1. No category

Department of Physics, Chemistry and Biology
Master’s Thesis
X-ray Analysis of a Complete Sample of Giga-Hertz
Peaked Spectrum Galaxies
Olof Tengstrand
LiTH-IFM-A-EX--08/1954--SE
Department of Physics, Chemistry and Biology
Link¨
opings universitet, SE-581 83 Link¨oping, Sweden
Master’s Thesis
LiTH-IFM-A-EX--08/1954--SE
X-ray Analysis of a Complete Sample of Giga-Hertz
Peaked Spectrum Galaxies
Olof Tengstrand
Adviser:
Dr. Matteo Guainazzi
European Space Agency
Examiner:
Prof. Leif Johansson
IFM
Link¨
oping, 12 May, 2008
Avdelning, Institution
Division, Department
Datum
Date
IFM
Department of Physics, Chemistry and Biology
Link¨
opings universitet, SE-581 83 Link¨
oping, Sweden
2008-05-12
Spr˚
ak
Language
Rapporttyp
Report category
ISBN
Svenska/Swedish
Licentiatavhandling
ISRN
Engelska/English
Examensarbete
C-uppsats
D-uppsats
¨
Ovrig
rapport
—
LiTH-IFM-A-EX--08/1954--SE
Serietitel och serienummer ISSN
Title of series, numbering
—
URL f¨
or elektronisk version
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11909
Titel
Title
Analys av r¨
ontgenstr˚
alning fr˚
an en komplett upps¨
attning av GPS galaxer
X-ray Analysis of a Complete Sample of Giga-Hertz Peaked Spectrum Galaxies
F¨
orfattare Olof Tengstrand
Author
Sammanfattning
Abstract
This thesis investigates the X-ray properties of the entire Stanghellini et al. (1998)
complete sample of GHz Peaked Spectrum galaxies with redshift lower than 1. In
total 19 sources are included mainly from observations made by the European
space telescope, XMM-Newton. Out of these the analysis of seven ”new” observations made between 2006 and 2008 are throughout described. Data from the
new observations shows consistency with already analysed data. As a new result a
tentative discovery of a bi-modal structure in the X-ray to radio luminosity ratio
within the sample is presented.
Nyckelord Active Galaxies, GPS, X-ray astronomy, XMM Newton
Keywords
Abstract
This thesis investigates the X-ray properties of the entire Stanghellini et al. (1998)
complete sample of GHz Peaked Spectrum galaxies with redshift lower than 1. In
total 19 sources are included mainly from observations made by the European
space telescope, XMM-Newton. Out of these the analysis of seven ”new” observations made between 2006 and 2008 are throughout described. Data from the
new observations shows consistency with already analysed data. As a new result a
tentative discovery of a bi-modal structure in the X-ray to radio luminosity ratio
within the sample is presented.
v
Acknowledgements
I would like to acknowledge the European Space Astronomy Center (ESAC) and
their trainee project which has made this thesis possible. Especially I would like
to thank my tutor Dr. M. Guainazzi for being a friendly and helpful person, both
within and outside the project.
I would also wish to thank Benjamin, Maria and all other persons that had the
kindness of giving us trainees ride between ESAC and Madrid.
Of course also a special thanks to all the other trainees who helped to make
the project and the stay in Madrid even more pleasurable.
This research has made use of the NASA/IPAC Extragalactic Database (NED)
which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Adminisrtation.
vii
Nomenclature
Acronyms and abbreviations
Acronym
AGN
CCF
EPIC
ESA
ESAC
FRI
FRII
GPS
HR
MOS
ODF
OM
RGS
SAS
XMM-Newton
Explanation
Active Galactic Nucleus
Current Calibration File
European Photon Imaging Camera
European Space Agency
European Space Astronomy Centre
Fanaroff-Riley type I
Fanaroff-Riley type II
Giga-Hertz Peaked Spectrum
Hardness ratio
Metal Oxide Semi-conductor
Observation Data File
Optical Monitor
Reflection Grating Spectrometer
Science Analysis Subsystem
X-ray Multi-Mirror Mission
Physical symbols
Symbol
α
Γ
F
L
nH
ν
z
Explanation
spectral index
photon index
flux
luminosity
column density
frequency
relativistic redshift
unit
ergs/(s ∗ cm2 )
ergs/s
cm−2
Hz
-
ix
Contents
1 Introduction
1.1 Structure of this work . .
1.2 Project purpose . . . . . .
1.2.1 Scientific goal . . .
1.3 Samples . . . . . . . . . .
1.4 Limitations and problems
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1
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2 Data reduction
2.1 Analytical tools . . . . . . . . . . . . . . . . .
2.2 Choice of energy bands . . . . . . . . . . . . .
2.3 Generating a spectra . . . . . . . . . . . . . .
2.3.1 Selecting source and background areas
2.3.2 Optimising signal to noise ratio . . . .
2.3.3 The final steps . . . . . . . . . . . . .
2.4 Spectral modeling . . . . . . . . . . . . . . .
2.4.1 Models used . . . . . . . . . . . . . . .
2.5 Timing analysis . . . . . . . . . . . . . . . . .
2.6 Other methods . . . . . . . . . . . . . . . . .
2.6.1 Using ximage . . . . . . . . . . . . . .
2.6.2 Deriving Γ and nH . . . . . . . . . . .
2.6.3 Deriving flux and luminosity . . . . .
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3 Results
3.1 Results from the new observations
3.1.1 Spectral analysis . . . . . .
3.1.2 Timing analysis . . . . . . .
3.1.3 Contour plots . . . . . . . .
3.2 Properties from literature . . . . .
3.3 Flux in Restframe . . . . . . . . .
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4 Discussion and conclusions
4.1 Discussion of the results . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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xii
Contents
Bibliography
25
A Active Galaxies
A.1 Radio galaxies . . . . . .
A.2 GPS galaxies . . . . . . .
A.2.1 Radio properties .
A.2.2 X-ray properties .
A.2.3 Evolution of GPS .
B XMM-Newton telescope
B.1 The spacecraft . . . .
B.2 Instruments on board
B.2.1 EPIC . . . . .
B.3 EPIC calibration . . .
B.4 Comparison with other
C Derived data.
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x-ray telescopes
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35
Chapter 1
Introduction
This thesis was carried out as a six month long trainee project at the European
Space Astronomy Centre, ESAC, in Villafranca de Castillo outside Madrid, Spain.
It builds on seven recently taken observations done by the European X-ray telescope XMM-Newton put together with eleven older observations analysed or reanalysed by the responsible coordinator for the project Dr. M. Guainazzi.
1.1
Structure of this work
This thesis is written in the form of a scientific report. The purpose of the first
chapter is to give a very short overview of the project and the sources analysed
therein. For a person not familiar with radio and X-ray astronomy it is advisable
to first read appendix A, where the needed terminology of active galaxies are described, before continuing with the other parts of the thesis.
Chapter 2 describes the procedure of datareduction from the point of a user of
XMM-Newton data. The effects and calibration of the scientific instruments on
board XMM-Newton is not described here since the analysis assumes the data to
be properly calibrated. For an introducing description of the telescope including
a short section on calibration the interested is refered to appendix B.
The two last chapters describe results and conclusions that can be drawn from
the work. The last chapter also contains some suggestions for future work.
1.2
Project purpose
GHz Peaked Spectrum (GPS) radio sources are strong and compact objects with
a simple convex radio spectrum. [14] They are defined by a spectrum turnover
frequency between 0.4 and 6 GHz and a radio defined spectral index above the
peak steeper than -0.5. [2] About half of the GPS sources are classified as GPS
galaxies. The GPS galaxies are active galaxies often showing strong and small
1
2
Introduction
radio jets. (See appendix A for more a more detailed description of GPS sources.)
