# The Gravity Collective: A Comprehensive Analysis of the Electromagnetic
Search for the Binary Neutron Star Merger GW190425

D. A. Coulter Space Telescope Science Institute, 3700 San Martin Drive,
Baltimore, MD 21218, USA  Department of Astronomy and Astrophysics, University
of California, Santa Cruz, CA 95064, USA  C. D. Kilpatrick Center for
Interdisciplinary Exploration and Research in Astrophysics (CIERA),
Northwestern University, Evanston, IL 60201, USA  D. O. Jones Institute for
Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822, USA
R. J. Foley Department of Astronomy and Astrophysics, University of
California, Santa Cruz, CA 95064, USA  J. Anais Vilchez Astronomy Center
(CITEVA), University of Antofagasta, Avenida U. de Antofagasta, 02800
Antofagasta, Chile  I. Arcavi The School of Physics and Astronomy, Tel Aviv
University, Tel Aviv 69978, Israel  K. E. Clever Department of Astronomy and
Astrophysics, University of California, Santa Cruz, CA 95064, USA  G.
Dimitriadis School of Physics, Trinity College Dublin, The University of
Dublin, Dublin 2, Ireland  A. V. Filippenko Department of Astronomy,
University of California, Berkeley, CA 94720-3411, USA  N. Muñoz-Elgueta  Max-
Planck-Institut fur Astrophysik, Karl-Schwarzschild-Str 1, D-85748 Garching
bei München, Germany  A. L. Piro The Observatories of the Carnegie Institution
for Science, 813 Santa Barbara St., Pasadena, CA 91101, USA  P. J. Quiñonez
Department of Astronomy and Astrophysics, University of California, Santa
Cruz, CA 95064, USA  G. S. Rahman  Thacher Observatory, Thacher School, 5025
Thacher Rd. Ojai, CA 93023, USA  Department of Mathematics and Computer
Science, Wesleyan University, 45 Wyllys Ave, Middletown, CT 06457, USA  C.
Rojas-Bravo Department of Astronomy and Astrophysics, University of
California, Santa Cruz, CA 95064, USA  M. R. Siebert Space Telescope Science
Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA  H. E. Stacey
Thacher Observatory, Thacher School, 5025 Thacher Rd. Ojai, CA 93023, USA  J.
J. Swift Thacher Observatory, Thacher School, 5025 Thacher Rd. Ojai, CA 93023,
USA  W. Zheng Department of Astronomy, University of California, Berkeley, CA
94720-3411, USA  J. S. Bloom Department of Astronomy, University of
California, Berkeley, CA 94720-3411, USA  M. J. Bustamante-Rosell Department
of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064,
USA  K. W. Davis Department of Astronomy and Astrophysics, University of
California, Santa Cruz, CA 95064, USA  J. Kutcka Department of Astronomy and
Astrophysics, University of California, Santa Cruz, CA 95064, USA  P. Macias
Department of Astronomy and Astrophysics, University of California, Santa
Cruz, CA 95064, USA  P. McGill Department of Astronomy and Astrophysics,
University of California, Santa Cruz, CA 95064, USA  Space Science Institute,
Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550,
USA  E. Ramirez-Ruiz Department of Astronomy and Astrophysics, University of
California, Santa Cruz, CA 95064, USA  K. Siellez  University of Tasmania,
Physics, UTAS Physics Building - Private Bag 37, Hobart, Tasmania, 7001,
Australia  S. Tinyanont National Astronomical Research Institute of Thailand,
260 Moo 4, Donkaew, Maerim, Chiang Mai, 50180, Thailand  S. B. Cenko
Astrophysics Science Division, NASA Goddard Space Flight Center, Greenbelt, MD
20771, USA  Joint Space-Science Institute, University of Maryland, College
Park, MD 20742, USA  M. R. Drout David A. Dunlap Department of Astronomy and
Astrophysics, University of Toronto, 50 St. George Street, Toronto, Ontario,
M5S 3H4, Canada  R. Hausen Department of Physics and Astronomy, Johns Hopkins
University, 3400 North Charles Street, Baltimore, MD 21218, USA  D. Andrew
Howell Las Cumbres Observatory, 6740 Cortona Dr, Suite 102, Goleta, CA
93117-5575, USA  Department of Physics, University of California, Santa
Barbara, CA 93106-9530, USA  W. V. Jacobson-Galán Department of Astronomy,
University of California, Berkeley, CA 94720-3411, USA  D. Kasen Department of
Astronomy, University of California, Berkeley, CA 94720-3411, USA  Lawrence
Berkeley National Laboratory, 1 Cyclotron Road, MS 50B-4206, Berkeley, CA
94720-3411, USA  C. McCully Las Cumbres Observatory, 6740 Cortona Dr, Suite
102, Goleta, CA 93117-5575, USA  A. Rest Space Telescope Science Institute,
3700 San Martin Drive, Baltimore, MD 21218, USA  Department of Physics and
Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD
21218, USA  K. Taggart Department of Astronomy and Astrophysics, University of
California, Santa Cruz, CA 95064, USA  S. Valenti Department of Physics and
Astronomy, University of California, Davis, 1 Shields Avenue, Davis, CA
95616-5270, USA

###### Abstract

We present an ultraviolet-to-infrared search for the electromagnetic (EM)
counterpart to GW190425, the second-ever binary neutron star (BNS) merger
discovered by the LIGO-Virgo-KAGRA Collaboration (LVK). GW190425 was more
distant and had a larger localization area than GW170817, therefore we use a
new tool Teglon to redistribute the GW190425 localization probability in the
context of galaxy catalogs within the final localization volume. We derive a
90th percentile area of 6,688 deg2, a $\sim$1.5$\times$ improvement relative
to the LIGO/Virgo map, and show how Teglon provides an order of magnitude
boost to the search efficiency of small ($\leq$1 deg2) field-of-view
instruments. We combine our data with all publicly reported imaging data,
covering 9,078.59 deg2 of unique area and 48.13% of the LIGO/Virgo-assigned
localization probability, to calculate the most comprehensive kilonova, short
gamma-ray burst (sGRB) afterglow, and model-independent constraints on the EM
emission from a hypothetical counterpart to GW190425 to date under the
assumption that no counterpart was found in these data. If the counterpart
were similar to AT 2017gfo, there was a 28.4% chance that it would have been
detected in the combined dataset. We are relatively insensitive to an on-axis
sGRB, and rule out a generic transient with a similar peak luminosity and
decline rate as AT 2017gfo to $30$% confidence. Finally, across our new
imaging and all publicly-reported data, we find 28 candidate optical
counterparts that we cannot rule out as being associated with GW190425,
finding that 4 such counterparts discovered within the localization volume and
within 5 days of merger exhibit luminosities consistent with a kilonova.

gravitational waves — merger: black holes, neutron stars; astronomy —
software: databases, open source software, publicly available software; time
domain astronomy; transient sources

††software: astropy (Astropy Collaboration et al., 2013), DoPhot (Schechter et
al., 1993), dustmaps (Green, 2018), healpy (Zonca et al., 2019), hotpants
(Becker, 2015), ligo.skymap (Singer et al., 2016a, b), PypeIt (Prochaska et
al., 2020a, b), SExtractor (Bertin & Arnouts, 1996), Teglon (Coulter, 2021),
Treasure Map (Wyatt et al., 2020)††facilities: KAIT, Keck:I (MOSFIRE), Nickel
(Direct 2K), SMARTS 1.3m (ANDICAM), Swope (Direct 4K), Thacher (ACP).

fixltx2e firstofone

##  1 Introduction

The mergers of neutron stars (NSs) and black holes (BHs) produce sufficiently
strong gravitational waves (GWs) that they can be detected by modern
interferometric instruments such as the Laser Interferometer Gravitational-
wave Observatory (LIGO) and Virgo (Abbott et al., 2016a, b, 2017a, 2017b,
2017c). The majority of detected GW events involve binary black holes (BBHs;
The LIGO Scientific Collaboration et al., 2021), systems that are naively
expected to produce no electromagnetic (EM) emission. However, the LIGO-Virgo-
KAGRA (LVK) collaboration has detected nine mergers of compact binaries where
at least one component has a mass consistent with being an NS (Abbott et al.,
2021; The LIGO Scientific Collaboration et al., 2021, 2024). In these cases,
there is the potential for an electromagnetically luminous counterpart, such
as as a short gamma-ray burst (sGRB) or a radioactively powered kilonova (KN;
Li & Paczyński, 1998; Shibata & Taniguchi, 2006; Metzger et al., 2010; Roberts
et al., 2011; Kasen et al., 2017).

A single GW event, GW170817 (Abbott et al., 2017d), has been observed
electromagnetically as GRB 170817A (Goldstein et al., 2017; Savchenko et al.,
2017) and SSS17a/AT 2017gfo (Coulter et al., 2017). This event was the result
of the merger of two roughly equal-mass NSs with component masses of
1.46$\begin{subarray}{c}+0.12\\\ -0.10\end{subarray}$ and 1.27$\pm$0.09 M☉ and
a total mass of 2.73$\begin{subarray}{c}+0.04\\\ -0.01\end{subarray}$ M☉
(Abbott et al., 2017d). The ultraviolet (UV), optical, and infrared (IR;
collectively denoted as UVOIR) data are consistent with a radioactively
powered KN with 0.06 M☉ of ejecta that is rich in $r$-process material (Arcavi
et al., 2017a; Cowperthwaite et al., 2017; Drout et al., 2017; Kasliwal et
al., 2017; Kilpatrick et al., 2017; Smartt et al., 2017; Soares-Santos et al.,
2017; Valenti et al., 2017). The GRB and its afterglow, observed as a
nonthermal component for several years (Haggard et al., 2017; Margutti et al.,
2017; Murguia-Berthier et al., 2017; Alexander et al., 2018; Lyman et al.,
2018; Margutti et al., 2018; Nynka et al., 2018; Pooley et al., 2018; Ruan et
al., 2018; Troja et al., 2018; Fong et al., 2019; Hajela et al., 2019; Piro et
al., 2019; Troja et al., 2019, 2020; Murguia-Berthier et al., 2021; Makhathini
et al., 2021; Hajela et al., 2022; Kilpatrick et al., 2022), are consistent
with a structured jet having an opening angle of $\sim 5^{\circ}$ pointed
$\sim 20^{\circ}$ from our line of sight.

Localizing new EM counterparts to GW events has been a major focus of GW
astronomy since 2017. While GW events up through LVK observing run 4a (O4a;
Abbott et al., 2021; The LIGO Scientific Collaboration et al., 2021, 2024)
have been localized to a precision of, at best, tens of square degrees,
arcsecond localizations of their EM counterparts are necessary to enable
analysis of their host environments, the mechanisms that power their GRB and
KN emission, and new studies in cosmology and NS physics that require both GW
and EM emission. For example, simultaneous detection of NS mergers in GW and
EM emission have led to new constraints on the nuclear equation of state
(Capano et al., 2020), studies of the nature of gravity (Baker et al., 2017),
analysis of NS merger populations in the local Universe to compare with GRBs
discovered at redshift $z>0.1$ (Fong et al., 2017, 2022; Nugent et al., 2022),
a novel method to measure the Hubble constant (Abbott et al., 2017e), and
analysis of the sites and mechanisms for $r$-process production (Cowperthwaite
et al., 2017; Drout et al., 2017; Kasliwal et al., 2017; Kilpatrick et al.,
2017; Smartt et al., 2017).

Of the eight compact-binary mergers that the LVK has detected through its
third observing run (O3), five have one component that is consistent with that
of a BH (i.e., a neutron-star–black-hole merger, NSBH) and a mass ratio where
the secondary component (if an NS) is expected to be disrupted inside the
innermost stable circular orbit, precluding any EM emission.

Besides GW170817, the only other BNS merger yet detected is GW190425, which
consisted of a 2.02$\begin{subarray}{c}+0.58\\\ -0.34\end{subarray}$ and
1.35$\pm$0.26 M⊙ NS with a total mass of 3.4$\begin{subarray}{c}+0.3\\\
-0.1\end{subarray}$ M⊙ (Abbott et al., 2020a). Unfortunately, GW190425 was a
“single-detector” event, only observed by the LIGO Livingston detector.
Consequently, its initial (final) localization was constrained to $10,183$
deg2 ($9,881$ deg2) at 90% confidence, covering roughly one quarter of the
sky. Additionally, its high total mass implies a KN that is fainter and redder
than AT 2017gfo (Foley et al., 2020). Because a large fraction of the
localization region was close to the Sun, no observatory could practically
observe the entire localization region. Moreover, the size of the localization
region and its extent over both hemispheres meant multiple telescopes were
necessary to cover the maximum area possible.

