A&A 640, A69 (2020)
https:
//
doi.org
/
10.1051
/
0004-6361
/
202037493
c
©
J.-Y. Kim et al. 2020
Astronomy
&
Astrophysics
Event Horizon Telescope imaging of the archetypal blazar 3C 279 at
an extreme 20 microarcsecond resolution
?
Jae-Young Kim
1
, Thomas P. Krichbaum
1
, Avery E. Broderick
2 ,3 ,4
, Maciek Wielgus
5 ,6
, Lindy Blackburn
5 ,6
, José L. Gómez
7
, Michael
D. Johnson
5 ,6
, Katherine L. Bouman
5 ,6 ,8
, Andrew Chael
9 ,10
, Kazunori Akiyama
11 ,12 ,13 ,5
, Svetlana Jorstad
14 ,15
, Alan P. Marscher
14
,
Sara Issaoun
16
, Michael Janssen
16
, Chi-kwan Chan
17 ,18
, Tuomas Savolainen
19 ,20 ,1
, Dominic W. Pesce
5 ,6
, Feryal Özel
17
, Antxon Alberdi
7
,
Walter Alef
1
, Keiichi Asada
21
, Rebecca Azulay
22 ,23 ,1
, Anne-Kathrin Baczko
1
, David Ball
17
, Mislav Balokovi
́
c
5 ,6
, John Barrett
12
, Dan Bintley
24
,
Wilfred Boland
25
, Geo
ff
rey C. Bower
26
, Michael Bremer
27
, Christiaan D. Brinkerink
16
, Roger Brissenden
5 ,6
, Silke Britzen
1
,
Dominique Broguiere
27
, Thomas Bronzwaer
16
, Do-Young Byun
28 ,29
, John E. Carlstrom
30 ,31 ,32 ,33
, Shami Chatterjee
34
, Koushik Chatterjee
35
,
Ming-Tang Chen
26
, Yongjun Chen (
陈
永
军
)
36 ,37
, Ilje Cho
28 ,29
, Pierre Christian
17 ,6
, John E. Conway
38
, James M. Cordes
34
, Geo
ff
rey B. Crew
12
,
Yuzhu Cui
39 ,40
, Jordy Davelaar
16
, Mariafelicia De Laurentis
41 ,42 ,43
, Roger Deane
44 ,45
, Jessica Dempsey
24
, Gregory Desvignes
46
, Jason Dexter
47
,
Sheperd S. Doeleman
5 ,6
, Ralph P. Eatough
1
, Heino Falcke
16
, Vincent L. Fish
12
, Ed Fomalont
11
, Raquel Fraga-Encinas
16
, Per Friberg
24
,
Christian M. Fromm
42
, Peter Galison
5 ,48 ,49
, Charles F. Gammie
50 ,51
, Roberto García
27
, Olivier Gentaz
27
, Boris Georgiev
3 ,4
, Ciriaco Goddi
16 ,52
,
Roman Gold
53 ,42 ,2
, Arturo I. Gómez-Ruiz
54
, Minfeng Gu (
顾
敏
峰
)
36 ,55
, Mark Gurwell
6
, Kazuhiro Hada
39 ,40
, Michael H. Hecht
12
,
Ronald Hesper
56
, Luis C. Ho (
何
子
山
)
57 ,58
, Paul Ho
21
, Mareki Honma
39 ,40
, Chih-Wei L. Huang
21
, Lei Huang (
黄
磊
)
36 ,55
, David H. Hughes
59
,
Shiro Ikeda
13 ,60 ,61 ,62
, Makoto Inoue
21
, David J. James
63
, Buell T. Jannuzi
17
, Britton Jeter
3 ,4
, Wu Jiang (
江
悟
)
36
, Alejandra Jimenez-Rosales
64
,
Taehyun Jung
28 ,29
, Mansour Karami
2 ,3
, Ramesh Karuppusamy
1
, Tomohisa Kawashima
13
, Garrett K. Keating
6
, Mark Kettenis
65
, Junhan Kim
17 ,8
,
Jongsoo Kim
28
, Motoki Kino
13 ,66
, Jun Yi Koay
21
, Patrick M. Koch
21
, Shoko Koyama
21
, Michael Kramer
1
, Carsten Kramer
27
, Cheng-Yu Kuo
67
,
Tod R. Lauer
68
, Sang-Sung Lee
28
, Yan-Rong Li (
李
彦
荣
)
69
, Zhiyuan Li (
李
志
远
)
70 ,71
, Michael Lindqvist
38
, Rocco Lico
1
, Kuo Liu
1
,
Elisabetta Liuzzo
72
, Wen-Ping Lo
21 ,73
, Andrei P. Lobanov
1
, Laurent Loinard
74 ,75
, Colin Lonsdale
12
, Ru-Sen Lu (
路
如
森
)
36 ,37 ,1
, Nicholas
R. MacDonald
1
, Jirong Mao (
毛
基
荣
)
76 ,77 ,78
, Sera Marko
ff
35 ,79
, Daniel P. Marrone
17
, Iván Martí-Vidal
22 ,23
, Satoki Matsushita
21
, Lynn
D. Matthews
12
, Lia Medeiros
80 ,17
, Karl M. Menten
1
, Yosuke Mizuno
42
, Izumi Mizuno
24
, James M. Moran
5 ,6
, Kotaro Moriyama
12 ,39
,
Monika Moscibrodzka