In contrast to the radio spectrum, GPS galaxies often tend to be weak in Xrays and only a few GPS have been analysed in this spectral energy range. Prior
to NASAs X-ray telescope Chandra (launched July, 1999 [1]) and XMM-Newton
(December, 1999 [17]) only two high-quality CCD-resolution spectra in hard Xrays were available for GPS sources [7] and using different datasets of available
X-ray data from Chandra and XMM-Newton, [7] and [6] arrives at apparently
different conclusions.
The purpose with my project is therefore to extend the number of observed GPS
sources by describing the X-ray properties of a complete sample GPS galaxies. This
is important and necessary if conclusions about the properties of GPS sources shall
be put on a robust statistical basis.
1.2.1
Scientific goal
GPS galaxies are believed to be the initial face of giant radio jets and a study of
these galaxies are therefore interesting because they might provide information on
the origin and evolution of the radio power in the universe. Alternatively the GPS
galaxies could be hosted in dense environments that prevent them from evolving
into larger radio structures.
To conclude an answer three questions was originally formulated as the scientific
goal of this project [2]:
• Is there any systematic differences in the X-ray versus radio luminosity ratio
between compact GPS and normal radio galaxies, which may point to an
intrinsic difference in the physical process responsible for the spectral energy
distribution in the two classes?
• Are compact GPS radio sources hosted in dense environments?
• Does the environment brake or prevent the evolution of the radio structure?
When investigating the first question an interesting separation in the X-ray versus
radio luminosity ratio within the group of GPS galaxies was discovered. This
resulted in that an additional question was added to the goal of project:
• Is there a bi-modal structure of the X-ray versus radio luminosity ratio?
1.3
Samples
The sources analysed in this thesis covers a complete sample of GPS galaxies with
redshift z<1 taken from [4]. The parent sample is defined with:
• Flux density at 5 GHz above 1 Jy.
1.3 Samples
3
• Observed turnover frequency between 0.4-6 GHz.
• Radio spectral index above the peak steeper than -0.5
Where the two last points is simply definitions of GPS galaxies.
With aim to cover the entire sample with XMM-Newton observations, seven objects were observed within AO4 between 2006 and 2008. For PKS0941-08 no
XMM-Newton observation was granted and therefore a Chandra observation of
the object were instead analysed.
Table 1.1 shows the position and which telescope was used for the X-ray observation analysed in this thesis. The table also shows three other sources (COINSJ0029,
4C+55.16 and 3C303.1) that has been added to the sample.
Table 1.1. A complete sample of GPS galaxies
GPS
4C+00.02
COINSJ0029+3456
COINSJ0111+3906
PKS0428+20
PKS0500+019
B30710+439
4C+55.16
PKS0941-080
B1031+567
4C+14.41
4C+32.44
PKS1345+125
4C+62.22
OQ+208
3C303.1
PKS1607+26
PKS2008-068
PKS2127+04
COINSJ2355+4950
a
b
alt. name
0019-000
0026+346
0108+388
0428+205
0500+019
0710+439
0831+557
0941-080
1031+567
1117+146
1323+321
1344+125
1358+624
1404+286
1443+77
1607+268
2008-068
2128+048
2352+4950
positiona (EquJ2000.0)
00h22m25.4s +00d14m56s
00h29m14.2s +34d56m32s
01h11m37.3s +39d06m28s
04h31m03.7s +20d37m34s
05h03m21.2s +02d03m05s
07h13m38.1s +43d49m17s
08h34m54.9s +55d34m21s
09h43m36.9s -08d19m31s
10h35m07.0s +56d28m47s
11h20m27.8s +14d20m55s
13h26m16.5s +31d54m10s
13h47m33.3s +12d17m24s
14h00m28.6s +62d10m39s
14h07m00.4s +28d27m15s
14h43m14.8s +77d07m29s
16h09m13.3s +26d41m29s
20h11m14.2s -06d44m04s
21h30m32.9s +05d02m17s
23h55m09.4s +49d50m08s
Observed
XMMb
XMM
XMM
XMMb
XMM
XMM
ASCA/GIS
Chandra
XMM
XMMb
XMMb
ASCA
XMM
XMM (ASCA)
XMM
XMMb
XMMb
XMMb
XMM
Data taken from NED (http://nedwww.ipac.caltech.edu/forms/byname.html)
Observations made within XMM-Newton AO4.
The sample was compared with a control sample of ’normal’ radio sources made up
of both FRI and FRII galaxies. The latter being a sparse collection of ASCA and
BeppoSAX observations already used by Guainazzi et al. (2005), merged with a
sample of high redshift objects observed by Chandra and XMM-Newton, published
by Belsole et al. (2005). The control sample of FRI is a sample of approximately
25 high-resolution observations by Chandra that has been published by Donato et
al. (2004).
4
1.4
Introduction
Limitations and problems
In this X-ray analysis the limitations in deriving valuable data are mostly set by
the problem of detecting and collecting enough photons from the observed source.
Although XMM-Newton has a large effective area [17], the analysis failed to make
a true spectral fitting for several of the observed GPS galaxies. Instead alternative
methods had to be used to limit some of the wanted parameters, which results in
a lower accuracy for the obtained data.
The failure of obtaining true spectra also made it impossible to do a simple spectral comparison between the GPS galaxies in their restframes, which would have
been a great advantage, when investigating the possibility of a separation into two
sub-groups.
In some cases flares and high radiation background affected the observations. This
shortened the time of useful data, and reduced the signal to noise ratio.
For the GPS galaxy, PKS0941-080, no XMM-Newton observation was granted.
Instead an available observation from NASAs X-ray telescope Chandra was used.
Since there was no time to learn the structure of the data files from Chandra
within this project, the data could not be fully analysed. When available already
analysed data from [7] was therefore used.
The last planed observation (PKS1607+26) for this project took place as late as
the 19th of Jan. 2008. Calculated data from this observation can not be considered useful without the data that could not be derived before the project finished.
PKS1607+26 is therefore excluded from this thesis.
Chapter 2
Data reduction
As an overview figure 2.1 shows the main steps in the procedure of datareduction for the XMM-Newton observations made within AO4 (See table 1.1) and for
PKS0500+019. Further and more detailed information about the steps in the flow
chart and tools used in the procedure is described throughout this chapter. For
the other GPS galaxies in the sample a similar procedure had already been done
by Dr. M. Guainazzi and the results summarized in tables.
Figure 2.1. Flow chart showing the main steps in the procedure of data reduction: From the
ODF files a spectra is created. If there are enough energy bins in the spectra a spectral fitting
was done together with a simple timing analysis. If no true spectral fitting could be done other
methods based on the hardness ratio was instead used to derive the wanted parameters.
5
6
Data reduction
2.1
Analytical tools
For reduction and analysis of the data several different computer programs designed for astrophysics were used. The most important ones are:
• SAS: The Science Analysis Software, contains a lot of mission dependent
tools for XMM-Newton data. For the data in this thesis SAS version 7.1.0
was used.
• xspec: An X-ray spectral fitting program distributed by HEARSAC/NASA.
Xspec is a mission independent program that uses the χ2 to find the best
fit of a chosen model to the given data. In this thesis xspec version 11 was
used.
• ximage: A multi-mission X-ray image display and analysis program, here
used to calculate count rates for the most X-ray weak GPS galaxies.
