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First M87 Event Horizon Telescope Results. I.
The Shadow of the Supermassive Black Hole
The Event Horizon Telescope Collaboration
(See the end matter for the full list of authors.)
Received 2019 March 1; revised 2019 March 12; accepted 2019 March 12; published 2019 April 10
Abstract
When surrounded by a transparent emission region, black holes are expected to reveal a dark shadow caused by
gravitational light bending and photon capture at the event horizon. To image and study this phenomenon, we have
assembled the Event Horizon Telescope, a global very long baseline interferometry array observing at a wavelength of
1.3 mm. This allows us to reconstruct event-horizon-scale images of the supermassive black hole candidate in the center
of the giant elliptical galaxy M87. We have resolved the central compact radio source as an asymmetric bright emission
ring with a diameter of 42±3μas, which is circular and encompasses a central depression in brightness with a flux
ratio 10:1. The emission ring is recovered using different calibration and imaging schemes, with its diameter and
width remaining stable over four different observations carried out in different days. Overall, the observed image is
consistent with expectations for the shadow of a Kerr black hole as predicted by general relativity. The asymmetry in
brightness in the ring can be explained in terms of relativistic beaming of the emission from a plasma rotating close to
the speed of light around a black hole. We compare our images to an extensive library of ray-traced general-relativistic
magnetohydrodynamic simulations of black holes and derive a central mass of M=(6.5±0.7)×10
9
M
e
. Our radio-
wave observations thus provide powerful evidence for the presence of supermassive black holes in centers of galaxies
and as the central engines of active galactic nuclei. They also present a new tool to explore gravity in its most extreme
limit and on a mass scale that was so far not accessible.
Key words: accretion, accretion disks –black hole physics –galaxies: active –galaxies: individual (M87)–
galaxies: jets –gravitation
1. Introduction
Black holes are a fundamental prediction of the theory of
general relativity (GR; Einstein 1915).Adefining feature of
black holes is their event horizon, a one-way causal boundary in
spacetime from which not even light can escape (Schwarzschild
1916). The production of black holes is generic in GR (Penrose
1965), and more than a century after Schwarzschild, they remain
at the heart of fundamental questions in unifying GR with
quantum physics (Hawking 1976; Giddings 2017).
Black holes are common in astrophysics and are found over
a wide range of masses. Evidence for stellar-mass black holes
comes from X-ray (Webster & Murdin 1972; Remillard &
McClintock 2006)and gravitational-wave measurements
(Abbott et al. 2016). Supermassive black holes, with masses
from millions to tens of billions of solar masses, are thought to
exist in the centers of nearly all galaxies(Lynden-Bell 1969;
Kormendy & Richstone 1995; Miyoshi et al. 1995), including
in the Galactic center (Eckart & Genzel 1997; Ghez et al. 1998;
Gravity Collaboration et al. 2018a)and in the nucleus of the
nearby elliptical galaxy M87 (Gebhardt et al. 2011; Walsh et al.
2013).
Active galactic nuclei (AGNs)are central bright regions that
can outshine the entire stellar population of their host galaxy.
Some of these objects, quasars, are the most luminous steady
sources in the universe (Schmidt 1963; Sanders et al. 1989)and
are thought to be powered by supermassive black holes
accreting matter at very high rates through a geometrically thin,
optically thick accretion disk (Shakura & Sunyaev 1973; Sun &
Malkan 1989). In contrast, most AGNs in the local universe,
including the Galactic center and M87, are associated with
supermassive black holes fed by hot, tenuous accretion flows
with much lower accretion rates (Ichimaru 1977; Narayan & Yi
1995; Blandford & Begelman 1999; Yuan & Narayan 2014).
In many AGNs, collimated relativistic plasma jets (Bridle &
Perley 1984; Zensus 1997)launched by the central black hole
contribute to the observed emission. These jets may be
powered either by magnetic fields threading the event horizon,
extracting the rotational energy from the black hole (Blandford
& Znajek 1977), or from the accretion flow (Blandford &
Payne 1982). The near-horizon emission from low-luminosity
active galactic nuclei (LLAGNs; Ho 1999)is produced by
synchrotron radiation that peaks from the radio through the far-
infrared. This emission may be produced either in the accretion
flow (Narayan et al. 1995), the jet (Falcke et al. 1993), or both
(Yuan et al. 2002).
When viewed from infinity, a nonrotating Schwarzschild
(1916)black hole has a photon capture radius
R
r27
cg
=,
where
r
GM c
g2
º
is the characteristic lengthscale of a black
hole. The photon capture radius is larger than the Schwarzschild
radius R
S
that marks the event horizon of a nonrotating black
hole, R
S
≡2r
g
. Photons approaching the black hole with an
impact parameter b<R
c
are captured and plunge into the black
hole (Hilbert 1917);photonswithb>R
c
escape to infinity;
photons with b=R
c
are captured on an unstable circular orbit
and produce what is commonly referred to as the lensed “photon
ring.”In the Kerr (1963)metric, which describes black holes
with spin angular momentum, R
c
changes with the ray’s
orientation relative to the angular-momentum vector, and
the black hole’s cross section is not necessarily circular
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 https://doi.org/10.3847/2041-8213/ab0ec7
© 2019. The American Astronomical Society.
Original content from this work may be used under the terms
of the Creative Commons Attribution 3.0 licence. Any further
distribution of this work must maintain attribution to the author(s)and the title
of the work, journal citation and DOI.
1
(Bardeen 1973). This change is small (4%), but potentially
detectable (Takahashi 2004;Johannsen&Psaltis2010).
The simulations of Luminet (1979)showed that for a black
hole embedded in a geometrically thin, optically thick accretion
disk, the photon capture radius would appear to a distant
observer as a thin emission ring inside a lensed image of the
accretion disk. For accreting black holes embedded in a
geometrically thick, optically thin emission region, as in
LLAGNs, the combination of an event horizon and light
bending leads to the appearance of a dark “shadow”together
with a bright emission ring that should be detectable through
very long baseline interferometery (VLBI)experiments (Falcke
et al. 2000a). Its shape can appear as a “crescent”because of
fast rotation and relativistic beaming (Falcke et al. 2000b;
Bromley et al. 2001; Noble et al. 2007; Broderick & Loeb
2009; Kamruddin & Dexter 2013; Lu et al. 2014).
The observed projected diameter of the emission ring, which
contains radiation primarily from the gravitationally lensed
photon ring, is proportional to R
c
and hence to the mass of the
black hole, but also depends nontrivially on a number of
factors: the observing resolution, the spin vector of the black
hole and its inclination, as well as the size and structure of the
emitting region. These factors are typically of order unity and
can be calibrated using theoretical models.
Modern general-relativistic simulations of accretion flows
and radiative transfer produce realistic images of black hole
shadows and crescents for a wide range of near-horizon
emission models (Broderick & Loeb 2006;Mościbrodzka et al.
2009; Dexter et al. 2012; Dibi et al. 2012; Chan et al. 2015;
Mościbrodzka et al. 2016; Porth et al. 2017; Chael et al. 2018a;
Ryan et al. 2018; Davelaar et al. 2019). These images can be
used to test basic properties of black holes as predicted in GR
(Johannsen & Psaltis 2010; Broderick et al. 2014; Psaltis et al.
2015), or in alternative theories of gravity (Grenzebach et al.
2014; Younsi et al. 2016; Mizuno et al. 2018). They can also be
used to test alternatives to black holes (Bambi & Freese 2009;
Vincent et al. 2016; Olivares et al. 2019).
VLBI at an observing wavelength of 1.3 mm (230 GHz)with
Earth-diameter-scale baselines is required to resolve the shadows of
thecoreofM87(M87
*
hereafter)and of the Galactic center of
Sagittarius A
*
(Sgr A
*
, Balick & Brown 1974), the two super-
massive black holes with the largest apparent angular sizes
(Johannsen et al. 2012). At 1.3 mm and shorter wavelengths, Earth-
diameter VLBI baselines achieve an angular resolution sufficient to
resolve the shadow of both sources, while the spectra of both
sources become optically thin, thus revealing the structure of the
innermost emission region. Early pathfinder experiments (Padin
et al. 1990; Krichbaum et al. 1998)demonstrated the feasibility of
VLBI techniques at ∼1.3 mm wavelengths. Over the following
decade, a program to improve sensitivity of 1.3 mm-VLBI through
development of broadband instrumentation led to the detection of
event-horizon-scale structures in both Sgr A
*
and M87
*
(Doeleman
et al. 2008,2012). Building on these observations, the Event
Horizon Telescope (EHT)collaboration was established to
assemble a global VLBI array operating at a wavelength of
1.3 mm with the required angular resolution, sensitivity, and
baseline coverage to image the shadows in M87
*
and Sgr A
*
.
In this paper, we present and discuss the first event-horizon-
scale images of the supermassive black hole candidate M87
*
from an EHT VLBI campaign conducted in 2017 April at a
wavelength of 1.3 mm. The accompanying papers give a more
extensive description of the instrument (EHT Collaboration
et al. 2019a, Paper II), data reduction (EHT Collaoration et al.
2019b, hereafter Paper III), imaging of the M87 shadow (EHT
Collaboration et al. 2019c, hereafter Paper IV), theoretical
models (EHT Collaboration et al. 2019d, hereafter Paper V),
and the black hole mass estimate (EHT Collaboration et al.
2019e, hereafter Paper VI).
2. The Radio Core in M87
In Curtis (1918), Heber Curtis detected a linear feature in
M87, later called a “jet”by Baade & Minkowski (1954). The
jet is seen as a bright radio source, VirgoA or 3C 274 (Bolton
et al. 1949; Kassim et al. 1993; Owen et al. 2000), which
extends out to 65 kpc with an age estimated at about 40 Myr
and a kinetic power of about 10
42
to 10
45
erg s
−1
(de Gasperin
et al. 2012; Broderick et al. 2015). It is also well studied in the
optical (Biretta et al. 1999; Perlman et al. 2011), X-ray
(Marshall et al. 2002), and gamma-ray bands (Abramowski
et al. 2012). The upstream end of the jet is marked by a
compact radio source (Cohen et al. 1969). Such compact radio
sources are ubiquitous in LLAGNs (Wrobel & Heeschen 1984;
Nagar et al. 2005)and are believed to be signatures of
supermassive black holes.
The radio structures of the large-scale jet (Owen et al. 1989;
de Gasperin et al. 2012)and of the core of M87 (Reid et al.
1989; Junor et al. 1999; Hada et al. 2016; Mertens et al. 2016;
Kim et al. 2018b; Walker et al. 2018)have been resolved in
great detail and at multiple wavelengths. Furthermore, the
leveling-off of the “core-shift”effect (Blandford & Königl
1979), where the apparent position of the radio core shifts in
the upstream jet direction with decreasing wavelength from
increased transparency to synchrotron self-absorption, indicates
that at a wavelength of 1.3 mm M87
*
is coincident with the
supermassive black hole (Hada et al. 2011). The envelope of
the jet limb maintains a quasi-parabolic shape over a wide
range of distances from ∼10
5
r
g
down to ∼20 r
g
(Asada &
Nakamura 2012; Hada et al. 2013; Nakamura & Asada 2013;
Nakamura et al. 2018; Walker et al. 2018).
VLBI observations at 1.3 mm have revealed a diameter of the
emission region of ∼40 μas, which is comparable to the expected
horizon-scale structure (Doeleman et al. 2012; Akiyama et al.
2015). These observations, however, were not able to image the
black hole shadow due to limited baseline coverage.
