A Distant Fast Radio Burst Associated with Its Host Galaxy by the Very Large Array
Casey J. Law
1
, Bryan J. Butler
2
, J. Xavier Prochaska
3,4
, Barak Zackay
5
, Sarah Burke-Spolaor
6,7,8
,
Alexandra Mannings
3
, Nicolas Tejos
9
, Alexander Josephy
10,11
, Bridget Andersen
10,11
, Pragya Chawla
10,11
,
Kasper E. Heintz
12
, Kshitij Aggarwal
7
, Geoffrey C. Bower
13
, Paul B. Demorest
2
, Charles D. Kilpatrick
3
,
T. Joseph W. Lazio
14
, Justin Linford
2
, Ryan Mckinven
15,16
, Shriharsh Tendulkar
10,11
, and Sunil Simha
3
1
Cahill Center for Astronomy and Astrophysics, MC 249-17 California Institute of Technology, Pasadena, CA 91125, USA; claw@astro.caltech.edu
2
National Radio Astronomy Observatory, Socorro, NM 87801, USA
3
University of California Observatories-Lick Observatory, University of California, 1156 High Street, Santa Cruz, CA 95064, USA
4
Kavli Institute for the Physics and Mathematics of the Universe, 5-1-5 Kashiwanoha, Kashiwa, 277-8583, Japan
5
Institute for Advanced Study, Princeton, USA
6
Center for Gravitational Waves and Cosmology, West Virginia University, Chestnut Ridge Research Building, Morgantown, WV 26505, USA
7
Department of Physics and Astronomy, West Virginia University, Morgantown, WV 26506, USA
8
CIFAR Azrieli Global Scholars program, CIFAR, Toronto, Canada
9
Instituto de Física, Pontificia Universidad Católica de Valparaíso, Casilla 4059, Valparaíso, Chile
10
Department of Physics, McGill University, 3600 University Street, Montréal, QC H3A 2T8, Canada
11
McGill Space Institute, McGill University, 3550 University Street, Montréal, QC H3A 2A7, Canada
12
Centre for Astrophysics and Cosmology, Science Institute, University of Iceland, Dunhagi 5, 107 Reykjavìk, Iceland
13
Academia Sinica Institute of Astronomy and Astrophysics, 645 N. A’ohoku Place, Hilo, HI 96720, USA
14
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, M/S 67-201, Pasadena, CA 91109 USA
15
Department of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4, Canada
16
Dunlap Institute for Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4, Canada
Received 2020 June 5; revised 2020 July 4; accepted 2020 July 8; published 2020 August 26
Abstract
We present the discovery and subarcsecond localization of a new fast radio burst (FRB) by the Karl G. Jansky Very
Large Array (VLA) and realfast search system. The FRB was discovered on 2019 June14 with a dispersion
measure of 959
-
pc cm
3
. This is the highest DM of any localized FRB and its measured burst fluence of 0.6 Jy ms
is less than nearly all other FRBs. The source is not detected to repeat in 15 hr of VLA observing and 153 hr of
CHIME/FRB observing. We describe a suite of statistical and data quality tests we used to verify the significance
of the event and its localization precision. Follow-up optical/infrared photometry with Keck and Gemini
associate the FRB with a pair of galaxies with
~
r
23
mag. The false-alarm rate for radio transients of this
significance that are associated with a host galaxy is roughly
´
--
3
10 hr
41
. The two putative host galaxies have
similar photometric redshifts of
~
z
0.6
phot
, but different colors and stellar masses. Comparing the host distance to
that implied by the dispersion measure suggests a modest (
~
-
50 pc cm
3
) electron column density associated with
the FRB environment or host galaxy/galaxies.
Unified Astronomy Thesaurus concepts: Radio transient sources (2008); Radio interferometry (1346); Extragalactic
astronomy (506); Radio bursts (1339)
1. Introduction
Fast radio bursts (FRBs) are millisecond-timescale radio
transients of extremely high brightness originating at cosmological
distances (Cordes & Chatterjee 2019; Petroff et al. 2019).