16
, Gibwa Musoke
35 ,16
, Cornelia Müller
1 ,16
, Hiroshi Nagai
13 ,40
, Neil M. Nagar
81
, Masanori Nakamura
21
,
Ramesh Narayan
5 ,6
, Gopal Narayanan
82
, Iniyan Natarajan
45
, Roberto Neri
27
, Chunchong Ni
3 ,4
, Aristeidis Noutsos
1
, Hiroki Okino
39 ,83
,
Héctor Olivares
42
, Gisela N. Ortiz-León
1
, Tomoaki Oyama
39
, Daniel C. M. Palumbo
5 ,6
, Jongho Park
21
, Nimesh Patel
6
, Ue-Li Pen
2 ,84 ,85 ,86
,
Vincent Piétu
27
, Richard Plambeck
87
, Aleksandar PopStefanija
82
, Oliver Porth
35 ,42
, Ben Prather
50
, Jorge A. Preciado-López
2
,
Dimitrios Psaltis
17
, Hung-Yi Pu
2
, Venkatessh Ramakrishnan
81
, Ramprasad Rao
26
, Mark G. Rawlings
24
, Alexander W. Raymond
5 ,6
,
Luciano Rezzolla
42
, Bart Ripperda
88 ,89
, Freek Roelofs
16
, Alan Rogers
12
, Eduardo Ros
1
, Mel Rose
17
, Arash Roshanineshat
17
, Helge Rottmann
1
,
Alan L. Roy
1
, Chet Ruszczyk
12
, Benjamin R. Ryan
90 ,91
, Kazi L. J. Rygl
72
, Salvador Sánchez
92
, David Sánchez-Arguelles
54
, Mahito Sasada
39 ,93
,
F. Peter Schloerb
82
, Karl-Friedrich Schuster
27
, Lijing Shao
1 ,58
, Zhiqiang Shen (
沈
志强
)
36 ,37
, Des Small
65
, Bong Won Sohn
28 ,29 ,94
,
Jason SooHoo
12
, Fumie Tazaki
39
, Paul Tiede
3 ,4
, Remo P. J. Tilanus
16 ,52 ,95 ,17
, Michael Titus
12
, Kenji Toma
96 ,97
, Pablo Torne
1 ,92
, Tyler Trent
17
,
Efthalia Traianou
1
, Sascha Trippe
98
, Shuichiro Tsuda
39
, Ilse van Bemmel
65
, Huib Jan van Langevelde
65 ,99
, Daniel R. van Rossum
16
,
Jan Wagner
1
, John Wardle
100
, Derek Ward-Thompson
101
, Jonathan Weintroub
5 ,6
, Norbert Wex
1
, Robert Wharton
1
, George N. Wong
50 ,90
,
Qingwen Wu (
吴
庆
文
)
102
, Doosoo Yoon
35
, André Young
16
, Ken Young
6
, Ziri Younsi
103 ,42
, Feng Yuan (
袁
峰
)
36 ,55 ,104
, Ye-Fei Yuan (
袁
业
飞
)
105
,
J. Anton Zensus
1
, Guangyao Zhao
28
, Shan-Shan Zhao
16 ,70
, Ziyan Zhu
49
, Juan-Carlos Algaba
21 ,106
, Alexander Allardi
107
, Rodrigo Amestica
108
,
Jadyn Anczarski
109
, Uwe Bach
1
, Frederick K. Bagano
ff
110
, Christopher Beaudoin
12
, Bradford A. Benson
111 ,31 ,30
, Ryan Berthold
24
,
Jay M. Blanchard
81 ,65
, Ray Blundell
6
, Sandra Bustamente
112
, Roger Cappallo
12
, Edgar Castillo-Domínguez
112 ,113
, Chih-Cheng Chang
21 ,114
,
Shu-Hao Chang
21
, Song-Chu Chang
114
, Chung-Chen Chen
21
, Ryan Chilson
26
, Tim C. Chuter
24
, Rodrigo Córdova Rosado
5 ,6
, Iain M. Coulson
24
,
Joseph Crowley
12
, Mark Derome
12
, Matthew Dexter
115
, Sven Dornbusch
1
, Kevin A. Dudevoir
12
,
†
, Sergio A. Dzib
1
, Andreas Eckart
1 ,116
,
Chris Eckert
12
, Neal R. Erickson
82
, Wendeline B. Everett
117
, Aaron Faber
118
, Joseph R. Farah
5 ,6 ,119
, Vernon Fath
82
, Thomas W. Folkers
17
, David
C. Forbes
17
, Robert Freund
17
, David M. Gale
112
, Feng Gao
36 ,64
, Gertie Geertsema
120
, David A. Graham
1
, Christopher H. Greer
17
,
Ronald Grosslein
82
, Frédéric Gueth
27
, Daryl Haggard
121 ,122 ,123
, Nils W. Halverson
124
, Chih-Chiang Han
21
, Kuo-Chang Han
114
, Jinchi Hao
114
,
Yutaka Hasegawa
125
, Jason W. Henning
30 ,126
, Antonio Hernández-Gómez
1
, Rubén Herrero-Illana
127 ,128
, Stefan Heyminck
1
, Akihiko Hirota
13 ,21
,
James Hoge
24