Based on three recent stellar population measurements, we here
adopt a distance to M87 of 16.8±0.8 Mpc (Blakeslee et al. 2009;
Bird et al. 2010; Cantiello et al. 2018,seePaperVI). Using this
distance and the modeling of surface brightness and stellar velocity
dispersion at optical wavelengths (Gebhardt & Thomas 2009;
Gebhardt et al. 2011), we infer the mass of M87
*
to be
M6.2 10
0.6
1.1
9
=´
-
+M
e
(see Table 9 in Paper VI). On the other
hand, mass measurements modeling the kinematic structure of the
gas disk (Harms et al. 1994; Macchetto et al. 1997)yield
M3.5 10
0.3
0.9 9
=´
-
+M
e
(Walsh et al. 2013, Paper VI).Thesetwo
mass estimates, from stellar and gas dynamics, predict a theoretical
shadow diameter for a Schwarzschild black hole of
3
7.6 as
3.5
6.2 m
-
+
and
2
1.3 as
1.7
5m
-
+, respectively.
3. The Event Horizon Telescope
The EHT (Paper II)is a VLBI experiment that directly
measures “visibilities,”or Fourier components, of the radio
brightness distribution on the sky. As the Earth rotates, each
telescope pair in the network samples many spatial frequencies.
2
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
The array has a nominal angular resolution of λ/L,whereλis the
observing wavelength and Lis the maximum projected baseline
length between telescopes in the array (Thompson et al. 2017).In
this way, VLBI creates a virtual telescope that spans nearly the
full diameter of the Earth.
To measure interferometric visibilities, the widely separated
telescopes simultaneously sample and coherently record the
radiation field from the source. Synchronization using the
Global Positioning System typically achieves temporal align-
ment of these recordings within tens of nanoseconds. Each
station is equipped with a hydrogen maser frequency standard.
With the atmospheric conditions during our observations the
coherent integration time was typically 10 s (see Figure 2 in
Paper II). Use of hydrogen maser frequency standards at all
EHT sites ensures coherence across the array over this
timescale. After observations, recordings are staged at a central
location, aligned in time, and signals from each telescope-pair
are cross-correlated.
While VLBI is well established at centimeter and millimeter
wavelengths (Boccardi et al. 2017;Thompsonetal.2017)and
can be used to study the immediate environments of black holes
(Krichbaum et al. 1993;Doelemanetal.2001), the extension of
VLBI to a wavelength of 1.3 mm has required long-term
technical developments. Challenges at shorter wavelengths
include increased noise in radio receiver electronics, higher
atmospheric opacity, increased phase fluctuations caused by
atmospheric turbulence, and decreased efficiency and size of
radio telescopes in the millimeter and submillimeter observing
bands. Started in 2009 (Doeleman et al. 2009a),theEHTbegan
a program to address these challenges by increasing array
sensitivity. Development and deployment of broadband VLBI
systems (Whitney et al. 2013; Vertatschitsch et al. 2015)led to
data recording rates that now exceed those of typical cm-VLBI
arrays by more than an order of magnitude. Parallel efforts to
support infrastructure upgrades at additional VLBI sites,
including the Atacama Large Millimeter/submillimeter Array
(ALMA; Matthews et al. 2018; Goddi et al. 2019)and the
Atacama Pathfinder Experiment telescope (APEX)in Chile
(Wagner et al. 2015), the Large Millimeter Telescope Alfonso
Serrano (LMT)in Mexico (Ortiz-León et al. 2016),theIRAM
30 m telescope on Pico Veleta (PV)in Spain (Greve et al. 1995),
the Submillimeter Telescope Observatory in Arizona (SMT;
Baars et al. 1999), the James Clerk Maxwell Telescope (JCMT)
and the Submillimeter Array (SMA)in Hawai’i(Doeleman et al.
2008; Primiani et al. 2016; Young et al. 2016), and the South
Pole Telescope (SPT)in Antarctica (Kim et al. 2018a), extended
the range of EHT baselines and coverage, and the overall
collecting area of the array. These developments increased the
sensitivity of the EHT by a factor of ∼30 over early experiments
that confirmed horizon-scale structures in M87
*
and Sgr A
*
(Doeleman et al. 2008,2012; Akiyama et al. 2015; Johnson et al.
2015;Fishetal.2016;Luetal.2018).
For the observations at a wavelength of 1.3 mm presented
here, the EHT collaboration fielded a global VLBI array of
eight stations over six geographical locations. Baseline lengths
ranged from 160 m to 10,700 km toward M87
*
, resulting in an
array with a theoretical diffraction-limit resolution of ∼25 μas
(see Figures 1and 2, and Paper II).
4. Observations, Correlation, and Calibration
We observed M87
*
on 2017 April 5, 6, 10, and 11 with the
EHT. Weather was uniformly good to excellent with nightly
median zenith atmospheric opacities at 230 GHz ranging from
0.03 to 0.28 over the different locations. The observations were
scheduled as a series of scans of three to seven minutes in
duration, with M87
*
scans interleaved with those on the quasar
3C 279. The number of scans obtained on M87
*
per night
ranged from 7 (April 10)to 25 (April 6)as a result of different
observing schedules. A description of the M87
*
observations,
their correlation, calibration, and validated final data products is
presented in Paper III and briefly summarized here.
At each station, the astronomical signal in both polarizations
and two adjacent 2 GHz wide frequency bands centered at
227.1 and 229.1 GHz were converted to baseband using
standard heterodyne techniques, then digitized and recorded
at atotal rate of 32 Gbps. Correlation of the data was carried
out using a software correlator (Deller et al. 2007)at the MIT
Haystack Observatory and at the Max-Planck-Institut für
Radioastronomie, each handling one of the two frequency
bands. Differences between the two independent correlators
were shown to be negligible through the exchange of a few
identical scans for cross comparison. At correlation, signals
were aligned to a common time reference using an apriori
Earth geometry and clock model.
A subsequent fringe-fitting step identified detections in
correlated signal power while phase calibrating the data for
residual delays and atmospheric effects. Using ALMA as a highly
sensitive reference station enabled critical corrections for iono-
spheric and tropospheric distortions at the other sites. Fringe
fitting was performed with three independent automated pipelines,
each tailored to the specific characteristics of the EHT
observations, such as the wide bandwidth, susceptibility to
atmospheric turbulence, and array heterogeneity (Blackburn et al.
2019; Janssen et al. 2019, Paper III). The pipelines made use of
standard software for the processing of radio-interferometric data
Figure 1. Eight stations of the EHT 2017 campaign over six geographic
locations as viewed from the equatorial plane. Solid baselines represent mutual
visibility on M87
*
(+12°declination). The dashed baselines were used for the
calibration source 3C279 (see Papers III and IV).
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The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
(Greisen 2003; Whitney et al. 2004;McMullinetal.2007,I.M.
van Bemmel et al. 2019, in preparation).
Data from the fringe-fitting pipelines were scaled from
correlation coefficients to a uniform physical flux density scale
(in Jansky)by using an independent apriori estimate of the
sensitivity of each telescope. The accuracies of the derived
station sensitivities were estimated to be 5%–10% in amplitude,
although certain uncharacterized losses (e.g., from poor
pointing or focus)can exceed the error budget. By assuming
total flux density values derived from ALMA interferometric
data (Goddi et al. 2019)and utilizing array redundancy via
network calibration (Paper III),werefined the absolute
amplitude calibration of telescopes that are colocated and have
redundant baselines, i.e., ALMA/APEX and JCMT/SMA.
The median scan-averaged signal-to-noise ratio for M87
*
was >10 on non-ALMA baselines and >100 on baselines to
ALMA, leading to small statistical errors in visibility amplitude
and phase. Comparisons between the three independent
pipelines, the two polarizations, and the two frequency bands
enabled estimation of systematic baseline errors of around 1°in
visibility phase and 2% for visibility amplitudes. These small
limiting errors remain after fitting station sensitivities and
unknown station phases via self-calibration (Pearson & Readhead
1984)and affect interferometric closure quantities (Rogers et al.
1974; Readhead et al. 1980). Following data validation and
pipeline comparisons, a single pipeline output was designated as
the primary data set of the firstEHTsciencedatareleaseandused
for subsequent results, while the outputs of the other two pipelines
offer supporting validation data sets.
The final calibrated complex visibilities V(u,v)correspond to
the Fourier components of the brightness distribution on the
sky at spatial frequency (u,v)determined by the projected
baseline expressed in units of the observing wavelength (van
Cittert 1934; Thompson et al. 2017). Figure 2shows the (u,v)
coverage and calibrated visibility amplitudes of M87
*
for
April11. The visibility amplitudes resemble those of a thin
ring (i.e., a Bessel function J
0
; see Figure 10.12 in Thompson
et al. 2017). Such a ring model with diameter 46 μas has afirst
null at 3.4 Gλ, matching the minimum in observed flux density
and is consistent with a reduced flux density on the longest
Hawai’i–Spain baseline (JCMT/SMA-PV)near 8 Gλ. This
particular ring model, shown with a dashed line in the bottom
panel of Figure 2, is only illustrative and does not fit all features
in the data. First, visibility amplitudes on the shortest VLBI
baselines suggest that about half of the compact flux density
seen on the ∼2 km ALMA–APEX baseline is resolved out by
the interferometer beam (Paper IV). Second, differences in the
depth of the first minimum as a function of orientation, as well
as highly nonzero measured closure phases, indicate some
degree of asymmetry in the source (Papers III,VI). Finally, the
visibility amplitudes represent only half of the information
available to us. We will next explore images and more complex
geometrical models that can fit the measured visibility
amplitudes and phases.
5. Images and Features
We reconstructed images from the calibrated EHT visibi-
lities, which provide results that are independent of models
(Paper IV). However, there are two major challenges in
reconstructing images from EHT data. First, EHT baselines
sample a limited range of spatial frequencies, corresponding to
angular scales between 25 and 160 μas. Because the (u,v)
plane is only sparsely sampled (Figure 2), the inverse problem
is under-constrained. Second, the measured visibilities lack
absolute phase calibration and can have large amplitude
calibration uncertainties.
To address these challenges, imaging algorithms incorporate
additional assumptions and constraints that are designed to produce
images that are physically plausible (e.g., positive and compact)or
conservative (e.g., smooth), while remaining consistent with the
data. We explored two classes of algorithms for reconstructing
images from EHT data. The first class of algorithms is the
traditional CLEAN approach used in radio interferometry (e.g.,
Högbom 1974;Clark1980).CLEAN is an inverse-modeling
approach that deconvolves the interferometer point-spread function
from the Fourier-transformed visibilities. When applying CLEAN,it
is necessary to iteratively self-calibrate the data between rounds of
imaging to solve for time-variable phase and amplitude errors in the
data. The second class of algorithms is the so-called regularized
Figure 2. Top: (u,v)coverage for M87
*
, aggregated over all four days of the
observations. (u,v)coordinates for each antenna pair are the source-projected
baseline length in units of the observing wavelength λand are given for
conjugate pairs. Baselines to ALMA/APEX and to JCMT/SMA are
redundant. Dotted circular lines indicate baseline lengths corresponding to
fringe spacings of 50 and 25 μas. Bottom:final calibrated visibility amplitudes
of M87
*
as a function of projected baseline length on April 11. Redundant
baselines to APEX and JCMT are plotted as diamonds. Error bars correspond
to thermal (statistical)uncertainties. The Fourier transform of an azimuthally
symmetric thin ring model with diameter 46 μas is also shown with a dashed
line for comparison.