• pimms: Portable, Interactive Multi-Mission Simulator, here used to simulate the flux from pn camera when no spectra could be obtained. The tool
is distributed by HEARSAC/NASA and webpimms v.3.9 was used as well as
the interactive web version at http://hearsac.gsfc.nasa.gov/Tools/w3pimms.html
2.2
Choice of energy bands
X-ray parameters are when possible derived from a spectral fitting in the observed
energy range between 0.2 and 10.0 keV. Otherwise the hardness ratio (HR) had
to be used to limit the parameters. The hardness ratio can be defined in many
different ways but this thesis will consistently use the definition:
HR =
count rate hard energy band
count rate 1.0 − 10.0 keV
=
count rate 0.2 − 1.0 keV
count rate sof t energy band
(2.1)
For rest frame calculations the two rest frame energy ranges 1.0-2.0 keV and 2.010.0 keV were used.
2.3
Generating a spectra
Data from the XMM-Newton observations were provided in a bundle of files called
Observation Data Files (ODF). These files contains uncalibrated data from all the
instruments onboard XMM-Newton. Using SAS 7.1.0 on the ODF together with
a calibration file, eventfiles could be obtained for each one of the EPIC instruments. Eventfiles are calibrated and concatenated files containing the important
information, i.e. energy, time and place, of the incoming photons, for constructing
a lightcurve, spectrum or image.
2.3 Generating a spectra
2.3.1
7
Selecting source and background areas
Before a source spectrum can be obtained the incoming photons from the source
has to be separated from the other photons in the observation. This was done by
enclosing the source with a circular region. The source position (table 1.1) was
taken from the NASA/IPAC extragalactic database (NED).
In order to get the true spectrum it is also important to subtract the background
radiation from the source. Following the advises for point sources in [9] a circular background region was chosen from the same observation as the source region
using the criteria:
• For MOS: From a source free region on the same CCD as, and near the
source.
• For pn: From a source free region at a nearby CCD and at the same height
in the image as the source.
2.3.2
Optimising signal to noise ratio
While many of the sources were very faint, there were important to choose thresholds so that intervals of flaring particle background were removed and the signal to
noise ratio was optimised. Ten different thresholds logarithmically spaced between
0.1 and about two times the highest value of counts/s on the lightcurve for the
entire observation, were tested to find the highest value of the signal to noise ratio.
For each threshold the radius of the source extraction region were also varied to
obtain the highest number of counts in relation to the area.
2.3.3
The final steps
Having a background and a source spectrum generated with an optimised threshold the final step is to subtract the background from the source and generate a
spectrum file. In order to do this the source and the background counts have to
be scaled in proportion of there areas. Thereafter a redistribution matrix have to
be generated from the source file, which describes the probability distribution in
channel space for incident photons at a range of energies.
The final preparation is to group the events in bins with appropriate size in energy
range and counts/bin. Since every intrinsic energy is spread out by the measurement, nearby energy-bins will be dependent of each other. To mainly avoid oversampling of the intrinsic instrumental energy resolution by a factor larger than
3, each bin were adjusted in size on the energyscale so that the spread from one
intrinsic energy was covered by three energybins.
A Gaussian count distribution in each spectral channel is a pre-condition for using
the χ2 -statistics in the spectral fit. The central limit theorem states that every distribution of random independent variables can be approximated with a Gaussian
distribution if large enough and it is therefore important to have enough counts in
8
Data reduction
each energy bin. This was made by merging the independent bins above so that
every bin had at least 25 counts.
2.4
Spectral modeling
To be able to create a spectrum and fit a model the X-ray spectral-fitting program
xspec was used. A model can be fitted to the spectrum only if the spectrum
contains more bins than the number of free parameters in the model. In several of
the cases the number of detected counts from the source was too small to obtain
more than a few (1-3) energy bins in the spectra. In these cases no model could
be fitted and other methods had to be used to estimate some of the searched
parameters. (See these methods described in section 2.6.) The idea of making
more energy bins by reducing the number of counts in each bin was not applicable
since this would have negative effect on the statistical Gaussian distribution of the
bins.
When possible the following parameters were calculated with xspec:
• Column density, nHGP S , where the GPS index is introduced to separate it
from the known column density, nH in our own Galaxy.
• Photon index, Γ
• Flux
• Luminosity
2.4.1
Models used
To model the slope of the spectra a photon powerlaw was introduced to the model.
Considering also the photo-electric absorption two more components were added.
The first one modelling the photo-electric absorption in our own Galaxy and the
second one doing the same for the GPS. The absorption between the two galaxies
were ignored due to the fact that the electron density, ne , between the galaxies
is very small compared to the one in the interstellar medium within the galaxies.
A redshift had also to be introduced in the absorption component for the GPS to
take the relative velocities between the galaxies into account.
Later a fourth component was introduced to determine whether or not an iron Kα
emission line could be detected.
The models and model parameters are described in the following two sections.
model 1: Base model
The basic model consists of three components:
M (E)
MGP S (E)
A(E)
= e−nH σ(E)
(2.2)
= e−nHGP S σ(E[1+z])
(2.3)
= KE
−Γ
(2.4)
2.5 Timing analysis
9
Where (2.2) and (2.3) are photo-electric absorption using Wisconsin crosssections, while (2.4) is a simple photon powerlaw, with the normalization parameter K [photons/(eV ∗ cm2 ∗ s)] at 1 keV. Wisconsins cross-section, σ(E),
describes the interstellar effective photo-electric cross section per hydrogen atom,
calculated as a function of energy [13]. The cross-section is not including Thomson
scattering. Component (2.2) refers to the photo-electric absorption in our own
Galaxy while (2.3) refers to the GPS.
In the fitting the redshift was taken as given from the NASA/IPAC extragalactic database (NED), when the source was searched for by name. The nH was
calculated using the web-interface version1 of the ftool nh. The value taken as
the weighted average nH calculated from a cone radius of 1◦ around the source
position using the Leiden/Argentine/Bonn (LAB) Survey of Galactic HI. These
two parameters were then kept fixed during the fitting.
model 2: Adding of iron Kα emission line
To be able to look for the presence of a fluorescent iron Kα emission line a Gaussian line profile was introduced to the model:
A(E) = √
2
1
K
∗ e 2 [(E(1+z)−EL )/σ] → δ(E(1 + z) − EL ) when
2πσ 2 (1 + z)
σ → 0(2.5)
As we were only interested in a specific spectral iron line the line energy EL was
fixed at 6.4 keV and the line width σ was set to 0 keV which makes xspec treat the
function as a delta function. The redshift z is the same as in the previous model
and the normalization constant K [photons/(cm2 s)] was left free.
After the new model was fitted an F-test was made between model 1 and 2 to
determine whether or not an emission line is of significance for the final spectral
model and if no emission line could be found the equivalent width upper limit for
FeKα was calculated.
2.5
Timing analysis
In order to determine if there were any variations in the ratio between the hard
and the soft energy band during the observation, two lightcurves were extracted
from the pn camera in each observation2 . Using the ftool lcurve with a time bin
size of 1024s, the lightcurves were ploted together with the hardness ratio between
them. The lcurve model const was then used to fit the HR with a constant and by
looking at a doublesided 90% confidence interval, the χ2 -value was tested against
the model.
1
http://heasarc.gsfc.nasa.gov/cgi-bin/Tools/w3nh/w3nh.pl
this was only done with the sources that had enough counts to be analyzed in xspec as
2 N.B.
well.
