaging Survey

Cited by 34 publications

References 1 publication

Finding galaxy clusters using Voronoi tessellations

Finding galaxy clusters using Voronoi tessellations

Multi-object spectroscopy of low redshift EIS clusters

The Heidelberg InfraRed Optical Cluster Survey (HIROCS)

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