4
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
maximum likelihood (RML; e.g., Narayan & Nityananda 1986;
Wiaux et al. 2009; Thiébaut 2013).RML is a forward-modeling
approach that searches for an image that is not only consistent with
the observed data but also favors specified image properties (e.g.,
smoothness or compactness).AswithCLEAN,RML methods
typically iterate between imaging and self-calibration, although
they can also be used to image directly on robust closure quantities
immune to station-based calibration errors. RML methods have been
extensively developed for the EHT (e.g., Honma et al. 2014;
Bouman et al. 2016; Akiyama et al. 2017; Chael et al. 2018b;see
also Paper IV).
Every imaging algorithm has a variety of free parameters
that can significantly affect the final image. We adopted a two-
stage imaging approach to control and evaluate biases in the
reconstructions from our choices of these parameters. In
the first stage, four teams worked independently to reconstruct
the first EHT images of M87
*
using an early engineering data
release. The teams worked without interaction to minimize
shared bias, yet each produced an image with a similar
prominent feature: a ring of diameter ∼38–44 μas with
enhanced brightness to the south (see Figure 4 in Paper IV).
In the second imaging stage, we developed three imaging
pipelines, each using a different software package and
associated methodology. Each pipeline surveyed a range of
imaging parameters, producing between ∼10
3
and 10
4
images
from different parameter combinations. We determined a “Top-
Set”of parameter combinations that both produced images of
M87
*
that were consistent with the observed data and that
reconstructed accurate images from synthetic data sets
corresponding to four known geometric models (ring, crescent,
filled disk, and asymmetric double source). For all pipelines,
the Top-Set images showed an asymmetric ring with a diameter
of ∼40 μas, with differences arising primarily in the effective
angular resolutions achieved by different methods.
For each pipeline, we determined the single combination of
fiducial imaging parameters out of the Top-Set that performed
best across all the synthetic data sets and for each associated
imaging methodology (seeFigure11inPaperIV). Because the
angular resolutions of the reconstructed images vary among the
pipelines, we blurred each image with a circular Gaussian to a
common, conservative angular resolution of 20 μas. The top part
of Figure 3shows an image of M87
*
on April11 obtained by
averaging the three pipelines’blurred fiducial images. The image
is dominated by a ring with an asymmetric azimuthal profile that
is oriented at a position angle ∼170°east of north. Although the
measured position angle increases by ∼20°between the first two
days and the last two days, the image features are broadly
consistent across the different imaging methods and across all
four observing days. This is shown in the bottom part of Figure 3,
which reports the images on different days (seealsoFigure15in
Paper IV). These results are also consistent with those obtained
from visibility-domain fitting of geometric and general-relativistic
magnetohydrodynamics (GRMHD)models (Paper VI).
6. Theoretical Modeling
The appearance of M87
*
has been modeled successfully using
GRMHD simulations, which describe a turbulent, hot, magnetized
disk orbiting a Kerr black hole. They naturally produce a powerful
jet and can explain the broadband spectral energy distribution
observed in LLAGNs. At a wavelength of 1.3 mm, and as
observed here, the simulations also predict a shadow and an
asymmetric emission ring. The latter does not necessarily coincide
with the innermost stable circular orbit, or ISCO, and is instead
related to the lensed photon ring. To explore this scenario in great
detail, we have built a library of synthetic images (Image Library)
describing magnetized accretion flows onto black holes in GR
145
(Paper V). The images themselves are produced from a library
of simulations (Simulation Library)collecting the results of
four codes solving the equations of GRMHD (Gammie et al.
2003;Sa̧dowski et al. 2014; Porth et al. 2017; Liska et al.
2018). The elements of the Simulation Library have been
coupled to three different general-relativistic ray-tracing and
radiative-transfer codes (GRRT, Bronzwaer et al. 2018;
Mościbrodzka & Gammie 2018; Z. Younsi et al. 2019, in
preparation). We limit ourselves to providing here a brief
description of the initial setups and the physical scenarios
explored in the simulations; see Paper Vfor details on both the
GRMHD and GRRT codes, which have been cross-validated
Figure 3. Top: EHT image of M87
*
from observations on 2017 April 11 as a
representative example of the images collected in the 2017 campaign. The
image is the average of three different imaging methods after convolving each
with a circular Gaussian kernel to give matched resolutions. The largest of the
three kernels (20 μas FWHM)is shown in the lower right. The image is shown
in units of brightness temperature, TS k2
b2B
l=
W
, where Sis the flux density,
λis the observing wavelength, k
B
is the Boltzmann constant, and Ωis the solid
angle of the resolution element. Bottom: similar images taken over different
days showing the stability of the basic image structure and the equivalence
among different days. North is up and east is to the left.
145
More exotic spacetimes, such as dilaton black holes, boson stars, and
gravastars, have also been considered (Paper V).
5
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
for accuracy and consistency (Gold et al. 2019; Porth et al.
2019).
A typical GRMHD simulation in the library is characterized by
two parameters: the dimensionless spin
a
Jc GM 2
*º,whereJ
and Mare, respectively, the spin angular momentum and mass of
the black hole, and the net dimensionless magnetic flux over the
event horizon MRg
212
f
ºF (˙),whereΦand M
˙are the magnetic
flux and mass flux (or accretion rate)across the horizon,
respectively. Since the GRMHD simulations scale with the black
hole mass, Mis set only at the time of producing the synthetic
images with the GRRT codes. The magnetic flux is generally
nonzero because magnetic field is trapped in the black hole by the
accretion flow and sustained by currents in the surrounding plasma.
These two parameters allow us to describe accretion disks
that are either prograde (a
*
0)or retrograde (a
*
<0)with
respect to the black hole spin axis, and whose accretion
flows are either “SANE”(from “Standard and Normal
Evolution,”Narayan et al. 2012)with f∼1, or “MAD”(from
“Magnetically Arrested Disk,”Narayan et al. 2003)with
f∼15.
146
In essence, SANE accretion flows are characterized
by moderate dimensionless magnetic flux and result from initial
magnetic fields that are smaller than those in MAD flows.
Furthermore, the opening angles of the magnetic funnel in
SANE flows are generically smaller than those in MAD flows.
Varying a
*
and f, we have performed 43 high-resolution,
three-dimensional and long-term simulations covering well the
physical properties of magnetized accretion flows onto Kerr
black holes.
All GRMHD simulations were initialized with a weakly
magnetized torus orbiting around the black hole and driven into
a turbulent state by instabilities, including the magnetorotational
instability (Balbus & Hawley 1991), rapidly reaching a quasi-
stationary state. Once a simulation was completed, the relevant
flow properties at different times are collected to be employed
for the further post-processing of the GRRT codes. The
generation of synthetic images requires, besides the properties
of the fluid (magnetic field, velocity field, and rest-mass density),
also the emission and absorption coefficients, the inclination i
(the angle between the accretion-flow angular-momentum vector
and the line of sight), the position angle PA (the angle east of
north, i.e., counter-clockwise on our images, of the projection on
the sky of the accretion-flow angular momentum), the black hole
mass Mand distance Dto the observer.
Because the photons at 1.3 mm wavelength observed by the
EHT are believed to be produced by synchrotron emission,
whose absorption and emission coefficients depend on the
electron distribution function, we consider the plasma to be
composed of electrons and ions that have the same temperature
in the magnetically dominated regions of the flow (funnel),but
have a substantially different temperature in the gas dominated
regions (disk midplane). In particular, we consider the plasma to
be composed of nonrelativistic ions with temperature T
i
and
relativistic electrons with temperature T
e
. A simple prescription
for the ratio of the temperatures of the two species can then be
imposed in terms of a single parameter (Mościbrodzka et al.
2016), such that the bulk of the emission comes either from
weakly magnetized (small R
high
,Te ;Ti/R
high
)or strongly
magnetized (large R
high
,Te ;Ti)regions. In SANE models, the
disk (jet)is weakly (strongly)magnetized, so that low (high)
R
high
models produce most of the emission in the disk (jet).In
MAD models, there are strongly magnetized regions everywhere
and the emission is mostly from the disk midplane. While this
prescription is not the only one possible, it has the advantage of
being simple, sufficiently generic, and robust (see Paper Vfor a
discussion of nonthermal particles and radiative cooling).
Since each GRMHD simulation can be used to describe several
different physical scenarios by changing the prescribed electron
distribution function, we have used the Simulation Library to
generate more than 420 different physical scenarios. Each scenario
is then used to generate hundreds of snapshots at different times in
the simulation leading to more than 62,000 objects in the Image
Library. From the images we have created model visibilities that
correspond to the EHT observing schedule and compared them to
the measured VLBI visibilities as detailed in Paper VI.
As an example, the top row of Figure 4shows three GRMHD
model snapshots from the Image Library with different spins and
flow type, which fitted closure phases and amplitudes of the
April 11 data best. For these models we produced simulated
visibilities for the April 11 schedule and weather parameters and
calibrated them with a synthetic data generation and calibration
pipeline (Blecher et al. 2017; Janssen et al. 2019; Roelofs et al.
2019a). The simulated data were then imaged with the same
pipeline used for the observed images. The similarities between
the simulated images (bottom row of Figure 4)and the observed
images (Figure 3)are remarkable.
Overall, when combining all the information contained in
both the Simulation Library and Image Library, the physical
origin of the emission features of the image observed in M87
*
can be summarized as follows.
First, the observed image is consistent with the hypothesis
that it is produced by a magnetized accretion flow orbiting
within a few r
g
of the event horizon of a Kerr black hole. The
asymmetric ring is produced by a combination of strong
gravitational lensing and relativistic beaming, while the central
flux depression is the observational signature of the black hole
shadow. Interestingly, all of the accretion models are consistent
with the EHT image, except for the a
*
=−0.94 MAD models,
which fail to produce images that are sufficiently stable (i.e.,
the variance among snapshots is too large to be statistically
consistent with the observed image).
Second, the north–south asymmetry in the emission ring is
controlled by the black hole spin and can be used to deduce its
orientation. In corotating disk models (where the angular
momentum of the matter and of the black hole are aligned), the
funnel wall, or jet sheath, rotates with the disk and the black
hole; in counterrotating disk models, instead, the luminous
funnel wall rotates with the black hole but against the disk. The
north–south asymmetry is consistent with models in which the
black hole spin is pointing away from Earth and inconsistent
with models in which the spin points toward Earth.
Third, adopting an inclination of 17°between the approaching
jet and the line of sight (Walker et al. 2018), the west orientation
of the jet, and a corotating disk model, matter in the bottom part
of the image is moving toward the observer (clockwise rotation
as seen from Earth). This is consistent with the rotation of the
ionized gas on scales of 20 pc, i.e., 7000 r
g
(Ford et al. 1994;
Walsh et al. 2013)and with the inferred sense of rotation from
VLBI observations at 7 mm (Walker et al. 2018).
Finally, models with a
*
=0 are disfavored by the very
conservative observational requirement that the jet power be
P
jet
>10
42
erg s
−1
. Furthermore, in those models that produce a
sufficiently powerful jet, it is powered by extraction of black hole
146
We here use Heaviside units, where a factor of 4pis absorbed into the
definition of the magnetic field.
6
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
spin energy through mechanisms akin to the Blandford–Znajek
process.
7. Model Comparison and Parameter Estimation
In Paper VI, the black hole mass is derived from fitting to the
visibility data of geometric and GRMHD models, as well as
from measurements of the ring diameter in the image domain.
Our measurements remain consistent across methodologies,
algorithms, data representations, and observed data sets.