10
Data reduction
2.6
Other methods
When there were impossible to obtain a good spectra with xspec (due to too few
counts from the source), the parameters Γ and nH had to be estimated through
other methods. This was done using the ratio between the counts in the hard and
the soft energy bands. The counts from the source in each band were calculated
either with SAS tasks or by using the ftool ximage. The individual SAS subtasks
of edetect chain were run to find sources in the observations. This was done three
times, analysing the hard, the soft and the total energy band. The basic steps in
edetect chain are as follows:
1. Generate an image in the chosen energy band, using a cleaned event
list and including all valid patterns.
2. Create an exposure map. Making use of the calibration information in
the CCF an exposure map, corrected for the defects in the telescopes image
(i.e. quantum efficiency, filter transmission, mirror vignetting, and field of
view), is generated. There are also corrections for bad pixels which are
excluded from the exposure map.
3. In order to know in which areas to search for sources a detection mask is
generated. In our case all areas with an exposure time greater than 25% of
the maximum exposure time and where the gradient of the exposure map is
less than 0.5 will be included for this search.
4. Perform a first sliding box detection in order to mark out the sources
for the next step. A 5x5 pixel box is used to accumulate the source counts
and the surrounding 56 pixels are used as background. In order to be able
to detect extended sources three different runs are made, each one doubling
the box size.
5. A source brightness dependent cut-out radius (set to 0.005 counts/arcsec2 ) is
used to remove the sources found in the previous step and from the remaining
image a background map is created.
6. Perform a second sliding box detection using the background map in
order to improve the detection sensitivity of step 4.
7. Fitting the parameters source location, source extension and source count
rate, the final source list is generated.
In the cases a source was detected the count rate and the corresponding error was
read from the source list generated in step 7 using the ftool fv.
2.6.1
Using ximage
In the cases where the SAS tasks described above failed to find the source the ftool
ximage was used to obtain the limits for the HR.
2.6 Other methods
11
First the cleaned eventfiles for all three cameras were merged with the SAS task
merge. After this ximage command sosta was used, which returns the number of
counts encircled in a box, with corrections for vingnetting, exposure and the PSF.
The background was taken from within two boxes centred at the position of the
source.
The returned uncertainty in the count rate does not include systematic errors
and is thus purely statistical. In the cases where the statistical significance were
less than 10−3 only a upper 3σ limit could be calculated for the count rate.
2.6.2
Deriving Γ and nH
From the process described in the sections above the count rates and corresponding
error bars, or at least an upper limit on the counts could be calculated. These
results were used to create intervals for the observed HR:
HR ∈ [hardM IN /sof tM AX , hardM AX /sof tM IN ]
(2.6)
A contour plot of HR were then made in the Γ nH plane wich gives intervals in Γ
and nH which are consistent with the observed HR.
2.6.3
Deriving flux and luminosity
To derive the flux the source was modeled with a powerlaw model in pimms. The
parameters for this model were:
• Mission parameters (i.e. telescope, instrument and optical blocking filter).
• Galactic nH
• redshift, z
• A (Γ,nHGP S )-pare
The (Γ,nHGP S )-pare was then changed so that the flux was calculated for all pares
derived from the contour plot in order to find the extreme flux values.
Luminosity could then be derived from the flux using the formula [3]:
L = 4πd2L (1 + z)α−1 F
Where dL is the luminosity distance.
(2.7)
12
Data reduction
Chapter 3
Results
The first section in this chapter describes the sources fully analyzed in the thesis.
In all other cases the data was either given by earlier analyzes by Dr. M. Guainazzi
or taken from other literature (section 3.2). An exception is the flux (section 3.3)
that had to be fully analysed for all sources. A table summarizing the properties
of the entire sample can be found in appendix C.
3.1
Results from the new observations
New observations refers to those made within the AO4 (see table 1.1), excluding
the unfinished analysis of PKS1607+26. In this section also PKS0500+019 is included since this observation was as well fully analysed in this thesis.
After generating spectra for all the seven GPS galaxies, the decision was taken
to use three of the spectra for further analysis. The remaining four GPS galaxies
had not enough energy bins in their spectra and was therefore analysed via contour
plots (section 3.1.3).
3.1.1
Spectral analysis
The spectra fitted with the best fit model together with the residuals for this model
can be seen in appendix C.
An F-test comparing the two models in section 2.4.1 shows no significant improvement in adding a fixed Gaussian line profile at 6.4 keV. Therefore an upper
limit for the equivalent width (table 3.1) was calculated and the wanted parameters (table 3.2) were derived from the base model.
Looking at the spectrum of PKS2127+04 (appendix C) a possible emission line
can be seen at an observed frequency of approximately 1.5 keV. This was confirmed by an F-test when adding a Gaussian line profile as an emission line at the
13
14
Results
+0.16
restframe energy 2.98−0.11
keV, but since there are no strong emission lines at this
frequency the line are not considered a true spectral quality.
Table 3.1. Upper limit equivalent width for an Fe
GPS
PKS0500+019
4C+32.44
PKS2127+04
Kα
emission line at 6.4 keV
Eqw. FeKα [keV]
0.163
1.00
0.915
Table 3.2. Spectral properties. The column density is shown in ∗1022 /cm2 , the flux in
∗10−13 ergs/(cm2 s) and the luminosity in ergs/cm2
GPS
PKS0500+019
4C+32.44
PKS2127+04
3.1.2
Γ
1.61
1.74
1.98
+0.16
−0.15
+0.2
−0.2
+0.5
−0.4
nHGP S
50+18
−16
12+5.5
−4.9
72+120
−71
F2−10
5.4+0.47
−0.52
0.78+0.13
−0.13
0.49+0.12
−0.16
L2−10
(5.0 ± 0.6 )∗1044
(3.7 ± 0.45)∗1043
(2.9 ± 0.4 )∗1044
χ2 /D.O.F.
45.4/45
20.6/36
14.7/14
Timing analysis
The timing analysis shows no variation in the hardness ratio during the observations at a confidence level of 90% (table 3.3). For PKS2127+04 the low count
rate caused ’negative’ counts in some time bins when subtracting the background.
The reason for this is only due to statistical fluctuations in the low signal-to-noise
data from this source. To obtain positive results the time bin size in this case
was extended to 4096 s instead of the originally proposed 1024 s. The lightcurves
together with the ratio and fitted constant can be seen in appendix C.
Table 3.3. Results from constant fitting of the ratio between lightcurve 1 - 10 and 0.2-1
keV
GPS
PKS0500+019
4C+32.44
PKS2127+04
3.1.3
Fit const.
3.154
1.060
1.294
χ2 /D.O.F
4.2/6
7.7/19
1.7/5
Contour plots
In the case of 4C+00.02, PKS0428+20, 4C+14.41 and PKS2008-068 there were
not enough spectral bins for spectral analysis of this data, but count rates and
3.2 Properties from literature
15
corresponding error bars, or at least an upper limit on the counts could be calculated. These results were used to create intervals for the observed HR. A contour
plot of HR was then made in the Γ nH plane (see figure 3.1) which gives intervals
in Γ and nH wich are consistent with the observed HR. The Γ range in the plot
[0.636,2.616] was calculated by calculating the mean and standard deviation (σ)
from the GPS sources with known Γ and then choose the range Γmean ± 3σ. The
nH range was chosen so that all known GPS would fall therein. The resulting
constraints on the column density can be seen in table 3.4.
Table 3.4. Constraints on the intrinsic column density derived from the contour plots.