Starting 15.5 hr after the trigger, we observed portions of the GW190425
localization region using five small-aperture telescopes as part of the One-
Meter, Two-Hemispheres (1M2H) team. At the same time, several other teams,
including GRANDMA, GROWTH, GOTO-4, SAGUARO, and others, began their own
observing campaigns (Coughlin et al., 2019; Hosseinzadeh et al., 2019;
Lundquist et al., 2019; Antier et al., 2020; Gompertz et al., 2020). Each
facility has different capabilities in aperture, field of view (FOV), and
location. Additionally, strategies related to choosing pointings, filters, and
cadence resulted in a heterogeneous but vast dataset. No candidate counterpart
has been reported with high confidence in these data (though see Moroianu et
al., 2023, for discussion of a low-significance fast radio burst (FRB)
counterpart), and the possible emission from a KN or sGRB has been limited by
the multiple analyses from the above individual teams on their separate
datasets.

A combined analysis will clearly result in better constraints than analyses of
subsets of the full dataset. Here, we present our UVOIR search for an EM
counterpart to GW190425 and combine those data with previously published data
in Section 2. We are left with 28 viable optical counterparts in this combined
dataset, 4 of which were discovered within 5 days of merger, are confirmed in
the localization volume, and have luminosities that could be consistent with
KNe.

Our detailed candidate vetting process is described in Section 3. We introduce
Teglon111https://github.com/davecoulter/teglon_O4,222https://anathem.fandom.com/wiki/Teglon
(Coulter 2024, in prep.; Coulter, 2021), a new, open-source tool for analyzing
EM search data and performing pixel-level upper limits calculations in Section
4. In Section 4.1, we describe how Teglon is used to perform a sophisticated
analysis of the imaging data from all publicly reported observations and data
newly reported here. We account for the recovery of artificial sources in each
image (when available), line-of-sight extinction, the three-dimensional (3D)
probability from GW data, and available galaxy catalogs and their 3D
completeness. From this analysis, we present in Section 5 the most
comprehensive KN, sGRB, and model-independent constraints on the UVOIR
emission from GW190425 under the assumption that no counterpart to GW190425
was found. Section 6 discusses these results in the context of the LVK’s
current (i.e., fourth; O4) and future observing runs (O5+), and how future
observational campaigns can adjust to improve our chances of discovering the
next GW counterpart, along with a broader discussion of our analysis methods
and prospects for improving the localizations of GW events based on contextual
data.

Throughout this paper, we adopt a flat $\Lambda$CDM cosmology with the
following parameters: H${}_{0}=100h=70$ km s-1 Mpc-1, $\Omega_{\rm M}=0.27$,
and $\Omega_{\rm\Lambda}=0.73$.

##  2 Observations

GW190425 (denoted as S190425z by LIGO Scientific Collaboration & Virgo
Collaboration, 2019) was initially reported to have a BAYESTAR (Singer &
Price, 2016) 90% credible localization of $10,183$ deg2 and a luminosity
distance of $155\pm 45$ Mpc. These were later refined to a final localization
of $9,881$ deg2 and a luminosity distance of 159${}^{+71}_{-69}$ Mpc (Abbott
et al., 2020a). Because of this large area, we consider any data across the
sky relevant if obtained within two weeks of 25 April 2019, including targeted
search data for GW190425 and GW190426_152155, a purported NSBH merger with a
final localization of 1,393 deg2 and a luminosity distance of $377\pm 45$ Mpc
(Abbott et al., 2021). Therefore, we include in our analysis targeted search
imaging data from the 1M2H Collaboration, from Gravity Collective (GC)
partners Las Cumbres Observatory (LCO) and the 0.76 m Katzman Automatic
Imaging Telescope (KAIT; filippenko01) at Lick Observatory, from publicly
reported limits through the Treasure Map (TM) application (Wyatt et al.,
2020), and from the literature and private communication for the Pan-STARRS
and ATLAS telescopes, for both GW190425 and S190426c. These TM data include
limits for both GW events from the Zwicky Transient Facility (ZTF; Bellm et
al., 2019), the Gravitational-wave Optical Transient Observer 4 telescope
(GOTO-4; Steeghs et al., 2022), the Swift Ultra-Violet/Optical Telescope
(Roming et al., 2005), the MLS 10K CCD camera via the Catalina Sky Survey
(CSS; Christensen et al., 2018), and the MMT Cam via the Fred Lawrence Whipple
Observatory (Williams, 2018). In addition to these targeted search data, we
also include untargeted imaging data across all 1M2H telescopes, collecting a
total of 3,598 public and private pointings for this analysis, which
cumulatively cover 48.13% of the two-dimensional (2D) probability and 48.28%
of Teglon-redistributed probability (see Section 4 and 4.1) from the final
maps presented by Abbott et al. (2020a).

Figure 1: The LVC localization region for GW190425. Contours correspond to the
50th ($2,400$ deg2) and 90th ($9,881$ deg2) percentile regions. In blue is the
contour corresponding to the Milky Way $r$-band extinction of 0.5 mag. Near 3
hr of right ascension (R.A.) is the location of the Sun on 25 April 2019, with
a yellow Sun-separation contour of 45∘.

###  2.1 One-Meter Two-Hemispheres Data

The 1M2H Collaboration was established in 2017 and originally used two 1 m
telescopes, the Nickel telescope at Lick Observatory in California and the
Swope telescope at Las Campanas Observatory in Chile, to search for EM
counterparts to GW sources. In 2019 this collaboration was expanded to include
the 0.7 m robotic Thacher telescope at the Thacher School Observatory in Ojai,
CA (Swift et al., 2022), and the A Novel Dual Imaging Camera (ANDICAM; DePoy
et al., 2003) on the SMARTS 1.3 m telescope at Cerro Tololo Interamerican
Observatory, Chile. We present data from this collaboration for the first time
and describe our reduction process and limits below.

####  2.1.1 ANDICAM

We observed galaxies in the localization region of GW190425 with ANDICAM. All
observations were performed from 25–26 April 2019 as described in Table 2.
ANDICAM enables simultaneous optical observations using a charge-coupled
device (CCD) with a $10^{\prime}\times 10^{\prime}$ FOV and IR observations
using an array with a $3.3^{\prime}\times 3.3^{\prime}$ FOV. We searched the
initial localization with the CCD and IR detectors to obtain $I$\- and
$H$-band observations of 25 galaxies within the GW190425 90th percentile
localization region and followed two optical candidates with a combined CCD +
IR filter set of $I$, $J$, $H$, and $K$. All images for the CCD and IR
detectors were reduced using photpipe (Rest et al., 2005), including bias
subtraction, dark corrections for the IR detector, and flatfielding. The
images were aligned using Gaia astrometric standards (Gaia Collaboration et
al., 2021). We then performed photometry in each image using DoPhot (Schechter
et al., 1993). Finally, the images were flux calibrated using Pan-STARRS DR2
photometric standards (Flewelling et al., 2020) transformed into $I$-band
(following transformations by Jester et al., 2005) and 2MASS $H$-band
standards (Skrutskie et al., 2006). We obtained follow-up observations of each
field to use as templates for subtraction from 5–11 June 2019. After
processing each image using the methods mentioned above, we subtracted the
reference images from our science frames using HOTPANTS (Becker, 2015). Final
photometry for all transient sources in each difference image was obtained
using a custom version of DoPhot.

####  2.1.2 Nickel

We observed galaxies in the localization region of GW190425 with the Direct 2k
$\times$ 2k ($6.8^{\prime}\times 6.8^{\prime}$) camera on the Nickel 1 m
telescope at Lick Observatory, Mt. Hamilton, California. We performed targeted
observations of candidate host galaxies in the $r$ band from 26 April 2019 to
9 May 2019, and we include in our analysis untargeted $BVri$ observations in
the same date range that are also within the GW190425 90th percentile
localization region. All observations were reduced following the procedure
described above for ANDICAM CCD imaging, including image subtraction with
templates obtained from 22 April 2018 to 10 May 2020 and forced photometry on
all candidate optical counterparts using DoPhot.

####  2.1.3 Thacher

We observed GW190425 with the Andor 2k $\times$ 2k camera
($20.8^{\prime}\times 20.8^{\prime}$) on the 0.7 m robotic Thacher telescope
at the Thacher School Observatory in Ojai, CA (Swift et al., 2022). We include
$griz$ follow-up data targeting the 90th percentile localization region of
GW190425 obtained from 26 April 2019 to 4 May 2019. All imaging was reduced
following the aforementioned methods and by Kilpatrick et al. (2021). Template
imaging of each field was obtained from 23 February 2019 to 6 August 2021. Our
final observation list is given in Table 2.

####  2.1.4 Swope

We observed the localization region of GW190425 with the Direct 4k $\times$ 4k
camera ($29.8^{\prime}\times 29.7^{\prime}$) on the 1 m Swope telescope at Las
Campanas Observatory, Chile. Our Swope observations consisted of targeted
observations within the 90th percentile localization region of GW190425 in the
$i$ band obtained from 25 April 2019 to 9 May 2019 and untargeted $uBVgri$
observations within the same area and time frame. These data were reduced
following the ANDICAM/CCD procedures described above. We obtained template
imaging from 16 August 2018 to 25 February 2020 to perform image subtraction
in each frame and search for optical transients, and to generate forced
photometry on known optical transients in each image.

####  2.1.5 SN 2019ebq and MOSFIRE

We obtained near-infrared (NIR) spectroscopy of the candidate counterpart to
GW190425 SN 2019ebq on 2019 Apr 26, 14:32:11 UTC with the Multi-Object
Spectrometer For Infra-Red Exploration (MOSFIRE; McLean et al., 2012) on the
Keck I 10 m telescope. The spectrum was originally reported and described by
Dimitriadis et al. (2019). We reduced the spectrum following standard
procedures using spextool and show the final reduced spectrum in Figure 2.
Similar to findings by Dimitriadis et al. (2019) and Nicholl et al. (2019), we
classify this source as an SN Ib/c near peak light based on comparison to a
Keck/NIRES spectrum of the Type Ib SN 2022bck presented by Tinyanont et al.
(2024).

Figure 2: MOSFIRE NIR spectrum of SN 2019ebq (black), covering the $J$ band
blueward of 12,900 Å, obtained on 2019 Apr 26, 14:32:11 UTC on Keck I. The
spectrum has been smoothed to a resolution of 17 Å (yellow) for analysis of
the broad transient features present at these wavelengths. Our SN 2019ebq
MOSFIRE spectrum appears consistent with a Type Ib/c SN, and is therefore
unrelated to the GW event (see 2.1.5; Dimitriadis et al., 2019). We
demonstrate this point by comparing it to a Keck/NIRES spectrum of the Type Ib
SN 2022bck presented by Tinyanont et al. (2024). The similarity between these
spectra reinforces the nature of this object as an SN and not a GW
counterpart.

###  2.2 Gravity Collective Data

####  2.2.1 KAIT

The 0.76 m KAIT (Richmond et al., 1993; Filippenko et al., 2001) at Lick
Observatory targeted galaxies in the localization regions of GW190425 and
GW190426 between 2019 April 25 and 27, as described by (Zheng et al., 2019a,
b). Galaxies were selected from GLADE (Dálya et al., 2018), according to their
$B$-band luminosity, with target priority reweighted by elevation at the time
of observation. All observations were performed in a “Clear” filter. 688
galaxies were targeted between both events, with all fields being reimaged in
July 2023 to provide templates of the same fields for detailed analysis.
Following standard imaging and photometry procedures (e.g., (Ganeshalingam et
al., 2010); (Zheng et al., 2017)), the images were calibrated, and point-
spread-function (PSF) photometry was performed using DAOPHOT (Stetson, 1987)
in IDL. The throughput of the KAIT “Clear” filter is close to that of the $R$
band (Li et al., 2003), so local AAVSO Photometric All-Sky Survey (APASS)
standards (Henden et al., 2015) were transformed to the Landolt (1992) $R$
band following Jester et al. (2005). Template images were then subtracted from
the August 15 and 18 epochs using a custom IDL-based image-subtraction
pipeline for PSF convolution. Finally, we estimate the limiting magnitude in
each subtracted image using the flux-weighted average of the sky background in
the convolved science and template frames, which is reported in Table 2.