Motivated by the asymmetric emission ring structures seen in
the reconstructed images (Section 5)and the similar emission
structures seen in the images from GRMHD simulations
(Section 6), we developed a family of geometric crescent
models(see, e.g., Kamruddin & Dexter 2013)to compare directly
to the visibility data. We used two distinct Bayesian-inference
algorithms and demonstrate that such crescent models are
statistically preferred over other comparably complex geometric
models that we have explored. We find that the crescent models
provide fits to the data that are statistically comparable to those of
the reconstructed images presented in Section 5, allowing us to
determine the basic parameters of the crescents. The best-fit
models for the asymmetric emission ring have diameters of
43±0.9 μas and fractional widths relative to the diameter of
<0.5. The emission drops sharply interior to the asymmetric
emission ring with the central depression having a brightness
<10% of the average brightness in the ring.
The diameters of the geometric crescent models measure the
characteristic sizes of the emitting regions that surround the
shadows and not the sizes of the shadows themselves (see, e.g.,
Psaltis et al. 2015; Johannsen et al. 2016; Kuramochi et al.
2018, for potential biases).
We model the crescent angular diameter din terms of the
gravitational radius and distance, GM c
D
g2
q
º,asd=αθ
g
,
where αis a function of spin, inclination, and R
high
(α;9.6–10.4
corresponds to emission from the lensed photon ring only).We
calibrate αby fitting the geometric crescent models to a large
number of visibility data generated from the Image Library. We
can also fit the model visibilities generated from the Image Library
to the M87
*
data, which allows us to measure θ
g
directly.
However, such a procedure is complicated by the stochastic nature
of the emission in the accretion flow(see, e.g., Kim et al. 2016).
To account for this turbulent structure, we developed a formalism
and multiple algorithms that estimate the statistics of the stochastic
components using ensembles of images from individual GRMHD
simulations. We find that the visibility data are not inconsistent
with being a realization of many of the GRMHD simulations. We
conclude that the recovered model parameters are consistent
across algorithms.
Finally, we extract ring diameter, width, and shape directly
from reconstructed images (see Section 5). The results are
consistent with the parameter estimates from geometric
crescent models. Following the same GRMHD calibration
Figure 4. Top: three example models of some of the best-fitting snapshots from the image library of GRMHD simulations for April 11 corresponding to different spin
parameters and accretion flows. Bottom: the same theoretical models, processed through a VLBI simulation pipeline with the same schedule, telescope characteristics,
and weather parameters as in the April 11 run and imaged in the same way as Figure 3. Note that although the fit to the observations is equally good in the three cases,
they refer to radically different physical scenarios; this highlights that a single good fit does not imply that a model is preferred over others (see Paper V).
7
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
procedure, we infer values of θ
g
and αfor regularized
maximum likelihood and CLEAN reconstructed images.
Combining results from all methods, we measure emission
region diameters of 42±3μas, angular sizes of the gravita-
tional radius θ
g
=3.8±0.4 μas, and scaling factors in the
range α=10.7–11.5, with associated errors of ∼10%. For the
distance of 16.8±0.8 Mpc adopted here, the black hole mass
is M=(6.5±0.7)×10
9
M
e
; the systematic error refers to
the 68% confidence level and is much larger than the statistical
error of 0.2×10
9
M
e
. Moreover, by tracing the peak of the
emission in the ring we can determine the shape of the image
and obtain a ratio between major and minor axis of the ring that
is 4:3; this corresponds to a 10% deviation from circularity
in terms of root-mean-square distance from an average radius.
Table 1summarizes the measured parameters of the image
features and the inferred black hole properties based on data
from all bands and all days combined. The inferred black hole
mass strongly favors the measurement based on stellar
dynamics(Gebhardt et al. 2011). The size, asymmetry, bright-
ness contrast, and circularity of the reconstructed images and
geometric models, as well as the success of the GRMHD
simulations in describing the interferometric data, are consis-
tent with the EHT images of M87
*
being associated with
strongly lensed emission from the vicinity of a Kerr black hole.
8. Discussion
A number of elements reinforce the robustness of our image
and the conclusion that it is consistent with the shadow of a
black hole as predicted by GR. First, our analysis has used
multiple independent calibration and imaging techniques, as
well as four independent data sets taken on four different days
in two separate frequency bands. Second, the image structure
matches previous predictions well (Dexter et al. 2012;
Mościbrodzka et al. 2016)and is well reproduced by our
extensive modeling effort presented in Section 6. Third, because
our measurement of the black hole mass in M87
*
is not
inconsistent with all of the prior mass measurements, this allows
us to conclude that the null hypothesis of the Kerr metric
(Psaltis et al. 2015; Johannsen et al. 2016), namely, the
assumption that the black hole is described by the Kerr metric,
has not been violated. Fourth, the observed emission ring
reconstructed in our images is close to circular with an axial
ratio 4:3; similarly, the time average images from our
GRMHD simulations also show a circular shape. After
associating to the shape of the shadow a deviation from the
circularity—measured in terms of root-mean-square distance
from an average radius in the image—that is 10%, we can set
an initial limit of order four on relative deviations of the
quadrupole moment from the Kerr value (Johannsen & Psaltis
2010). Stated differently, if Qis the quadrupole moment of a
Kerr black hole and ΔQthe deviation as deduced from
circularity, our measurement—and the fact that the inclination
angle is assumed to be small—implies that ΔQ/Q4
(ΔQ/Q=εin Johannsen & Psaltis 2010).
Finally, when comparing the visibility amplitudes of M87
*
with 2009 and 2012 data(Doeleman et al. 2012; Akiyama et al.
2015), the overall radio core size at a wavelength of 1.3 mm
has not changed appreciably, despite variability in total flux
density. This stability is consistent with the expectation that the
size of the shadow is a feature tied to the mass of the black hole
and not to properties of a variable plasma flow.
It is also straightforward to reject some alternative astrophysical
interpretations. For instance, the image is unlikely to be produced
by a jet-feature as multi-epoch VLBI observations of the plasma
jet in M87 (Walker et al. 2018)on scales outside the horizon do
not show circular rings. The same is typically true for AGN jets in
large VLBI surveys (Lister et al. 2018). Similarly, were the
apparent ring a random alignment of emission blobs, they should
also have moved away at relativistic speeds, i.e., at ∼5μas day
−1
(Kim et al. 2018b), leading to measurable structural changes and
sizes. GRMHD models of hollow jet cones could show under
extreme conditions stable ring features (Pu et al. 2017), but this
effect is included to a certain extent in our Simulation Library for
models with R
high
>10.Finally,anEinsteinringformedby
gravitational lensing of a bright region in the counter-jet would
require a fine-tuned alignment and a size larger than that measured
in 2012 and 2009.
At the same time, it is more difficult to rule out alternatives
to black holes in GR, because a shadow can be produced by
any compact object with a spacetime characterized by unstable
circular photon orbits(Mizuno et al. 2018). Indeed, while the
Kerr metric remains a solution in some alternative theories of
gravity (Barausse & Sotiriou 2008; Psaltis et al. 2008), non-
Kerr black hole solutions do exist in a variety of such modified
theories (Berti et al. 2015). Furthermore, exotic alternatives to
black holes, such as naked singularities(Shaikh et al. 2019),
boson stars (Kaup 1968; Liebling & Palenzuela 2012), and
gravastars (Mazur & Mottola 2004; Chirenti & Rezzolla 2007),
are admissible solutions within GR and provide concrete, albeit
contrived, models. Some of such exotic compact objects can
already be shown to be incompatible with our observations
given our maximum mass prior. For example, the shadows of
naked singularities associated with Kerr spacetimes with
a1
*>
∣
∣are substantially smaller and very asymmetric
compared to those of Kerr black holes(Bambi & Freese 2009).
Also, some commonly used types of wormholes (Bambi 2013)
predict much smaller shadows than we have measured.
Table 1
Parameters of M87
*
Parameter Estimate
Ring diameter
a
d42±3μas
Ring width
a
20 asm
<
Crescent contrast
b
>10:1
Axial ratio
a
<4:3
Orientation PA 150°–200°east of north
GM Dc
g
2
q
=
c
3.8±0.4 μas
dg
aq=
d
1
10.3
0.5
-
+
M
c
(6.5±0.7)×10
9
M
e
Parameter Prior Estimate
D
e
(16.8±0.8)Mpc
M(stars)
e
6.2 10
0.6
1.1 9
´
-
+M
e
M(gas)
e
3
.5 10
0.3
0.9 9
´
-
+M
e
Notes.
a
Derived from the image domain.
b
Derived from crescent model fitting.
c
The mass and systematic errors are averages of the three methods (geometric
models, GRMHD models, and image domain ring extraction).
d
The exact value depends on the method used to extract d, which is reflected
in the range given.
e
Rederived from likelihood distributions (Paper VI).
8
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
However, other compact-object candidates need to be analyzed
with more care. Boson stars are an example of compact objects
having circular photon orbits but without a surface or an event
horizon. In such a spacetime, null geodesics are redirected
outwards toward distant observers (Cunha et al. 2016),sothatthe
shadow can in principle be filled with emission from lensed
images of distant radio sources generating a complex mirror
image of the sky. More importantly, accretion flows onto boson
stars behave differently as they do not produce jets but stalled
accretion tori that make them distinguishable from black holes
(Olivares et al. 2019). Gravastars provide examples of compact
objects having unstable photon orbits and a hard surface, but not
an event horizon. In this case, while a single image of the
accretion flow could in principle be very similar to that coming
from a black hole, differences of the flow dynamics at the stellar
surface (H. Olivares et al. 2019, in preparation), strong magnetic
fields (Lobanov 2017), or excess radiation in the infrared
(Broderick & Narayan 2006)would allow one to distinguish a
gravastar from a black hole.
Altogether, the results derived here provide a new way to
study compact-object spacetimes and are complementary to the
detection of gravitational waves from coalescing stellar-mass
black holes with LIGO/Virgo (Abbott et al. 2016). Our
constraints on deviations from the Kerr geometry rely only on
the validity of the equivalence principle and are agnostic about
the underlying theory of gravity, but can be used to measure,
with ever improved precision, the parameters of the back-
ground metric. On the other hand, current gravitational-wave
observations of mergers probe the dynamics of the underlying
theory, but cannot rely on the possibility of multiple and
repeated measurements of the same source.
To underline the complementarity of gravitational-wave and
electromagnetic observations of black holes, we note that a
basic feature of black holes in GR is that their size scales
linearly with mass. Combining our constraints on the super-
massive black hole in M87 with those on the stellar-mass black
holes detected via gravitational waves we can infer that this
property holds over eight orders of magnitude. While this
invariance is a basic prediction of GR, which is a scale-free
theory, it need not be satisfied in other theories that introduce a
scale to the gravitational field.
Finally, the radio core in M87 is quite typical for powerful
radio jets in general. It falls on the fundamental plane of black
hole activity for radio cores (Falcke et al. 2004), connecting via
simple scaling laws the radio and X-ray properties of low-
luminosity black hole candidates across vastly different mass
and accretion rate scales. This suggests that they are powered
by a scale-invariant common object. Therefore, establishing the
black hole nature for M87
*
also supports the general paradigm
that black holes are the power source for active galaxies.
9. Conclusion and Outlook
We have assembled the EHT, a global VLBI array operating
at a wavelength of 1.3 mm and imaged horizon-scale structures
around the supermassive black hole candidate in M87. Using
multiple independent calibration, imaging, and analysis
methods, we find the image to be dominated by a ring
structure of 42±3μas diameter that is brighter in the south.