, Yau-De Huang
21
, C. M. Violette Impellizzeri
21 ,11
, Homin Jiang
21
, David John
92
, Atish Kamble
5 ,6
, Ryan Keisler
32
,
Kimihiro Kimura
21
, Yusuke Kono
13
, Derek Kubo
129
, John Kuroda
24
, Richard Lacasse
108
, Robert A. Laing
130
, Erik M. Leitch
30
, Chao-Te Li
21
,
Lupin C.-C. Lin
21 ,131
, Ching-Tang Liu
114
, Kuan-Yu Liu
21
, Li-Ming Lu
114
, Ralph G. Marson
132
, Pierre L. Martin-Cocher
21
, Kyle D. Massingill
17
,
Callie Matulonis
24
, Martin P. McColl
17
, Stephen R. McWhirter
12
, Hugo Messias
127 ,133
, Zheng Meyer-Zhao
21 ,134
, Daniel Michalik
135 ,136
,
Alfredo Montaña
112 ,113
, William Montgomerie
24
, Matias Mora-Klein
108
, Dirk Muders
1
, Andrew Nadolski
51
, Santiago Navarro
92
,
Joseph Neilsen
109
, Chi H. Nguyen
137
, Hiroaki Nishioka
21
, Timothy Norton
6
, Michael A. Nowak
138
, George Nystrom
26
, Hideo Ogawa
125
,
Peter Oshiro
26
, Tomoaki Oyama
139
, Harriet Parsons
24
, Juan Peñalver
92
, Neil M. Phillips
127 ,133
, Michael Poirier
12
, Nicolas Pradel
21
, Rurik
A. Primiani
140
, Philippe A. Ra
ffi
n
26
, Alexandra S. Rahlin
30 ,111
, George Reiland
17
, Christopher Risacher
27
, Ignacio Ruiz
92
,
Alejandro F. Sáez-Madaín
108 ,133
, Remi Sassella
27
, Pim Schellart
16 ,141
, Paul Shaw
21
, Kevin M. Silva
24
, Hotaka Shiokawa
6
, David R. Smith
142 ,143
,
William Snow
26
, Kamal Souccar
82
, Don Sousa
12
, Tirupati K. Sridharan
6
, Ranjani Srinivasan
26
, William Stahm
24
, Antony A. Stark
6
,
Kyle Story
144
, Sjoerd T. Timmer
16
, Laura Vertatschitsch
6 ,140
, Craig Walther
24
, Ta-Shun Wei
21
, Nathan Whitehorn
145
, Alan R. Whitney
12
,
David P. Woody
146
, Jan G. A. Wouterloot
24
, Melvin Wright
147
, Paul Yamaguchi
6
, Chen-Yu Yu
21
, Milagros Zeballos
112 ,148
,
Shuo Zhang
110
, and Lucy Ziurys
17
(The Event Horizon Telescope Collaboration)
(A
ffi
liations can be found after the references)
Received 13 January 2020
/
Accepted 3 March 2020
?
The data are only available at the CDS via anonymous ftp to
cdsarc.u-strasbg.fr
(
130.79.128.5
) or via
http://cdsarc.u-strasbg.
fr/viz-bin/cat/J/A+A/640/A69
and at
https://eventhorizontelescope.org/for-astronomers/data
†
Deceased.
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https:
//
creativecommons.org
/
licenses
/
by
/
4.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Open Access funding provided by Max Planck Society.
A69, page 1 of 21
A&A 640, A69 (2020)
ABSTRACT
3C 279 is an archetypal blazar with a prominent radio jet that show broadband flux density variability across the entire electromagnetic spectrum.
We use an ultra-high angular resolution technique – global Very Long Baseline Interferometry (VLBI) at 1.3 mm (230 GHz) – to resolve the
innermost jet of 3C 279 in order to study its fine-scale morphology close to the jet base where highly variable
γ
-ray emission is thought to
originate, according to various models. The source was observed during four days in April 2017 with the Event Horizon Telescope at 230 GHz,
including the phased Atacama Large Millimeter
/
submillimeter Array, at an angular resolution of
∼
20
μ
as (at a redshift of
z
=
0
.
536 this corresponds
to
∼
0
.