Hundreds of FRBs are known currently, and the inferred
occurrence rate is roughly 10
3
sky
−1
day
−1
above a fluence limit
of 1 Jy ms at frequencies near 1.4 GHz (Champion et al. 2016;
Lawrence et al. 2017). FRB distances can be estimated from the
dispersive delay induced by propagation through ionized gas
(quantified by a dispersion measure, DM, which measures the
total electron column density along the line of sight to the source);
for FRBs, the measured DMs are significantly larger than those
expected due to contributions from our own Galaxy (Cordes &
Lazio 2002). By attributing the dispersion induced outside of our
Galaxy to predictions for the intergalactic medium (IGM),FRBs
are estimated to originate at characteristic distances of one to a few
gigaparsecs (Inoue 2004; Lorimer et al. 2007). Several FRBs have
been localized by radio interferometers and associated with host
galaxies of known distance; their luminosity distances range from
149 Mpc to 4 Gpc (Tendulkar et al. 2017; Bannister et al. 2019;
Prochaska et al. 2019b;Ravietal.2019; Macqua rt et al. 2020;
Marcote et al. 2020).
It is not yet known what causes FRBs or whether there are
multiple formation channels (Lu & Kumar 2016; Ravi 2019a) .
The identification of FRB host galaxies is a critical test of
formation models, as it can constrain the age of the stellar
populations in FRB environments. The first host galaxy
suggested that FRBs are associated with peculiar star-forming
environments (Bassa et al. 2017) but later hosts have a wider
range of environments (Bannister et al. 2019; Ravi et al. 2019;
Bhandari et al. 2020).
Radio waves are modified as they propagate through ionized
gas (e.g., dispersion, scattering, lensing, and Faraday rotation;
Cordes et al. 2017
;Vedantham&Ravi2019).Thisfact,
combined with the large distance to FRBs, makes them novel
probes of the IGM and other galaxies (Ginzburg 1973;Masui
et al. 2015; Prochaska et al. 2019b). Furthermore, the fact
that dispersion is an unambiguous tracer of baryonic mass has
revealed the potential of using FRBs to study galaxy halos and
cosmology (Prochaska & Zheng 2019; Ravi 2019b).However,
most of this scientific potential can only be achieved by
measuring distances to FRBs. Multiple radio interferometers
that can be used for precise FRB localization are in phases
of conceptual development, construction, or commissioning
The Astrophysical Journal, 899:161 (11pp), 2020 August 20 https://doi.org/10.3847/1538-4357/aba4ac
© 2020. The American Astronomical Society. All rights reserved.
1
(Oostrum et al. 2017; Law et al. 2018; Bannister et al. 2019;
Caleb et al. 2019;Koczetal.2019). The goal of all these
projects is to localize FRBs to arcsecond precision, which is
required to unambiguously associate them with a host galaxy
(Eftekhari et al. 2018).
Many FRBs are seemingly single flashes, and before the
advent of widespread use of GPUs to accelerate complex
processing, single-dish telescopes generally led blind searches
for new FRBs (Burke-Spolaor et al. 2011; Thornton et al. 2013;
Spitler et al. 2014). However, some FRBs, such as FRB
121102, emit multiple bursts at irregular intervals (Spitler et al.
2016; Zhang et al. 2018), which made it possible to target them
with interferometers (Chatterjee et al. 2017; Marcote et al.
2017). The Canadian Hydrogen Intensity Mapping Experiment
(CHIME) is a transit telescope operating between 400 and
800 MHz that is rapidly discovering both repeating and
nonrepeating FRBs (CHIME/FRB Collaboration et al. 2018;
The CHIME/FRB Collaboration et al. 2019). The CHIME/
FRB search has a localization precision of roughly 10′, which
is too large to unambiguously identify host galaxies for FRBs.
Here, we present a new FRB discovery and localization by
the Karl G. Jansky Very Large Array (VLA) using realfast
(Law et al. 2018). The FRB was found coincidentally during a
search for CHIME/FRB FRB180814.J0422+73 (hereafter
FRB 180814, CHIME/FRB Collaboration et al. 2019
). This
new FRB is associated with a unique host galaxy with a
distance that is consistent with expectations for its DM. The
combination of radio interferometric data and optical associa-
tions support the conclusion that it is a new FRB, and we refer
to it as FRB 20190614D. We discuss the FRB environment and
constraints on the distribution of DM in the IGM and host
galaxy.