GPS
4C+00.02
PKS0428+20
4C+14.41
PKS2008-0.68
a
nHGP S [1/cm2 ]
[1.00 ∗ 1020 , 1.00 ∗ 1024 ]a
[1.00 ∗ 1020 , 6.92 ∗ 1021 ]
[1.00 ∗ 1020 , 1.58 ∗ 1021 ]
[1.00 ∗ 1020 , 4.78 ∗ 1021 ]
The contour plot do not put constrictions to the column density.
3.2
Properties from literature
Many of the properties compared in this thesis are not possible to derive from
X-ray analysis. The size of the radio structure and the redshift was found in the
NASA/IPAC Extragalactic Database, NED. The column density was taken using
the LAB survey weighted average from the online tool nh. The HI was found in
[10] and [6].
The X-ray properties of the sources not found in section 3.1 are either given by
Dr. M. Guainazzi or can be found in [6] and [7].
All the properties found or given can be seen in appendix C were the properties of the entire sample are described together.
3.3
Flux in Restframe
The flux was calculated for pn in the range 0.5-2 keV and 2-10 keV. This to be
able to calculate the flux ratio between the hard and soft energy band.
First all spectra were investigated to determine if there would be possible to use
xspec for calculating the flux. The two GPS 4C+55.16, PKS0941-080 are not included in this analysis. 4C+55.16 because it is an embedded source for which no
observational data was available and PKS0941-080 because of problems doing a
source detection on Chandra data.
16
Results
Figure 3.1. Contour plots in the (Γ,nH )-plane. For 4C+00.02 the white area shows
were the model is consistent with the measured HR. In the other pictures the black shows
were the model is consistent and the grayscale measures the error.
3.3 Flux in Restframe
17
If possible the spectra were fitted with the base model (section 2.4.1) in the different energy ranges. Then the galactic and intrinsic nH were set to 0 and the flux
was calculated using the xspec command flux.
Otherwise, in the cases where there were too few energy bins in the spectra, pimms
was instead used. The input parameters were a point (Γ,nH ), the optical blocking
filter used during the observation, and the observed count rate. The points tested
was (Γmax ,nH max ),(Γmax ,nH min ),(Γmin ,nH max ) and (Γmin ,nH min ) or the points
that were consistent with the model in the contour plots. (see section 3.1.3) To
find the count rate the source finding algorithm described in 2.6 was used. If this
failed, the count rate was taken from ximage. Table 3.5 shows the resulting fluxes
calculated for all GPS galaxies.
Table 3.5. Flux in restframe energi 0.5-2 keV and 2-10 keV. (in ergs/(s∗cm2 ) ∗10−13 )
The values have either been calculated with xspec, or with the help of edetect or ximage.
GPS
4C+00.02
COINSJ0029+3456
COINSJ0111+3906
PKS0428+20
PKS0500+019
B30710+439
4C+55.16
PKS0941-080
B1031+567
4C+14.41
4C+32.44
PKS1345+125
4C+62.22
OQ+208
3C303.1
PKS2008-068
PKS2127+04
COINSJ2355+4950
0.5-2 keV
>0.0723 1
0.203+0.0792
−0.139
[0.265, 0.535] 1
[0.0624, 0.448] 2
1.40+0.35
−0.21
0.777+0.21
−0.04
n.a.
< 7.369 2
[0.137, 0.337] 2
0.521+0.087
−.043
23.6+12.5
−15.5
[1.23, 10.5] 2
0.833+0.184
−0.078
1.45+0.155
−0.806
[0.0487, 0.305] 1
[0.251, 4.12] 2
[0.326, 68.2] 1
1 Flux from pimms, count rate calculated with ximage.
2 Flux from pimms, count rate calculated with edetect.
2-10 keV
<16.8 1
2.10+0.510
−0.156
[0.753, 1.93] 2
[0.289, 0.651] 2
3.49+0.73
−0.03
3.44+0.64
−0.11
n.a.
[0.115, 0.498] 2
[0.235, 0.455] 2
0.854+0.235
−0.166
10.8+2.65
−2.35
4.17+1.11
−1.05
3.13+0.707
−0.474
[0.249, 0.497] 2
[0.247, 0.518] 2
0.734+0.199
−0.307
0.746+0.234
−0.668
18
Results
Chapter 4
Discussion and conclusions
Because of the X-ray weakness in the analysed sources it has been difficult to constrain all the wanted parameters. This and problems with finding other parameters
in literature makes it hard to draw robust conclusions about all the questions asked
for in the scientific goal of this thesis. But in fact, if only upper limits had been
found for the new sources this would have be seen as a great result, so a discussion
of the obtained results is well justified.
4.1
Discussion of the results
The results have been derived both through spectral analysis and the hardness
ratio. Data derived from HR could be questioned if there are significant variations
in this property during the observation. For the three sources for which timing analysis was possible, no such variations could be found. Neither [7] detects
significant variations for HR in their derived lightcurves although a total variability of approximately a factor 3 within a few thousand seconds were observed for
COINSJ0029+3456. In total this gives 4 sources which implicates the GPS galaxies to be associated with constant hardness ratio and allow methods based on the
HR to be used.
Assuming all the data to have been correctly derived following discussion concern the scientific goals of this project.
Are GPS-galaxies intrinsically X-ray weaker than normal radio galaxies?
In order to try to answer this question, the X-ray to radio luminosity ratio was
studied. In figure 4.1 this ratio can be seen versus the redshift. The observed
values are inconsistent with those observed in FRII, but matches well with the
values observed in FRI.
19
20
Discussion and conclusions
Figure 4.1. Comparison. The obliquely shaded box indicates the locus of the FRI, Chandra
sample of Donato et al. (2004); the horizontally shaded box the locus of the blazar sample
of Fossati et al. (1998); the dot-dashed line locus corresponding to a typical Spectral Energy
Distribution of radio-loud quasar after Elvis et al. (1994).
Are GPS-galaxies hosted in dense environments?
In X-ray astronomy it is conventional to talk about obscured sources as an AGN
covered with column density larger than 1022 cm−2 . In this sense the GPS galaxies
in the sample are on the average obscured. Figure 4.2 shows a comparison between
the column density in the GPS sample and the control sample of FRI and FRII
respectively.
A model were the jet would have to pierce its way through a cocoon of gas and
dust, with decreasing density at larger distances from the radio core, have been
proposed. From this an anti-correlation between the measured column density and
the size of the radio structure might be expected. The result of this can be seen
in figure 4.3 altough the result is still very tentative.
Does the environment brake or prevent the evolution of the radio structure?
Even if the GPS galaxies in the sample are considered as obscured the level of
obscuration is not enough to ultimately prevent the evolution of large-scale radio
jets. This supports the scenarios where GPS are depicted as young sources.
Looking back at the answers discussed above we see that GPS galaxies are compatible with FRI in X-ray weakness, but hosted in a denser environment. This
may imply that GPS galaxies are the precursors of FRI, i.e. GPS are small-scale
FRI, in an early stage of evolution.
4.2 Conclusions
21
Figure 4.2. nHGP S -distribution for the FRI, FRII and GPS respectively.
Is there a separation into two sub-classes?
A great effort was put into the trial of showing a separation in the GPS sample between sources having a ratio between the luminosity in the X-ray and the
luminosity at 5 GHz, higher resp. lower than 100.5 (figure 4.1). The low number of sources made it impossible to make a χ2 -test on the distribution. Instead
the cumulative probability function was studied using Kolmogorov-Smirnov (K-S)
statistics. The K-S test shows there is less than 10% probability that the distribution of this ratio is from a single Gaussian distribution. The hypothesis that
the distribution instead is a double Gaussian distribution is much more likely (See
figure 4.4).