13 pc
∼
1700 Schwarzschild radii with a black hole mass
M
BH
=
8
×
10
8
M
). Imaging and model-fitting techniques were applied to the data
to parameterize the fine-scale source structure and its variation. We find a multicomponent inner jet morphology with the northernmost component
elongated perpendicular to the direction of the jet, as imaged at longer wavelengths. The elongated nuclear structure is consistent on all four
observing days and across di
ff
erent imaging methods and model-fitting techniques, and therefore appears robust. Owing to its compactness and
brightness, we associate the northern nuclear structure as the VLBI “core”. This morphology can be interpreted as either a broad resolved jet base
or a spatially bent jet. We also find significant day-to-day variations in the closure phases, which appear most pronounced on the triangles with the
longest baselines. Our analysis shows that this variation is related to a systematic change of the source structure. Two inner jet components move
non-radially at apparent speeds of
∼
15
c
and
∼
20
c
(
∼
1
.
3 and
∼
1
.
7
μ
as day
−
1
, respectively), which more strongly supports the scenario of traveling
shocks or instabilities in a bent, possibly rotating jet. The observed apparent speeds are also coincident with the 3C 279 large-scale jet kinematics
observed at longer (cm) wavelengths, suggesting no significant jet acceleration between the 1.3 mm core and the outer jet. The intrinsic brightness
temperature of the jet components are
.
10
10
K, a magnitude or more lower than typical values seen at
≥
7 mm wavelengths. The low brightness
temperature and morphological complexity suggest that the core region of 3C 279 becomes optically thin at short (mm) wavelengths.
Key words.
galaxies: active – galaxies: jets – galaxies: individual: 3C 279 – techniques: interferometric
1. Introduction
Relativistic jets in active galactic nuclei (AGN) are believed to
originate from the vicinity of a supermassive black hole (SMBH),
which is located at the center of the galaxy. Understanding
the detailed physical processes of jet formation, acceleration,
collimation, and subsequent propagation has been one of the
major quests in modern astrophysics (see, e.g., Boccardi et al.
2017; Blandford et al. 2019 and references therein for recent
reviews)
Extensive studies on these topics have been carried out
over the last several decades, in particular by using the tech-
nique of millimeter-wave (mm) very long baseline interferom-
etry (VLBI), which provides especially high angular resolution
and can penetrate regions that are opaque at longer wavelengths.
Notably, recent Event Horizon Telescope (EHT) observations of
M 87 at 1.3 mm (230 GHz) have revealed a ring-like structure on
event horizon scales surrounding the SMBH, interpreted as the
black hole “shadow” (Event Horizon Telescope Collaboration
2019a,b,c,d,e,f; hereafter Papers I–VI). Although the EHT
results for M 87 provide an important step toward understand-
ing jet formation near a BH and in AGN systems in general,
the first EHT images of M 87 do not yet provide a direct con-
nection between the SMBH and the large-scale jet. Therefore,
imaging of fine-scale structures of AGN jets close to the SMBHs
still remains crucial in order to better understand the accretion
and outflow activities. Also, a more comprehensive understand-
ing of AGN jet formation will require systematic studies over
a wider range of AGN classes, given intrinsic di
ff
erences such
as luminosity, accretion rate, and environmental e
ff
ects (e.g.,
Yuan & Narayan 2014). We also note that M 87 and the Galac-
tic Center SMBH Sagittarius A* are relatively weak sources of
γ
-ray emission (e.g., Lucchini et al. 2019), while many other
AGN produce prominent and variable high-energy emission,
often from compact regions in their jets (e.g., Madejski & Sikora
2016). Therefore, studies of the high-power, high-luminosity
AGN also provide more clues regarding
γ
-ray emission mech-
anisms (see, e.g., Blandford et al. 2019 for a review).
Unfortunately, most high-power AGN are located at much
larger luminosity distances than M 87 and Sgr A*. Observing
frequencies up to 86 GHz have thus limited us in the past to
studying relatively large-scale jet morphology and evolution in
many di
ff
erent types of AGN. However, it is only with the EHT
at 230 GHz and beyond that the finest details at the base of those
gigantic dynamic structures become accessible. Combined with
other VLBI arrays, for example the Very Long Baseline Array
(VLBA) or Global Millimeter VLBI Array (GMVA) at 86 GHz,
the EHT can also connect the innermost regions of jets with
the downstream sections, revealing detailed profiles of the jet
collimation and locations of the collimation profile changes to
better constrain jet collimation and propagation theories (e.g.,
Asada & Nakamura 2012; Hada et al. 2013).
The blazar 3C 279 (1253
−
055) is one of the sources
that provided the first evidence of rapid structure variabil-
ity (Knight et al. 1971) and apparent superluminal motions in
compact AGN jets (Whitney et al. 1971; Cohen et al. 1971).
Since the discovery of the apparent superluminal motions,
the detailed structure of the radio jet in 3C 279 has been
imaged and its properties have been studied by a number of
VLBI observations until the present day. The 3C 279 jet con-
sists of a compact core and straight jet extended from sub-
parsec (sub-pc) to kiloparsec (kpc) scales. The compact core
has high apparent brightness temperature at centimeter wave-
lengths (
T
B
,
app
&
10
12
K; see, e.g., Kovalev et al. 2005). Both
the core and the extended jet show high fractional linear polar-
ization (
&
10%), and strong circular polarization on the order
of
∼
1% is also detected in the core region at
≤
15 GHz (e.g.,
Homan & Wardle 1999; Homan & Lister 2006; Homan et al.
