MNRAS
490,
5300–5316 (2019)
doi:10.1093/mnras/stz2792
Advance Access publication 2019 October 9
Investigating the multiwavelength behaviour of the flat spectrum radio
quasar CTA 102 during 2013–2017
F. D’Ammando
,
1
‹
C. M. Raiteri
,
2
M. Villata,
2
J. A. Acosta-Pulido,
3
,
4
I. Agudo,
5
A. A. Arkharov,
6
R. Bachev,
7
G. V. Baida,
8
E. Ben
́
ıtez
,
9
G. A. Borman,
8
W. Boschin,
3
,
4
,
10
V. Bozhilov,
11
M. S. Butuzova
,
8
P. Calcidese,
12
M. I. Carnerero,
2
D. Carosati,
10
,
13
C. Casadio,
5
,
14
N. Castro-Segura,
4
,
15
W.-P. Chen,
16
G. Damljanovic,
17
A. Di Paola,
18
J. Echevarr
́
ıa,
9
N. V. Efimova,
6
Sh. A. Ehgamberdiev,
19
C. Espinosa,
9
A. Fuentes,
5
A. Giunta,
18
J. L. G
́
omez,
5
T. S. Grishina,
20
M. A. Gurwell,
21
D. Hiriart,
9
H. Jermak,
22
B. Jordan,
23
S. G. Jorstad,
20
,
24
M. Joshi,
24
G. N. Kimeridze,
25
E. N. Kopatskaya,
20
K. Kuratov,
26
,
27
O. M. Kurtanidze,
25
,
28
,
29
,
30
S. O. Kurtanidze,
25
A. L
̈
ahteenm
̈
aki,
31
,
32
V. M. Larionov,
6
,
20
E. G. Larionova,
20
L. V. Larionova,
20
C. L
́
azaro,
3
,
4
C. S. Lin,
16
M. P. Malmrose,
24
A. P. Marscher,
24
K. Matsumoto,
33
B. McBreen,
34
R. Michel,
9
B. Mihov,
7
M. Minev,
11
D. O. Mirzaqulov,
19
S. N. Molina,
5
J. W. Moody,
35
D. A. Morozova,
20
S. V. Nazarov,
8
A. A. Nikiforova,
6
,
20
M. G. Nikolashvili,
25
J. M. Ohlert,
36
,
37
N. Okhmat,
8
E. Ovcharov,
9
F. Pinna,
3
,
4
T. A. Polakis,
38
C. Protasio,
3
,
4
T. Pursimo,
39
F. J. Redondo-Lorenzo,
3
,
4
N. Rizzi,
40
G. Rodriguez-Coira,
41
K. Sadakane,
33
A. C. Sadun,
42
M. R. Samal
,
16
S. S. Savchenko,
20
E. Semkov,
7
L. Sigua,
25
B. A. Skiff,
43
L. Slavcheva-Mihova,
7
P. S. Smith,
44
I. A. Steele,
22
A. Strigachev,
7
J. Tammi,
31
C. Thum,
45
M. Tornikoski,
31
Yu. V. Troitskaya,
20
I. S. Troitsky,
20
A. A. Vasilyev
,
20
O. Vince,
17
(the WEBT Collaboration), T. Hovatta,
46
,
47
S. Kiehlmann
,
48
W. Max-Moerbeck,
49
A. C. S. Readhead,
48
R. Reeves,
50
T. J. Pearson
,
48
(the OVRO Team),
T. Mufakharov,
51
,
52
Yu.V.Sotnikova
53
and M. G. Mingaliev
52
,
53
Affiliations are listed at the end of the paper
Accepted 2019 October 1. Received 2019 October 1; in original form 2019 March 11
ABSTRACT
We present a multiwavelength study of the flat-spectrum radio quasar CTA 102 during 2013–
2017. We use radio-to-optical data obtained by the Whole Earth Blazar Telescope, 15 GHz
data from the Owens Valley Radio Observatory, 91 and 103 GHz data from the Atacama Large
Millimeter Array, near-infrared data from the Rapid Eye Monitor telescope, as well as data
from the
Swift
(optical-UV and X-rays) and
Fermi
(
γ
-rays) satellites to study flux and spectral
variability and the correlation between flux changes at different wavelengths. Unprecedented
γ
-ray flaring activity was observed during 2016 November–2017 February, with four major
outbursts. A peak flux of (2158
±
63)
×
10
−
8
ph cm
−
2
s
−
1
, corresponding to a luminosity of
(2.2
±
0.1)
×
10
50
erg s
−
1
, was reached on 2016 December 28. These four
γ
-ray outbursts have
corresponding events in the near-infrared, optical, and UV bands, with the peaks observed at
the same time. A general agreement between X-ray and
γ
-ray activity is found. The
γ
-ray flux
E-mail:
dammando@ira.inaf.it
C
2019 The Author(s)
Published by Oxford University Press on behalf of the Royal Astronomical Society
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MWL behaviour of CTA 102 during 2013–2017
5301
variations show a general, strong correlation with the optical ones with no time lag between
the two bands and a comparable variability amplitude. This
γ
-ray/optical relationship is in
agreement with the geometrical model that has successfully explained the low-energy flux and
spectral behaviour, suggesting that the long-term flux variations are mainly due to changes
in the Doppler factor produced by variations of the viewing angle of the emitting regions.
The difference in behaviour between radio and higher energy emission would be ascribed to
different viewing angles of the jet regions producing their emission.
Key words:
radiation mechanisms: non-thermal – galaxies: individual: CTA 102 – galaxies:
jets – galaxies: nuclei – gamma-rays: general.