Considering the low number of GPS used in the test the evidence for a separation
is still very weak. Furthermore a comparison between the spectra of the groups
in the rest frames of the GPS would be desirable, but impossible since I was not
able to obtain spectra for all GPS. Instead a comparison in the flux-ratio between
the energy range 2-10 keV and the energy range 0.5-2 keV in the rest frame of the
galaxy was done (figure 4.5). A K-S test comparing the two distributions shows a
25.4% probability to be drawn from the same parent distribution.
4.2
Conclusions
By adding X-ray data from 7 GPS galaxies never before observed in this energyrange the number of X-ray observations of GPS galaxies is significantly enlarged.
The results from the new sources are consistent with the data from the other GPS
galaxies in the Stanghellini sample.
22
Discussion and conclusions
Figure 4.3. X-ray column density versus the size of the radio structure. Solid line represent
the best censored data linear fit with a function log(nH )= A + B∗log(sizekpc )
Looking at the complete sample, the column density seems in avarage to be more
obscure than FRI. If instead looking at the X-ray to radio luminosity ratio the
GPS galaxies are intrinsically X-ray weaker than the control sample of FRII, compatible with the FRI. This may imply that GPS galaxies are precursors to the FRI.
Two other tentative results were also found. Firstly a possible anti-correlation
between the linear size and the column density, which may help explain the structure of surrounding gas. Secondly a detection of a bi-modal structure in the
distribution of the X-ray to radio luminosity ratio.
4.3
Future work
To finish the analysis of the sample completely it is necessary to finish the analysis
of PKS1607+26. A first look at the data shows that it can be analysed through
spectral analysis which will give more information than the contour-plot analysis.
The specific analysis of PKS1607+26 and more analysis of all observational data
will be done during the spring and summer 2008, from which the outcome will
hopfully be a scientific paper describing the properties of the sample.
However more observations will most probably be needed to confirm or discard
the tentative detection of a bi-modal distribution in the X-ray to radio luminosity
ratio or the tentative anti-correlation between GPS size and column density. A
number of short observations made by NASAs X-ray telescope Chandra would be
useful for solving both these problems. The data analysed in this thesis could then
be used as argument for observations in a future proposal for Chandra.
4.3 Future work
23
Figure 4.4. Cumulative probability function of the X-ray to radio ratio compared to cumulative
probability function of a single Gaussian distribution to the left resp. of a double Gaussian
distribution to the right.
Figure 4.5. Comparison of the flux ratio distribution in GPS restframe between the two
suggested sub-groups of GPS galaxies.
24
Discussion and conclusions
Bibliography
[1] http://chandra.harvard.edu/about/.
[2] X-ray clues on the ultimate fate of compact radio sources.
[3] Arthur N. Cox, editor. Allens Astrophysical Quantities 4th ed., page 645.
[4] C. Stanghellini et al. A complete sample of ghz-peaked-spectrum radio sources
and its radio properties. Astronomy & Astrophysics, 1998.
[5] F. Jansen et al. Xmm-newton observatory. A&A, 2000.
[6] Jacco Vink et al. The x-ray properties of young radio-loud agn. Mon. Not.
R. Astron. Soc. 000, 1-?? (2002), 2006.
[7] M. Guainazzi et al. A hard x-ray view of giga-hertz peaked spectrum radio
galaxies. Astronomy & Astrophysics manuscript no. corrected, 2005.
[8] M. J. L. Turner et al. The european photo imaging camera on xmm-newton:
The mos cameras. 2000.
[9] M. Kirsch et al. Epic status of calibration and data analysis. 2007.
[10] Y. M. Philstr¨
om et al. The presence and distribution of hi absorbing gas
in sub-galactic sized radio sources. Astronomy & Astrophysics manuscript,
2003.
[11] B. L. Fanaroff and J. M. Riley. The morphology of extragalactic radio sources
of high and low luminosity. Mon. Not. R. astr. Soc. (1974) 167, Short Communication, 31P-35P, 1974.
[12] C. A. Jackson and J. V. Wall. Extragalactic radio source evolution under
the dual-population unification scheme. Mon. Not. R. Astron. Soc. 000, 1-18
(1998), 1998.
[13] R. Morrison and D. McCammon. Interstellar photoelectric absorption cross
sections, 0.03-10 kev. The Astrophysical Journal, 270:119-122,1983 July 1,
1982.
[14] Christopher P. O’Dea. The compact steep-spectrum and gigahertz peakedspectrum radio sources. The Astronomical Society of the Pacific, 1998.
25
26
Bibliography
[15] Frank H. Shu. The physical universe, an introduction to astronomy., chapter
13, Quiet and Active Galaxies.
[16] Zeilik & Smith. Introductory Astronomy and Astrophysics, chapter 23, Active
Galaxies.
[17] XMM-Newton SOC Team. Xmm-newton users´ handbook (xmm-ps-gm-14).
internet, 2007.
[18] Gustav Winroth. Energy calibration of different modes of a pn-ccd-camera
on board the x-ray observatory xmm-newton. Master’s thesis, Link¨oping
University, 2007.
Appendix A
Active Galaxies
A small part of the observed galaxies in Universe shows a very high activity. These
galaxies are known as active galaxies and can be divided into many different subgroups out of which some will be described in this chapter. The extreme activity
are believed to come from energetic events in the nuclei of the galaxies [15]. To be
called an active galaxy most or all of the following characteristics should be seen
[16]:
• Luminosity greater than 1037 W.
• Nonthermal emission, with excessive ultraviolet, infrared, radio and X-ray
flux compared to normal galaxies.
• A small region (i.e. less than a few lightyear) of rapid variability.
• High contrast of brightness in the nucleus and large-scale structures.
• Explosive appearance or jet-like protuberances.
• Broad emission lines.
A.1
Radio galaxies
The term radio galaxy is used for galaxies with a radio luminosity higher than 1033
W [16]. A radio galaxy is either compact which means that the radio emission is
smaller or the same size as the optical image, or extended in which case the radio
emission can be many times larger than the optical image. Compact radio sources
are often nuclear and no more than a few lightyears in diameter. Extended sources
on the other hand can be millions of lightyears across with giant lobes taking a
third to a fifth of the space.
A common structure for the extended sources are two aligned lobes (typically
50-1000 kpc in diameter) lying of each side, and equally far away, from the central
nucleus. These galaxies are called doubles or classical doubles. (Figure A.1)
27
28
Active Galaxies
Figure A.1. Cygnus A is the strongest emitting radio source in the known Universe, and a
typical example on a classical double. On the radio map the central nucleus and the two lobes
is clearly seen. A weak neadle-like jet towards the right lobe can also be seen. (Source: NED)
Jets with high-energy electrons can be seen shooting out from the nucleus either as a fairly constant stream of particles or in ionized blobs. The magnetic
field causes the particles to fly in two opposite directions and if the process in the
nucleus is active and stable, lobes will build up at the end of the jets.
The emission from the lobes and the jet are believed to be synchrotron radiation. The flux of such nonthermal emission has the spectral form
F (ν) = F0 ν −α
(A.1)
where α is the spectral index. On a log-log plot α will be the slope of the spectra.
Depending on the ratio between the highest surface brightness on opposite sides
of the central galaxy, and the total extent of the source [11], the radio galaxies can
be classified as core-dominated (Fanaroff-Riley type I (FRI)) or lobe-dominated
(FRII). Lobe-dominated radio sources consistently shows a higher radio luminosity
than those belonging to FRI [12].