2009a) and
≤
43 GHz (Vitrishchak et al. 2008). The extended jet
components show various propagation speeds (bulk Lorentz fac-
tor
Γ
∼
10
−
40; e.g., Bloom et al. 2013; Homan et al. 2015;
Jorstad et al. 2017), indicating the presence of not only under-
lying bulk plasma motions, but also patterns associated with
propagating shocks or instabilities. Interestingly, the inner jet
components of 3C 279 often display various position angles
(see, e.g., Homan et al. 2003; Jorstad et al. 2004 and refer-
ences therein), but later on such components tend to align
with the larger-scale jet direction while propagating toward
the jet downstream (e.g., Kellermann et al. 2004; Homan et al.
2009b). Based on the small viewing angle of the 3C 279 jet of
θ
∼
2
◦
(Jorstad et al. 2017), the misaligned jet components are
often modeled as spatially bent (and perhaps helical) jet struc-
tures, in which the jet Lorentz factor is constant along the out-
flow but the jet viewing angle changes (e.g., Abdo et al. 2010;
Aleksi
́
c et al. 2014). We also note that jet bending on VLBI
scales is common in many blazar jets (e.g., Hong et al. 2004;
Lobanov & Roland 2005; Zhao et al. 2011; Perucho et al. 2012;
A69, page 2 of 21
J.-Y. Kim et al.: EHT observations of 3C 279
−
5
0
5
10
−
5
0
5
v (G
λ
)
April 5
−
5
0
5
u (G
λ
)
−
5
0
5
April 6
−
5
0
5
−
5
0
5
April 10
−
10
−
5
0
5
−
5
0
5
April 11
ALMA-LMT
ALMA-PV
ALMA-SMA
ALMA-APEX
ALMA-SPT
ALMA-SMT
LMT-PV
LMT-SMA
LMT-SPT
PV-SPT
SMA-SPT
SMT-LMT
SMT-PV
SMT-SMA
SMT-SPT
Fig. 1.
Event Horizon Telescope (
u
,v
) coverage of 3C 279 on (
from left to right
) 2017 April 5, 6, 10, and 11. The color-coding for the corresponding
baselines is shown in the legend. The JCMT and APEX baselines are omitted because they repeat the SMA and ALMA baselines, respectively.
Fromm et al. 2013). For the innermost region of the 3C 279
jet (
.
100
μ
as
∼
0
.
65 pc projected
1
), earlier pilot VLBI studies
at 230 GHz revealed a complex microarcsecond-scale substruc-
ture within the nuclear region of the milliarcsecond scale jet
(Lu et al. 2013; Wagner et al. 2015). However, the (
u
,v
) cover-
age, and therefore the imaging fidelity, of these observations
was very limited. We also note that 3C 279 is well known
for its highly time-variable flux densities, from radio to
γ
-rays
(e.g., Chatterjee et al. 2008; Abdo et al. 2010; Aleksi
́
c et al.
2014; Kiehlmann et al. 2016; Rani et al. 2018; Larionov et al.
2020), while the exact locations of the
γ
-ray emission zones are
often controversial (e.g., Patiño-Álvarez et al. 2018, 2019). In
particular, 3C 279 shows flux density variations down to minute
timescales, which are often di
ffi
cult to interpret given the size
scales and Doppler factors inferred from radio VLBI observa-
tions (e.g., Ackermann et al. 2016).
In April 2017, 3C 279 was observed with a significantly
expanded EHT array over four nights. The EHT 2017 observa-
tions result in new and more detailed maps of the core region of
3C 279, providing an angular resolution of 20
μ
as, or
∼
0
.
13 pc
(corresponding to
∼
1700
R
s
for a SMBH of mass
M
BH
∼
8
×
10
8
M
; Nilsson et al. 2009). This paper presents the main
results from the EHT observation in 2017 and their scientific
interpretations. In Sect. 2 we briefly describe the observations,
imaging procedures, and model-fitting techniques. In Sect. 3 the
source images and model-fit parameters are presented. In Sect. 4
we discuss some physical implications of the peculiar compact
jet structure, in relation to the observed rapid variation of the
source structure and brightness temperature. Section 5 summa-
rizes our results. Throughout this paper we adopt a cosmology
with
H
0
=
67
.
7 km s
−
1
Mpc
−
1
,
Ω
m
=
0
.
307, and
Ω
Λ
=
0
.
693
(Planck Collaboration XIII 2016)
2
.
2. Observations and data processing
2.1. Observations and calibration
3C 279 was observed by the EHT on 2017 April 5, 6, 10,
and 11. We refer to Papers II and III, and references therein
1
At the redshift of 3C 279 (
z
=
0
.