1 INTRODUCTION
Blazars are an extreme class of active galactic nuclei (AGNs) whose
bright and violently variable non-thermal radiation across the entire
electromagnetic spectrum is ascribed to the presence of a collimated
relativistic jet closely aligned to our line of sight (e.g. Blandford &
Rees
1978
). This peculiar setting implies a strong amplification of
the rest-frame radiation because of Doppler boosting, together with
a contraction of the variability time-scales, and a blueshift of the
frequencies.
The relativistic jets of blazars are able to transport a huge
amount of power away from the central engine in the form of
radiation, kinetic energy, and magnetic fields. When this power
is dissipated, the particles emit the observed radiation, showing
the typical double-hump spectral energy distribution (SED) of
blazars. The first peak of the SED, usually observed between radio
and X-rays, is due to the synchrotron radiation from relativistic
electrons, while the second peak, usually observed from X-ray up
to TeV energies, is commonly interpreted as inverse Compton (IC)
scattering of seed photons, either internal or external to the jet,
by highly relativistic electrons. However, the nature of this second
hump is a controversial issue and other models involving hadronic
and lepto-hadronic processes have been proposed (e.g. B
̈
ottcher
et al.
2013
).
Blazars are traditionally divided into flat-spectrum radio quasars
(FSRQs) and BL Lac objects (BL Lacs) based on the presence
or not, respectively, of broad emission lines (i.e. equivalent width
>
5 Å) in their optical and UV spectrum (e.g. Stickel et al.
1991
).
Recently, a new classification was proposed based on the luminosity
of the broad-line region (BLR) in Eddington luminosity (Ghisellini
et al.
2011
): sources with
L
BLR
/
L
Edd
higher or lower than 5
×
10
−
4
being classified as FSRQ or BL Lacs, respectively, in agreement
with a transition of the accretion regime from efficient to inefficient
between the two classes.
Blazar emission shows strong and unpredictable variability over
all the electromagnetic spectrum, from the radio band to
γ
-rays, with
time-scales ranging from minutes to years. Long-term observations
of blazars during different activity states provide an ideal laboratory
for investigating the emission mechanisms at work in this class of
sources. In this paper we present multifrequency observations of
the blazar CTA 102 during 2013–2017. CTA 102 (also known as
4C
+
11.69) is an FSRQ at redshift
z
=
1.037 (Schmidt
1965
).
Flaring activity in the optical band has been observed from this
source in 1978 (Pica et al.
1988
), 1996 (Katajainen et al.
2000
),
and 2004 (Osterman Meyer
2009
). However, simultaneous
γ
-ray
observations were not available for those events. The source was
detected for the first time in
γ
-rays by the
Compton Gamma Ray
Observatory
in 1992 with both the EGRET (Hartman et al.
1999
)
and COMPTEL (Blom et al.
1995
) instruments. Unfortunately,
no optical observations were available during the
γ
-ray detec-
tion (Villata et al.
1997
). On the other hand, during the
Fermi
era a remarkable outburst was simultaneously observed in 2012
September–October in near-infrared (near-IR) and optical bands
by the Whole Earth Blazar Telescope
1
(WEBT) and
γ
-rays by the
Large Area Telescope (LAT) on board
Fermi Gamma-ray Space
Telescope
. Correlated variability in the two energy bands suggested
a co-spatial origin of the optical and
γ
-ray-emitting regions during
the flaring activity (Larionov et al.
2016
).
In 2016 November, CTA 102 entered a new very-high-activity
state in
γ
-rays, as observed by
Fermi
-LAT, reaching a daily flux
higher than 1
×
10
−
5
ph cm
−
2
s
−
1
on 2016 December 16 (Ciprini
et al.
2016
). This flaring activity continued for a few weeks in
γ
-rays
(e.g. Bulgarelli et al.
2016
;Xuetal.
2016
). A significant increase
of activity was observed over the entire electromagnetic spectrum
(e.g. Calcidese et al.
2016
; Ojha, Carpenter & D’Ammando
2016
;
Righini et al.
2016
). In particular, an extreme optical and near-IR
outburst occurred in 2016 December, with a brightness increase up
to six magnitudes with respect to the faint state of the source (Raiteri
et al.
2017
). In Raiteri et al. (
2017
) we explained the flux and spectral
variations in optical, near-IR, and radio bands by means of an
inhomogeneous curved jet with different jet regions changing their
orientation, and hence their Doppler factors, in time. Alternative
theoretical scenarios have been proposed to explain the 2016–2017
flaring behaviour of CTA 102. According to Casadio et al. (
2019
)
the outburst was produced by a superluminal component crossing a
recollimation shock, while for Zacharias et al. (
2017
,
2019
)itwas
due to ablation of a gas cloud penetrating the relativistic jet in a
leptonic or hadronic scenario.
The radio-to-optical and
γ
-ray emission are produced by two
different mechanisms (i.e. synchrotron and IC emission in leptonic
models), although related to the same relativistic electron popula-
tion. Therefore, the
γ
-ray variability can be used as a further test
to verify the geometrical model that we proposed to explain the
low-energy flux variability in CTA 102 during 2013–2017. In the
geometrical scenario, the
γ
-ray and optical radiation are produced
in the same jet region, therefore the
γ
-ray and optical fluxes undergo
the same Doppler beaming and should be linearly correlated.