2. Observations
2.1. Program and Overall Description
In 2018, the VLA and CHIME/FRB teams began collabor-
ating to use the VLA for follow-up of repeating FRBs found by
CHIME/FRB. We have carried out two approved projects:
VLA/18B-405 and VLA/19A-331. We targeted FRB 180916.
J0158+65 and FRB 190303.J1353+48 for 40 hr scheduled
under VLA/18B-405 and FRB180814 for 39 hr scheduled
under VLA/19A-331; this paper focuses on the second project.
We observed using the L-band system of the VLA, spanning
1–2 GHz , in 20 separate observations. We observed a field
centered at (R.A., decl.) [J2000]=(04
h
22
m
22
s
, +73
d
40
m
00
s
),
the approximate position of FRB180814. The nominal field of
view of the VLA antennas at L-band is
~
¢
30
(FWHM at
1.4 GHz), but the realfast system is configured to image a field
two times wider than that. The first seven observations were
performed in 2018 December, in the C-configuration of the
VLA, with maximum baselines
~
3
km and a resolution of
~
14
at 1.4 GHz. Thirteen later observations were performed in
February through July of 2019, in the B- or BnA-configurations
of the VLA, with maximum baselines
~1
1
km in length and a
resolution of
~4. 5
at 1.4 GHz. Each observation had an on-
source time of around 1.5 hr that was searched by the realfast
system. The detection reported here is the strongest FRB-like
event found in this campaign and is the focus of the analysis
presented.
2.2. Search Technique
The observations used a commensal correlator mode that
generated visibilities with an integration time of 5ms to be
searched by realfast. The same data were also used to generate
and save the standard visibility data product to the NRAO
archive with a sampling time of 3s, for all observations in
2019 June and July (nine of them). Prior to that, all visibilities
were saved to the archive at their full time resolution, resulting
in large data sets (of order 1.5 TB). Both fast and slow
visibilities were made in 16 64-channel spectral windows, with
each channel set to a width of 1 MHz. Taking typical
interference flagging into account, the usable bandwidth is
600 MHz.
The fast-sampled visibilities were distributed to a dedicated
GPU cluster using vysmaw (Pokorny et al. 2018) and searched
with rfpipe (Law 2017). After applying available online
calibrations, the search pipeline dedispersed and integrated
visibilities in time before forming images. Calibration solutions
were derived from ∼minute-long scans and are stable in time
(less than 5° change from the mean value).Imageswere
generated with a simple, custom algorithm that uses natural
weighting and a pillbox gridding scheme. The search used 215
DM values from0to1000
-
pc cm
3
and four temporal widths
from5to40ms, which is inclusive of the known properties of
FRB 180814 (CHIME/FRB Collaboration et al. 2019).
For the B-configuration observations, each image had
2048×2048 pixels with a pixel size of 1
7, covering a field
of view of 1°. The C-configuration images were 512×512
pixels with a pixel size of roughly 6
8. The nominal
1σsensitivity in a single 5ms integration is 6mJybeam
−1
.
All candidates detected with significance greater than 7.5σtrig-
ger the recording of 2–3s of fast-sampled visibilities and a
visualization of the candidate. Each candidate is classified by
fetch, a convolutional neural network for radio transients
(Agarwal et al. 2020). Finally, realfast team members review
the visualizations of the real-time analysis to either remove data
corrupted by interference or identify candidates for more
refined offline analysis.
2.3. Discovery
On2019 June14 (UT),therealfast system detected a candidate
transient in the FRB180814 field. The real-time detection system
reported a candidate with image significance of 8.0σan d
=
-
D
M 959 pc cm
3
, far in excess of the expected DM contrib-
utionoftheMilkyWay(83.5
-
pc cm
3
; Cordes & Lazio 2002).
However, the DM of FRB180814 is 189.4pc cm
−3
;noFRB
has shown changes in DM of more than a few pccm
−3
(Gajjar
et al. 2018), so the candidate FRB is likely unrelated to the
CHIME FRB.