This structure has a central brightness depression with a
contrast of >10:1, which we identify with the black hole
shadow. Comparing the data with an extensive library of
synthetic images obtained from GRMHD simulations covering
different physical scenarios and plasma conditions reveals that
the basic features of our image are relatively independent of the
detailed astrophysical model. This allows us to derive an
estimate for the black hole mass of M=(6.5±0.7)×
10
9
M
e
. Based on our modeling and information on the
inclination angle, we derive the sense of rotation of the black
hole to be in the clockwise direction, i.e., the spin of the black
hole points away from us. The brightness excess in the south
part of the emission ring is explained as relativistic beaming of
material rotating in the clockwise direction as seen by the
observer, i.e., the bottom part of the emission region is moving
toward the observer.
Future observations and further analysis will test the
stability, shape, and depth of the shadow more accurately.
One of its key features is that it should remain largely constant
with time as the mass of M87
*
is not expected to change
measurably on human timescales. Polarimetric analysis of the
images, which we will report in the future, will provide
information on the accretion rate via Faraday rotation (Bower
et al. 2003; Marrone et al. 2007; Kuo et al. 2014;Mościbrodzka
et al. 2017)and on the magnetic flux. Higher-resolution images
can be achieved by going to a shorter wavelength, i.e., 0.8 mm
(345 GHz), by adding more telescopes and, in a more distant
future, with space-based interferometry (Kardashev et al. 2014;
Fish et al. 2019; Palumbo et al. 2019; F. Roelofs et al. 2019b,
in preparation).
Another primary EHT source, Sgr A
*
, has a precisely
measured mass three orders of magnitude smaller than that of
M87
*
, with dynamical timescales of minutes instead of days.
Observing the shadow of Sgr A
*
will require accounting for
this variability and mitigation of scattering effects caused by
the interstellar medium (Johnson 2016; Lu et al. 2016; Bouman
et al. 2018). Time dependent nonimaging analysis can be used
to potentially track the motion of emitting matter near the black
hole, as reported recently through interferometric observations
in the near-infrared (Gravity Collaboration et al. 2018b). Such
observations provide separate tests and probes of GR on yet
another mass scale (Broderick & Loeb 2005; Doeleman et al.
2009b; Roelofs et al. 2017; Medeiros et al. 2017).
In conclusion, we have shown that direct studies of the event
horizon shadow of supermassive black hole candidates are now
possible via electromagnetic waves, thus transforming this
elusive boundary from a mathematical concept to a physical
entity that can be studied and tested via repeated astronomical
observations.
The authors of this Letter thank the following organizations and
programs: the Academy of Finland (projects 274477, 284495,
312496); the Advanced European Network of E-infrastructures
for Astronomy with the SKA (AENEAS)project, supported by
the European Commission Framework Programme Horizon 2020
Research and Innovation action under grant agreement 731016;
the Alexander von Humboldt Stiftung; the Black Hole Initiative at
Harvard University, through a grant (60477)from the John
Templeton Foundation; the China Scholarship Council; Comisión
Nacional de Investigación Científica y Tecnológica (CONICYT,
Chile, via PIA ACT172033, Fondecyt 1171506, BASAL AFB-
170002, ALMA-conicyt 31140007); Consejo Nacional de Ciencia
y Tecnología (CONACYT, Mexico, projects 104497, 275201,
279006, 281692); the Delaney Family via the Delaney Family
John A. Wheeler Chair at Perimeter Institute; Dirección General
de Asuntos del Personal Académico-Universidad Nacional
9
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
Autónoma de México (DGAPA-UNAM, project IN112417);the
European Research Council (ERC)Synergy Grant “Black-
HoleCam: Imaging the Event Horizon of Black Holes”(grant
610058); the Generalitat Valenciana postdoctoral grant
APOSTD/2018/177; the Gordon and Betty Moore Foundation
(grants GBMF-3561, GBMF-5278); the Istituto Nazionale di
Fisica Nucleare (INFN)sezione di Napoli, iniziative specifiche
TEONGRAV; the International Max Planck Research School for
Astronomy and Astrophysics at the Universities of Bonn and
Cologne; the Jansky Fellowship program of the National Radio
Astronomy Observatory (NRAO); the Japanese Government
(Monbukagakusho: MEXT)Scholarship; the Japan Society for
the Promotion of Science (JSPS)Grant-in-Aid for JSPS Research
Fellowship (JP17J08829); JSPS Overseas Research Fellowships;
the Key Research Program of Frontier Sciences, Chinese
Academy of Sciences (CAS, grants QYZDJ-SSW-SLH057,
QYZDJ-SSW-SYS008); the Leverhulme Trust Early Career
Research Fellowship; the Max-Planck-Gesellschaft (MPG);the
Max Planck Partner Group of the MPG and the CAS; the
MEXT/JSPS KAKENHI (grants 18KK0090, JP18K13594,
JP18K03656, JP18H03721, 18K03709, 18H01245, 25120007);
the MIT International Science and Technology Initiatives
(MISTI)Funds; the Ministry of Science and Technology
(MOST)of Taiwan (105-2112-M-001-025-MY3, 106-2112-M-
001-011, 106-2119-M-001-027, 107-2119-M-001-017, 107-
2119-M-001-020, and 107-2119-M-110-005); the National
Aeronautics and Space Administration (NASA, Fermi Guest
Investigator grant 80NSSC17K0649); the National Institute of
Natural Sciences (NINS)of Japan; the National Key Research
and Development Program of China (grant 2016YFA0400704,
2016YFA0400702); the National Science Foundation (NSF,
grants AST-0096454, AST-0352953, AST-0521233, AST-
0705062, AST-0905844, AST-0922984, AST-1126433, AST-
1140030, DGE-1144085, AST-1207704, AST-1207730, AST-
1207752, MRI-1228509, OPP-1248097, AST-1310896, AST-
1312651, AST-1337663, AST-1440254, AST-1555365, AST-
1715061, AST-1615796, AST-1614868, AST-1716327, OISE-
1743747, AST-1816420); the Natural Science Foundation of
China (grants 11573051, 11633006, 11650110427, 10625314,
11721303, 11725312, 11873028, 11873073, U1531245,
11473010); the Natural Sciences and Engineering Research
Council of Canada (NSERC, including a Discovery Grant and
the NSERC Alexander Graham Bell Canada Graduate Scholar-
ships-Doctoral Program); the National Youth Thousand Talents
Program of China; the National Research Foundation of
Korea (grant 2015-R1D1A1A01056807, the Global PhD
Fellowship Grant: NRF-2015H1A2A1033752, and the Korea
Research Fellowship Program: NRF-2015H1D3A1066561);the
Netherlands Organization for Scientific Research (NWO)VICI
award (grant 639.043.513)and Spinoza Prize (SPI 78-409);the
New Scientific Frontiers with Precision Radio Interferometry
Fellowship awarded by the South African Radio Astronomy
Observatory (SARAO), which is a facility of the National
Research Foundation (NRF), an agency of the Department of
Science and Technology (DST)of South Africa; the Onsala
Space Observatory (OSO)national infrastructure, for the
provisioning of its facilities/observational support (OSO receives
funding through the Swedish Research Council under grant
2017-00648); the Perimeter Institute for Theoretical Physics
(research at Perimeter Institute is supported by the Government of
Canada through the Department of Innovation, Science and
Economic Development Canada and by the Province of Ontario
through the Ministry of Economic Development, Job Creation
and Trade); the Russian Science Foundation (grant 17-12-01029);
the Spanish Ministerio de Economía y Competitividad
(grants AYA2015-63939-C2-1-P, AYA2016-80889-P); the State
Agency for Research of the Spanish MCIU through the “Center
of Excellence Severo Ochoa”award for the Instituto de
Astrofísica de Andalucía (SEV-2017-0709); the Toray Science
Foundation; the US Department of Energy (USDOE)through the
Los Alamos National Laboratory (operated by Triad National
Security, LLC, for the National Nuclear Security Administration
of the USDOE (Contract 89233218CNA000001)); the Italian
Ministero dell’Istruzione Università e Ricerca through the grant
Progetti Premiali 2012-iALMA (CUP C52I13000140001);the
European Unionʼs Horizon 2020 research and innovation
programme under grant agreement No 730562 RadioNet; ALMA
North America Development Fund; Chandra TM6-17006X.
This work used the Extreme Science and Engineering
Discovery Environment (XSEDE), supported by NSF grant
ACI-1548562, and CyVerse, supported by NSF grants DBI-
0735191, DBI-1265383, and DBI-1743442. XSEDE Stampede2
resource at TACC was allocated through TG-AST170024 and
TG-AST080026N. XSEDE JetStream resource at PTI and TACC
was allocated through AST170028. The simulations were
performed in part on the SuperMUC cluster at the LRZ in
Garching, on the LOEWE cluster in CSC in Frankfurt, and on the
HazelHen cluster at the HLRS in Stuttgart. This research was
enabled in part by support provided by Compute Ontario (http://
computeontario.ca), Calcul Quebec (http://www.calculquebec.
ca)and Compute Canada (http://www.computecanada.ca).
We thank the staff at the participating observatories, correla-
tion centers, and institutions for their enthusiastic support.
This Letter makes use of the following ALMA data: ADS/
JAO.ALMA#2016.1.01154.V. ALMA is a partnership of the
European Southern Observatory (ESO; Europe, representing its
member states), NSF, and National Institutes of Natural
Sciences of Japan, together with National Research Council
(Canada), Ministry of Science and Technology (MOST;
Taiwan), Academia Sinica Institute of Astronomy and Astro-
physics (ASIAA; Taiwan), and Korea Astronomy and Space
Science Institute (KASI; Republic of Korea), in cooperation
with the Republic of Chile. The Joint ALMA Observatory is
operated by ESO, Associated Universities, Inc. (AUI)/NRAO,
and the National Astronomical Observatory of Japan (NAOJ).
The NRAO is a facility of the NSF operated under cooperative
agreement by AUI. APEX is a collaboration between the Max-
Planck-Institut für Radioastronomie (Germany), ESO, and the
Onsala Space Observatory (Sweden). The SMA is a joint
project between the SAO and ASIAA and is funded by the
Smithsonian Institution and the Academia Sinica. The JCMT is
operated by the East Asian Observatory on behalf of the NAOJ,
ASIAA, and KASI, as well as the Ministry of Finance of
China, Chinese Academy of Sciences, and the National Key
R&D Program (No. 2017YFA0402700)of China. Additional
funding support for the JCMT is provided by the Science and
Technologies Facility Council (UK)and participating uni-
versities in the UK and Canada. The LMT project is a joint
effort of the Instituto Nacional de Astrófisica, Óptica, y
Electrónica (Mexico)and the University of Massachusetts at
Amherst (USA). The IRAM 30-m telescope on Pico Veleta,
Spain is operated by IRAM and supported by CNRS (Centre
National de la Recherche Scientifique, France), MPG (Max-
10
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
Planck-Gesellschaft, Germany)and IGN (Instituto Geográfico
Nacional, Spain).
The SMT is operated by the Arizona Radio Observatory, a
part of the Steward Observatory of the University of Arizona,
with financial support of operations from the State of Arizona
and financial support for instrumentation development from the
NSF. Partial SPT support is provided by the NSF Physics
Frontier Center award (PHY-0114422)to the Kavli Institute of
Cosmological Physics at the University of Chicago (USA), the
Kavli Foundation, and the GBMF (GBMF-947). The SPT
hydrogen maser was provided on loan from the GLT, courtesy
of ASIAA. The SPT is supported by the National Science
Foundation through grant PLR-1248097. Partial support is also
provided by the NSF Physics Frontier Center grant PHY-
1125897 to the Kavli Institute of Cosmological Physics at the
University of Chicago, the Kavli Foundation and the Gordon
and Betty Moore Foundation grant GBMF 947.
