Astronomical Data Analysis Software and Systems XIX
ASP Conference Series, Vol. XXX, 2009
Y. Mizumoto, K.-I. Morita, and M. Ohishi, eds.

P65

Environment Study of AGNs at z = 0.3 to 3.0 using theJapanese Virtual Observatory
Yuji Shirasaki, Masatoshi Ohishi, Yoshihiko Mizumoto, Tadafumi
TakataNational Astronomical Observatory of Japan, Mitaka, Tokyo, Japan
Masahiro Tanaka
University of Tsukuba, Tsukuba, Ibaraki, Japan
Naoki Yasuda
Institute for the Physics and Mathematics of the Universe, The
University of Tokyo, Kashiwa, Chiba, Japan
Abstract.
We present a science use case of Virtual Observatory, which was achieved toexamine an environment of AGN up to redshift of 3.0. We used the Japanese Virtual Observatory (JVO) to obtain Subaru Suprime-Cam images around knownAGNs. According to the hierarchical galaxy formation model, AGNs are expected to be found in an environment of higher galaxy density than that oftypical galaxies. The current observations, however, indicate that AGNs do notreside in a particularly high density environment. We investigated ∼1000 AGNs,
which is about ten times larger samples than the other studies covering the redshifts larger than 0.6. We successfully found signiﬁcant excess of galaxies around
AGNs at redshifts of 0.3 to 1.8. If this work was done in a classical manner,that is, raw data were retrieved from the archive through a form-based web interface in an interactive way, and the data were reduced on a low performancecomputer, it might take several years to ﬁnish it. Since the Virtual Observatory
system is accessible through a standard interface, it is easy to query and retrieve
data in an automatic way. We constructed a pipeline for retrieving the data andcalculating the galaxy number density around a given coordinate. This procedure was executed in parallel on ∼10 quad core PCs, and it took only one dayfor obtaining the ﬁnal result. Our result implies that the Virtual Observatory
can be a powerful tool to do an astronomical research based on large amount ofdata.

1.

Introduction

It has been thought that the origin of AGN activity is accretion of matters intoa massive black hole at the center of the galaxy (e.g. Lynden-Bell 1969). One
possible mechanism for causing rapid gas inﬂows into the central region is amajor merger between gas-rich galaxies. If this is the case, AGNs are expected
to be found in an environment of higher galaxy density than an environment of
typical galaxies. Thus the AGN produced at higher redshifts should be observedin a high galaxy density environment.
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Shirasaki et al.

The previous observations, however, indicated that AGNs did not reside ina particularly high density environment. We must, however, be cautious withthe results obtained especially at high redshift (z > 0.6). All the high redshiftobservations were based on the galaxies selected by adapting a color cut, so somekinds of galaxies were missed in their samples. The observations were limited toseveral speciﬁc ﬁelds, thus the results were strongly aﬀected by cosmic variance.
We investigated ∼1000 AGNs, which were distributed in wide area of thesky, without applying any color selection. The number of AGN examined isabout ten times larger than the other studies covering the redshifts larger than
0.6. We successfully found signiﬁcant excess of galaxies around AGNs at redshifts of 0.3 to 1.8.
If this work was done in a classical manner, that is, raw data were retrieved
from the archive through a form-based web interface in an interactive way, andthe data were reduced on a low performance computer, it might take several
years to ﬁnish it. Thus we have developed parallel computing system which
can communicates directly with the Subaru data archive in bandwidth of 32
Gbps at maximum (Shirasaki et al. 2007, Shirasaki et al. 2008). All the publicSuprime-Cam data were reduced using this system, and the data were provided
through the JVO system (Shirasaki et al. 2009). So it is possible to do anenvironment study for any types of object using the deep image obtained by theSuprime-Cam with very few eﬀort. Our result implies that the Japanese Virtual
Observatory can be a powerful tool to investigate the large scale structure of theintermediate redshift Universe.
2.