The real-time candidate analysis revealed multiple signatures
consistent with an astrophysical source. First, the spectrum
(Figure 1, right panel) shows emission over a range of
frequencies spanning at least 50 MHz and the image shows a
compact source. Most sources of interference tend to have
circular polarization, narrow spectral extent, or are spatially
incoherent (i.e., radio frequency interference in the near-field of
the array). Second, the fetch FRB classification system
reported an astrophysical probability of 99.9%. Third, there is a
weak prior expectation for blindly detected astrophysical
events to be detected where the antenna sensitivity is highest.
The candidate was detected roughly 9′ away from the pointing
2
The Astrophysical Journal, 899:161 (11pp), 2020 August 20 Law et al.
center, where the antenna has roughly 80% of its nominal
sensitivity; only 10% of the image has this sensitivity or higher.
The realfast search system was starting to receive visibilities
from the VLA correlator during the burst. This is seen in
Figure 1, which shows that the mean of all recorded visibilities
during the burst (phased toward the event) is noisier at early
times and at higher frequencies. Visibilities for each baseline,
polarization, and spectral window (64 channels) are distributed
separately such that the fraction of data grows to 100% over a
few hundred milliseconds as the system turns on.
2.4. Verification Tests and Significance Analysis
Traditional fast transient surveys measure event significance
based on a noise estimate that is local in time (e.g., a standard
deviation of a time series). Our interferometric search measures
significance in a single image, so the noise estimate is made
simultaneously. The Appendix describes how the visibility
domain search can be thought of as a time-domain search that
allows for more accurate noise estimates.
In our initial analysis of the candidate, we confirmed that the
event significance was not affected by different flagging
algorithms or calibration solutions from a calibrator observa-
tion a few minutes after the event. We also confirmed that
removing an antenna from the 27-antenna array reduced the
detection significance by roughly 5% (
»127
antennas). With
confidence in the quality of data, we proceeded to more
carefully quantify the event significance.
We used the raw, saved visibilities to rerun the search with a
larger image (8192 × 8192 pixels) and finer DM grid. This
optimized search improved the detection significance slightly
to a signal-to-noise ratio (S/N) of8.27 at
=
D
M 959.19
-
pc cm
3
. Using the same refinement procedure on other
candidates typically does not reproduce the initial detection.
Noise-like events are expected to be sensitive to the image
gridding parameters, so we ignore all events that cannot be
reproduced in larger images. We use these refined properties
for visualizations and all further analysis.
Figure 2 shows the cumulative distribution of event
significance for all events seen in this campaign. The FRB
search pipeline automatically applies flags for bad calibration,
antenna state, missing data, and interference. We visually
inspected the 263 candidates detected above 7.5σ in observa-
tions of this field and removed those affected by unflagged
interference to get a sample of 31 candidates.
Figure 2 also shows an independe nt estimate of the ideal event
rate significance distribution for thearrayandcorrelatorconfig-
urationusedtofind this candidate. The ideal cumulative event rate
assumes that each pixel imaged has a brightness that is drawn from
a stationary Gaussian distribution. The number of independent
pixels searched is
(
)()´*NO N N O
pix pix
2
int DM DM
,where
N
pix
is the width of an image in pixels,
N
int
number of integrations (at
all time widths),
N
DM
is the number of DM trials, and
O
pix DM
are the oversampling of the synthesized beam and dispersion
sensitivity function, respectively. Both images and DMs are
oversampled to maintain uniform sensitivity to all locations and
DMs.Thesearchwerunhereuses
=
O
2.5
pix
and
=
O 3
DM
.In
this configuration, we have 8.4hr of observing time and 5×10
14
independent pixels. The candidate S/N of 8.27 corresponds to a
false-alarm rate (FAR) of once in 250hr. The measured and ideal
distributions are independent and in rough agreement, which
shows that the significance distribution approximately follows a
Gaussian distribution and that this candidate is an outlier.