The EHTC has received generous donations of FPGA chips
from Xilinx Inc., under the Xilinx University Program. The
EHTC has benefited from technology shared under open-
source license by the Collaboration for Astronomy Signal
Processing and Electronics Research (CASPER). The EHT
project is grateful to T4Science and Microsemi for their
assistance with Hydrogen Masers. This research has made use
of NASAʼs Astrophysics Data System. We gratefully acknowl-
edge the support provided by the extended staff of the ALMA,
both from the inception of the ALMA Phasing Project through
the observational campaigns of 2017 and 2018. We would like
to thank A. Deller and W. Brisken for EHT-specific support
with the use of DiFX. We acknowledge the significance that
Maunakea, where the SMA and JCMT EHT stations are
located, has for the indigenous Hawaiian people.
ORCID iDs
Kazunori Akiyama https://orcid.org/0000-0002-9475-4254
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Rebecca Azulay https://orcid.org/0000-0002-2200-5393
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Geoffrey B. Crew https://orcid.org/0000-0002-2079-3189
Yuzhu Cui https://orcid.org/0000-0001-6311-4345
Jordy Davelaar https://orcid.org/0000-0002-2685-2434
Mariafelicia De Laurentis https://orcid.org/0000-0002-
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Roger Deane https://orcid.org/0000-0003-1027-5043
Jessica Dempsey https://orcid.org/0000-0003-1269-9667
Gregory Desvignes https://orcid.org/0000-0003-3922-4055
Jason Dexter https://orcid.org/0000-0003-3903-0373
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Ralph P. Eatough https://orcid.org/0000-0001-6196-4135
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Peter Galison https://orcid.org/0000-0002-6429-3872
Charles F. Gammie https://orcid.org/0000-0001-7451-8935
Boris Georgiev https://orcid.org/0000-0002-3586-6424
Roman Gold https://orcid.org/0000-0003-2492-1966
Minfeng Gu (顾敏峰)https://orcid.org/0000-0002-4455-6946
Mark Gurwell https://orcid.org/0000-0003-0685-3621
Kazuhiro Hada https://orcid.org/0000-0001-6906-772X
Ronald Hesper https://orcid.org/0000-0003-1918-6098
Luis C. Ho (何子山)https://orcid.org/0000-0001-6947-5846
Mareki Honma https://orcid.org/0000-0003-4058-9000
Chih-Wei L. Huang https://orcid.org/0000-0001-5641-3953
Shiro Ikeda https://orcid.org/0000-0002-2462-1448
Sara Issaoun https://orcid.org/0000-0002-5297-921X
David J. James https://orcid.org/0000-0001-5160-4486
Michael Janssen https://orcid.org/0000-0001-8685-6544
Britton Jeter https://orcid.org/0000-0003-2847-1712
Wu Jiang (江悟)https://orcid.org/0000-0001-7369-3539
Michael D. Johnson https://orcid.org/0000-0002-4120-3029
Svetlana Jorstad https://orcid.org/0000-0001-6158-1708
Taehyun Jung https://orcid.org/0000-0001-7003-8643
Mansour Karami https://orcid.org/0000-0001-7387-9333
Ramesh Karuppusamy https://orcid.org/0000-0002-
5307-2919
Tomohisa Kawashima https://orcid.org/0000-0001-8527-0496
Garrett K. Keating https://orcid.org/0000-0002-3490-146X
Mark Kettenis https://orcid.org/0000-0002-6156-5617
Jae-Young Kim https://orcid.org/0000-0001-8229-7183
Junhan Kim https://orcid.org/0000-0002-4274-9373
Motoki Kino https://orcid.org/0000-0002-2709-7338
Jun Yi Koay https://orcid.org/0000-0002-7029-6658
Patrick M. Koch https://orcid.org/0000-0003-2777-5861
Shoko Koyama https://orcid.org/0000-0002-3723-3372
Michael Kramer https://orcid.org/0000-0002-4175-2271
Carsten Kramer https://orcid.org/0000-0002-4908-4925
Thomas P. Krichbaum https://orcid.org/0000-0002-
4892-9586
Tod R. Lauer https://orcid.org/0000-0003-3234-7247
Sang-Sung Lee https://orcid.org/0000-0002-6269-594X
Yan-Rong Li (李彦荣)https://orcid.org/0000-0001-5841-9179
Zhiyuan Li (李志远)https://orcid.org/0000-0003-0355-6437
Michael Lindqvist https://orcid.org/0000-0002-3669-0715
Kuo Liu https://orcid.org/0000-0002-2953-7376
Elisabetta Liuzzo https://orcid.org/0000-0003-0995-5201
Laurent Loinard https://orcid.org/0000-0002-5635-3345
Ru-Sen Lu (路如森)https://orcid.org/0000-0002-7692-7967
Nicholas R. MacDonald https://orcid.org/0000-0002-
6684-8691
Jirong Mao (毛基荣)https://orcid.org/0000-0002-7077-7195
Sera Markoff https://orcid.org/0000-0001-9564-0876
Daniel P. Marrone https://orcid.org/0000-0002-2367-1080
11
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
Alan P. Marscher https://orcid.org/0000-0001-7396-3332
Iván Martí-Vidal https://orcid.org/0000-0003-3708-9611
Lynn D. Matthews https://orcid.org/0000-0002-3728-8082
Lia Medeiros https://orcid.org/0000-0003-2342-6728
Karl M. Menten https://orcid.org/0000-0001-6459-0669
Yosuke Mizuno https://orcid.org/0000-0002-8131-6730
Izumi Mizuno https://orcid.org/0000-0002-7210-6264
James M. Moran https://orcid.org/0000-0002-3882-4414
Kotaro Moriyama https://orcid.org/0000-0003-1364-3761
Monika Moscibrodzka https://orcid.org/0000-0002-
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Cornelia Müller https://orcid.org/0000-0002-2739-2994
Hiroshi Nagai https://orcid.org/0000-0003-0292-3645
Neil M. Nagar https://orcid.org/0000-0001-6920-662X
Masanori Nakamura https://orcid.org/0000-0001-
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Ramesh Narayan https://orcid.org/0000-0002-1919-2730
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Aristeidis Noutsos https://orcid.org/0000-0002-4151-3860
Héctor Olivares https://orcid.org/0000-0001-6833-7580
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Daniel C. M. Palumbo https://orcid.org/0000-0002-
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Ue-Li Pen https://orcid.org/0000-0003-2155-9578
Dominic W. Pesce https://orcid.org/0000-0002-5278-9221
Oliver Porth https://orcid.org/0000-0002-4584-2557
Ben Prather https://orcid.org/0000-0002-0393-7734
Jorge A. Preciado-López https://orcid.org/0000-0002-
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Hung-Yi Pu https://orcid.org/0000-0001-9270-8812
Venkatessh Ramakrishnan https://orcid.org/0000-0002-
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Ramprasad Rao https://orcid.org/0000-0002-1407-7944
Alexander W. Raymond https://orcid.org/0000-0002-
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Luciano Rezzolla https://orcid.org/0000-0002-1330-7103
Bart Ripperda https://orcid.org/0000-0002-7301-3908
Freek Roelofs https://orcid.org/0000-0001-5461-3687
Eduardo Ros https://orcid.org/0000-0001-9503-4892
Mel Rose https://orcid.org/0000-0002-2016-8746
Alan L. Roy https://orcid.org/0000-0002-1931-0135
Chet Ruszczyk https://orcid.org/0000-0001-7278-9707
Benjamin R. Ryan https://orcid.org/0000-0001-8939-4461
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David Sánchez-Arguelles https://orcid.org/0000-0002-
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Tuomas Savolainen https://orcid.org/0000-0001-6214-1085
Lijing Shao https://orcid.org/0000-0002-1334-8853
Zhiqiang Shen (沈志强)https://orcid.org/0000-0003-3540-
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Des Small https://orcid.org/0000-0003-3723-5404
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André Young https://orcid.org/0000-0003-0000-2682
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The Event Horizon Telescope Collaboration,
Kazunori Akiyama
1,2,3,4
, Antxon Alberdi
5
, Walter Alef
6
, Keiichi Asada
7
, Rebecca Azulay
8,9,6
, Anne-Kathrin Baczko
6
,
David Ball
10
, Mislav Baloković
4,11
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2
, Dan Bintley
12
, Lindy Blackburn
4,11
, Wilfred Boland
13
,
Katherine L. Bouman
4,11,14
, Geoffrey C. Bower
15
, Michael Bremer
16
, Christiaan D. Brinkerink
17
, Roger Brissenden
4,11
,
Silke Britzen
6
, Avery E. Broderick
18,19,20
, Dominique Broguiere
16
, Thomas Bronzwaer
17
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21,22
,
John E. Carlstrom
23,24,25,26
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28
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29