In this paper we present a multiwavelength analysis of the
CTA 102 emission from radio to
γ
-rays between 2013 January
1 and 2017 February 9, in particular during the bright flaring
activity occurred during 2016 November–2017 February. The radio-
to-optical observations performed in the framework of a campaign
led by the WEBT, already presented in Raiteri et al. (
2017
), are
complemented by the Atacama Large millimeter/Submillimeter
Array (ALMA) at 91 and 103 GHz, the Owens Valley Radio
Observatory (OVRO) data at 15 GHz, the Rapid Eye Mount (REM)
near-IR data, and a detailed analysis of data collected by the
Neil
1
http://www.oato.inaf.it/blazars/webt
MNRAS
490,
5300–5316 (2019)
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5302
F. D’Ammando et al.
Gehrels Swift Observatory
(optical–UV and X rays) and
Fermi
(
γ
-
rays) satellites. The data set used in this paper is the richest in terms
of number of data points and broad-band coverage presented in
literature for the period considered here.
Sun constraints prevented us to have observations from optical
and near-infrared WEBT observatories and
Swift
satellite after
2017 February 9, not allowing us to investigate the connection
between the
γ
-ray flaring activity observed in 2017 March–April
(see e.g. Shukla et al.
2018
) and the emission from near-IR to X-
rays. After that period the infrared-to-X-ray coverage is insufficient
to adequately test the geometrical model and to investigate the
connection between low-energy and
γ
-ray emission.
The paper is organized as follows. In Sections 2 and 3 we present
Fermi
-LAT and
Swift
data analysis and results, respectively, whereas
in Section 4 we report on the radio-to-optical observations. Multi-
frequency flux and spectral variability are discussed in Sections 5
and 6, respectively. The application of the geometrical model by
Raiteri et al. (
2017
)tothe
γ
-ray, optical, and radio variability is
discussed in Section 7. We discuss the previous results and draw
our conclusions in Section 8. Throughout this paper, we assume
the following cosmology:
H
0
=
71 km s
−
1
Mpc
−
1
,
M
=
0.27, and
=
0.73 in a flat Universe (Ade et al.
2016
).
2
FERMI
-LAT DATA: ANALYSIS AND RESULTS
The
Fermi
-LAT is a pair-conversion telescope operating from 20
MeV to
>
300 GeV. Further details about the
Fermi
-LAT are given
in Atwood et al. (
2009
).
The LAT data used in this paper were collected from 2013
January 1 (MJD 56293) to 2017 February 9 (MJD 57793).
During this time, the LAT instrument operated almost entirely
in survey mode. The Pass 8 data (Atwood et al.
2013
), based
on a complete and improved revision of the entire LAT event-
level analysis, were used. The analysis was performed with the
SCIENCETOOLS
software package version v11r5p3. Only events be-
longing to the ‘Source’ class (
evclass
=
128
,
evtype
=
3
)
were used. We selected only events within a maximum zenith
angle of 90 deg to reduce contamination from the Earth limb
γ
-rays, which are produced by cosmic rays interacting with the
upper atmosphere. The spectral analysis was performed with
the instrument response functions
P8R2
SOURCE
V6
using a
binned maximum-likelihood method implemented in the Science
tool
gtlike
. Isotropic (‘iso
source
v06.txt’) and Galactic diffuse
emission (‘gll
iem
v06.fit’) components were used to model the
background (Acero et al.
2016
).
2
The normalization of both com-
ponents was allowed to vary freely during the spectral fitting.
We analysed a region of interest of 20
◦
radius centred at the
location of CTA 102. We evaluated the significance of the
γ
-ray
signal from the source by means of a maximum-likelihood test
statistic (TS) defined as TS
=
2
×
(log
L
1
−
log
L
0
), where
L
is the
likelihood of the data given the model with (
L
1
) or without (
L
0
)a
point source at the position of CTA 102 (e.g. Mattox et al.
1996
).
The source model used in
gtlike
includes all the point sources
from the 3FGL catalogue that fall within 30
◦
of CTA 102. We also
included new candidates within 10
◦
of CTA 102 from a preliminary
eight-year point source list (FL8Y
3
). The spectra of these sources
were parametrized by a power law (PL), a log-parabola (LP), or a
super exponential cut-off, as in the catalogues.
2
http://fermi.gsfc.nasa.gov/ssc/data/access/lat/BackgroundModels.html
3
https://fermi.gsfc.nasa.gov/ssc/data/access/lat/fl8y/
Figure 1.
Integrated flux light curve of CTA 102 (upper panel), spectral
slope (middle panel), curvature parameter (bottom panel) obtained in the
0.1–300 GeV energy range during 2013 January 1–2017 February 9 (MJD
56293–57793) with 30-d time bins. The open symbols refer to results
obtained with
β
fixed to 0.07 (see the text for details).
A first maximum-likelihood analysis was performed over the
whole period to remove from the model the sources having TS
<
25. A second maximum-likelihood analysis was performed on the
updated source model. In the fitting procedure, the normalization
factors and the spectral parameters of the sources lying within 10
◦
of CTA 102 were left as free parameters. For the sources located
between 10
◦
and 30
◦
from our target, we kept the normalization and
the spectral shape parameters fixed to the values from the 3FGL
catalogue.