A.2
GPS galaxies
The archetype GPS source (1934-G3) was discovered in the early days of extragalactic radio astronomy by Bolton, Garderner and Mackey in 1963. But it was
not until the beginning of the 1980s the symmetric compact double structures in
GPS sources first drew the astronomers attention for further investigations. [14]
A.2.1
Radio properties
All GPS sources are very strong and compact radio sources and make up about
10% of the radio selected sources at frequencies around 5 GHz. (Typical Lradio
eq. or larger 1045 ergs/s, size 10-1000 pc.) The GPS sources are characterized by
a simple steep convex radio spectrum that peaks between 0.4 and 6 GHz and have
A.2 GPS galaxies
29
a spectral index above the peak steeper than -0.5. An example of a typical radio
GPS radio spectrum can be seen in figure A.2. About half of the GPS sources are
classified as GPS galaxies.
The Morphology of the GPS sources shows cores, jets, hot spots, and lobes and
is hence very similar to extended radio source structures, but on a much smaller
scale. GPS galaxies almost always have double or triple morphologies.
Figure A.2. Example of a typical radio spectrum from a GPS source. The axis shows the
frequence [GHz] versus the flux density [Jy]. (Source: [14])
A.2.2
X-ray properties
In contrast to the radio spectrum, GPS galaxies often tend to be weak in X-rays.
This can be the effect of two different cases, either GPS galaxies are intrinsically
X-ray weak or the X-rays are obscured by a dense enviroment. Since one of the
scientific goals of this thesis is to answer this question a more throughout discussion
on the subject can be found in chapter 4.
A.2.3
Evolution of GPS
The evolution of GPS sources is a well debated question. Originally the GPS
sources were suggested to evolve into large extended classical radio sources like
Cygnus A. Other alternatives would be that GPS sources could be frustrated, i.e.
located in a dense environment preventing them from growing, or they could be
young radio sources that will ’fizzle’ out and die young.
By comparing the hotspot separation from several observations of the same objects
the mean growth rate of the sources can be calculated. This gives ages of approximately 3000 years, which is supported by other, e.g. spectral age, estimations.
If the GPS sources are frustrated the kinematic age could be severely under estimated. Strong highly excited line emission with large equivalent widths in optical
observations, low radio polarisation and free-free absorption observations, is found
evidence that support a dense environment.
30
Active Galaxies
Appendix B
XMM-Newton telescope
Following appendix is a short introduction of the European X-ray telescope XMMNewton, which was used to perform most of the observations analysed in this
thesis. Since only the EPIC cameras were used for the data analysis, the focus
will be mainly towards these instruments.
B.1
The spacecraft
XMM-Newton is the second cornerstone in the ESA horizon 2000 program and was
launched 10th of December 1999. [17] The satellite consists of two large payload
modules connected by a long carbon fiber tube (see figure B.1) and is the largest
scientific satellite ever launched by ESA [5]. The orbit is highly elliptical and is
constanly changing slightly, with a perigee and appogee of approximately 20000
km and 101000 km respectively (In March 2007). To control XMM-Newton three
ground stations in Perth, Kourou and Santiago de Chile are used. Data from the
different instruments, housekeeping data and spacecraft telemetry is sent to the
ground station and is from there transmitted to the Mission Operation Centre in
Darmstadt, Germany. In Darmstadt commanding operations and some analysis
of the spacecraft is performed. The operation of the scientific instruments is done
at the Science Operation Centre at Villafranca, Spain.
B.2
Instruments on board
There are in total six scientific instruments on board XMM-Newton, which are
divided into following three types.
• European Photon Imaging Cameras (EPIC): 3 CCD cameras for X-ray imaging, moderate resolution spectroscopy and X-ray photometry. (see section
B.2.1)
• Reflection Grating Spectrometer (RGS): 2 spectrometers for high-resolution
X-ray spectroscopy and spectro-photometry.
31
32
XMM-Newton telescope
• Optical Monitor (OM): For optical/UV imaging and grism spectroscopy.
Due to the radiation belt of the Earth the elevation has to be higher than 46000
km for scientific observations to be performed. This means that in average 132
ks out of the 48 h epoch can be used for observations. Even at elevation higher
than 46000 km the background radiation has to be checked in order to protect a
damaging photon flux reaching the instruments. Bright objects, e.g. planets and
the moon, are avoided. Solar particle emission is dominating the background and
during periods of intense solar flares instruments are switched of.
The long continuous target visibility is favourable for studying source variability
and to achieve a high overall observatory efficiency. Another important characteristic of XMM-Newton is the ability of independently and simultaneously operating
all six instruments.
High sensitivity is achieved by using three co-aligned X-ray telescopes, each consisting of 58 Wolter I mirrors nested in a coaxial and confocal configuration, which
gives the largest effective area of a focusing telescope ever. The incoming X-rays
are in two of the telescopes divided between one EPIC (MOS) camera and one
RGS, while they in the third telescope are focused only on the EPIC (pn) camera.
Figure B.1. XMM-Newton payload. At the right the three mirror modules are shown and
at the upper right the the focal X-ray instruments can be seen. (Figure courtesy of Dornier
Satellitensysteme GmbH)
B.3 EPIC calibration
B.2.1
33
EPIC
There are three EPIC cameras, two Metal-Oxide-Semiconductor-cameras refered
to as MOS, and one pn-camera. To protect the cameras from being exposed to
too strong radiation four different filters, Thick, Medium, Thin 1 and Thin 2, can
be used [18].
The two MOS-cameras are situated together with the RGSs. The incoming flux is
therefore divided between the MOS and the RGS so that about 44% reaches the
MOS-camera [8].
The field of view is a circle about 30’ in diameter which are covered by 7 (12)
CCDs in the case of MOS (pn). For the MOSs each pixel is covers 1.1” which
is smaller than the 4.1” for pn. [17] The pn-camera have though a much smaller
readout time.
The EPIC instruments can be operated in many different operating modes depending on the purpose of the observation, but for this thesis only the full frame
mode, were all the CCDs are used for photon detection, was used.
B.3
EPIC calibration
When a photon is detected the position on the CCD, the time for the event, and
the energy of the photon is stored as an event. With help of the events the user is
able to plot:
• An image showing the coordinate position of each event.
• A spectrum showing the intensity of incoming photons as a function of their
energy.
• A lightcurve showing the intensity of incoming photons as a function of time.
But to do this directly would yield incorrect data due to the intrinsic properties
of the telescope.
For a user the data is provided in a bundle of files called Observation Data Files,
ODF, which has to be calibrated for these errors. This is done using the the tasks
provided by the Scientific Analysing System, SAS, and through this tasks a Current Calibration File, CCF, is applied to the data. The CCF is continously updated
in order to give a correct calibration. Some effects that affects the observation is:
• Effective area: The effective area varies depending on the incoming photons
energi. This means that the effective area is smaller for photons with higher
energy and above 15 keV the photons will not be detected. There is also an
absorbtion dip in the effective area due to the mirrors material (Au).
• Quantum effects: Is made up by absorbtions in the CCD material.
34
XMM-Newton telescope
• Filter: The different filters have different absorbtion dips.
• Contamination: In the ideal case incoming photons with the same energy
would spread as a Gaussian distribution, but depending on oxidations the
distribution is smeared out.
An ancillary response file, ARF, is used to describe these effects and a redistribution matrix file, RMF, describes the probability for incident photons at a range of
energies. With help of these an exposure map can be created. The exposure map
contains information how to correct for the defects in the telescopes image. The
exposure map also excludes the pixels from the image that is believed to be wrong.
The calibration also takes in account the off-axis angle of the photons in the
viewed image, but since all the objects described in this thesis is on-axis objects
it is of less importance to describe this effects in detail.