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Ming-Tang Chen
15
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30,31
, Ilje Cho
21,22
, Pierre Christian
10,11
, John E. Conway
32
, James M. Cordes
28
,
Geoffrey B. Crew
2
, Yuzhu Cui
33,34
, Jordy Davelaar
17
, Mariafelicia De Laurentis
35,36,37
, Roger Deane
38,39
,
Jessica Dempsey
12
, Gregory Desvignes
6
, Jason Dexter
40
, Sheperd S. Doeleman
4,11
, Ralph P. Eatough
6
,
Heino Falcke
17
, Vincent L. Fish
2
, Ed Fomalont
1
, Raquel Fraga-Encinas
17
, William T. Freeman
41,42
, Per Friberg
12
,
Christian M. Fromm
36
, José L. Gómez
5
, Peter Galison
4,43,44
, Charles F. Gammie
45,46
, Roberto García
16
, Olivier Gentaz
16
,
Boris Georgiev
19,20
, Ciriaco Goddi
17,47
, Roman Gold
36
, Minfeng Gu (顾敏峰)
30,48
, Mark Gurwell
11
,
Kazuhiro Hada
33,34
, Michael H. Hecht
2
, Ronald Hesper
49
, Luis C. Ho (何子山)
50,51
, Paul Ho
7
, Mareki Honma
33,34
,
Chih-Wei L. Huang
7
, Lei Huang (黄磊)
30,48
, David H. Hughes
52
, Shiro Ikeda
3,53,54,55
, Makoto Inoue
7
, Sara Issaoun
17
,
14
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
David J. James
4,11
, Buell T. Jannuzi
10
, Michael Janssen
17
, Britton Jeter
19,20
, Wu Jiang (江悟)
30
,
Michael D. Johnson
4,11
, Svetlana Jorstad
56,57
, Taehyun Jung
21,22
, Mansour Karami
18,19
, Ramesh Karuppusamy
6
,
Tomohisa Kawashima
3
, Garrett K. Keating
11
, Mark Kettenis
58
, Jae-Young Kim
6
, Junhan Kim
10
, Jongsoo Kim
21
,
Motoki Kino
3,59
, Jun Yi Koay
7
, Patrick M. Koch
7
, Shoko Koyama
7
, Michael Kramer
6
, Carsten Kramer
16
,
Thomas P. Krichbaum
6
, Cheng-Yu Kuo
60
, Tod R. Lauer
61
, Sang-Sung Lee
21
, Yan-Rong Li (李彦荣)
62
,
Zhiyuan Li (李志远)
63,64
, Michael Lindqvist
32
, Kuo Liu
6
, Elisabetta Liuzzo
65
, Wen-Ping Lo
7,66
, Andrei P. Lobanov
6
,
Laurent Loinard
67,68
, Colin Lonsdale
2
, Ru-Sen Lu (路如森)
30,6
, Nicholas R. MacDonald
6
, Jirong Mao (毛基荣)
69,70,71
,
Sera Markoff
29,72
, Daniel P. Marrone
10
, Alan P. Marscher
56
, Iván Martí-Vidal
32,73
, Satoki Matsushita
7
,
Lynn D. Matthews
2
, Lia Medeiros
10,74
, Karl M. Menten
6
, Yosuke Mizuno
36
, Izumi Mizuno
12
, James M. Moran
4,11
,
Kotaro Moriyama
33,2
, Monika Moscibrodzka
17
, Cornelia Müller
6,17
, Hiroshi Nagai
3,34
, Neil M. Nagar
75
,
Masanori Nakamura
7
, Ramesh Narayan
4,11
, Gopal Narayanan
76
, Iniyan Natarajan
39
, Roberto Neri
16
, Chunchong Ni
19,20
,
Aristeidis Noutsos
6
, Hiroki Okino
33,77
, Héctor Olivares
36
, Gisela N. Ortiz-León
6
, Tomoaki Oyama
33
, Feryal Özel
10
,
Daniel C. M. Palumbo
4,11
, Nimesh Patel
11
, Ue-Li Pen
18,78,79,80
, Dominic W. Pesce
4,11
, Vincent Piétu
16
,
Richard Plambeck
81
, Aleksandar PopStefanija
76
, Oliver Porth
29,36
, Ben Prather
45
, Jorge A. Preciado-López
18
,
Dimitrios Psaltis
10
, Hung-Yi Pu
18
, Venkatessh Ramakrishnan
75
, Ramprasad Rao
15
, Mark G. Rawlings
12
,
Alexander W. Raymond
4,11
, Luciano Rezzolla
36
, Bart Ripperda
36
, Freek Roelofs
17
, Alan Rogers
2
, Eduardo Ros
6
,
Mel Rose
10
, Arash Roshanineshat
10
, Helge Rottmann
6
, Alan L. Roy
6
, Chet Ruszczyk
2
, Benjamin R. Ryan
82,83
,
Kazi L. J. Rygl
65
, Salvador Sánchez
84
, David Sánchez-Arguelles
52,85
, Mahito Sasada
33,86
, Tuomas Savolainen
6,87,88
,
F. Peter Schloerb
76
, Karl-Friedrich Schuster
16
, Lijing Shao
6,51
, Zhiqiang Shen (沈志强)
30,31
, Des Small
58
,
Bong Won Sohn
21,22,89
, Jason SooHoo
2
, Fumie Tazaki
33
, Paul Tiede
19,20
, Remo P. J. Tilanus
17,47,90
, Michael Titus
2
,
Kenji Toma
91,92
, Pablo Torne
6,84
, Tyler Trent
10
, Sascha Trippe
93
, Shuichiro Tsuda
33
, Ilse van Bemmel
58
,
Huib Jan van Langevelde
58,94
, Daniel R. van Rossum
17
, Jan Wagner
6
, John Wardle
95
, Jonathan Weintroub
4,11
,
Norbert Wex
6
, Robert Wharton
6
, Maciek Wielgus
4,11
, George N. Wong
45
, Qingwen Wu (吴庆文)
96
, Ken Young
11
,
André Young
17
, Ziri Younsi
97,36
, Feng Yuan (袁峰)
30,48,98
, Ye-Fei Yuan (袁业飞)
99
, J. Anton Zensus
6
,
Guangyao Zhao
21
, Shan-Shan Zhao
17,63
, Ziyan Zhu
44
, Juan-Carlos Algaba
7,100
, Alexander Allardi
101
, Rodrigo Amestica
102
,
Jadyn Anczarski
103
, Uwe Bach
6
, Frederick K. Baganoff
104
, Christopher Beaudoin
2
, Bradford A. Benson
26,24
,
Ryan Berthold
12
, Jay M. Blanchard
75,58
, Ray Blundell
11
, Sandra Bustamente
105
, Roger Cappallo
2
,
Edgar Castillo-Domínguez
105,106
, Chih-Cheng Chang
7,107
, Shu-Hao Chang
7
, Song-Chu Chang
107
, Chung-Chen Chen
7
,
Ryan Chilson
15
, Tim C. Chuter
12
, Rodrigo Córdova Rosado
4,11
, Iain M. Coulson
12
, Thomas M. Crawford
24,25
,
Joseph Crowley
108
, John David
84
, Mark Derome
2
, Matthew Dexter
109
, Sven Dornbusch
6
, Kevin A. Dudevoir
2,144
,
Sergio A. Dzib
6
, Andreas Eckart
6,110
, Chris Eckert
2
, Neal R. Erickson
76
, Wendeline B. Everett
111
, Aaron Faber
112
,
Joseph R. Farah
4,11,113
, Vernon Fath
76
, Thomas W. Folkers
10
, David C. Forbes
10
, Robert Freund
10
, Arturo I. Gómez-Ruiz
105,106
,
David M. Gale
105
, Feng Gao
30,40
, Gertie Geertsema
114
, David A. Graham
6
, Christopher H. Greer
10
, Ronald Grosslein
76
,
Frédéric Gueth
16
, Daryl Haggard
115,116,117
, Nils W. Halverson
118
, Chih-Chiang Han
7
, Kuo-Chang Han
107
, Jinchi Hao
107
,
Yutaka Hasegawa
7
, Jason W. Henning
23,119
, Antonio Hernández-Gómez
67,120
, Rubén Herrero-Illana
121
, Stefan Heyminck
6
,
Akihiko Hirota
3,7
, James Hoge
12
, Yau-De Huang
7
, C. M. Violette Impellizzeri
7,1
, Homin Jiang
7
, Atish Kamble
4,11
,
Ryan Keisler
25
, Kimihiro Kimura
7
, Yusuke Kono
3
, Derek Kubo
122
, John Kuroda
12
, Richard Lacasse
102
, Robert A. Laing
123
,
Erik M. Leitch
23
, Chao-Te Li
7
, Lupin C.-C. Lin
7,124
, Ching-Tang Liu
107
, Kuan-Yu Liu
7
, Li-Ming Lu
107
, Ralph G. Marson
125
,
Pierre L. Martin-Cocher
7
, Kyle D. Massingill
10
, Callie Matulonis
12
, Martin P. McColl
10
, Stephen R. McWhirter
2
,
Hugo Messias
121,126
, Zheng Meyer-Zhao
7,127
, Daniel Michalik
128,129
, Alfredo Montaña
105,106
, William Montgomerie
12
,
Matias Mora-Klein
102
, Dirk Muders
6
, Andrew Nadolski
46
, Santiago Navarro
84
, Joseph Neilsen
103
, Chi H. Nguyen
10,130
,
Hiroaki Nishioka
7
, Timothy Norton
11
, Michael A. Nowak
131
, George Nystrom
15
, Hideo Ogawa
132
, Peter Oshiro
15
,
Tomoaki Oyama
133
, Harriet Parsons
12
, Scott N. Paine
11
, Juan Peñalver
84
, Neil M. Phillips
121,126
, Michael Poirier
2
,
Nicolas Pradel
7
, Rurik A. Primiani
134
, Philippe A. Raffin
15
, Alexandra S. Rahlin
23,135
, George Reiland
10
,
Christopher Risacher
16
, Ignacio Ruiz
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, Alejandro F. Sáez-Madaín
102,126
, Remi Sassella
16
, Pim Schellart
17,136
, Paul Shaw
7
,
Kevin M. Silva
12
, Hotaka Shiokawa
11
, David R. Smith
137,138
, William Snow
15
, Kamal Souccar
76
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2
,
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11
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11
, Kyle Story
139
, Sjoerd T. Timmer
17
,
Laura Vertatschitsch
11,134
, Craig Walther
12
, Ta-Shun Wei
7
, Nathan Whitehorn
140
, Alan R. Whitney
2
, David P. Woody
141
,
Jan G. A. Wouterloot
12
, Melvin Wright
142
, Paul Yamaguchi
11
, Chen-Yu Yu
7
, Milagros Zeballos
105,143
,
Shuo Zhang
104
, and Lucy Ziurys
10
1
National Radio Astronomy Observatory, 520 Edgemont Road, Charlottesville, VA 22903, USA
2
Massachusetts Institute of Technology, Haystack Observatory, 99 Millstone Road, Westford, MA 01886, USA
3
National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan
4
Black Hole Initiative at Harvard University, 20 Garden Street, Cambridge, MA 02138, USA
5
Instituto de Astrofísica de Andalucía-CSIC, Glorieta de la Astronomía s/n, E-18008 Granada, Spain
6
Max-Planck-Institut für Radioastronomie, Auf dem Hügel 69, D-53121 Bonn, Germany
15
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
7
Institute of Astronomy and Astrophysics, Academia Sinica, 11F of Astronomy-Mathematics Building,
AS/NTU No. 1, Sec. 4, Roosevelt Rd, Taipei 10617, Taiwan, R.O.C.