The FRB search pipeline also uses spectral brightness
fluctuations to distinguish candidate events from noise (Law
et al. 2017; The CHIME/FRB Collaboration et al. 2019).The
Kalman detector (B. Zackay 2020, in preparation) is a method to
estimate the statistical significance of FRB spectral variations for
an assumed noise model and signal smoothness. For a given
noise and signal model, we can marginalize the detection statistic
over all matched filters, weighted by their prior probability. This
prior probability is defined by a random walk with one free
parameter, the coherence bandwidth. We calculated the Kalman
score on the candidate FRB, using logarithmic spaced options
Figure 1. (Left) StokesI dynamic spectrum for the candidate FRB as seen by
VLA/realfast. The dynamic spectrum was generated by summing calibrated
visibilities for all baselines and the two orthogonal polarizations. The gap and
higher noise level toward the top left of the dynamic spectrum results from
when the data recording was initiated. (Right) StokesI spectrum taken from a
single 5ms integration of the dynamic spectrum.
Figure 2. Circles show the cumulative distribution of candidates in this
observing campaign as a function of image S/N ratio. The solid line shows the
expected cumulative event rate for a Gaussian (noise-like) S/N distribution. The
yellow cross shows the candidate FRB S/N ratio after refinement analysis.
3
The Astrophysical Journal, 899:161 (11pp), 2020 August 20 Law et al.
for the smoothing scale, but found no significant change in the
total confidence for the candidate FRB (other FRBs do show
some improvement; B. Zackay 2020, in preparation).We
conclude that the candidate FRB spectrum is consistent with a
constant flux density.
2.5. Localization
The real-time FRB search software makes several assump-
tions to improve computational efficiency, and as a result
images that are used within it are not optimal. To address this,
we used the stored raw, dedispersed visibilities to reimage the
burst data with a combination of CASA (McMullin et al. 2007)
and AIPS (Greisen 2003).
17
Here, we describe a unified
calibration and imaging procedure used in both fast and deep
imaging. This procedure allows us to quantify the systematic
error in the FRB localization.
Prior to reimaging the burst data, we reduced all of the data
taken in 2019 June and July for a deep image of the field. Nine
data sets during B configuration were included in this analysis.
We excluded C con figuration data, as it has poorer spatial
resolution. We also excluded early B configuration data
recorded at the fast sampling rate, as it was computationally
expensive to include in the deep imaging analysis.
We started by applying the calibration and flagging tables for
each observation, which were provided by the VLA calibration
pipeline. For all observations, the flux density scale was set
with an observation of the calibrator source 3C147, and at
these frequencies is accurate to 1%–2% (Perley & Butler 2017).
Bandpass and delay calibrations were also determined by the
3C147 observation. Complex gain (amplitude and phase)
fluctuations over time were calibrated with observations of the
calibrator source J0410+7656 every 30 minutes. We then
exported the calibrated visibilities from CASA and imported
them into AIPS. After further RFI flagging, we averaged in
time (to 9 s) and frequency (to 4 MHz channels) to reduce the
computational load for the imaging.
We used faceted imaging in AIPS to image beyond the first
null of the antenna primary beam response (1°.1 width). A total
of 73 separate fields, each 1024×1024 pixels (with 0
5 pixel
size), and 250 CLEAN boxes were used to image and clean the
area. After cleaning, the 73 images of the fields were combined
together, and that result was used to self-calibrate (Cornwell &
Fomalont 1999) the visibilities on a 1 minute timescale. The
imaging and self-calibration were then repeated using this
self-calibrated data set, on a 9 s timescale—essentially self-
calibrating every visibility. A final image was then made, and a
primary beam correction performed on it, based on Perley
(2016). This is the final deep image used for further analysis.
The synthesized beam in this final deep image is 3
6×2 8at
a position angle of 79° (north through east). The image has a 1σ
sensitivity of3.6 μJy beam
-1
, consistent with expectations for
the total on-source time and flagging.
For the reimaging of the burst data, we first copied the VLA
calibration pipeline tables (calibration and flagging) from the
full June 14th observation, and ran a modified version of the
procedure to reapply these tables. Calibration tables from
the three spectral windows (384 MHz of bandwidth) with valid,
uncorrupted data were applied. The synthesized beam in this
final burst image is 10
3×4 2 at a position angle of 67°.Itis
significantly worse than the resolution of the deep image
because of the drastically reduced amount of data that went
into it.