Integrating over 2013 January 1–2017 February 9 the fit with an
LP model, d
N
/d
E
∝
E/E
−
α
−
β
log(
E/E
0
)
0
, as in the 3FGL and FL8Y
catalogues, results in TS
=
125 005 in the 0.1–300 GeV energy
range, with an integrated average flux of (93.8
±
0.6)
×
10
−
8
ph cm
−
2
s
−
1
, a spectral slope
α
=
2.16
±
0.01 at the reference
energy
E
0
=
308 MeV, and a curvature parameter around the
peak
β
=
0.07
±
0.01. The corresponding apparent isotropic
γ
-
ray luminosity is (5.1
±
0.1)
×
10
48
erg s
−
1
. As a comparison in the
3FGL catalogue, covering the period 2008 August 4–2012 July 31,
the integrated average flux is (16.1
±
0.5)
×
10
−
8
ph cm
−
2
s
−
1
,
and the spectrum is described by an LP with a spectral slope
α
=
2.34
±
0.03 at the reference energy
E
0
=
308 MeV, and a
curvature parameter around the peak
β
=
0.13
±
0.02. This indicates
a moderate change of the average
γ
-ray spectrum during the period
studied here, in which the flux is a factor of approximately six higher
than the first four years of LAT operation.
Fig.
1
shows the
γ
-ray flux (top panel) and spectral parameters
(middle panel: spectral slope; bottom panel: curvature parameter)
evolution of CTA 102 for the period 2013 January 1–2017 February
9 using an LP model and 30-d time bins. For each time bin, the
spectral parameters of both CTA 102 and all sources within 10
◦
from it were left free to vary. For the time bins in which the fit
results in a TS
<
300 for CTA 102, the statistics is not enough for
obtaining a detailed characterization of the spectrum with complex
spectral models, therefore we run again the likelihood analysis using
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490,
5300–5316 (2019)
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MWL behaviour of CTA 102 during 2013–2017
5303
Figure 2.
Upper panel: Integrated flux light curve of CTA 102 obtained in
the 0.1–300 GeV energy range during 2013 January 1–2017 February 9 with
five-day time bins. The arrow refers to 2
σ
upper limit on the source flux.
Upper limits are computed when TS
<
10. Different outbursts are labelled
with an identification number in the plot. Bottom panel: X-ray light curve
in the 0.3–10 keV energy range obtained by
Swift
-XRT (see Section 3 for
details).
an LP model with the curvature parameter fixed to the value obtained
integrating over the entire period (i.e
β
=
0.07). The
γ
-ray spectrum
of CTA 102 shows a remarkable variability on monthly time-scale,
with a spectral slope between 1.88 and 2.97 (the average spectral
slope is
α
=
2.30
±
0.09), and a curvature parameter between 0.04
and 0.26 (the average curvature parameter is
β
=
0.13
±
0.04),
although for the latter the uncertainties are relatively large.
For investigating the
γ
-ray variability on different time-scales,
we have produced a
γ
-ray light curve for the entire period with five-
day time bins (Fig.
2
). For each time bin, the spectral parameters of
CTA 102 and all sources within 10
◦
of it were frozen to the values
resulting from the likelihood analysis over the respective monthly
time bin. When TS
<
10, 2
σ
upper limits were calculated. Six
peaks corresponding to periods with fluxes higher than 2
×
10
−
6
ph cm
2
s
−
1
were observed in 2013 April 4–8 (MJD 56386–56390; I),
2014 October 21–25 (MJD 56951–56955; II), 2015 December 26–
30 (MJD 57382–57386; III), 2016 February 19–23 (MJD 57437–
57441; IV), 2016 August 22–26 (MJD 57622–57626; V), and 2016
December 30–2017 January 3 (MJD 57752–57756; VI), with an
increase of the flux of a factor between 2.5 and 14 with respect to
the average flux estimated during 2013–2017.
Finally, we have produced a
γ
-ray light curve with one-day and
12-h time bins for the period of high activity, i.e. 2016 November
11–2017 February 9 (MJD 57703–57793), as shown in Fig.
3
.In
the analysis of the sub-daily light curves, we fixed the flux of the
diffuse emission components at the value obtained by fitting the
data over the entire period analysed in this paper. For each time
bin, the spectral parameters of both CTA 102 and all sources within
10
◦
of it were frozen to the values resulting from the likelihood
analysis in the monthly time bins. The peak flux of the daily
light curve dates 2016 December 28 (MJD 57750), with a flux
of (2158
±
63)
×
10
−
8
ph cm
−
2
s
−
1
, corresponding to a
γ
-ray
Figure 3.
Integrated flux light curve of CTA 102 obtained by
Fermi
-LAT
in the 0.1–300 GeV energy range during 2016 November 11–2017 February
9, with one-day time bins (top panel), and 12-h time bins (bottom panel).
luminosity (2.2
±
0.1)
×
10
50
erg s
−
1
. A similar peak flux was
observed on 12-h time-scales, (2200
±
111)
×
10
−
8
ph cm
−
2
s
−
1
in the second bin of 2016 December 28, corresponding to a
γ
-ray
luminosity (2.2
±
0.1)
×
10
50
erg s
−
1
. These values are among the
highest
γ
-ray luminosities ever measured for blazars, comparable
to what was observed for 3C 454.3 (Abdo et al.
2011
)andS5
0836
+
710 (Orienti et al.
2019
). As a comparison, in 2012 the
γ
-ray
flux of CTA 102 reached a peak flux of
∼
9
×
10
−
6
ph cm
−
2
s
−
1
(Larionov et al.
2016
).
The search for variability on very short time-scale in
γ
-rays is
beyond the scope of this paper. Rapid variability on time-scale
of minutes was observed in 2016 December, with a peak flux of
∼
3.5
×
10
−
5
ph cm
−
2
s
−
1
(Gasparyan et al.
2018
; Shukla et al.
2018
; Meyer, Scargle & Blandford
2019
).
3
NEIL GEHRELS SWIFT OBSERVATORY
DATA:
ANALYSIS AND RESULTS
The
Neil Gehrels Swift Observatory
satellite (Gehrels et al.