####  2.2.2 LCO

The Gravity Collective combines follow-up efforts by 1M2H and the Las Cumbres
Observatory (LCO) Global Telescope network (Brown et al., 2013), which
includes fourteen 0.7-1 m telescopes distributed worldwide. LCO observed the
localization region of both GW190814 and S190426c, with a galaxy-targeted
search and prioritization strategy described by (Arcavi et al., 2017b). For
both GW events, LCO obtained 773 exposures of duration 300 s each in $gri$
using the Sinistro cameras ($26^{\prime}\times 26^{\prime}$ FOV) mounted on
these telescopes (Keinan et al. in prep.). Image processing was performed by
the LCO BANZAI pipeline (McCully et al., 2018), and limiting magnitudes were
calculated using LCOGTSNpipe (Valenti et al., 2016). Sloan Digital Sky Survey
(SDSS) (Abazajian et al., 2009), PS1 (Flewelling et al., 2020), or DECam
(Abbott et al., 2018) template images were used in the science image bands to
perform image subtraction using PyZOGY (Zackay et al., 2016; Guevel &
Hosseinzadeh, 2017). The limiting magnitudes were calculated by determining
the Poisson noise due to the sky using the median absolute deviation of the
entire image. The Poisson and read noise were combined, and the 3$\sigma$
limiting magnitude (median limiting magnitude of 22.1 mag) was estimated by
inverting the standard signal-to-noise ratio (S/N) equation.

###  2.3 Public Data via Treasure Map

####  2.3.1 ZTF

ZTF is a 47 deg2 FOV optical instrument on the Palomar 48-inch Schmidt
telescope (Bellm et al., 2019). We include 313 ZTF pointings reported to TM
with a status of “completed” for GW events GW190425 and GW190426_152155, and
whose image-reduction process is outlined by (Coughlin et al., 2019).
Pointings span the $g$, $r$, and $i$ bands, with a median $r$-band depth of
$\sim 21.5$ $m_{\mathrm{AB}}$. Within TM, each pointing includes the central
coordinate of the FOV, filter, MJD of the observation, and limiting AB
magnitude.

####  2.3.2 CSS

CSS operates the MLS 10k CCD camera on the Mt. Lemmon 1.5 m telescope, which
has a $\sim 5$ deg2 FOV and was used by the Searches after Gravitational Waves
Using ARizona Observatories (SAGUARO) team to search for 17 GW events within
O3 (Lundquist et al., 2019; Paterson et al., 2021). We include 61 pointings
taken in an open filter to a median limiting mag of $\sim 21.3$
$m_{\mathrm{AB}}$.

####  2.3.3 GOTO-4

The GOTO-4 telescope (Steeghs et al., 2022) is a prototype array of 4
telescopes with a combined FOV of $\sim 18$ deg2. The GOTO team searched for
29 GW event triggers in LIGO’s O3 (Gompertz et al., 2020), and we include 399
pointings that span the $g$ and $V$ bands, with a median $g$-band depth of
$\sim 19.8$ $m_{\mathrm{AB}}$.

####  2.3.4 MMT

The 6.5 m MMT at Fred L. Whipple Observatory in Arizona conducted a galaxy-
targeted search with MMTCam for EM counterparts to both GW190425 and S190425c
(Hosseinzadeh et al., 2019). We include 119 pointings in $g,i$, with a median
$i$-band depth of 21.9 $m_{\mathrm{AB}}$.

####  2.3.5 Swift

In O3, Swift searched 18 GW events using a galaxy-targeted approach (Evans et
al., 2016), including GW190425 and S190426c, with the Ultra-Violet/Optical
Telescope (Oates et al., 2021). These data include 1357 pointings for GW190425
and S190426c in the $u$ band with a median limiting magnitude of 19.4
$m_{\mathrm{AB}}$. These data are particularly interesting as they cover a
region of parameter space which is unique given the other optical filters in
this combined dataset.

###  2.4 Public Data via Literature Review

####  2.4.1 Pan-STARRS

The Pan-STARRS data used in this study come from the Pan-STARRS 1 (PS1)
telescope, at the summit of Haleakala on the Hawaiian island of Maui. PS1 is
equipped with a composite 1.4 Gigapixel camera and has a FOV of 7.06 deg2 in a
circular aperture; this FOV is broken into a tessellation of
“skycells”333https://outerspace.stsci.edu/display/PANSTARRS/PS1+Sky+tessellation+patterns,
each having a dimension of $\sim 24^{\prime}\times 24^{\prime}$ (Chambers et
al., 2016). Each skycell can be treated as an individual pointing that
inherits the parent’s world coordinate system and image depth, and allows PS1
upper-limits data to be more easily analyzed by Teglon. The PS1 telescope
began searching the localization of GW190425 $\sim 80$ min after the GW
trigger, and continued for the following three days, publishing their upper
limits (Smartt et al., 2024). The pointings and limits derived from these data
were shared with our team via private communication and include 6,558 skycells
covering a unique sky area of $\sim$$1,085$ deg2 in the $i$ band to an average
depth of $\sim 21.5$ mag.

####  2.4.2 ATLAS

The Asteroid Terrestrial-impact Last Alert System (ATLAS) telescope system is
a network of four identical telescopes, with two telescopes located on the
Hawaiian Islands (one on Haleakala and another on Mauna Loa), one telescope in
El Sauce, Chile, and the last telescope in Sutherland, South Africa (Tonry et
al., 2018). Each telescope has a rectangular FOV of 28.9 deg2, and over the
course of $\sim 7$ days observed the localization of GW190425, publishing
their upper limits (Smartt et al., 2024). The pointings and limits derived
from these data were shared with our team via private communication and
include 437 pointings covering a unique sky area of $\sim$$7,110$ deg2 in the
ATLAS $o$ and $c$ bands to an average depth of $\sim 18.9$ mag.

Figure 3: Visualization of the full EM search dataset for this work. In each
orthographic projection, black contours correspond to the 50th/90th
localization of GW190425, and Milky Way extinction is marked as a blue contour
at ${\rm A}_{r}=0.5$ mag. Overplotted are all instrument FOVs: ZTF (dark
blue), ATLAS (light orange), GOTO-4 (turquoise), CSS (purple), Swope (black),
Las Cumbres (magenta), PS1 Skycells (dark orange), Thacher (hot pink), Swift
(red), Nickel (cyan), KAIT (gray), ANDICAM CCD (lime green), MMTCam (light
blue), and ANDICAM IR (dark green). Upper left: Close-up view of the Eastern
Spur of probability as seen in Figure 1, R.A. $\in[95,315]$ deg. Every
instrument in our manifest has imaging in this hemisphere (10,365 total field
centers; 266 not shown), covering 45.2% of the final LVC 2D probability. Upper
right: A $12^{\circ}$-radius zoom-in on R.A. 245 deg, Declination (Decl.)
$+$20 deg, showing a detailed view of the smaller FOV instruments. The
grayscale gradient is the 2D probability of the localization, with the
50th/90th contours labeled. Many of these fields covered the same sky regions
multiple times in the same filters and highlight an opportunity to coordinate
EM follow-up efforts (see Section 6). Lower left: Close-up view of the Western
Spur of probability as seen in Figure 1, R.A. $\in[0,95]$ deg. Only ATLAS,
GOTO-4, Swope, and Swift have observations in this hemisphere (355 total)
owing to this region being close to the Sun, contributing only 3.1% of the
covered 2D probability. A yellow Sun contour denotes a $45^{\circ}$ separation
that marks Swift’s pointing limits.

##  3 Candidates

###  3.1 1M2H Vetted Candidates

After subtracting templates from the ANDICAM, Nickel, Swope, and Thacher
images, we identified candidate counterparts to GW190425 by searching for
sources of positive emission in the difference images. We first ran DoPhot on
the difference images, searching for sources detected at a S/N threshold of
$\geq 3\sigma$. We performed minimal filtering on the detected sources,
particularly removing those where $>30$% of pixels inside the PSF aperture are
negative or where $>40$% of pixels are masked. Apart from these cuts, we
required only that a candidate transient is detected in a single image at our
S/N threshold.

All candidates were then gathered by field into web pages with cutout images
showing the candidate detection from every epoch, the scatter in candidate
coordinates for each detection, and the difference light curve in terms of
flux and magnitude. Members of the 1M2H collaboration all visually vet these
web pages to rule out detections that appear consistent with artifacts such as
a convolved cosmic ray, correlated noise across a bad section of each
detector, dipole emission associated with a bright and poorly subtracted star,
or a satellite or other moving object passing through the image frame.

We required that a candidate transient be flagged only by a single human
vetter to elevate that source for our candidate analysis pipeline. Following
analysis similar to that of Kilpatrick et al. (2021) and public candidates
described below, we crossmatched the candidates to sources classified as stars
by Gaia (point source score (PSS) $>0.99$ following the PSS value from Gaia
Collaboration et al., 2021), were within 2${}^{\,\prime\prime}$ the location
of a minor planet at the time of observation based on ephemeris from the Minor
Planet Catalog444https://minorplanetcenter.net, or were crossmatched to known,
public transients in the Transient Name Server555https://www.wis-tns.org/.
After these checks, we identified four novel candidate transients that were
reported to TNS: AT 2019aasp, 2019aasq, 2019aasr, and 2019aass (Coulter et
al., 2023a). These and all other candidate transients reported to TNS were
then analyzed using methods described below. In Figure 4 we show photometry
from candidates discovered by 1M2H in comparison to model KN light curves
described in Section 5.1.

Figure 4: Photometry from the four candidate counterparts to GW190425
discovered within the localization region by 1M2H and described in Section
3.1. We show the time of detection as a circle in each panel, with green
corresponding to $r$-band photometry and yellow to $i$-band photometry. For
comparison, we overplot model KN light curves for a hypothetical event with
ejecta mass 0.023 M⊙, velocity 0.26$c$, and an electron fraction $Y_{e}=0.45$
as described in Section 5.1. Figure 5: Image cutout triplet for AT 2019aasq, a
counterpart candidate discovered by the Swope telescope +4.93 days after the
GW trigger, that our analysis cannot rule out as a candidate counterpart to
GW190425 and which we characterize as a “more likely” kilonova candidate (see
Sections 3 and Appendix A.1 for a detailed discussion). Both the reference
(left; MJD 58638.18288) and science (middle; MJD 58603.27694) images were
obtained by Swope and show the same $26.1^{\prime\prime}\times
26.1^{\prime\prime}$ region of sky centered on AT 2019aasq. The difference
image (right) highlights the discovery detection of the transient at
$i=21.30\pm 0.19$ mag. We note that the candidate is clearly visible $\sim
7.5$${}^{\,\prime\prime}$ from the center of its likely host galaxy WISEA
J154032.14+282013.7 at $z=0.031090$ (Coulter et al., 2023b), within the
1$\sigma$ most likely GW190425 volume. AT 2019aasq was not detected with
either ATLAS $c$ or $o$ bands, or ZTF $g$ or $r$ bands, despite coverage
within days of this detection, implying it was likely an intrinsically red,
faint transient.

###  3.2 Public Candidates

We used our candidate analysis pipeline to vet candidate counterparts to
GW190425 in the context of the final
GW190425_PublicationSamples666https://gracedb.ligo.org/superevents/S190425z/files/
localization map, time discovered from merger, coincidence with likely stars
or other known point sources and minor planets, spectral classification as a
transient type unlikely to be associated with an NS merger, association with a
host galaxy outside the localization volume defined by the bayestar map, and
photometric evolution that does not resemble a likely KN or afterglow
counterpart. In general, these cuts follow the methods described by Kilpatrick
et al. (2021) and the examples implemented by Kilpatrick (2023). Here we
summarize each step.

  1. 1.

Importation of candidates from our transient database YSE-PZ (Coulter et al.,
2023c), which includes all transients and metadata contained in TNS.

  2. 2.

We analyze only candidates discovered within the first 14 days after the
coalescence time of GW190425 on 2019 April 25, 08:18:05 UTC as defined by
Abbott et al. (2020a). Moreover, we only analyze candidates within the 2D 90th
percentile as defined by the final GW190425_PublicationSamples map of that
event. These two initial cuts define our sample of 290 candidate counterparts
analyzed in the remaining steps below.

  3. 3.

We crossmatch to minor planets using the time of discovery and coordinates of
each candidate and using the Minor Planet
Checker777https://cgi.minorplanetcenter.net/cgi-bin/checkmp.cgi. Any source
found within 2${}^{\,\prime\prime}$ of a known minor planet at the time of
observation is ruled out. In total, 2 candidates were ruled out by this check.