The deep and fast radio images were exported to CASA
format for source detection and modeling. The source detected
by the realfast system (using rfpipe) is also detected in the
burst image. We fit an ellipse to that source to measure the
centroid location, peak flux density, and their 1σuncertainties
(see Table 1). The localization precision is approximately
1/
10th
of the synthesized beam diameter, which is typical for
sources of this significance observed with the VLA (Becker
et al. 1995).
We then searched the deep image to determine whether there
is persistent radio emission associated with the candidate FRB.
We find no such associated persistent radio emission at the
location of the candidate FRB, to a 3σlimit of 11 μJy (see
Figure 3).
We tested the astrometric precision by associating compact
radio sources with optical sources in the Pan-STARRS DR2
catalog (Chambers et al. 2016). We ran the aegean source
Table 1
Measured Properties of FRB 20190614D with 1σ Errors
Time (MJD, @2.0 GHz) 58648.05071771
R.A. (J2000) 4
h
20
m
18 13
Decl. (J2000) +73
d
42
m
24 3
R.A. (J2000, deg) 65.07552
Decl. (J2000, deg ) 73.70674
Centroid ellipse (″, ″, °) 0
8, 0 4, 67
S/N ratio
imag
e
8.27
DM
obs
(
-
pc cm
3
) 959.2 ± 5
DM
MW
(
-
pc cm
3
) 83.5
Peak fl ux density (mJy) 124±14
Fluence (Jy ms) 0.62±0.07
Deep limit (μJy beam
−1
) <11
Note. The centroid ellipse is defined with the major and minor axes and
orientation (east of north). Deep limit refers to the flux density limit on 1.4 GHz
radio counterparts in a deep image of the FRB field. The Milky Way DM
estimate is calculated from Cordes & Lazio (2002).
Figure 3. Deep 1.4 GHz radio image of the FRB180814 field with the location
of FRB 20190614D shown with white cross-hairs. Black contours show radio
brightness levels of 25 and 50 μJy. No persistent radio emission brighter than
3σ(11 μJy) is seen at the location of the new FRB. The noise level of this
image is 3.6 μJybeam
−1
, and the beam shape is (3 6, 2 8, 78°), marked by a
yellow ellipse in the bottom left corner of the image.
17
Both CASA and AIPS calibrate with a different algorithm from that used by
the real-time calibration system known as “telcal” (Law et al. 2018).
4
The Astrophysical Journal, 899:161 (11pp), 2020 August 20 Law et al.
finding package (Hancock et al. 2018) and identified 270
compact radio sources with a flux density greater than 100 μJy
(
s>25
). Of these, 102 had optical counterparts within 3″ and
=
n
Detections 5
. No systematic offset is found between the
radio and optical sources; the standard deviation of the radio/
optical offsets is 0
2. We note that given the resolution of the
radio image (3
6×2 8), we expect the astrometric accuracy
to be of the order of 0
1 for these brighter sources (a few
percent of the synthesized beamwidth).
2.6. CHIME/FRB Limits
The CHIME/FRB system, operating in its commissioning
phase, has observed the sky position of FRB 20190614D for a
total of 153hr during the interval from 2018 August28 to
2019 September30. The large exposure is due to the
circumpolar nature of the source and is split between 88hr
for the upper transit and 65hr for the lower transit. The average
duration of the upper and lower transits is 17 and 13 minutes,
respectively, during which the source is within the FWHM
region of the synthesized beams at 600 MHz. We searched
through all low-significance events that were detected by the
CHIME/FRB system in the abovementioned observing time.
No significant event or excess event rate was found to be
consistent with the location and DM of FRB 20190614D, so
there is no evidence for repetition from this FRB.
