Search for clustering of background objects near distant radio galaxies using the MST method

Keshelava, T. V.; Верходанов, О. В.

doi:10.1134/s1990341315030025

Cited by 5 publications

(3 citation statements)

References 48 publications

(44 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to the set of their physical properties, radio sources are a powerful tool for testing cosmological epochs. They are associated with searching for the most distant active nuclei of galaxies [12,13], for protoclusters [14], estimating the background object clustering at different redshifts [15], and investigating the gravitational lensing. Taking into account the possibilities of millimeter and submillimeter surveys, the problem of searching for galaxy clusters with radio sources both at small and great redshifts naturally arises with the help of the Sunyaev-Zeldovich effect.…”

Section: Introductionmentioning

confidence: 99%

Advanced stream search for galaxy clusters with multifrequency microwave data

et al. 2018

View full text Add to dashboard Cite

Based on the data from the Westerbork Northern Sky Survey performed at a frequency of 325 MHz in the range of right ascensions 0h ≤ α < 2h and declinations 29o < δ < 78o and using multifrequency Planck maps, we selected candidate objects with the Sunyaev-Zeldovich effect. The list of the most probable candidates includes 381 sources. It is shown that the search for such objects can be accelerated by using a priori data on the negative level of fluctuations in the CMB map with remote low multipoles in the direction to radio sources.

show abstract

Section: Introductionmentioning

confidence: 99%

Advanced stream search for galaxy clusters with multifrequency microwave data

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Q has also been used to look for signatures of sequential star formation and mass segregation in observed star clusters (e.g. Kumar & Schmeja 2007;Caballero 2008;Allison et al 2009b;Küpper et al 2011;Camargo, Bonatto & Bica 2011;Gagné et al 2015), the distribution of cores in the Galaxy (Planck Collaboration et al 2011), the evolution of stellar distributions in the Magellanic Clouds and other external galaxies (Gieles, Bastian & Ercolano 2008;Bastian et al 2009;Gouliermis et al 2010;Bastian et al 2011;Haschke, Grebel & Duffau 2012;Gouliermis et al 2015), and even the distribution of field objects near radio galaxies (Keshelava & Verkhodanov 2015).…”

Section: Introductionmentioning

confidence: 99%

$\mathcal{Q}^{+}$: Characterising the structure of young star clusters

Jaffa,

Whitworth,

Lomax

2016

Preprint

View full text Add to dashboard Cite

Many young star clusters appear to be fractal, i.e. they appear to be concentrated in a nested hierarchy of clusters within clusters. We present a new algorithm for statistically analysing the distribution of stars to quantify the level of sub-structure. We suggest that, even at the simplest level, the internal structure of a fractal cluster requires the specification of three parameters. (i) The 3D fractal dimension, D, measures the extent to which the clusters on one level of the nested hierarchy fill the volume of their parent cluster. (ii) The number of levels, L, reflects the finite ratio between the linear size of the large root-cluster at the top of the hierarchy, and the smallest leafclusters at the bottom of the hierarchy. (iii) The volume-density scaling exponent, C = −d ln[δn]/d ln[L] measures the factor by which the excess density, δn, in a structure of scale L, exceeds that of the background formed by larger structures; it is similar, but not exactly equivalent, to the exponent in Larson's scaling relation between density and size for molecular clouds. We describe an algorithm which can be used to constrain the values of (D, L, C) and apply this method to artificial and observed clusters. We show that this algorithm is able to reliably describe the three dimensional structure of an artificial star cluster from the two dimensional projection, and quantify the varied structures observed in real and simulated clusters.

show abstract

“…Kumar & Schmeja 2007;Caballero 2008;Allison et al 2009b;Küpper et al 2011;Camargo, Bonatto & Bica 2011;Gagné et al 2015), the distribution of cores in the Galaxy (Planck Collaboration et al 2011), the evolution of stellar distributions in the Magellanic Clouds and other external galaxies (Gieles, Bastian & Ercolano 2008;Bastian et al 2009;Gouliermis et al 2010;Bastian et al 2011;Haschke, Grebel & Duffau 2012;Gouliermis et al 2015), and even the distribution of field objects near radio galaxies (Keshelava & Verkhodanov 2015).…”

Section: Introductionmentioning

confidence: 99%

$\mathcal {Q}^{+}$: characterizing the structure of young star clusters

Jaffa¹,

Whitworth²,

Lomax³

2016

Mon. Not. R. Astron. Soc.

View full text Add to dashboard Cite

Many young star clusters appear to be fractal, i.e. they appear to be concentrated in a nested hierarchy of clusters within clusters. We present a new algorithm for statistically analysing the distribution of stars to quantify the level of sub-structure. We suggest that, even at the simplest level, the internal structure of a fractal cluster requires the specification of three parameters. (i) The 3D fractal dimension, D, measures the extent to which the clusters on one level of the nested hierarchy fill the volume of their parent cluster. (ii) The number of levels, L, reflects the finite ratio between the linear size of the large root-cluster at the top of the hierarchy, and the smallest leafclusters at the bottom of the hierarchy. (iii) The volume-density scaling exponent,measures the factor by which the excess density, δn, in a structure of scale L, exceeds that of the background formed by larger structures; it is similar, but not exactly equivalent, to the exponent in Larson's scaling relation between density and size for molecular clouds. We describe an algorithm which can be used to constrain the values of (D, L, C) and apply this method to artificial and observed clusters. We show that this algorithm is able to reliably describe the three dimensional structure of an artificial star cluster from the two dimensional projection, and quantify the varied structures observed in real and simulated clusters.

show abstract

Search for clustering of background objects near distant radio galaxies using the MST method

Cited by 5 publications

References 48 publications

Advanced stream search for galaxy clusters with multifrequency microwave data

Advanced stream search for galaxy clusters with multifrequency microwave data

$\mathcal{Q}^{+}$: Characterising the structure of young star clusters

$\mathcal {Q}^{+}$: characterizing the structure of young star clusters

Contact Info

Product

Resources

About