  4. 4.

We crossmatch to point sources within the Gaia (Gaia Collaboration et al.,
2021) and Pan-STARRS DR2 catalogs (Flewelling et al., 2020). For Gaia, this
involves checking for sources aligned within 2${}^{\,\prime\prime}$ of a
source with point-source score $>0.99$, while for Pan-STARRS we check for
candidates within 2${}^{\,\prime\prime}$ of a source classified as point-like
by the PS1 detection-flagging
algorithm888https://outerspace.stsci.edu/display/PANSTARRS/PS1+Detection+Flags.
13 candidates were ruled out for coincidence with Gaia sources while no
candidates were ruled out owing to coincidence with Pan-STARRS sources.

  5. 5.

For candidates with spectroscopic follow-up observations, we rule out those
with a spectral classification that is inconsistent with a KN or GRB
afterglow. For GW190425, this sample comprises sources classified in TNS as a
cataclysmic variable (CV), SLSN, SN Ia, SN Ib, SN Ic, SN II, and SN IIn, which
are known to arise from progenitor systems other than NS mergers. 31
candidates were ruled out based on their spectral classifications.

  6. 6.

We rule out candidates with pre-merger activity within 2${}^{\,\prime\prime}$
of the transient location based on a positive detection using forced
photometry in ASAS-SN (Kochanek et al., 2017), ATLAS (Tonry et al., 2018;
Smith et al., 2020; Shingles et al., 2021), or ZTF (Bellm et al., 2019). For
additional details on our querying method, see Coulter et al. (2023c). We rule
out 3 candidates that have premerger variability.

  7. 7.

In addition to candidates outside the nominal localization area, we associate
all candidates with host galaxies when possible and rule out candidates that
are outside the 90th percentile localization volume defined by the final
GW190425_PublicationSamples localization map. We derive our host-galaxy sample
from those with spectroscopic redshifts in the NASA/IPAC Extragalactic
Database (NED)999http://ned.ipac.caltech.edu/ or a photometric redshift from
the PS1-STRM (Beck et al., 2021), Photometric Redshifts for the Legacy Surveys
(Legacy; Zhou et al., 2021), or 2MASS Photometric Redshift (2MRS; Bilicki et
al., 2014) catalogs. Note that we place priors on the galactocentric host
offsets of $<300$${}^{\,\prime\prime}$ and $<75$ kpc (consistent with the
maximum short GRB host offsets identified by, e.g., Fong & Berger, 2013; Fong
et al., 2022) in selecting the most likely host galaxy, then associate each
transient with the galaxy that provides the smallest physical offset from the
GW candidate. In this way, we ruled out 183 candidates.

  8. 8.

Finally, we rule out candidates with photometry whose absolute magnitude,
decline rate, or color evolution appears inconsistent with KN or afterglow
emission. The details of this calculation are described by Kilpatrick et al.
(2021). At this stage, there remained 58 viable candidates, of which we ruled
out 30 owing to photometric evolution inconsistent with being a counterpart to
GW190425. There remain 28 viable candidate counterparts.

Based on each of the steps described above and the lack of spectroscopic
follow-up observations, we cannot definitively characterize any of these
sources as a GW counterpart (i.e., as a KN or GRB afterglow), so additional
analysis of each source has limited utility. However, taking the remaining
sources in our analysis, we can differentiate between sources that are more
likely to be GW counterparts versus interloping transients. We provide a more
detailed description of four of the remaining candidates considered to be the
most likely counterparts to GW190425 in Appendix A.

Figure 6: Top: The localization map resampled by Teglon. At GW190425’s
distance, Teglon redistributes half of the total 2D probability to the highest
probability galaxies (see Section 4.1). A $12^{\circ}$-radius zoom-in panel is
marked by a square centered on R.A. 245 deg, Decl. $+$20 deg. All other
attributes are the same as in Figure 1. Bottom left: For comparison, we show a
zoom-in of the original localization map with white contours denoting the
original 50th/90th localization. Within the bounding box of R.A.
$\in[235,255]$ deg and Decl. $\in[10,30]$ deg, there is $\sim 8.2$% of the
localization probability within $\sim 377$ deg2. Bottom right: The same zoom-
in region with Teglon’s redistribution algorithm (matching the top plot). The
same amount of probability ($\sim 8.2$%) is covered in only $\sim 100$ deg2,
increasing the coverage efficiency by a factor of $\sim 3.8$.

##  4 Teglon

One effective method for localizing the EM counterparts of GW sources is to
target the bright/massive galaxies residing in the locus of high probability
within a GW localization volume (Kanner et al., 2012; Gehrels et al., 2016).
This technique relies on two key factors: a galaxy catalog that is relatively
complete at the ranges where GW sources are likely to be detected, and
localization regions that are small enough to be efficiently searched with
ground-based telescopes. To date, several catalogs have been used in GW
follow-up searches (Kopparapu et al., 2008; White et al., 2011; Dálya et al.,
2018, 2022; Cook et al., 2023), and all contain the key attributes of
position, distance, and $B$-band magnitudes. The $B$ band is used in
particular because the rate of BNS mergers is expected to follow the star-
formation rate (SFR) in the local universe, and $B$ is a convolution of this
SFR with a galaxy’s total stellar mass (Phinney, 1991; Belczynski et al.,
2002). In 2017, this technique led to the discovery of the first optical
counterpart, AT 2017gfo (Coulter et al., 2017), to a GW source, GW170817.
GW170817 was the first-ever BNS merger detected in GWs, and localized to an
area of 31 deg2 and a luminosity distance of $40^{+8}_{-14}$ Mpc (Abbott et
al., 2017d). In searching for this counterpart, 1M2H used the Gravitational
Wave Galaxy Catalogue (GWGC), which at 40 Mpc is nearly 100% complete when
compared to a Schechter galaxy luminosity function (Schechter, 1976) for
galaxies with a characteristic luminosity of $\leq-20.3$ mag.

However, as the LVK has improved the GW network detection sensitivity (Abbott
et al., 2016c), these catalogs and techniques have become less effective. In
O3, the typical BNS inspiral range was $\sim 108$–135 Mpc (Abbott et al.,
2021). For BNS mergers $>2.8$ M⊙, or face-on mergers, the detection distance
may be much larger. To this point, GW190425 was a uniquely massive BNS merger
at 3.4${}^{+0.3}_{-0.1}$ M⊙, and was detected at a luminosity distance of
$159^{+69}_{-71}$ Mpc (Abbott et al., 2020a). At this distance, the Galaxy
List for the Advanced Detector Era (GLADE; Dálya et al., 2018) catalog is only
$\sim 50$% complete in galaxy luminosity, meaning that a naive approach of
simply targeting bright galaxies in the catalog would miss half the total
galaxy luminosity in the volume. Despite this, as BNS detection ranges
increase, the surface density of galaxies in projection increases so that any
field of view should contain many galaxies (both cataloged and uncataloged).
Naively, a pure tiling approach to searching for a counterpart is more
effective at larger distances, but this picture is complicated by
inhomogeneous galaxy catalog coverage. Intelligently trading off between these
two approaches — to use our knowledge of where galaxies are to target them and
to tile the localization region when we do not — motivates the creation of a
new tool called Teglon. A detailed treatment of how Teglon transforms GLADE,
implements its completeness weighting, and calculates its pixel-level upper
limits will be presented in a forthcoming companion paper.

###  4.1 GW190425 Transformed By Teglon

Teglon’s EM search optimization depends on two properties: the $B$-band
luminosity completeness of its volume pixels, or voxels, in the GW
localization volume, and how much area that GW localization volume subtends on
the sky in projection. Completeness is largely dictated by the average
luminosity distance to an event; however, in regions of high galaxy catalog
completeness (e.g., SDSS Stripe 82 (Annis et al., 2014) or the survey
footprint of 2dF (Colless et al., 2001)), Teglon’s algorithm can still be
effective at redistributing probability in the original GW localization to
high-probability galaxies, thereby reducing the area an instrument needs to
search. However, the area in projection of a GW localization also matters — if
the area subtended by a GW localization fits within the FOV of a search
instrument (e.g., GW170817’s localization ), redistributing probability on
scales smaller than the FOV would not change the search strategy. In the edge
case of 0% completeness, or very small projected areas, Teglon’s optimization
is identical to a pure tiling pattern of the high-probability region.

The localization of GW190425 is a quintessential use case for Teglon. Because
this event was only detected by the LIGO Livingston detector, its location was
constrained to nearly a quarter of the sky ($9,881$ deg2). However, despite
this large area, the distance was relatively close at $159$ Mpc (Abbott et
al., 2020a). At this distance, the GLADE catalog is on average $\sim 50$%
complete, and therefore Teglon redistributed half of the localization
probability to galaxies at the correct distance. This resampling reduces the
90th percentile localization to $6,674$ deg2, a factor of $\sim 1.5$. Figure 6
shows the resulting localization, with insets that highlight this updated
concentration of probability.

Table 1 shows a synoptic view of the effect Teglon has on the search
efficiency increase, $\eta$, for each instrument in the dataset. The value of
$\eta$ is markedly enhanced for detectors with FOVs $\leq 1$ deg2. In general,
these instruments followed a galaxy-targeted approach, and owing to the high
completeness of GLADE with respect to GW190425’s localization, the
redistributed map provided by Teglon confirmed that these galaxies were in
regions of the sky more likely to host the progenitor of the GW event. For
this particular event, 3,402 of the original map pixels ($\sim 178$ deg2) had
their probability values boosted by factors of $\geq 10$ over their original
values, and constitute 16% of the total probability in the map.

For this dataset, while all instruments have $\eta\geq 1.0$, instruments with
FOVs $\geq 1$ deg2 saw diminishing returns owing to the fact that their large
footprint on the sky allowed them to simply tile the entire Western Spur of
the localization (see Figure 3). Because of this, the survey footprint of
these instruments encompassed both the pixels where probability was being
concentrated and the voids left in between, resulting in $\eta$ approaching
unity. However, in the maximal case where a GW event subtends the entire sky
but is detected at a distance where GLADE is 100% complete (e.g., at the
distance of GW170817; 40 Mpc), Teglon would be useful for even the largest FOV
instruments.

Table 1: GW190425 Search Synopsis

Search Instrument | FOV | # of Fields | Total 2D Probability | Total Redistributed ProbabilityaaSee Section 4 for a detailed description. | Efficiency Increase
---|---|---|---|---|---
| (deg2) |  |  $\sum_{i}$$P_{{\rm 2D}_{i}}$(%) |  $\sum_{i}$$P^{{}^{\prime\prime}}_{{\rm 2D}_{i}}$(%) |  $\eta$$\equiv$$\sum_{i}$$\frac{P^{{}^{\prime\prime}}_{{\rm 2D}_{i}}}{P_{{\rm 2D}_{i}}}$
ANDICAM IR | 0.0015 | 21 | 0.04 | 0.46 | 11.36
MMTCam | 0.0020 | 118 | 0.15 | 1 | 6.44
ANDICAM CCD | 0.0112 | 27 | 0.06 | 0.62 | 10.39
KAIT | 0.0128 | 412 | 0.23 | 1.7 | 7.37
Nickel | 0.0438 | 137 | 0.19 | 0.92 | 4.98
Swift | 0.0803 | 1357 | 0.72 | 3.84 | 5.32
Thacher | 0.1200 | 186 | 0.09 | 0.42 | 4.54
Las Cumbres | 0.1951 | 754 | 0.35 | 1.42 | 4.02
Swope | 0.2459 | 204 | 0.59 | 1.87 | 3.19
CSS | 4.9997 | 61 | 6.15 | 6.98 | 1.13
PS1bbPS1 effective FOV is calculated from the average number of PS1 skycells in a fiducial PS1 FOV. | 7.068 | 148 | 18.79 | 19.99 | 1.06
GOTO-4 | 18.1300 | 399 | 30.48 | 32.01 | 1.05
ATLAS | 28.8906 | 437 | 47.02 | 45.84 | 0.97
ZTF | 46.7253 | 313 | 28.99 | 30.4 | 1.05
All Tiles | 9078.59ccTotal unique area covered by all observations. | 10984 | 48.13 | 48.28 | 1.00ddEfficiency boost approaches 1 as both more area is observed and the FOV of the instrument increases; however, this relation is not monotonic because it depends on whether the original pointings remain in high-probability locales after Teglon redistributes probability.