To determine CHIME/FRB sensitivity to FRB 20190614D,
we follow the methods detailed in Josephy et al. (2019).The
sensitivity of CHIME/FRB varies with observing epoch,
position along transit, and burst spectral shape. We used a
Monte Carlo simulation with 10
6
realizations to generate fluence
thresholds for different detection scenarios within the quoted
exposure. These simulations define a set of relative sensitivities,
which are tied to a flux density scale using beam-formed,
bandpass-corrected observations. As a reference, we use a burst
from FRB 180814.J0422+73 detected on 2018 November11
with an S/N ratio of 9.8σ, fluence of 2.3±0.8Jyms, and a
Gaussian spectral fit with center frequency of 524 MHz and
FWHM of 72 MHz. Figure 4 shows the fluence threshold
distribution is 90% complete at 3.8 Jy ms. The distribution is
valid for the upper, more-sensitive transit; we estimate the lower
transit to be approximately a factor of 4 less sensitive (CHIME/
FRB Collaboration et al. 2019).
2.7. Optical Associations
We considered the significance of this candidate high
enough to trigger observations designed to find an optical
counterpart. On UT 2019 July 2, we observed the field
surrounding FRB 20190614D with the Gemini Multi-Object
Spectrograph (GMOS) on the Gemini-N telescope. We
obtained a series of
´8 300 s
image exposures in the r-band.
These data were reduced with standard procedures using the
Gemini’s
PYRAF package, and the images were registered using
Pan-STARRS DR1 astrometric standards (Flewelling et al.
2016). We performed photometry on these images using
DoPhot (Schechter et al. 1993) and calibrated the image using
Pan-STARRS r-band calibrators.
On UT 2019 September 25, we obtained a series of
4×600s images with the Low Resolution Imaging
Spectrograph (LRIS) on the KeckI telescope in V and I bands.
These data were reduced using a custom-built pipeline used for
transient searches and based on the photpipe imaging and
reduction package (Rest et al. 2005). Following standard
procedures, we removed bias and flattened our images using
bias and dome flat-field exposures obtained on the same night
and in the same instrumental configuration. We registered the
images using Pan-STARRS astrometric standards and com-
bined the individual exposures with SWarp (Bertin et al.
2002). We performed point-spread function photometry on the
final stacked images with DoPhot and calibrated these data
using Pan-STARRS grizy calibrators transformed to VI using
the bandpass transformations described in Tonry et al. (2012).
On UT 2019 November 26, we obtained an additional set of
´18 200 s
z-band images of the FRB field with the Alhambra
Faint Object Spectrograph and Camera on the Nordic Optical
Telescope (NOT). The images were processed with standard
procedures and astrometrically calibrated to the Gaia-DR2
reference frame.
On UT 2020 March 9, we also obtained a set of
´
4
300 s
images (each one coming from
´
5
60 s
co-adds) in the near-
infrared J-band using the Near InfraRed Imager and
spectrograph (NIRI; Hodapp et al. 2003) on the Gemini-N
telescope. The images were reduced with standard procedures
using the
DRAGONS
18
package and were astrometrically
calibrated to the Gaia-DR2 reference frame. A photometric
calibration was derived using Two Micron All Sky Survey
sources in the image.
Figure 5 shows the VrI images centered on the radio
localization of the candidate FRB. All optical images were
registered in the Pan-STARRS DR1 astrometric frame, and so
the uncertainty in their relative alignment is given by the
precision of the original alignment solutions. We estimate a
registration precision of
»0. 06
(1σ) for each image.
There are two optical sources that are plausibly associated
with the radio source. The brighter source is J042017.85
+734222.8, referred to as SourceA, and approximately 1″
north of that is J042017.86+734224.5, referred to as sourceB.
The 1σ radio localization region overlaps with source B, but
the 2σ (90% confidence interval) radio localization region
overlaps with sourceA. We consider both sources to be
potentially associated with the event. Final VrIzJ photometry of
Figure 4. Cumulative distribution of fluence detection thresholds for the
CHIME/FRB instrument. Note that the FRB candidate is circumpolar and thus
transits the CHIME field of view twice a day; thresholds shown here are valid
for the upper transit, whereas the lower transit is a factor of
~
4
less sensitive.
Dashed lines indicate the 90% completeness level at 3.8 Jy ms. For
comparison, the VLA fl uence limit is 0.5 Jy ms (8σ in 5 ms at 1.4 GHz).
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The Astrophysical Journal, 899:161 (11pp), 2020 August 20 Law et al.