8
Departament d’Astronomia i Astrofísica, Universitat de València, C. Dr. Moliner 50, E-46100 Burjassot, València, Spain
9
Observatori Astronòmic, Universitat de València, C. Catedrático José Beltrán 2, E-46980 Paterna, València, Spain
10
Steward Observatory and Department of Astronomy, University of Arizona, 933 N. Cherry Ave., Tucson, AZ 85721, USA
11
Center for Astrophysics |Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA
12
East Asian Observatory, 660 N. A’ohoku Pl., Hilo, HI 96720, USA
13
Nederlandse Onderzoekschool voor Astronomie (NOVA), PO Box 9513, 2300 RA Leiden, The Netherlands
14
California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125, USA
15
Institute of Astronomy and Astrophysics, Academia Sinica, 645 N. A’ohoku Place, Hilo, HI 96720, USA
16
Institut de Radioastronomie Millimétrique, 300 rue de la Piscine, F-38406 Saint Martin d’Hères, France
17
Department of Astrophysics, Institute for Mathematics, Astrophysics and Particle Physics (IMAPP),
Radboud University, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands
18
Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Waterloo, ON, N2L 2Y5, Canada
19
Department of Physics and Astronomy, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
20
Waterloo Centre for Astrophysics, University of Waterloo, Waterloo, ON N2L 3G1 Canada
21
Korea Astronomy and Space Science Institute, Daedeok-daero 776, Yuseong-gu, Daejeon 34055, Republic of Korea
22
University of Science and Technology, Gajeong-ro 217, Yuseong-gu, Daejeon 34113, Republic of Korea
23
Kavli Institute for Cosmological Physics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA
24
Department of Astronomy and Astrophysics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA
25
Department of Physics, University of Chicago, 5720 South Ellis Avenue, Chicago, IL 60637, USA
26
Enrico Fermi Institute, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA
27
Data Science Institute, University of Arizona, 1230 N. Cherry Ave., Tucson, AZ 85721, USA
28
Cornell Center for Astrophysics and Planetary Science, Cornell University, Ithaca, NY 14853, USA
29
Anton Pannekoek Institute for Astronomy, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands
30
Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030, People’s Republic of China
31
Key Laboratory of Radio Astronomy, Chinese Academy of Sciences, Nanjing 210008, People’s Republic of China
32
Department of Space, Earth and Environment, Chalmers University of Technology, Onsala Space Observatory, SE-439 92 Onsala, Sweden
33
Mizusawa VLBI Observatory, National Astronomical Observatory of Japan, 2-12 Hoshigaoka, Mizusawa, Oshu, Iwate 023-0861, Japan
34
Department of Astronomical Science, The Graduate University for Advanced Studies (SOKENDAI), 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan
35
Dipartimento di Fisica “E. Pancini,”Universitá di Napoli “Federico II,”Compl. Univ. di Monte S. Angelo, Edificio G, Via Cinthia, I-80126, Napoli, Italy
36
Institut für Theoretische Physik, Goethe-Universität Frankfurt, Max-von-Laue-Straße 1, D-60438 Frankfurt am Main, Germany
37
INFN Sez. di Napoli, Compl. Univ. di Monte S. Angelo, Edificio G, Via Cinthia, I-80126, Napoli, Italy
38
Department of Physics, University of Pretoria, Lynnwood Road, Hatfield, Pretoria 0083, South Africa
39
Centre for Radio Astronomy Techniques and Technologies, Department of Physics and Electronics, Rhodes University, Grahamstown 6140, South Africa
40
Max-Planck-Institut für Extraterrestrische Physik, Giessenbachstr. 1, D-85748 Garching, Germany
41
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology,
32-D476, 77 Massachussetts Ave., Cambridge, MA 02142, USA
42
Google Research, 355 Main St., Cambridge, MA 02142, USA
43
Department of History of Science, Harvard University, Cambridge, MA 02138, USA
44
Department of Physics, Harvard University, Cambridge, MA 02138, USA
45
Department of Physics, University of Illinois, 1110 West Green St, Urbana, IL 61801, USA
46
Department of Astronomy, University of Illinois at Urbana-Champaign, 1002 West Green Street, Urbana, IL 61801, USA
47
Leiden Observatory—Allegro, Leiden University, P.O. Box 9513, 2300 RA Leiden, The Netherlands
48
Key Laboratory for Research in Galaxies and Cosmology, Chinese Academy of Sciences, Shanghai 200030, People’s Republic of China
49
NOVA Sub-mm Instrumentation Group, Kapteyn Astronomical Institute, University of Groningen, Landleven 12, 9747 AD Groningen, The Netherlands
50
Department of Astronomy, School of Physics, Peking University, Beijing 100871, People’s Republic of China
51
Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871, People’s Republic of China
52
Instituto Nacional de Astrofísica, Óptica y Electrónica. Apartado Postal 51 y 216, 72000. Puebla Pue., México
53
The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo, 190-8562, Japan
54
Department of Statistical Science, The Graduate University for Advanced Studies (SOKENDAI), 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan
55
Kavli Institute for the Physics and Mathematics of the Universe, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, 277-8583, Japan
56
Institute for Astrophysical Research, Boston University, 725 Commonwealth Ave., Boston, MA 02215, USA
57
Astronomical Institute, St. Petersburg University, Universitetskij pr., 28, Petrodvorets, 198504 St. Petersburg, Russia
58
Joint Institute for VLBI ERIC (JIVE), Oude Hoogeveensedijk 4, 7991 PD Dwingeloo, The Netherlands
59
Kogakuin University of Technology & Engineering, Academic Support Center, 2665-1 Nakano, Hachioji, Tokyo 192-0015, Japan
60
Physics Department, National Sun Yat-Sen University, No. 70, Lien-Hai Rd, Kaosiung City 80424, Taiwan, R.O.C
61
National Optical Astronomy Observatory, 950 North Cherry Ave., Tucson, AZ 85719, USA
62
Key Laboratory for Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences,
19B Yuquan Road, Shijingshan District, Beijing, People’s Republic of China
63
School of Astronomy and Space Science, Nanjing University, Nanjing 210023, People’s Republic of China
64
Key Laboratory of Modern Astronomy and Astrophysics, Nanjing University, Nanjing 210023, People’s Republic of China
65
Italian ALMA Regional Centre, INAF-Istituto di Radioastronomia, Via P. Gobetti 101, I-40129 Bologna, Italy
66
Department of Physics, National Taiwan University, No.1, Sect.4, Roosevelt Rd., Taipei 10617, Taiwan, R.O.C
67
Instituto de Radioastronomía y Astrofísica, Universidad Nacional Autónoma de México, Morelia 58089, México
68
Instituto de Astronomía, Universidad Nacional Autónoma de México, CdMx 04510, México
69
Yunnan Observatories, Chinese Academy of Sciences, 650011 Kunming, Yunnan Province, People’s Republic of China
70
Center for Astronomical Mega-Science, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing, 100012, People’s Republic of China
71
Key Laboratory for the Structure and Evolution of Celestial Objects, Chinese Academy of Sciences, 650011 Kunming, People’s Republic of China
72
Gravitation Astroparticle Physics Amsterdam (GRAPPA)Institute, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
73
Centro Astronómico de Yebes (IGN), Apartado 148, E-19180 E-Yebes, Spain
74
Department of Physics, Broida Hall, University of California Santa Barbara, Santa Barbara, CA 93106, USA
75
Astronomy Department, Universidad de Concepción, Casilla 160-C, Concepción, Chile
76
Department of Astronomy, University of Massachusetts, 01003, Amherst, MA, USA
77
Department of Astronomy, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
16
The Astrophysical Journal Letters, 875:L1 (17pp), 2019 April 10 The EHT Collaboration et al.
78
Canadian Institute for Theoretical Astrophysics, University of Toronto, 60 St. George Street, Toronto, ON M5S 3H8, Canada
79
Dunlap Institute for Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4, Canada
80
Canadian Institute for Advanced Research, 180 Dundas St West, Toronto, ON M5G 1Z8, Canada
81
Radio Astronomy Laboratory, University of California, Berkeley, CA 94720, USA
82
CCS-2, Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM 87545, USA
83
Center for Theoretical Astrophysics, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
84
Instituto de Radioastronomía Milimétrica, IRAM, Avenida Divina Pastora 7, Local 20, E-18012, Granada, Spain
85
Consejo Nacional de Ciencia y Tecnología, Av. Insurgentes Sur 1582, 03940, Ciudad de México, México
86
Hiroshima Astrophysical Science Center, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8526, Japan
87
Aalto University Department of Electronics and Nanoengineering, PL 15500, FI-00076 Aalto, Finland
88
Aalto University Metsähovi Radio Observatory, Metsähovintie 114, FI-02540 Kylmälä, Finland
89
Department of Astronomy, Yonsei University, Yonsei-ro 50, Seodaemun-gu, 03722 Seoul, Republic of Korea
90
Netherlands Organisation for Scientific Research (NWO), Postbus 93138, 2509 AC Den Haag , The Netherlands
91
Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, Sendai 980-8578, Japan
92
Astronomical Institute, Tohoku University, Sendai 980-8578, Japan
93
Department of Physics and Astronomy, Seoul National University, Gwanak-gu, Seoul 08826, Republic of Korea
94
Leiden Observatory, Leiden University, Postbus 2300, 9513 RA Leiden, The Netherlands
95
Physics Department, Brandeis University, 415 South Street, Waltham, MA 02453, USA
96
School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, People’s Republic of China
97
Mullard Space Science Laboratory, University College London, Holmbury St. Mary, Dorking, Surrey, RH5 6NT, UK
98
School of Astronomy and Space Sciences, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, People’s Republic of China
99
Astronomy Department, University of Science and Technology of China, Hefei 230026, People’s Republic of China
100
Department of Physics, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia
101
University of Vermont, Burlington, VT 05405, USA
102
National Radio Astronomy Observatory, NRAO Technology Center, 1180 Boxwood Estate Road, Charlottesville, VA 22903, USA
103
Department of Physics, Villanova University, 800 E. Lancaster Ave, Villanova, PA, 19085, USA
104
Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
105
Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro 1, Tonantzintla, Puebla, C.P. 72840, Mexico
106
Consejo Nacional de Ciencia y Tecnología, Av. Insurgentes Sur 1582, Col. Crédito Constructor, CDMX, C.P. 03940, Mexico
107
National Chung-Shan Institute of Science and Technology, No.566, Ln. 134, Longyuan Rd., Longtan Dist., Taoyuan City 325, Taiwan, R.O.C.
108
MIT Haystack Observatory, 99 Millstone Road, Westford, MA 01886, USA
109
Dept. of Astronomy, Univ. of California Berkeley, 501 Campbell, Berkeley, CA 94720, USA
110
Physikalisches Institut der Universität zu Köln, Zülpicher Str. 77, D-50937 Köln, Germany
111
CASA, Department of Astrophysical and Planetary Sciences, University of Colorado, Boulder, CO 80309, USA
112
Western University, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada
113
University of Massachusetts Boston, 100 William T, Morrissey Blvd, Boston, MA 02125, USA
114
Research and Development Weather and Climate Models, Royal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA, De Bilt, The Netherlands
115
Department of Physics, McGill University, 3600 University Street, Montréal, QC H3A 2T8, Canada
116
McGill Space Institute, McGill University, 3550 University Street, Montréal, QC H3A 2A7, Canada
117
CIFAR Azrieli Global Scholar, Gravity & the Extreme Universe Program, Canadian Institute for Advanced Research,
661 University Avenue, Suite 505, Toronto, ON M5G 1M1, Canada
118
Department of Astrophysical and Planetary Sciences and Department of Physics, University of Colorado, Boulder, CO 80309, USA
119
High Energy Physics Division, Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL, 60439, USA
120
IRAP, Université de Toulouse, CNRS, UPS, CNES, Toulouse, France
121
European Southern Observatory, Alonso de Córdova 3107, Vitacura, Casilla 19001, Santiago de Chile, Chile
122
ASIAA Hilo Office, 645 N. A‘ohoku Place, University Park, Hilo, HI 96720, USA
123
Square Kilometre Array Organisation, Jodrell Bank Observatory, Lower Withington, Macclesfield, Cheshire SK11 9DL, UK
124
Department of Physics, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea
125
National Radio Astronomy Observatory, P.O. Box O, Socorro, NM 87801, USA
126
Joint ALMA Observatory, Alonso de Córdova 3107, Vitacura 763-0355, Santiago de Chile, Chile
127
ASTRON, Oude Hoogeveensedijk 4, 7991 PD Dwingeloo, The Netherlands
128
Science Support Office, Directorate of Science, European Space Research and Technology Centre (ESA/ESTEC),
Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands
129
University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA
130
Center for Detectors, School of Physics and Astronomy, Rochester Institute of Technology, 1 Lomb Memorial Drive, Rochester, NY 14623, USA
131
Physics Dept., CB 1105, Washington University, One Brookings Drive, St. Louis, MO 63130-4899, USA
132
Osaka Prefecture University, Gakuencyou Sakai Osaka, Sakai 599-8531, Kinki, Japan
133
Mizusawa VLBI Observatory, National Astronomical Observatory of Japan, Ohshu, Iwate 023-0861, Japan
134
Systems & Technology Research, 600 West Cummings Park, Woburn, MA 01801, USA
135
Fermi National Accelerator Laboratory, PO Box 500, Batavia, IL 60510, USA
136
Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544, USA
137
MERLAB, 357 S. Candler St., Decatur, GA 30030, USA
138
GWW School of Mechanical Engineering, Georgia Institute of Technology, 771 Ferst Dr., Atlanta, GA 30332, USA
139
Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, 452 Lomita Mall, Stanford, CA 94305, USA
140
Dept. of Physics and Astronomy, UCLA, Los Angeles, CA 90095, USA
141
Owens Valley Radio Observatory, California Institute of Technology, Big Pine, CA 93513, USA
142
Dept. of Astronomy, Radio Astronomy Laboratory, Univ. of California Berkeley, 601 Campbell, Berkeley, CA 94720, USA
143
Universidad de las Américas Puebla, Sta. Catarina Mártir S/N, San Andrés Cholula, Puebla, C.P. 72810, Mexico
144
Deceased.
17
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