Note. — A synopsis of Teglon’s effect on the community’s combined EM search
campaign for GW190425. Teglon strongly enhances $\eta$ for instruments with
FOVs $\leq 1.0$ deg2, see Section 4.1.

###  4.2 Model Detection Efficiencies Calculated By Teglon

A thorough presentation of Teglon’s pixel math will be presented by Coulter et
al. (2024, in prep.); however, a brief treatment here will serve to
contextualize our results in Section 5. To compute the efficiency with which
Teglon detects a model given a set of observations, or “model detection
efficiency,” each instrument referenced in Section 2 is represented as a
collection of polygons, and together with the celestial coordinates of every
pointing in Table 2, uses the healpy library to return every pixel contained
within these observations from the final localization map for GW190425. Each
of these pixels contain a marginal 2D probability for the GW originating from
its sky position, $P_{\mathrm{2D},i}$, as well as GW-derived distance
distribution parameters, $\bar{D_{i}}$ and $\sigma_{D_{i}}$.

For each pixel $i$, we then retrieve the set of covering $j$ observations
(i.e., filter $f$ and limiting magnitude $m_{j,f}$), as well as the matching
absolute magnitude for a model under consideration $M_{\mathrm{model}_{j,f}}$.
We combine the line-of-sight extinction ($A_{f}$; derived from Schlafly &
Finkbeiner, 2011), and reparameterize $m_{j,f}$ in terms of the distance
$D_{\mathrm{model}_{j,f}}$ we would expect to detect a source in pixel $i$, as

$\displaystyle\mu_{\mathrm{model}_{j,f}}=m_{j,f}-M_{\mathrm{model}_{j,f}}-A_{f}\,,$
(1) $\displaystyle
D_{\mathrm{model}_{j,f}}~{}\mathrm{[Mpc]}=10^{0.2\times(\mu_{\mathrm{model}_{j,f}}-25)}\,.$
(2)

To calculate the weight of finding the counterpart we integrate this distance
distribution,

$W_{\mathrm{model}_{i,j}}=\frac{1}{\sqrt{2\pi}\sigma_{D_{i}}}\int_{0}^{D_{\mathrm{model}_{j,f}}}e^{-\frac{1}{2}\left(\frac{\bar{D_{i}}-D}{\sigma_{D_{i}}}\right)}dD\,.$
(3)

To combine independent observations we take the complement of the joint
probability that we do not see the source in any epoch — that is, we weight
the relative likelihood we would detect a specific model in image $j$ with
$P_{\mathrm{2D},i}$ and sum over all pixels to obtain a cumulative probability
of detecting a specific model,

$P_{\mathrm{model}}=\displaystyle\sum_{i}P_{\mathrm{2D},i}\left[1-\prod_{j}\left(1-W_{\mathrm{model}_{i,j}}\right)\right]\,.$
(4)

This final model-detection efficiency is interpreted as the likelihood that we
would have seen a source with the properties of the given model with our
observations, for a wide range of models described below in Section 5.

##  5 Model Comparisons

Based on the results of Section 3.2, we assume that there are no credible EM
candidates for GW190425, and interpret the image depth for the data presented
in Table 2 and in the Treasure Map (described in Section 2) as limits on a few
classes of hypothetical EM counterparts to a BNS merger. To make this
physically meaningful, we assume (and in the case of the data in Table 2, we
know) that the data are homogeneous in that (1) each datum is the result of
subtracting an in-band template image from the search image using the same
instrument configuration, and (2) the reported depth of each image was
computed by estimating the $\geq 3\sigma$ limiting magnitude from the
difference image. We perform the joint model detection efficiency calculation,
combining all reported epochs, depths, and filters, using the formalism
described in Section 4.2. The maximum probability to detect any model is
limited by the total amount of probability that the full dataset covers;
therefore, we report our detection probability in two ways: (1) as the
probability calculated by Equation 4, and (2) as a percent of the total amount
of redistributed probability reported in Table 1, 48.28%, i.e., $X$%
($\frac{X}{48.28}$%). This relative detection efficiency characterizes the
effectiveness of the observations themselves, assuming they could have covered
the entire localization region.

###  5.1 Kilonovae

The discovery of the EM counterpart to GW170817, the KN AT 2017gfo (Coulter et
al., 2017; Abbott et al., 2016d), demonstrated that BNS mergers are associated
with short-lived thermal transients with luminous UVOIR emission, consistent
with radioactive decay of freshly synthesized heavy elements (Drout et al.,
2017). A KN light curve’s peak luminosity, color, and evolution timescale
depend on the amount of mass the merger ejected $M_{\rm ej}$, the ejecta’s
expansion velocity $v_{\rm ej}$, and the ejecta’s opacity $\kappa$ (Arnett,
1982). The exact value of $\kappa$ is driven by the atomic structure of the
specific chemical species, but in general, elements with atomic mass $A>140$
have many millions of bound-bound line transitions so that their opacities are
$>10$ times that of Fe. This high opacity increases the photon diffusion
timescale (and therefore the light curve evolution timescale), and shifts the
emission from the UV/optical to the IR (Kasen et al., 2013). Surprisingly,
observations of AT 2017gfo showed that multiple ejecta components of different
compositions (i.e., opacities) were required to accurately model its light
curves (Cowperthwaite et al., 2017; Kilpatrick et al., 2017; Villar et al.,
2017a).

We consider two fiducial KNe models, a “blue” KN and a “red” KN, following the
prescription of Villar et al. (2017a) to generate models with varying ejecta
masses ($M_{\rm ej}$), velocities ($v_{\rm ej}$), and opacities (see also
Villar et al., 2017b). We do so in the Modular Open Source Fitter for
Transients (MOSFiT) framework (Guillochon et al., 2018), with fixed parameters
and bandpasses matched to our dataset. In general, these models adopt a
blackbody spectral profile with the photospheric temperature evolving to a
floor, similar to the “freeze out” in spectral shape observed at late times
with GW170817/AT 2017gfo ($\sim 2500$ K; see Drout et al., 2017, corresponding
to the recombination temperature of species with open $f$ shells). We adopt
$\kappa=0.5$ cm2 g-1 as the “blue” model and $\kappa=3.65~{}$cm2 g-1 as the
“red” model, matching the parameters for a two-component model originally
presented by Cowperthwaite et al. (2017) and Villar et al. (2017a).
Furthermore, in the context of an extremely lanthanide-rich model with high
opacities, we consider $\kappa=10~{}$cm2 g-1, which is also the highest
opacity model adopted by Villar et al. (2017a). Otherwise, we consider ejecta
masses of 0.001–0.5 M⊙ and velocities of 0.05$c$–0.50$c$ for all sets of
models. For each KN model set, we show our estimated detection probabilities
in Figure 7. We detect a blue, AT 2017gfo-like KN at 28.4% (59.0%) and are
insensitive to a red, AT 2017gfo-like KN at 2.9% (6.0%). From these
constraints, an immediate conclusion is that to be sensitive to more-massive
events (e.g., another GW190425-like or NSBH event), EM search teams should
search at redder wavelengths with deeper limits. See Section 6 for a
discussion on coordinating multiband searches with Teglon.

Figure 7: Detection probabilities for KN models from Villar et al. (2017a) as
a function of ejecta mass ($M_{\rm ej}$ in M⊙), ejecta velocity ($\beta_{\rm
ej}$ in natural units), and opacity ($\kappa$). In the upper-left corner of
each plot, we have grayed out the region where the binding energy of the
ejecta mass exceeds its kinetic energy assuming a stiff NS equation of state
and an NS radius of $20$ km. We show contours of equal probability in
turquoise and contours of equal kinetic energy for the ejecta in white. Model
values for AT 2017gfo-like components are taken from Villar et al. (2017a),
Table 2. Left: KN models with $\kappa=0.50$ cm2 g-1, overplotted with the blue
component of AT 2017gfo ($\beta_{\rm ej}=0.256$, $M_{\rm ej}=0.023$ M⊙) which
we can rule out at detection probability 28.4%. Right: KN models with
$\kappa=3.65$ cm2 g-1, overplotted with the red component of AT 2017gfo
($\beta_{\rm ej}=0.149$, $M_{\rm ej}=0.050$ M⊙) which we cannot rule out at a
detection probability of 2.9%. Figure 8: “Red” KN models in the same style as
Figure 7, with $\kappa=10.0$ cm2 g-1, chosen to reflect the high opacity of
neutron-rich ejecta expected from a BNS merger that directly collapses to a
BH. Overplotted are two realizations of ejecta mass and ejecta velocity of
speculative KNe, following the arguments of Foley et al. (2020), based on
models from Rosswog et al. (2013) that consider the case where the merging NSs
have equal mass (1.6 M⊙ \+ 1.6 M⊙) or if one NS was more massive (1.4 M⊙ \+
2.0 M⊙). We cannot rule out these red models given the depth of this combined
dataset.

###  5.2 sGRB

We adopt an sGRB afterglow model JetFit originally presented by Wu & MacFadyen
(2018) and Wu & MacFadyen (2019), and used to model the afterglow light curve
of GRB 170817A in the literature (e.g., Hajela et al., 2019, 2022; Kilpatrick
et al., 2022). For our fiducial model, we adopt the general parameters from
the best fit to the multiwavelength GRB 170817A light curve of Hajela et al.
(2022). These fixed parameters correspond to the electron energy fraction
$\log\epsilon_{e}=-1$, the magnetic energy fraction $\log\epsilon_{B}=-5.17$,
the spectral index of the electron distribution $p=2.15$, the asymptotic
Lorentz factor $\eta_{0}=8.02$, and the boost Lorentz factor $\gamma_{B}=12$.
We then vary the explosion energy $E_{0}$, the ambient density $n$, and the
viewing angle $\theta_{\rm obs}$ to generate in-band light curves from our
fiducial model. We consider a range of ambient densities in units of particles
per cm3, ${\rm n}\in[10^{-6},10]$ cm-3, and isotropic equivalent energy
$E_{k,{\rm iso}}=2E_{0}/(1-\cos(\frac{1}{2\gamma_{B}}))$ in units of $10^{51}$
ergs (foe), $E_{k,{\rm iso}}\in[10^{-3},100]$ foe, consistent with observed
sGRB afterglows in Fong et al. (2015). Finally, we considered two viewing
angles ($\theta_{\rm obs}=0$ and $\theta_{\rm obs}=17^{\circ}$) for an “on-
axis” and “off-axis” model (respectively), but report only on our relatively
insensitive on-axis limits because our off-axis models are substantially
fainter. Our detection probability for a GRB 170918A-like model is $4.0\times
10^{-1}$% ($8.3\times 10^{-1}$%).

Figure 9: Limits on on-axis ($\theta_{\rm obs}=0^{\circ}$) sGRB models from Wu
& MacFadyen (2018), as a function of isotropic kinetic energy ($E_{k,{\rm
iso}}$ in foe) and circumburst density ($n$ in cm-3). This dataset is
relatively insensitive to these afterglow models, with a detection probability
of a GRB 170817A-like model at $4.0\times 10^{-1}$% ($E_{k,{\rm iso}}=2.5$
foe, $n=0.3$ cm-3, taken from Murguia-Berthier et al. (2017)).

###  5.3 Generic Models

KNe and sGRB afterglows have extremely short rise times, and it is likely that
ground-based discoveries catch only their decline (Arcavi et al., 2017a; Drout
et al., 2017; Kilpatrick et al., 2017). Motivated by this, we include a
generic class of empirical models parameterized by a peak absolute magnitude
at the time of the merger, $M_{0}$, and a linear decline rate, $\Delta M$, in
units of mag day-1,

$M(t)=M_{0}-\Delta M(t-t_{0})\,,$ (5)

where $t$ is in days. We make these models agnostic in their emission
mechanism and construct their light curves with a flat spectral energy
distribution (SED). Models are considered that span a peak magnitude range
$M_{0}\in[-14,-20]$ mag and decline rates of $\Delta M\in[10^{-3},1.5]$ mag
day-1 (in log space) to cover a parameter range that includes AT 2017gfo and
several classes of well-known transients.

In Figure 10, we show our results, with parameters for AT 2017gfo representing
an average of its decline across blue and red bands ($M\approx-16$ mag;
$\Delta M\approx 0.7$ mag day-1) and a collection of transient types
overplotted in juxtaposition (referenced from Siebert et al., 2017). To the
limits of this dataset’s coverage, we confidently detect these well-known
extragalactic transient types, reinforcing the results reported in Section 3.
We rule out an AT 2017gfo-like model at $30.0$% ($62.1$%) confidence.