2004
)
carried out 73 observations of CTA 102 between 2013 March 24
(MJD 56436) and 2017 January 18 (MJD 57771). The observations
were performed with all three instruments on board: the X-ray
Telescope (XRT; Burrows et al.
2005
, 0.2–10.0 keV), the Ultravi-
olet/Optical Telescope (UVOT; Roming et al.
2005
, 170–600 nm),
and the Burst Alert Telescope (BAT; Barthelmy et al.
2005
, 15–
150 keV).
The hard X-ray flux of this source turned out to be below the
sensitivity of the BAT instrument for such short exposures and
therefore the data from this instrument will not be used. Moreover,
the source is not present in the
Swift
BAT 105-month hard X-ray
catalogue (Oh et al.
2018
).
The XRT data were processed with standard procedures (
xrt-
pipeline v0.13.3
), filtering, and screening criteria by using
the
HEASOFT
package (v6.22). The data were collected in photon
counting mode in all the observations. The source position in
detector coordinates was optimized for each observation by means
of
XIMAGE
. The source extraction region is centred on these
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490,
5300–5316 (2019)
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5304
F. D’Ammando et al.
Figure 4.
Swift
-XRT photon index as a function of the 0.3–10 keV
unabsorbed flux. The red points highlight the high-activity period.
coordinates. The source count rate in some observations is higher
than 0.5 count s
−
1
: these observations were checked for pile-up
and a correction was applied following standard procedures (e.g.
Moretti et al.
2005
). To correct for pile-up we excluded from
the source extraction region the inner circle of three-pixel radius
by considering an annular region with outer radius of 30 pixel
(1 pixel
∼
2.36 arcsec). For the other observations source events
were extracted from a circular region with a radius of 20 pixels.
Background events were extracted from a circular region with
radius of 50 pixels far away from bright sources. Ancillary response
files were generated with
xrtmkarf
, and account for different
extraction regions, vignetting and point spread function corrections.
We used the spectral redistribution matrices v014 in the calibration
data base maintained by
HEASARC
.
4
We fitted the spectrum with
an absorbed PL using the photoelectric absorption model
tbabs
(Wilms, Allen & McCray
2000
), with a neutral hydrogen column
density fixed to its Galactic value in the source direction (
N
H
=
2.83
×
10
20
cm
−
2
; Kalberla et al.
2005
). The results of the fit are
reportedinTable
A1
and the 0.3–10 keV fluxes are shown in Fig.
2
in comparison to the
γ
-ray light curve obtained by
Fermi
-LAT.
The X-ray flux (0.3–10 keV) varied between 7.6
×
10
−
13
and
68.1
×
10
−
13
erg cm
−
2
s
−
1
and the photon index between 1.14 and
1.85, with an average value of
X
=
1.40
±
0.15. In Fig.
4
we
plotted the XRT photon index as a function of flux in the 0.3–
10 keV energy range. A harder-when-brighter spectral trend has
been observed in X-rays in several blazars (e.g. Krawczynski et al.
2004
; D’Ammando et al.
2011
; Raiteri et al.
2012
; Aleksic et al.
2015
; Hayashida et al.
2015
), although not always present also in
the same source (e.g. Hayashida et al.
2012
; Aleksic et al.
2017
;
Carnerero et al.
2017
). This behaviour is usually related to the
competition between acceleration and cooling processes acting on
relativistic electrons. No spectral hardening with increasing flux is
observed either in the entire period or in the high-activity period
alone for CTA 102. This suggests that a change in the electron energy
distribution is not the main driver of the long-term variability in this
4
https://heasarc.gsfc.nasa.gov/docs/heasarc/caldb/
energy band. However, at the peak of the X-ray activity the photon
index is harder than the average value observed over 2013–2017.
During the
Swift
pointings, the UVOT instrument observed
CTA 102 in all its optical (
v
,
b
,and
u
)andUV(
w
1,
m
2, and
w
2) photometric bands (Poole et al.
2008
;Breeveldetal.
2010
).
We analysed the data using the
uvotsource
task included in the
HEASOFT
package (v6.22). Source counts were extracted from a
circular region of five-arcsec radius centred on the source, while
background counts were derived from a circular region of 20 arcsec
radius in a nearby source-free region. Observed magnitudes are
reported in Table
B1
. An increase of 4.5–5.5 mag with respect to
the faint state of the source was observed in the UVOT bands, with
a range of values:
v
=
11.44–16.86,
b
=
12.56–17.24,
u
=
11.78–
16.27,
w
1
=
11.33–16.18,
m
2
=
11.36–16.17,
w
2
=
11.52–16.46.
Following Raiteri et al. (
2010
,
2011
) to obtain de-absorbed flux
densities we used the count rate to flux density conversion factors
CF and amount of Galactic extinction
A
for each UVOT band
that have been obtained by folding the quantities of interest with
the source spectrum and effective areas of UVOT filters and are
reported in Larionov et al. (
2016
).
Besides correcting flux densities for Galactic extinction, we also
subtracted the thermal emission contribution due to the accretion
disc and BLR according to the model by Raiteri et al. (
2014
).