536, Marziani et al. 1996), 1 mas
corresponds to a linear scale of 6.5 pc. An angular separation rate of
1 mas yr
−
1
therefore corresponds to an apparent speed of
β
app
∼
33
c
.
2
Adopting
H
0
=
70 km s
−
1
Mpc
−
1
,
Ω
m
=
0
.
3, and
Ω
Λ
=
0
.
7 leads to
∼
2% changes in the distances and apparent speeds, which we ignore.
0
2
4
6
8
Baseline (G
λ
)
10
−
2
10
−
1
10
0
10
1
Correlated Flux Density (Jy)
April 5
April 6
April 10
April 11
Fig. 2.
Flux-calibrated visibility amplitudes of 3C 279 in all epochs. The
visibility amplitude distributions are broadly consistent over four days,
while the closure phases are not (see Sect. 3).
for details of the scheduling, observations, data acquisition,
calibration, and data validation. Here we briefly outline the
overall procedures. A total of eight stations at six geographic
sites participated in the observations: Atacama Large Millime-
ter
/
submillimeter Array (ALMA), Atacama Pathfinder Experi-
ment telescope (APEX), Large Millimeter Telescope Alfonso
Serrano (LMT), IRAM 30 m Telescope (PV), Submillimeter
Telescope Observatory (SMT),
James Clerk Maxwell
Telescope
(JCMT), Submillimeter Array (SMA), and South Pole Telescope
(SPT). The signals were recorded at two 2 GHz bands (centered
at 227 and 229 GHz), using dual circularly polarized feeds (RCP
and LCP). JCMT observed only in one circular polarization.
ALMA observed using dual linear feeds. Because of this, the
polconvert
software (Martí-Vidal et al. 2016) was applied to
the correlated data to convert the ALMA visibilities from linear
to circular polarization.
The (
u
,v
) coverage is shown in Fig. 1. The high data record-
ing rate of 32 Gbps (corresponding to a total bandwidth of 2 GHz
per polarization per sideband) allowed robust fringe detections
up to a
∼
8
.
7
G
λ
baseline length, including the SPT, which signif-
icantly improved the fringe spacing toward 3C 279 in the north–
south direction. The correlated data were then calibrated using
various radio astronomical packages and validated through a
series of quality assurance tests (see Paper III for details). The
flux-calibrated visibility amplitude distributions are shown in
Fig. 2.
A69, page 3 of 21
A&A 640, A69 (2020)
Table 1.
CLEAN beam sizes of the EHT toward 3C 279.
Epoch
FWHM
maj
FWHM
min
PA
(
μ
as)
(
μ
as)
(
◦
)
April 05
25.8
17.2
20.1
April 06
21.0
18.0
15.6
April 10
21.6
15.1
82.8
April 11
22.6
13.9
88.3
Notes.
The beam sizes were obtained using
Difmap
and uniform
weighting. We adopt a 20
μ
as circular Gaussian beam for all 3C 279
CLEAN images.
2.2. Imaging and model-fitting analysis
For imaging, we used frequency-averaged visibility data from
the
EHT-HOPS
pipeline (see Paper III and Blackburn et al. 2019).
We note that image reconstruction with 1.3 mm wavelength
EHT data is particularly challenging because of the sparse
(
u
,v
) coverage, total loss of absolute atmospheric phase, and
large gain fluctuations at some stations. In addition, the 2017
EHT observations lack relatively short baselines at
.
1 G
λ
to
robustly recover extended emission structure on VLBI scale
at
&
100
μ
as (Paper IV). To ensure that the features we identi-
fied in our reconstructed images are robust, the source images
were generated by both traditional CLEAN and newer regular-
ized maximum likelihood algorithms implemented in the fol-
lowing programs:
Difmap
(Shepherd et al. 1994),
eht-imaging
(Chael et al. 2016, 2018), and
SMILI
(Akiyama et al. 2017a,b).
We used imaging pipelines for these three programs (see
Paper IV) to generate a total of 12 images of 3C 279 (i.e., one
per epoch per imaging method) within a limited field of view of
∼
100
μ
as due to lack of short EHT 2017 baselines (Paper IV). In
all methods, emission from the further extended milliarcsecond-
scale jet (Fig. 4), which lies beyond the compact EHT field
of view, was represented by a single large-scale Gaussian (see
Paper IV for details). We then averaged the three pipeline images
to obtain a representative image of the source at each epoch. We
refer to Paper IV for the details of the imaging pipelines and
image averaging procedures. In order to illustrate the EHT angu-
lar resolution toward 3C 279, we show in Table 1 the CLEAN
beam sizes of the EHT 3C 279 data calculated by
Difmap
.
In order to parameterize bright and compact features in the
source, we also performed Gaussian model-fitting analyses in
two distinct ways. The first is the traditional VLBI model-fitting
procedure (
DIFMAP modelfit
, which employs the Levenberg-
Marquardt algorithm for non-linear fits) to reconstruct a static
model with more than six components on each observation day.
Related components were then identified and the evolution in
their relative positions measured.