Figure 10: Limits on generic linear models parameterized by a peak absolute
magnitude at the time of the merger ($M_{0}$ in mag) and a linear decline rate
($\Delta M$ in mag day-1). Our models are agnostic in their emission mechanism
and have a uniform SED. We overplot a range of well-known classes of
transients taken from Siebert et al. (2017), as well as an average
representation of AT 2017gfo ($M\approx-16$ mag, $\Delta M\approx 0.7$ mag
day-1; based on Siebert et al., 2017; Drout et al., 2017; Kilpatrick et al.,
2017). We rule out an AT 2017gfo-like counterpart with 30.0% confidence.

##  6 Discussion

As the second BNS merger identified by the LVC, GW190425 had significantly
different source properties from the first BNS event GW170817. In particular,
the much larger total system mass of 3.4$\begin{subarray}{c}+0.3\\\
-0.1\end{subarray}$ M⊙ compared with 2.73$\begin{subarray}{c}+0.04\\\
-0.01\end{subarray}$ M⊙ (Abbott et al., 2017d) may lead to a significantly
different EM counterpart (see Foley et al., 2020). Now that the LVK’s O4 run
is well underway, we are faced with a new paradigm for EM searches: more-
distant events owing to an increase in detector sensitivity, larger than
expected localization areas owing to Virgo’s unexpected downtime during O4a,
and an intrinsic diversity in BNS and NSBH systems leading to a range of EM
counterparts. Therefore, it is likely that the search strategies that worked
for GW170817 will have to be updated. To address these scenarios in O4 and
beyond, we consider several updates to Teglon which will enhance existing
capabilities and add new ones. Here we explore our plan to optimize a network
of telescopes engaged in a counterpart search, add new catalogs to Teglon to
enable new types of counterpart searches, and consider combining different
types of localization information and source properties from coincident
sources such as FRBs, GRBs, and neutrino detections into Teglon.

###  6.1 EM Follow-up Coordination

If we sum the product of every pixel with the multiplicity of observations
that cover it and divide that number by two — one epoch for a search image and
one epoch for a template image — these observations could have in principle
uniquely covered $\sim 17,735$ deg2, or roughly 1.8 times the final 90th
percentile localization region. This ratio between the total area surveyed and
90th percentile localization region is even larger if we only consider the
portions of the sky with no Sun constraint (i.e., the Eastern Spur of
probability; see Figure 3). However, the EM community’s follow-up strategy for
GW sources is uncoordinated between observational teams, as evidenced by the
search statistics shown in Table 1 — only 5,638 deg2 of localization area was
uniquely searched. Furthermore, as seen in Figure 3, ZTF covered nearly the
entire Eastern Spur of probability in $g+r$ over the course of the first 3
nights. Despite this, there were $\sim 900$ other images taken of these same
fields in the same filters within the same time period with 5 other
instruments. In our analysis, these additional images offer little
constraining power on the models that we consider. Despite the stroke of luck
of GW170817 merging at a distance of only 40 Mpc, and its counterpart AT
2017gfo discovered just $\sim 11$ hr later, no KN was localized in O3 and the
prospects for localizing one in O4 remain challenging. Increasing the
coordination between follow-up facilities can drastically increase the odds of
rapidly and precisely localizing the next KN by leveraging Teglon to design
strategies that can optimize our sensitivity to a range of counterpart models.

To address these challenges, in an upcoming enhancement Teglon will publish
its redistributed localization map as a dynamic, real-time service that can be
subscribed to by a network of telescopes. For a given GW event, each telescope
within the network will be incorporated into a global queue that will query
Teglon for the next best observation (i.e., the next highest probability
observation). When an observation is scheduled, Teglon will decrement the
probability in the pixels that are covered, and the following query for the
next best observation will be dynamically updated. This coordination function
will operate on a per-filter basis, allowing different passbands to be
optimized independently. Finally, the pixel probability decrementation will be
dynamic: Teglon will alter the probability proportional to a model-specific
light curve as a function of filter. For instance, while KNe quickly decline
in blue bands, they rise more slowly in red bands. For joint searches in blue
and red filters, Teglon will restore probability to covered pixels at
different rates to force successive observations back to regions of high 2D
probability depending on what filter the search instrument is using. In this
way, Teglon will optimize a network of search telescopes in both their spatial
coverage and model sensitivity.

###  6.2 Specialized Catalog Additions: EM Counterparts to Binary Black Holes

Immediately preceding O4, the LVK was expected to detect
260$\begin{subarray}{c}+330\\\ -150\end{subarray}$ BBH mergers per year in
O4(see the International Gravitational-Wave Observatory Network Public Alerts
User
Guide101010https://emfollow.docs.ligo.org/userguide/capabilities.html#summary-
statistics, and Abbott et al., 2016c), whereas the LVK discovered 75 BBH
events in the 7.7 months of is O4a observing run111111Not counting three BBH
events in the engineering preceding O4a., a rate of 117 yr-1 and consistent
with the lower 1$\sigma$ bound of the expected rate. While these BBH mergers
are by themselves not expected to directly produce luminous transients, the
nuclei of galaxies should host the densest populations of BH binaries, and for
some of these binaries, they may be embedded in the disks of active galactic
nuclei (AGNs). These environments can provide torques and tidal forces that
can accelerate the pace of orbital decay (Bartos et al., 2017; Antoni et al.,
2019; Gröbner et al., 2020; Kaaz et al., 2023) and lead to mergers in baryon-
rich environments. For such systems, BBH mergers may trigger AGN flares; such
a transient is proposed to explain the optical flare discovered 34 days after
the GW detection of the BBH merger GW190521 (also known as S190521g; Graham et
al., 2020; Abbott et al., 2020b, although see Ashton et al. (2020) for a
rebuttal).

To facilitate the follow-up campaigns for BBHs, Teglon will be enhanced to
include the AGN catalog from Secrest et al. (2015), which contains 1.4 million
AGNs down to $g=26$ mag selected from the AllWISE catalog (Wright et al.,
2010). This catalog is estimated to be complete for known AGNs to $\gtrsim
84$%, and for all AGNs with $R<19$ mag. Therefore, for AGNs with $z<0.1$, the
catalog is expected to be close to $>90$% complete. This catalog will provide
an alternative galaxy catalog weighting scheme to accentuate AGN hosts within
the LVK volume.

###  6.3 FRB 190425A and Combining Coincident Sources within Teglon

While no optical counterparts were discovered in our follow-up campaign or
imaging from other efforts that appear consistent with a KN or GRB afterglow
from GW190425 (Coughlin et al., 2019; Hosseinzadeh et al., 2019; Lundquist et
al., 2019; Antier et al., 2020; Gompertz et al., 2020), Moroianu et al. (2023)
reported the potential coincidence between FRB 190425A and GW190425 based on
the former’s detection inside the 90th percentile credible region of the
latter and discovery of the FRB 2.5 hr after the GW190425 merger. Given their
highly energetic radio bursts, millisecond timescales, and the discovery of an
FRB from the Galactic magnetar SGR J1935+2154 (CHIME/FRB Collaboration et al.,
2020; Bochenek et al., 2020; Zhang, 2022), FRBs are thought to arise from or
in the immediate environments of magnetars (see, e.g., Margalit et al., 2019;
Metzger et al., 2019; Lyutikov et al., 2020, for a discussion of various FRB
emission models involving magnetars). Invoking the formation of a magnetar in
the post-merger collapse of a BNS system (Zhang, 2013; Most et al., 2018),
FRBs may be credible radio counterparts to BNS mergers, and combining
observables from GW events and FRBs within Teglon can aid in rapid
localization and identification of likely host galaxies (similar to the
analysis of Panther et al., 2023).

While arcsecond-scale localization of FRBs is possible with interferometers
such as ASKAP (Macquart et al., 2010), VLA (Law et al., 2018), and MeerKAT
(Rajwade et al., 2022), the vast majority of FRBs are discovered with
localizations of several deg2 (including FRB 20190425A, e.g., by CHIME;
CHIME/FRB Collaboration et al., 2021). At these angular scales, the Teglon
algorithm is effective at selecting high-likelihood galaxies within the 2D
localizations of both maps, for example by assuming that both the 2D
localization provided by the LVK ($P_{\rm 2D,GW}$) and the CHIME beam ($P_{\rm
2D,FRB}$) represent independent estimates of the same source location and are
combined into a single map ($P_{{\rm 2D}_{k}}=P_{\rm 2D,GW}\times P_{\rm
2D,FRB}$. This assumption can be extended to any class of sources with
localization on angular scales of degrees; indeed, the LVK produces combined
skymaps incorporating localization information from third parties such as GRBs
and neutrino alerts121212See
https://emfollow.docs.ligo.org/userguide/content.html..

Teglon can further benefit from FRB coincidences by incorporating distance
constraints based on the dispersion measure (DM) obtained directly from the
FRB signal. This quantity correlates directly with the column of electrons
along the line of sight to the FRB; combined with information on the density
of electrons in the Milky Way, host-galaxy environments, and the intergalactic
medium, this electron column density can constrain the distance to a FRB (Deng
& Zhang, 2014; Zhou et al., 2014; Macquart et al., 2020). In addition to
multiple independent 2D localization constraints, the Teglon algorithm can
accommodate multiple independent volume localizations by combining distance
distributions within each map pixel, such as replacing Equation 4.2 with a
nonparametric distribution for each map pixel.

##  7 Conclusions

We present the most comprehensive analysis to date of UVOIR follow-up
campaigns of the GW event GW190425 by the Gravity Collective and publicly
reported data.

  1. 1.

We present new follow-up data from the Gravity Collective for GW190425,
including optical and IR imaging from the KAIT, Nickel, Thacher, SMARTS 1.3 m,
and Swope telescopes covering a unique 54.76 deg2 of the 90th percentile
localization region and 3.99% of the Teglon redistributed 2D probability
(corresponding to 0.98% of the LVK-assigned 2D probability) across uBVgriIJHK
bands. In addition, we present a new MOSFIRE IR spectrum of the high-
probability candidate SN 2019ebq, demonstrating that it is consistent with an
SN Ib/c at $z=0.037$.

  2. 2.

We analyze all candidate counterparts discovered within the 90th-percentile
localization region for GW190425, including their available spectra, possible
identifications as minor planets or variable stars, host-galaxy associations
and redshifts relative to the localization volume of GW190425, and photometry.
We are left with 28 candidates that we cannot rule out as being associated
with GW190425, four of which we consider “more likely” candidates based on
their time of discovery, host-galaxy associations, and implied luminosity.

  3. 3.

Assuming that none of these candidates is the counterpart to GW190425, we
perform a joint analysis of our data combined with all publicly reported
imaging using a new tool, Teglon. This tool uses a 3D spatially varying galaxy
catalog completeness weighting scheme, based on galaxy luminosity, to
redistribute the original LVK 2D probability to account for local regions of
high catalog completeness. We have provided
Teglon131313https://github.com/davecoulter/teglon_O4(Coulter 2024, in prep.;
Coulter, 2021) as an open-source tool available to the broader GW follow-up
community.

  4. 4.

With Teglon, we homogeneously analyze this combined dataset, covering a unique
9,078.59 deg2 and 48.28% of the Teglon redistributed 2D probability
(corresponding to 48.13% of the LVK-assigned 2D probability) across UVOIR
bands. We find that there was a 28.4% and 2.9% chance of detecting a KN
similar to the blue and components (respectively) of AT 2017gfo in the
combined dataset. Furthermore, we find that the data are generally insensitive
to an on-axis sGRB, and rule out a generic transient with a similar peak
luminosity and decline rate as AT 2017gfo to 30% confidence. Combining all new
imaging data presented here as well as publicly available imaging in the
literature, our Teglon analysis is the most comprehensive meta-analysis of
GW190425 presented to date.

  5. 5.

Finally, we analyze the full search for optical counterparts to GW190425 in
terms of the search strategy adopted across the astronomical community, unique
optical counterparts such as those arising from NS mergers in the disks of
AGNs, and the possible radio counterpart FRB 190425A discovered 2.5 hr after
the GW190425 merger. We argue that Teglon can aid in each of these cases by
optimally analyzing the search strategies for multiple telescopes with varying
FOVs and depth, incorporating source catalogs apart from galaxies in its
algorithm, and calculating the overlap between GW events and those from
coincident events such as GRBs and FRBs into the localization maps that it
generates.