4 OPTICAL-TO-RADIO OBSERVATIONS
CTA 102 has been monitored by the GLAST-AGILE Support Pro-
gram (GASP) of the WEBT in the optical, near-infrared, and radio
bands since 2008. Optical-to-radio GASP-WEBT data collected
in 2013–2017 have been presented in Raiteri et al. (
2017
). That
data set is here complemented with data at 15 GHz by the OVRO
telescope, at 91 and 103 GHz by ALMA, in the near-IR by the
REM telescope, in the optical by the
Swift
satellite. The optical
photometric observations used in this paper were acquired at the fol-
lowing observatories: Abastumani (Georgia), AstroCamp (Spain),
Belogradchik (Bulgaria), Calar Alto (Spain), Campo Imperatore
(Italy), Crimean (Russia), Kitt Peak (USA), Lowell (USA; 70 cm,
DCT and Perkins telescopes), Lulin (Taiwan), Michael Adrian
(Germany), Mt. Maidanak (Uzbekistan), New Mexico Skies (USA),
Osaka Kyoiku (Japan), Polakis (USA), Roque de los Muchachos
(Spain; Liverpool, NOT and TNG telescopes), ROVOR (USA),
Rozhen (Bulgaria; 200 and 50/70 cm telescopes), San Pedro Martir
(Mexico), Sirio (Italy), Skinakas (Greece), Steward (USA; Kuiper,
Bok, and Super-LOTIS), St. Petersburg (Russia), Teide (Spain),
Tien Shan (Kazakhstan), Tijarafe (Spain), Tucson (USA), Valle
d’Aosta (Italy), and Vidojevica (Serbia).
Near-IR data were collected within the WEBT project in the
J
,
H
,
and
K
bands at the Campo Imperatore, Lowell (Perkins) and Teide
observatories. These data are here complemented with observations
performed by REM (Zerbi et al.
2001
;Covinoetal.
2004
), a robotic
telescope located at the ESO Cerro La Silla observatory (Chile), in
the period 2016 November 15–2016 December 11. All raw near-IR
frames obtained with the REM telescope were reduced following
standard procedures. Instrumental magnitudes were obtained via
aperture photometry and absolute calibration has been performed by
means of secondary standard stars in the field reported by 2MASS.
5
The data presented here were obtained as Target of Opportunity
observations triggered by the
γ
-ray flaring activity of the source (PI:
F. D’Ammando). Observed magnitudes are reported in Table
C1
.
5
http://www.ipac.caltech.edu/2mass/
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MWL behaviour of CTA 102 during 2013–2017
5305
Table 1.
Variability amplitude estimated over the period 2013 January 1–2017 February 9 in the different energy bands. Values are
corrected for Galactic extinction and the thermal emission contribution. For the minimum and maximum flux density the MJD at
which the value is collected is reported in parenthesis.
Band
Minimum flux density
Maximum flux density
Variability amplitude
(erg cm
−
2
s
−
1
)(ergcm
−
2
s
−
1
)
γ
-rays
5.91
×
10
−
13
(MJD 57177–57181)
3.02
×
10
−
9
(MJD 57752–57756)
5110
X-ray
7.60
×
10
−
12
(MJD 57386)
6.81
×
10
−
11
(MJD 57759)
9
W2
1.95
×
10
−
12
(MJD 56958)
4.92
×
10
−
10
(MJD 57751)
253
M2
3.41
×
10
−
12
(MJD 56958)
6.90
×
10
−
10
(MJD 57752)
202
W1
2.55
×
10
−
12
(MJD 56958)
5.95
×
10
−
10
(MJD 57751)
233
U2.50
×
10
−
12
(MJD 56958)
3.37
×
10
−
10
(MJD 57752)
135
B2.98
×
10
−
13
(MJD 56893)
7.20
×
10
−
10
(MJD 57750)
2416
V1.97
×
10
−
13
(MJD 56874)
7.71
×
10
−
10
(MJD 57750)
3920
R2.20
×
10
−
13
(MJD 56785)
7.76
×
10
−
10
(MJD 57750)
3523
I3.62
×
10
−
13
(MJD 56785)
8.01
×
10
−
10
(MJD 57750)
2210
J6.18
×
10
−
13
(MJD 56879)
6.96
×
10
−
10
(MJD 57752)
1126
H8.59
×
10
−
13
(MJD 56879)
7.10
×
10
−
10
(MJD 57752)
827
K1.09
×
10
−
12
(MJD 56879)
5.73
×
10
−
10
(MJD 57751)
526
230 GHz
2.25
×
10
−
12
(MJD 56832)
1.62
×
10
−
11
(MJD 57754)
7
103 GHz
1.63
×
10
−
12
(MJD 56837)
6.93
×
10
−
12
(MJD 57649)
4.3
91 GHz
1.51
×
10
−
12
(MJD 56837)
5.84
×
10
−
12
(MJD 57649)
3.9
37 GHz
7.92
×
10
−
13
(MJD 56839)
1.89
×
10
−
12
(MJD 57671)
2
15 GHz
4.28
×
10
−
13
(MJD 56651)
5.99
×
10
−
13
(MJD 57708)
1.5
Optical and near-IR flux densities were dereddened following the
prescriptions of the NASA/IPAC Extragalactic Database
6
(NED)
and corrected for the thermal emission contribution according to
the model of Raiteri et al. (
2017
).
Radio and mm observations were done at the Mets
̈
ahovi Radio
Observatory (Finland) at 37 GHz, and at the 30-m IRAM telescope
(Spain) and the Sub-millimeter Array (Hawaii, USA) at 230 GHz.
We also added the ALMA data collected at 91 and 103 GHz (Band
3) during 2013–2017 and included in the ALMA calibrator source
catalogue.
7
As part of an ongoing blazar monitoring program, the OVRO
40-Meter Telescope has observed CTA 102 at 15 GHz regularly
since the beginning of 2009. The OVRO 40-Meter Telescope uses
off-axis dual-beam optics and a cryogenic receiver with 2 GHz
equivalent noise bandwidth centred at 15 GHz. Atmospheric and
ground contributions as well as gain fluctuations are removed with
the double switching technique (Readhead et al.