B.4
Comparison with other x-ray telescopes
Since not all the observational data in this thesis is taken from XMM-Newton a
small comparison (see table B.1) is done to show the difference between XMMNewton and the other satellites from which data has been taken. The comparison
shows that XMM-Newton and Chandra belongs to a new generation of telescopes,
much better than their predecessors ASCA and ROSAT. The main difference between Chandra and XMM-Newton is that with XMM-Newton all instruments can
operate simultaneously in contrast to Chandra where they are alternated.
Table B.1. Comparison between different X-ray telescopes
Satellite
XMM-Newton
Chandra
ROSAT
ASCA
a
b
c
E range
[keV]
0.15-15
0.1-10
0.1-2.4
0.5-10
Ae at 1 keV
[cm2 ]a
4650
555 (ACIS-S)
400
350
Orbital target
visibility [h]
36.7b
44.4b
1.3c
0.9c
Mirror effective area
Orbital visibility outside the particle-radiation zone
Low orbit with Earth occulation.
Energy resolution
at 1 keV [eV]
2.9
1.0
500
100
Appendix C
Derived data.
In this appendix data for PKS0500+019, 4C+32.44 and PKS2127+04 from section
3.1.1 and 3.1.2 are represented. First the spectra fitted to the best fit model and
its residuals are shown in figure C.1. Then also the fitting of a constant line to
the lightcurve is shown in figure C.2.
Finally the properties from all the GPS galaxies in the sample is summed together
in table C.1 to C.4.
35
36
Derived data.
Figure C.1. Spectra fitted to the three EPIC instruments with the base model, and
residuals in units of standard deviation. The pn shows a higher count rate than the MOSs
simply due to its larger effective area. Note the difference in the energyrange shown in
the spectra.
37
Figure C.2. Ligthcurves from the GPS in 1-10 keV 0.2-1 keV and the ratio between
them.
38
Derived data.
Table C.1. Given properties
GPS
4C+00.02
COINSJ0029+3456
COINSJ0111+3906
PKS0428+20
PKS0500+019
B30710+439
4C+55.16
PKS0941-080
B1031+567
4C+14.41
4C+32.44
PKS1345+125
4C+62.22
OQ+208
3C303.1
PKS2008-068
PKS2127+04
COINSJ2355+4950
size (kps)
220
0.190
0.033
0.653
0.055
0.118
0.0
0.148
0.206
0.306
0.247
0.166
0.218
0.010
6.295
0.218
218
0.199
z
0.305
0.517
0.668
0.219
0.585
0.518
0.241
0.228
0.450
0.362
0.370
0.122
0.431
0.077
0.267
0.547
0.990
0.238
log(HI)
...
00.0
21.9
20.5
20.8
0.00
0.00
<20.1
<20.1
<19.8
19.9
20.6
20.3
20.3
<20.1
...
...
20.5
galactic nH
2.72∗1020
5.09∗1020
5.64∗1020
1.96∗1021
7.28∗1020
8.22∗1020
4.29∗1020
2.86∗1020
5.46∗1019
1.97∗1020
1.19∗1020
1.88∗1020
1.61∗1020
1.56∗1020
3.16∗1020
4.95∗1020
4.97∗1020
1.14∗1021
1
1
nH is calculated with the online tool nh [http://heasarc.gsfc.nasa.gov/cgibin/Tools/w3nh/w3nh.pl] taking the LAB survey weighted average.
Table C.2. Flux in restframe energi 0.5-2 keV and 2-10 keV. (in ergs/(s∗cm2 ) ∗10−13 )
GPS
4C+00.02
COINSJ0029+3456
COINSJ0111+3906
PKS0428+20
PKS0500+019
B30710+439
4C+55.16
PKS0941-080
B1031+567
4C+14.41
4C+32.44
PKS1345+125
4C+62.22
OQ+208
3C303.1
PKS2008-068
PKS2127+04
COINSJ2355+4950
0.5-2 keV
>0.0723 1
0.203+0.0792
−0.139
[0.265, 0.535] 1
[0.0624, 0.448] 2
1.40+0.35
−0.21
0.777+0.21
−0.04
< 7.369 2
[0.137, 0.337] 2
0.521+0.087
−.043
23.6+12.5
−15.5
[1.23, 10.5] 2
0.833+0.184
−0.078
1.45+0.155
−0.806
[0.0487, 0.305] 1
[0.251, 4.12] 2
[0.326, 68.2] 1
1 Flux from pimms, count rate calculated with ximage.
2 Flux from pimms, count rate calculated with edetect.
2-10 keV
<16.8 1
2.10+0.510
−0.156
[0.753, 1.93] 2
[0.289, 0.651] 2
3.49+0.73
−0.03
3.44+0.64
−0.11
[0.115, 0.498] 2
[0.235, 0.455] 2
0.854+0.235
−0.166
10.8+2.65
−2.35
4.17+1.11
−1.05
3.13+0.707
−0.474
[0.249, 0.497] 2
[0.247, 0.518] 2
0.734+0.199
−0.307
0.746+0.234
−0.668
39
Table C.3. Luminosity
GPS
4C+00.02
COINSJ0029+3456
COINSJ0111+3906
PKS0428+20
PKS0500+019
B30710+439
4C+55.16
PKS0941-080
B1031+567
4C+14.41
4C+32.44
PKS1345+125
4C+62.22
OQ+208
3C303.1
PKS2008-068
PKS2127+04
COINSJ2355+4950
log(L5GHz )
43.1
43.42
44.00
43.1
43.57
43.80
43.33
42.80
43.40
43.2
43.6
42.70
43.60
42.20
42.70
44.5
44.6
43.00
log(L2−10keV )
>42.74
44.36 +0.04
−0.04
43.85 +0.15
−0.24
43.15 +0.15
−0.22
44.70 +0.05
−0.06
44.53 +0.00
−0.00
44.18 +0.01
−0.01
41.96 +0.26
−0.75
43.34 +0.04
−0.04
43.15 +0.06
−0.06
43.57 +0.05
−0.06
43.89 +0.08
−0.09
44.48 +0.22
−0.48
44.95 +0.00
−0.00
42.26 +0.14
−0.21
43.81 +0.14
−0.21
44.46 +0.06
−0.06
43.11 +0.08
−0.10
Table C.4. Intrinsic properties
GPS
4C+00.02c
COINSJ0029+3456
COINSJ0111+3906
PKS0428+20c
PKS0500+019
B30710+439
4C+55.16
PKS0941-080
B1031+567
4C+14.41c
4C+32.44
PKS1345+125
4C+62.22
OQ+208
3C303.1
PKS2008-068c
PKS2127+04
COINSJ2355+4950
c Contour plot used to derive properties.
nHGP S
5000 +5000
−4999
96 +47
−40
>500
35 +34
−34
50 +18
−16
51 +17
−14
50 +18
−18
8 +8
−7
12 +5.5
−4.9
480 +40
−40
290 +200
−100
>9000
<97
24 +24
−23
72 +120
−71
390 +660
−280
Γ
1.63
1.43
1.63
1.61
1.59
2.21
1.74
1.12
1.24
2.21
1.51
1.63
1.98
1.83
+0.99
−0.99
+0.20
−0.19
+0.99
−0.99
+0.16
−0.15
+0.06
−0.06
+0.41
−0.41
+0.2
−0.2
+0.7
−0.8
+0.17
−0.17
+0.19
−0.14
+0.08
−0.08
+0.99
−0.99
+0.5
−0.4
+1.6
−0.92