We appreciate the expert assistance of the staffs at the various observatories
where data were obtained. We also acknowledge the important work that the
Treasure Map is engaged in, by facilitating the public distribution of GW
search data, which allowed this analysis to be conducted. D.A.C. thanks Leo
Singer for many insightful conversations on topics as diverse as plotting to
understanding GW posteriors through his comprehensive set of
tools141414https://lscsoft.docs.ligo.org/ligo.skymap/, Michael Coughlin for
many conversations about EM search optimizations, R. H. for important
conversations on the software engineering required to build Teglon, D. O.
Jones for his technical expertise in quantifying our imaging depth, Antonella
Palmese for her sharp eyes reviewing equations, Stephen Smartt and I.A. for
graciously sharing their pointing data with our team, Aaron Tohuvavohu and Sam
Wyatt for their help integrating Treasure Map queries into Teglon, and Ashley
Villar for her insight into MOSFiT modeling. C.D.K. acknowledges partial
support from a CIERA postdoctoral fellowship. The work of P.M. was partly
performed under the auspices of the U.S. Department of Energy by Lawrence
Livermore National Laboratory under Contract DE-AC52-07NA27344. The document
number is LLNL-JRNL-863367.. I.A. is grateful for support from the European
Research Council (ERC) under the European Union’s Horizon 2020 research and
innovation program (grant agreement 852097), from the Israel Science
Foundation (grant 2752/19), from the United States – Israel Binational Science
Foundation (BSF; grant 2018166), and from the Pazy Foundation (grant 216312).
J.A.V. acknowledges the Doctorate in Astrophysics and Astroinformatics and
Postgraduate School of the Universidad de Antofagasta for its support and
allocated grants. E.R.-R. is supported by the Heising-Simons Foundation and
the NSF (AST-2307710, AST-2206243, AST-1911206, and AST-1852393). J.S.B. is
partially supported by the Gordon and Betty Moore Foundation and the NSF.
M.R.D. acknowledges support from the NSERC through grant RGPIN-2019-06186, the
Canada Research Chairs Program, and the Dunlap Institute at the University of
Toronto. A.V.F.’s research group at UC Berkeley acknowledges financial
assistance from the Christopher R. Redlich Fund, as well as donations from
Gary and Cynthia Bengier, Clark and Sharon Winslow, Alan Eustace (W.Z. is a
Bengier-Winslow-Eustace Specialist in Astronomy), and many other individuals.
This work includes data obtained with the Swope telescope at Las Campanas
Observatory, Chile, as part of the Swope Time Domain Key Project (PI Piro;
CoIs Burns, Coulter, Cowperthwaite, Dimitriadis, Drout, Foley, French,
Holoien, Hsiao, Kilpatrick, Madore, Phillips, and Rojas-Bravo). This work
makes use of data from the Las Cumbres Observatory global telescope network.
The LCO group is supported by NSF grants AST-1911225 and AST-1911151, and BSF
grant 2018166. This research has used data from the SMARTS 1.3 m telescope,
which is operated as part of the SMARTS Consortium. Some of the data presented
herein were obtained at the W. M. Keck Observatory, which is operated as a
scientific partnership among the California Institute of Technology, the
University of California, and NASA. The Observatory was made possible by the
generous financial support of the W. M. Keck Foundation. The authors wish to
recognize and acknowledge the very significant cultural role and reverence
that the summit of Maunakea has always had within the indigenous Hawaiian
community. We are most fortunate to have the opportunity to conduct
observations from this mountain. Research at Lick Observatory is partially
supported by a generous gift from Google. KAIT and its ongoing operation were
made possible by donations from Sun Microsystems, Inc., the Hewlett-Packard
Company, AutoScope Corporation, Lick Observatory, the NSF, the University of
California, the Sylvia and Jim Katzman Foundation, and the TABASGO Foundation.
We also appreciate data Keinan et al. in prep. shared by I.A. on behalf of Las
Cumbres Observatory.

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Table 2: 1M2H UVOIR Imaging of the GW190425 Localization Region