1989
) where the
observations are conducted in an ON–ON fashion so that one of
the beams is always pointed on the source. Until 2014 May the
two beams were rapidly alternated using a Dicke switch. Since
2014 May, when a new pseudo-correlation receiver replaced the
old receiver, a 180 deg phase switch is used. Relative calibration
is obtained with a temperature-stable noise diode to compensate
for gain drifts. The primary flux density calibrator is 3C 286,
with an assumed value of 3.44 Jy (Baars et al.
1977
); DR21 is
used as secondary calibrator source. Details of the observation
and data reduction schemes are given in Richards et al. (
2011
).
Observations acquired at 15 GHz by OVRO were used in this
paper together with those obtained within the WEBT project. The
radio flux at 15 GHz varied between 2.85 and 3.88 Jy during
2013–2017.
Radio-to-optical light curves collected by WEBT, REM, ALMA,
and OVRO will be compared to the
γ
-ray light curve obtained by
Fermi
-LAT in the Section 5.
6
http://ned.ipac.caltech.edu/
7
https://almascience.eso.org/alma-data/calibrator-catalogue
5 MULTIFREQUENCY FLUX VARIABILITY
Variability studies of radio-to-
γ
-ray emission from blazars can
provide important insights into the physics of the jet and the
mechanisms at work in these sources. Flares can be explained e.g.
by a shock propagating downstream the jet and/or by variations of
the Doppler factor, which depends on the bulk Lorentz factor of
the relativistic plasma in the jet and on the viewing angle. During
flares, blazars usually show greater variability amplitudes in the
high-energy part of the spectrum than in the low-energy one (e.g.
Wehrle et al.
1998
; Raiteri et al.
2012
). However, some sources
increased their brightness by hundreds of times also in infrared and
optical bands. In this context, the 2016–2017 outburst of CTA 102
presented here is one of the best cases to study.
We quantify the observed variability of the CTA 102 jet emission
in the different energy bands through the variability amplitude,
calculated as the ratio of maximum to minimum flux. Values
in the
γ
-ray band are based on the light curve with five-day
time bins. Near-infrared-to-UV fluxes are corrected for Galactic
extinction. Moreover, the contribution of the thermal emission from
the disc, BLR, and torus is removed to properly consider only the
jet contribution to the flux. In Table
1
and Fig.
5
, we report the
variability amplitude estimated over the period 2013 January 1–
2017 February 9 in the different bands. The variability amplitude
may depend on the sampling of the light curves at the different
frequencies. In the case of CTA 102, observations were available
in all energy bands at the peak of the flare, making the values
obtained representative of the increase of activity of the source. The
variability amplitude shows a rising trend with increasing frequency
in the radio-to-optical range and it declines in the UV. The X-ray
band has a small variability amplitude, in particular if compared
to the
γ
-ray one. This can be related to the lower energies of the
electrons producing X-rays with respect to those producing
γ
-rays.
The similar variability amplitude at 230 GHz and in the X rays may
be a hint that they are produced by the same electron population
in the same jet region through the synchrotron and IC emission
mechanism, respectively, as found e.g. for BL Lacertae (Raiteri
et al.
2013
).
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5306
F. D’Ammando et al.
Figure 5.
Variability amplitude versus frequency in the different energy
bands estimated over the period 2013 January 1–2017 February 9. Values
are corrected for Galactic extinction and the thermal emission contribution.
Figure 6.
Multifrequency light curve normalized to the maximum value
observed for the period 2016 November 11–2017 February 8 (MJD 57003–
57792) in the following energy bands (from top to bottom):
γ
-rays (100
MeV–300 GeV), X-rays (0.3–10 keV),
B
,
V
,
R
,
I
,
J
,
H
,and
K
. Filled triangles:
WEBT data; open triangles: UVOT data; open squares: REM data. Main
γ
-ray outbursts are labelled as F1, F2, F3, and F4 in the top panel.
Simultaneous flux variations at low and high energies indicate
that their emission comes from the same region of the jet and that
the same electrons produce both the synchrotron and IC fluxes (e.g.
Fossati et al.
2008
). However, flaring events in the optical band with
no counterpart at high energies were observed in some blazars (e.g.
Chatterjee et al.
2013
; D’Ammando et al.
2013
). Strong variability
characterizes the emission over the entire electromagnetic spectrum
Figure 7.
Comparison of the
Fermi
-LAT
γ
-ray light curve with 12-h time
bins (top panel) and
R
-band light curve (bottom panel) normalized to the low-
est value observed in the period 2016 November 11–2017 February 8. Main
γ
-ray outbursts and ‘orphan’ flares are labelled as F1, F2, F3, F4, and orphan
in the top panel. The ‘sterile’ flare is labelled as sterile in the bottom panel.
of CTA 102 in 2016–2017, in particular during the period 2016
November 11–2017 February 8 (MJD 57003–57792), making this
an ideal target to investigate the connection of the flux behaviour
observed in
γ
-rays with the flux behaviour at lower energies.
In Fig.
6
, we compare the
γ
-ray light curve obtained by
Fermi
-
LAT with 12-h time bins during the highest activity period, 2016
November 11–2017 February 8 (MJD 57003–57792, corresponding
to the outburst VI in Fig.
2
), to the infrared-to-X-ray light curves.