The second method utilizes T
hemis
, an EHT-specific anal-
ysis package, using a parallel-tempered, a
ffi
ne invariant Markov
chain Monte Carlo sampler (Broderick et al., in prep., and refer-
ences therein). In this case, a fully time-variable, ten-component
(nine compact and one large-scale) Gaussian component model
was reconstructed to naturally facilitate the identification of fea-
tures in subsequent observations and directly reconstruct their
evolution. From this time variable model, component parameters
and uncertainties are reconstructed for individual days. Addi-
tional descriptions of the underlying model and T
hemis
anal-
ysis can be found in Appendix A (also see Paper VI for more
general details for the EHT model-fitting and model-comparison
analysis).
In order to examine the reliability of the converged images
and models, we also compared antenna gains reconstructed by
amplitude self-calibration with both imaging and model-fitting
software. Figure B.1 shows plots of antenna gain corrections
for all days across di
ff
erent imaging pipelines and T
hemis
for
LMT, which has the largest systematic gain uncertainties in
the EHT 2017 observation (Papers III–VI). Consistent gain cor-
rections across independent imaging methods and model-fitting
analysis suggest that the results are robust against possible biases
in each algorithm.
3. Results
3.1. First 230 GHz images
Figure 3 shows an overview of the 3C 279 jet structure in April
2017 at 43, 86, and 230 GHz, where the 43 and 86 GHz images
are from quasi-simultaneous observations by the VLBA-BU-
BLAZAR 43 GHz (Jorstad et al. 2017) and the GMVA blazar
monitoring programs
3
, shown here for an illustration of the
larger-scale jet structure. In Fig. 4 we show the final EHT 1.3 mm
images of 3C 279 on April 5, 6, 10, and 11 obtained as described
in Sect. 2.2. The individual source images for all pipelines and
epochs are shown in Fig. C.1. The images show two bright and
somewhat extended emission regions, separated by
∼
100
μ
as,
with complex substructures within each of them. Hereafter we
refer to the northern and southern complexes as C0 and C1,
respectively. The C0 feature is substantially elongated in the
NW-SE direction by
∼
30
−
40
μ
as, as defined by the separation
between its subcomponents (see Sect. 3.3). This elongation is
perpendicular to the long-term larger-scale jet direction (SW;
see, e.g., Jorstad et al. 2017). We find a prominent and rapid
change of the brightness in the center of the C0 region over
∼
6 days (see also Sect. 3.3).
3.2. Inter-day closure phase variations
We show in Fig. 5 the closure phases of several long EHT tri-
angles for all days. Remarkably, the ALMA-SMA-SMT trian-
gle reveals large inter-day closure phase variations of
∼
100
◦
in
∼
6 days. Comparable closure phase changes are also seen for
other large triangles (Fig. 5). We note that similar inter-day clo-
sure phase changes were previously found in 3C 279 at 230 GHz
by Lu et al. (2013), but the much higher-sensitivity and longer-
baseline data presented here reveal much more dramatic closure
phase variations. This strongly implies the presence of inter-day
variability of the surface brightness distribution and compact
structure in the jet.
3.3. Model-fitting results
Values of parameters resulting from the Gaussian model-fitting
analysis for all days, such as component flux densities, sizes,
and relative positions are provided in Table D.1. Where these
are obtained from T
hemis
, they are evaluated from the dynam-
ical model at 6 UTC on each observation day. The component
kinematics are displayed in Figs. 6 and 7. Visibility amplitudes
and closure phases of the self-calibrated data and the Gaussian
model-fit are shown in Fig. D.1.
Quantitatively similar results were obtained on each day by
both
Difmap modelfit
and T
hemis
analyses; hereafter, we
3
https://www.bu.edu/blazars/vlbi3mm/index.html
A69, page 4 of 21
J.-Y. Kim et al.: EHT observations of 3C 279
−
−
−
! "
μ
−
−
−
! "
μ
#
−
−
! "
μ
−
−
−
#
−
−
! "
μ
−
−
−
#
−
−
−
−
Fig. 3.
Illustration of multiwavelength 3C 279 jet structure in April 2017. The observing epochs, arrays, and frequencies are noted at the top of
each panel. The color bars show the pixel values in Jy beam
−
1
. The white circles in the bottom left corners indicate the convolving beams. The
white rectangles shows the field of view of the next panels at the higher 86 and 230 GHz frequencies. We note that the centers of the images (0,0)
correspond to the location of the peak of total intensity. (From left to right) the beam sizes are 150
×
380, 50
×
139, and 20
×
20
μ
as
2
. For a spatially
resolved emitting region, an intensity of 1 Jy beam
−
1
in the 43, 86, and 230 GHz images correspond to brightness temperatures of 1
.
16
×
10
10
,
2
.
37
×
10
10
, and 5
.
78
×
10
10
K, respectively.
90 as
April 05
E
N
90 as
April 06
90 as
April 10
90 as
April 11
C0-0
C0-1
C0-2
C1-0
C1-1
C1-2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
Intensity (Jy/Beam)
Fig. 4.