MethodWe have constructed a pipeline for calculating the distribution of galaxy number density around a given coordinate. The procedure of the study of QSO
environment using the JVO is as follows (see also Figure 1) :Step 0 (Admin) : Parallel processing of large amount of data
Data reduction of all the Suprime-Cam data were performed on the JVO
grid computing system (12 servers, 48 CPU cores). 10 TB of RAW data
are reduced through the JVO web interface. The processing time was ∼10days. The metadata of the processed image were registered to databaseand made public through the VO interface.
Step 1 : Multiple database query
Suprime-Cam image and UKIDSS catalog data (Warren et al. 2007) weresearched around known AGNs (Veron-Cetty and Veron 2006, Schneider etal. 2007). The JVO Query Language (JVOQL) shown in the Figure 1
is an example to do a coordinate join between AGN catalog table andSuprime-Cam metadata table.
Step 2 : Workflow for calculating galaxy density around each AGN
We made a script “qso-dataset.sh” which executes the following workﬂow:
1. Retrieve images and catalog data around a speciﬁed coordinate ofAGN. The query was directly sent to the SkyNode.

Environment Study of AGNs using JVOFigure 1.

3

The procedure of the study of QSO environment using the JVO

2. Extract objects from the images, and cross-match to create a multibands catalog.
3. Calculate galaxy number density around the AGN coordinate Thiswas executed for every AGN found in the step 1:
Step 3 : Detailed analysis on a local machine
Stack the galaxy density proﬁles around each AGN, and calculate a correlation length between AGN and galaxies for each AGN’s redshift andluminosity range.
The step 2 was executed in parallel on ∼10 quad core PCs, and it took only
one day for obtaining the ﬁnal result.
3.

Conclusion

Using JVO, we were able to measure the clustering property for ∼ 1000 AGNs atredshifts 0.3–3.0 with optical brightness of MV = −30 to −20. It is emphasized4Shirasaki et al.

that this work uses the largest sample with deep optical images, which are
typically deeper than 24 mag. By using the deep optical images, we can alsomeasure the clustering property of faint and blue star forming galaxies around
AGNs at high redshift (z ∼ 1 – 2), which have not been well explored by anyother studies. It is also noted that our work would be a bias-free task (free fromthe cosmic variance), since the AGNs we have used are distributed in a wide areaof the sky. The detailed of the result can be found in Shirasaki et al. (2009b).
The functionality of JVO to join the two distributed tables, AGN catalog
and the Subaru Suprime-Cam image metadata table, enabled us to easily ﬁnd
Subaru Suprime-Cam images which contained an AGN at the center of theimage. Since the data access to the VOs is programmable in a uniform interface,
both of the data retrieval and data analysis can be integrated into a single script,
and can be executed in an automated way. Just by changing the tables usedin the script, we can adapt this script to another science case, which might
accelerate astronomical discoveries.
We would like to emphasize that the usefulness to open to public the reduced
wide ﬁeld images like those of Suprime-Cam. Those images might provide roomfor further studies which were not aimed by the PI observers. The raw data isuseful for making detailed analysis on user’s local machine, however, it is not
appropriate for doing statistical analysis based on large amount of data. It ispainful to download all the Suprime-Cam images and reduce them on a low
performance PC, which may take over one year to complete. We could ﬁnish
the workﬂow to calculate the distributions of galaxy number density around
AGNs in about one day, which promises that the VO will be a powerful tool toinvestigate based on large amount of data.
Acknowledgments. This work was supported by the JSPS Core-to-Core
Program and Grant-in-aid for Information Science (15017289, 16016292, 18049074
and 19024070) carried out by the Ministry of Education, Culture, Sports, Scienceand Technology (MEXT) of Japan. YS is grateful for support under Grant-inaid for Young Scientists (B) (17700085, 21740143) carried out by the MEXT ofJapan.
References
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