All fluxes are normalized to the maximum value observed in the
considered period in order to compare when and how much the flux
increased in the different energy bands. In the
γ
-ray light curve we
can see four major outbursts peaked on 2016 December 15 (MJD
57737; F1), 2016 December 22 (MJD 57744; F2), 2016 December
27 (MJD 57749; F3), and 2017 January 4 (MJD 57757; F4). The
third outburst appears more prominent and shows a larger increase
with respect to the others. These four outbursts have corresponding
events in optical, with the peaks observed at the same time. In
J
,
H
,
and
K
bands the sampling is sparse and only two of the four peaks
are observed. A high X-ray flux has been observed in the period that
covers the
γ
-ray flares F1 and F2, and two X-ray peaks are evident
at the time of the
γ
-ray flares F3 and F4.
If we compare the
γ
-ray and optical (
R
band, the best sampled
band) fluxes normalized to the respective lowest values observed
during 2016 November 11–2017 February 9 (Fig.
7
), it is evident
that the four main flares occurred at the same time. A similar
amplitude has been observed in the two bands, except for the
first flare. In particular, the same variability amplitude has been
observed during the main peak. On the other hand, not all the
events observed in the optical band have a counterpart in
γ
-rays
and vice versa. In addition to the ‘sterile’ optical flare
8
occurred
around 2016 December 1 (MJD 57723), no significant optical
8
With ‘sterile flare’ and ‘orphan flare’ we mean a flare observed in the
optical band with no counterpart at
γ
-ray frequencies, and a flare that is
observed at the high energies only, respectively.
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MWL behaviour of CTA 102 during 2013–2017
5307
Figure 8.
DCF between the
γ
-ray fluxes obtained with five-day time bins
and the
R
-band flux densities with one day binning over the whole 2013–
2017 period.
Figure 9.
DCF between the
γ
-ray fluxes obtained with 12-h time bins
and the
R
-band flux densities with one-hour binning during the 2016–
2017 flaring period. The inset shows the result of cross-correlating 1000
Monte Carlo realizations of the two data sets according to the ‘flux
redistribution/random subset selection’ technique.
activity corresponds to the increase of
γ
-ray activity peaked on
2017 January 24 (MJD 57777) and 2017 February 6 (MJD 57790)
(‘orphan’ flares). This indicates that the interpretation of the source
variability must be more complicated than the fair overall optical–
γ
correlation would suggest.
Cross-correlation analysis between flux variations in different
bands can allow us to determine whether the emissions come from
the same region of the jet or not. We used the discrete correlation
function (DCF; Edelson & Krolik
1988
; Hufnagel & Bregman
1992
)
to analyse cross-correlations. Correlation produces positive peaks
in the DCF and is strong if the peak value approaches or even
exceeds one. The DCF between the
γ
-ray and the optical (
R
-band)
light curves over the whole 2013–2017 period is displayed in Fig.
8
,
showing a main peak compatible with no time lag. When comparing
the
γ
-ray light curve with 12-h time bin with the optical light curve
with one-hour binning in the high-activity period of Fig.
7
,theDCF
shows again a main peak compatible with no time lag, with DCF
p
=
0.94 (Fig.
9
). This indicates strong correlation between
γ
-ray
and optical emission, with no evidence of delay between the flux
variations in the two bands, in agreement with the results presented
in Larionov et al. (
2017
). We determine the uncertainty in this
Figure 10.
Multifrequency light curve normalized to the maximum value
observed for the period 2016 November 11–2017 February 8 (MJD 57003–
57792) in the following energy bands (from top to bottom):
γ
-rays (100
MeV–300 GeV),
w
2,
m
2, and
w
1 bands.
result by performing 1000 Monte Carlo simulations according to the
‘flux redistribution/random subset selection’ technique (Peterson
et al.
1998
; Raiteri et al.
2003
), which tests the importance of
sampling and data errors. Among the 1000 simulations, we obtain
that 78.3 per cent of simulations (
>
1
σ
) give a time lag between 0
and 0.6 d, as shown in the inset of Fig.
9
. This is compatible with
no delay between optical and
γ
-ray emission. The secondary DCF
peaks in Fig.
9
are due to the multipeaked structure of the outburst.
Although the UV data collected by
Swift
-UVOT are sparser than
the optical ones, we can recognize a similar behaviour in the
γ
-
ray and UV light curves with similar increase of flux during the
flaring period when normalized to the maximum value (Fig.
10
),
even though the variability amplitude is smaller in UV with respect
to the
γ
-ray band.
The sparse X-ray data in 2013–2015 indicate a low flux, in
keeping with the relatively low activity observed also in
γ
-rays
(see Fig.
2
). The comparison between the
γ
-ray and the X-ray light
curves during the high-activity period shows a general agreement,
with the
γ
-ray peaks corresponding to high X-ray fluxes (Fig.
11
).
Cross-correlation of the
γ
-ray (12-h time bins) and X-ray light
curves in the high-activity period shows a good correlation with
a time lag compatible to zero within the DCF bin size of six days
(Fig.
12
). The different sampling of the light curves does not allow a
more detailed comparison. However, the X-ray variability amplitude
appears much smaller than at
γ
-rays.
The correlation between the radio-mm fluxes on one side and
the optical and
γ
-ray fluxes on the other side is rather puzzling.
In general, they present a different behaviour, but sometimes they
share common features. As one can see in Fig.
13
, the mm data
at 230 GHz show a steady flux increase starting from the end of
2015 and culminating with a prominent outburst peaking on 2017
January 1 (MJD 57754). A comparison with the
γ
-ray light curve
reveals that the end of 2015 also marks the beginning of the activity
in this band, with the major peak observed at the same time of the
230 GHz one.
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