EHT images of 3C 279 on each day, generated by three di
ff
erent pipelines, then aligned and averaged. See Paper IV for details on the
method. The circular 20
μ
as restoring beam is shown in the bottom right corner of each panel. The pixel values are in units of Jy beam
−
1
. In each
panel, the contour levels are 5%, 12%, 25%, 50%, and 75% of the peak value. The component identification is shown in the April 11 panel and is
only for illustration (see Fig. 6).
focus on the T
hemis
results that naturally identify components
across observation epochs. We find that the closure phases, clo-
sure amplitudes, and visibilities can be consistently described
by a model consisting of the ten Gaussian components, with a
reduced
χ
2
of
∼
1
.
3 for the best-fit models with
∼
1
.
5% systematic
errors in the visibility amplitudes (and equivalently
∼
2
◦
errors in
phases; see Paper III).
Six compact and bright features among the nine evolving
components are the most robustly constrained across epochs.
The other three extra components are much fainter (e.g., by an
order of magnitude), and are located outside the intensity distri-
butions reconstructed by imaging methods (Fig. 4). Therefore,
we do not discuss these three components hereafter. Figure 8
summarizes the time evolution over all epochs of the parameters
of these features. Three of them – C0-0, C0-1, and C0-2 – belong
to the C0 region, while the remainder (labeled C1-0, C1-1,
and C1-2) belong to the C1 region (see the rightmost panel
of Figs. 4 and 6). We note that there are consistent, outward
∼
1
.
1
−
1
.
2
μ
as day
−
1
proper motions of all C1 components when
the C0-0 feature is used as a reference. In contrast, C0-1 moves
perpendicular to its center position angle with respect to C0-0
with flux density decrease, and C0-2 moves toward C0-0 with a
pronounced increase in its flux density (see Sect. 3.4 for more
details).
Using the jet component parameters, we can compute their
apparent brightness temperatures in the frame of the observer
(thus not redshift or Doppler-boosting corrected),
T
B
, as
T
B
=
1
.
22
×
10
12
F
/
(
ν
2
d
maj
d
min
) K where for each component
F
is the
flux density in Jy,
ν
is the observing frequency in GHz, and
d
maj
,
min
are the major and minor full width at half maximum
(FWHM) sizes of the Gaussians in milliarcseconds, respectively.
The
T
B
values for all days are shown in Fig. 8 and Table D.1.
The apparent brightness temperatures are in the range of
T
B
∼
10
10
−
11
K. We note that the C0-1 and C0-2 components show
particularly large flux and size variations, which essentially lead
to rapid changes in the brightness temperature over the one-week
observing period.
3.4. Kinematic reference
Because of the nontrivial, complicated motions of C0-1 and
C0-2 with respect to C0-0, we also selected C0-1 and C0-2 as
A69, page 5 of 21
A&A 640, A69 (2020)
19
20
21
22
GMST (h)
125
150
175
200
225
250
Closure Phase (deg)
ALMA-SMA-SMT
April 5
April 6
April 10
April 11
19
20
21
22
GMST (h)
−
100
−
50
0
50
100
Closure Phase (deg)
ALMA-LMT-SMA
17
18
19
20
21
22
GMST (h)
−
60
−
40
−
20
0
20
Closure Phase (deg)
ALMA-LMT-SMT
Fig. 5.
Example of the closure phase variation in 3C 279 over four
epochs for the large ALMA-SMT-SMA, ALMA-LMT-SMA, and
ALMA-LMT-SMT triangles. The points show the data, and their error
bars include 1.5% systematic visibility errors (Paper III). The solid
lines show the model closure phases corresponding to the images from
each pipeline and day, and the dashed lines represent the model closure
phases of the average images shown in Fig. 4. Regions constrained by
predictions of the three independent image models are shaded.
alternative kinematic references and recalculated motions in
order to see if the complex kinematics could be described
more simply (e.g., simple radial outward motion in all com-
ponents). We find that the component speeds are still compa-
rable with the alternative references (although the directions of
the proper motions are even more complicated), for example the
−
μ
−
−
−
−
−
−
−
μ
−
μ
−
−
−
μ
−
μ
−
−
−
−
−
−
μ
Fig. 6.
Model-fit component kinematics during April 5–11.
Top panel
:
kinematics for all components. The center positions of di
ff
erent Gaus-
sian components, and their uncertainties are color-coded (see legend).
The Gaussian FWHM sizes are shown by dashed gray ellipses. The
black cross at (0,0) indicates the kinematic reference (C0-0). Red arrows
show the component motions; their lengths are proportional to the
apparent velocities.
Middle and bottom panel
: same as the top panel,
but zoomed in to the nuclear (C0) and extended jet regions (C1), respec-
tively. We note that the center (0,0) in all panels is chosen as the center
of C0-0, not the peak of total intensity.
C0 subcomponents moving toward the north (i.e., in the oppo-
site direction to the large-scale jet; see Figs. 7, top panel, and 3)
A69, page 6 of 21