SourceaaImaging as described in Section 2. | $\alpha$ | $\delta$ | Exposure Time | DatebbMJD is taken from the center of the exposure time. | Filter | Magnitude LimitccIn-band 3$\sigma$ limit for the reported image as described in Section 2 and Section 5. All magnitudes are on the AB system (Oke & Gunn, 1983).
---|---|---|---|---|---|---
| (J2000) | (J2000) | (s) | (MJD) |  | (3$\sigma$)
ANDICAM CCD | 17:31:09.72 | -08:27:14.40 | 900 | 58599.2453 | $I$ | 21.60
ANDICAM CCD | 16:52:07.06 | -17:03:27.72 | 240 | 58599.2798 | $I$ | 19.91
ANDICAM CCD | 15:40:36.10 | +28:30:30.60 | 240 | 58599.2895 | $I$ | 20.24
ANDICAM CCD | 15:41:53.64 | +28:07:50.52 | 240 | 58599.2938 | $I$ | 19.60
ANDICAM CCD | 15:47:53.42 | +25:43:31.80 | 240 | 58599.2984 | $I$ | 21.06
ANDICAM CCD | 15:56:03.36 | +24:26:40.56 | 240 | 58599.3027 | $I$ | 20.81
ANDICAM CCD | 15:57:13.85 | +25:48:54.36 | 240 | 58599.3074 | $I$ | 20.87
ANDICAM CCD | 16:02:59.59 | +27:00:23.40 | 240 | 58599.3125 | $I$ | 21.15
ANDICAM CCD | 16:04:46.22 | +24:16:31.08 | 240 | 58599.3175 | $I$ | 20.92
ANDICAM CCD | 16:09:05.81 | +24:52:00.84 | 240 | 58599.3219 | $I$ | 21.05
ANDICAM CCD | 16:07:38.98 | +22:20:19.32 | 240 | 58599.3263 | $I$ | 21.03
ANDICAM CCD | 15:59:51.17 | +25:56:14.28 | 240 | 58599.3353 | $I$ | 20.82
ANDICAM CCD | 16:04:15.72 | +24:48:32.76 | 240 | 58599.3396 | $I$ | 20.93
ANDICAM CCD | 16:14:57.24 | +21:56:04.20 | 240 | 58599.3440 | $I$ | 20.97
ANDICAM CCD | 16:24:14.76 | +20:10:47.64 | 240 | 58599.3486 | $I$ | 20.97
ANDICAM CCD | 16:04:56.28 | +23:55:46.92 | 240 | 58599.3530 | $I$ | 20.54
ANDICAM CCD | 16:24:27.00 | +19:28:41.88 | 240 | 58599.3575 | $I$ | 20.92
ANDICAM CCD | 16:19:29.18 | +18:28:35.04 | 240 | 58599.3621 | $I$ | 20.85
ANDICAM CCD | 16:30:49.66 | +16:14:47.40 | 240 | 58599.3666 | $I$ | 20.93
ANDICAM CCD | 16:23:10.90 | +16:55:45.84 | 240 | 58599.3712 | $I$ | 20.62
ANDICAM CCD | 16:40:02.93 | +15:52:47.64 | 240 | 58599.3757 | $I$ | 20.76
ANDICAM CCD | 17:13:21.60 | -09:58:06.24 | 900 | 58599.3921 | $I$ | 20.97
ANDICAM CCD | 16:49:20.35 | -17:38:53.16 | 240 | 58600.1619 | $I$ | 21.34
ANDICAM CCD | 16:53:04.61 | -16:17:39.12 | 240 | 58600.1664 | $I$ | 21.08
ANDICAM CCD | 16:54:53.38 | -16:57:16.20 | 240 | 58600.1710 | $I$ | 21.04
ANDICAM CCD | 16:50:52.92 | -15:00:28.44 | 240 | 58600.1756 | $I$ | 21.23
ANDICAM CCD | 16:54:08.33 | -07:38:20.04 | 240 | 58600.1803 | $I$ | 21.37
ANDICAM IR | 17:31:10.54 | -08:26:56.04 | 30 | 58599.2012 | $K$ | 14.28
ANDICAM IR | 16:52:07.90 | -17:03:09.36 | 30 | 58599.2797 | $H$ | 14.27
ANDICAM IR | 15:57:14.76 | +25:49:12.36 | 30 | 58599.3073 | $H$ | 14.37
ANDICAM IR | 16:04:47.11 | +24:16:48.72 | 30 | 58599.3174 | $H$ | 14.00
ANDICAM IR | 16:09:06.70 | +24:52:18.84 | 30 | 58599.3218 | $H$ | 14.81
ANDICAM IR | 16:07:39.84 | +22:20:37.32 | 30 | 58599.3262 | $H$ | 14.58
ANDICAM IR | 16:09:15.82 | +25:42:51.84 | 30 | 58599.3307 | $H$ | 15.03
ANDICAM IR | 16:14:58.10 | +21:56:21.84 | 30 | 58599.3439 | $H$ | 14.78
ANDICAM IR | 16:24:15.62 | +20:11:05.64 | 30 | 58599.3486 | $H$ | 15.25
ANDICAM IR | 16:24:27.84 | +19:28:59.88 | 30 | 58599.3575 | $H$ | 14.54
ANDICAM IR | 16:19:30.05 | +18:28:52.68 | 30 | 58599.3620 | $H$ | 15.17
ANDICAM IR | 16:30:50.52 | +16:15:05.40 | 30 | 58599.3666 | $H$ | 14.45
ANDICAM IR | 16:23:11.76 | +16:56:03.84 | 30 | 58599.3711 | $H$ | 14.53
ANDICAM IR | 16:40:03.77 | +15:53:05.64 | 30 | 58599.3756 | $H$ | 13.67
ANDICAM IR | 17:13:22.42 | -09:57:48.24 | 30 | 58599.4030 | $H$ | 14.62
ANDICAM IR | 17:13:22.44 | -09:57:48.24 | 30 | 58599.4140 | $J$ | 14.65
ANDICAM IR | 16:49:21.22 | -17:38:34.80 | 30 | 58600.1619 | $H$ | 15.05
ANDICAM IR | 16:53:05.42 | -16:17:21.12 | 30 | 58600.1664 | $H$ | 15.25
ANDICAM IR | 16:54:54.22 | -16:56:58.20 | 30 | 58600.1709 | $H$ | 14.98
ANDICAM IR | 16:50:53.74 | -15:00:10.08 | 30 | 58600.1756 | $H$ | 14.58
ANDICAM IR | 16:54:09.12 | -07:38:02.04 | 30 | 58600.1803 | $H$ | 15.09
Nickel | 13:54:45.17 | +44:46:44.76 | 600 | 58599.1986 | $r$ | 21.09
Nickel | 13:54:45.22 | +44:46:44.40 | 600 | 58599.2059 | $i$ | 20.44
Nickel | 14:32:30.31 | +55:45:11.52 | 600 | 58599.2297 | $r$ | 21.28
Nickel | 14:32:30.36 | +55:45:11.16 | 600 | 58599.2371 | $i$ | 20.33
Nickel | 14:36:47.74 | +34:17:57.48 | 180 | 58599.2458 | $r$ | 20.61
Nickel | 13:20:49.78 | +43:58:05.16 | 180 | 58599.2498 | $r$ | 20.72
Nickel | 15:31:39.43 | +40:52:21.36 | 180 | 58599.2538 | $r$ | 20.01
Nickel | 15:13:21.19 | +30:57:59.40 | 180 | 58599.2575 | $r$ | 20.50
Nickel | 15:29:23.45 | +28:19:00.84 | 180 | 58599.2615 | $r$ | 20.32
Nickel | 15:32:42.10 | +28:22:30.72 | 180 | 58599.2656 | $r$ | 20.37
Nickel | 16:02:36.14 | +37:21:59.40 | 180 | 58599.2695 | $r$ | 20.63
Nickel | 15:40:43.94 | +28:18:02.16 | 180 | 58599.2731 | $r$ | 20.44
Nickel | 15:40:32.18 | +28:31:15.96 | 180 | 58599.2764 | $r$ | 18.89
Nickel | 15:41:49.63 | +28:08:30.48 | 180 | 58599.2802 | $r$ | 20.31
Nickel | 15:43:52.90 | +28:31:59.16 | 180 | 58599.2847 | $r$ | 20.49
Nickel | 15:47:31.75 | +26:04:25.32 | 180 | 58599.2928 | $r$ | 20.48
Nickel | 15:47:49.20 | +25:44:19.32 | 180 | 58599.2968 | $r$ | 20.40
Nickel | 15:50:17.64 | +26:26:21.84 | 180 | 58599.3015 | $r$ | 20.06
Nickel | 15:51:54.96 | +24:21:03.96 | 180 | 58599.3058 | $r$ | 20.13
Nickel | 15:57:09.43 | +25:49:45.12 | 180 | 58599.3096 | $r$ | 19.23
Nickel | 15:58:46.87 | +26:08:47.04 | 180 | 58599.3141 | $r$ | 20.21
Nickel | 15:55:58.66 | +24:27:32.40 | 180 | 58599.3179 | $r$ | 19.97
Nickel | 15:59:46.10 | +25:57:05.04 | 180 | 58599.3218 | $r$ | 22.71
Nickel | 16:02:54.67 | +27:01:13.80 | 180 | 58599.3254 | $r$ | 19.77
Nickel | 16:04:30.02 | +25:12:05.76 | 180 | 58599.3297 | $r$ | 20.10
Nickel | 16:03:48.48 | +25:01:21.00 | 180 | 58599.3343 | $r$ | 20.07
Nickel | 16:03:08.54 | +24:23:10.32 | 180 | 58599.3382 | $r$ | 20.79
Nickel | 12:24:55.92 | +28:34:15.96 | 180 | 58599.3422 | $r$ | 19.91
Nickel | 16:04:10.10 | +24:49:27.48 | 180 | 58599.3464 | $r$ | 20.77
Nickel | 16:04:40.58 | +24:17:26.52 | 180 | 58599.3501 | $r$ | 19.81
Nickel | 16:04:54.14 | +23:40:17.04 | 180 | 58599.3580 | $r$ | 20.71
Nickel | 16:09:11.95 | +24:52:57.36 | 180 | 58599.3659 | $r$ | 18.51
Nickel | 16:05:17.54 | +22:31:18.48 | 180 | 58599.3696 | $r$ | 20.78
Nickel | 16:05:30.84 | +22:12:00.72 | 180 | 58599.3731 | $r$ | 19.88
Nickel | 16:11:16.49 | +23:58:45.48 | 180 | 58599.3768 | $r$ | 20.57
Nickel | 16:07:33.34 | +22:21:26.64 | 180 | 58599.3809 | $r$ | 18.90
Nickel | 16:08:43.85 | +22:03:24.84 | 180 | 58599.3854 | $r$ | 19.82
Nickel | 16:12:13.63 | +23:00:59.04 | 180 | 58599.3896 | $r$ | 19.63
Nickel | 16:13:39.10 | +22:56:00.24 | 180 | 58599.3938 | $r$ | 20.38
Nickel | 16:11:50.88 | +20:56:20.04 | 180 | 58599.3982 | $r$ | 20.00
Nickel | 16:14:50.57 | +21:57:14.40 | 180 | 58599.4020 | $r$ | 20.19
Nickel | 16:17:57.84 | +21:34:09.84 | 180 | 58599.4060 | $r$ | 20.14
Nickel | 16:16:04.18 | +20:37:46.56 | 180 | 58599.4105 | $r$ | 19.85
Nickel | 16:17:59.64 | +21:05:00.24 | 180 | 58599.4149 | $r$ | 20.31
Nickel | 16:15:34.70 | +19:39:15.48 | 180 | 58599.4189 | $r$ | 20.29
Nickel | 16:21:01.97 | +21:05:29.76 | 180 | 58599.4226 | $r$ | 20.30
Nickel | 16:19:21.82 | +18:29:51.72 | 180 | 58599.4270 | $r$ | 20.51
Nickel | 13:15:16.46 | +37:37:39.36 | 600 | 58601.4778 | $i$ | 20.18
Nickel | 14:36:48.55 | +34:17:42.36 | 180 | 58603.3436 | $r$ | 20.51
Nickel | 13:20:49.78 | +43:58:05.52 | 180 | 58603.3479 | $r$ | 20.31
Nickel | 15:31:40.85 | +40:52:05.16 | 180 | 58603.3512 | $r$ | 19.35
Nickel | 15:13:22.68 | +30:57:46.80 | 180 | 58603.3548 | $r$ | 20.06
Nickel | 15:29:25.13 | +28:18:47.88 | 180 | 58603.3577 | $r$ | 19.95
Nickel | 15:32:43.90 | +28:22:18.84 | 180 | 58603.3605 | $r$ | 20.08
Nickel | 16:02:38.06 | +37:21:49.68 | 180 | 58603.3634 | $r$ | 20.05
Nickel | 15:40:45.70 | +28:17:52.08 | 180 | 58603.3662 | $r$ | 20.18
Nickel | 15:40:33.96 | +28:31:05.16 | 180 | 58603.3689 | $r$ | 18.81
Nickel | 15:41:51.36 | +28:08:21.12 | 180 | 58603.3717 | $r$ | 20.07
Nickel | 15:43:54.43 | +28:31:47.64 | 180 | 58603.3750 | $r$ | 19.57
Nickel | 15:47:33.36 | +26:04:12.72 | 180 | 58603.3820 | $r$ | 19.81
Nickel | 15:47:51.10 | +25:44:06.36 | 180 | 58603.3855 | $r$ | 20.28
Nickel | 15:50:19.51 | +26:26:09.24 | 180 | 58603.3885 | $r$ | 19.70
Nickel | 15:51:56.76 | +24:20:46.68 | 180 | 58603.3918 | $r$ | 19.85
Nickel | 15:57:11.38 | +25:49:29.64 | 180 | 58603.3950 | $r$ | 19.68
Nickel | 15:58:48.86 | +26:08:30.84 | 180 | 58603.3981 | $r$ | 19.44
Nickel | 15:56:00.67 | +24:27:15.48 | 180 | 58603.4012 | $r$ | 20.09
Nickel | 15:59:48.62 | +25:56:47.40 | 180 | 58603.4041 | $r$ | 19.39
Nickel | 16:02:57.19 | +27:00:56.88 | 180 | 58603.4072 | $r$ | 19.79
Nickel | 16:04:32.52 | +25:11:48.48 | 180 | 58603.4104 | $r$ | 20.02
Nickel | 16:03:51.07 | +25:01:02.28 | 180 | 58603.4136 | $r$ | 19.56
Nickel | 16:03:11.02 | +24:22:50.16 | 180 | 58603.4165 | $r$ | 19.78
Nickel | 12:24:57.79 | +28:34:09.84 | 180 | 58603.4197 | $r$ | 19.34
Nickel | 16:04:12.24 | +24:49:00.48 | 180 | 58603.4231 | $r$ | 20.50
Nickel | 16:04:42.55 | +24:16:58.80 | 180 | 58603.4258 | $r$ | 20.02
Nickel | 16:04:55.80 | +23:39:47.52 | 180 | 58603.4314 | $r$ | 20.46
Nickel | 16:09:02.26 | +24:52:32.52 | 180 | 58603.4369 | $r$ | 17.77
Nickel | 16:05:19.08 | +22:30:50.04 | 180 | 58603.4396 | $r$ | 20.07
Nickel | 16:05:32.45 | +22:11:31.92 | 180 | 58603.4434 | $r$ | 18.10
Nickel | 16:11:18.34 | +23:58:14.88 | 180 | 58603.4462 | $r$ | 19.98
Nickel | 16:07:35.30 | +22:20:57.12 | 180 | 58603.4489 | $r$ | 18.82
Nickel | 16:08:45.84 | +22:02:56.76 | 180 | 58603.4520 | $r$ | 19.20
Nickel | 16:12:15.82 | +23:00:30.24 | 180 | 58603.4546 | $r$ | 19.03
Nickel | 16:13:41.57 | +22:55:31.44 | 180 | 58603.4573 | $r$ | 20.02
Nickel | 16:11:53.33 | +20:55:53.40 | 180 | 58603.4606 | $r$ | 19.52
Nickel | 16:14:53.14 | +21:56:44.16 | 180 | 58603.4636 | $r$ | 19.36
Nickel | 16:18:00.65 | +21:33:41.04 | 180 | 58603.4665 | $r$ | 19.35
Nickel | 16:16:07.13 | +20:37:16.32 | 180 | 58603.4699 | $r$ | 19.48
Nickel | 16:18:02.47 | +21:04:29.64 | 180 | 58603.4730 | $r$ | 19.95
Nickel | 16:15:37.46 | +19:38:44.16 | 180 | 58603.4766 | $r$ | 19.81
Nickel | 16:21:05.11 | +21:05:00.96 | 180 | 58603.4795 | $r$ | 19.73
Nickel | 16:19:25.01 | +18:29:17.52 | 180 | 58603.4829 | $r$ | 20.00
Nickel | 16:24:10.34 | +20:11:32.28 | 180 | 58603.4860 | $r$ | 19.58
Nickel | 17:31:04.44 | -08:26:16.80 | 600 | 58603.4979 | $r$ | 19.00
Nickel | 13:53:34.30 | +40:16:23.88 | 330 | 58606.2303 | $B$ | 19.68
Nickel | 13:53:34.39 | +40:16:26.40 | 240 | 58606.2345 | $V$ | 19.60
Nickel | 13:53:34.44 | +40:16:29.28 | 270 | 58606.2377 | $r$ | 19.59
Nickel | 13:53:34.54 | +40:16:30.72 | 300 | 58606.2412 | $i$ | 19.60
Nickel | 12:11:57.48 | +24:08:15.00 | 60 | 58606.2743 | $B$ | 19.90
Nickel | 12:11:57.48 | +24:08:16.08 | 60 | 58606.2765 | $r$ | 20.20
Nickel | 12:11:57.46 | +24:08:16.44 | 60 | 58606.2776 | $i$ | 20.05
Nickel | 12:11:57.46 | +24:08:16.44 | 60 | 58606.2776 | $i$ | 20.08
Nickel | 12:35:58.18 | +27:56:03.12 | 600 | 58606.2887 | $r$ | 19.87
Nickel | 12:35:58.20 | +27:56:03.12 | 600 | 58606.2960 | $i$ | 19.79
Nickel | 12:03:17.42 | +44:31:58.44 | 600 | 58606.3238 | $r$ | 20.49
Nickel | 12:03:17.40 | +44:31:58.44 | 600 | 58606.3311 | $i$ | 19.97
Nickel | 13:53:35.66 | +40:16:33.24 | 330 | 58606.3414 | $B$ | 20.94
Nickel | 13:53:35.64 | +40:16:33.60 | 240 | 58606.3456 | $V$ | 20.63
Nickel | 13:53:35.66 | +40:16:33.60 | 270 | 58606.3488 | $r$ | 20.91
Nickel | 13:53:35.62 | +40:16:34.68 | 300 | 58606.3523 | $i$ | 20.20
Nickel | 13:05:48.05 | +37:37:39.36 | 600 | 58606.4186 | $V$ | 19.96
Nickel | 13:05:48.07 | +37:37:39.72 | 600 | 58606.4260 | $r$ | 19.24
Nickel | 13:05:48.07 | +37:37:39.72 | 600 | 58606.4333 | $i$ | 18.99
Nickel | 16:24:30.77 | +19:29:07.08 | 180 | 58606.4523 | $r$ | 18.23
Nickel | 16:23:14.71 | +16:56:09.60 | 180 | 58606.4558 | $r$ | 17.88
Nickel | 16:25:41.30 | +16:27:28.80 | 180 | 58606.4593 | $r$ | 18.30
Nickel | 16:27:22.82 | +16:00:01.44 | 180 | 58606.4625 | $r$ | 18.18
Nickel | 16:28:55.37 | +15:25:30.00 | 180 | 58606.4657 | $r$ | 17.39
Nickel | 16:30:52.68 | +16:15:19.80 | 180 | 58606.4716 | $r$ | 17.76
Nickel | 16:29:38.62 | +15:39:50.40 | 180 | 58606.4749 | $r$ | 18.41
Nickel | 16:30:04.97 | +15:43:06.60 | 180 | 58606.4782 | $r$ | 18.79
Nickel | 16:31:37.97 | +13:51:57.24 | 180 | 58606.4824 | $r$ | 19.22
Nickel | 16:37:09.86 | +14:11:49.56 | 180 | 58606.4860 | $r$ | 19.35
Nickel | 16:40:42.74 | +14:21:24.84 | 180 | 58606.4897 | $r$ | 19.31
Nickel | 16:37:37.54 | +11:44:18.60 | 180 | 58606.4932 | $r$ | 18.93
Nickel | 16:39:28.87 | +11:12:57.60 | 180 | 58606.4968 | $r$ | 19.03
Nickel | 16:43:08.59 | +08:31:03.72 | 180 | 58606.5005 | $r$ | 18.56
Nickel | 16:46:24.86 | +09:02:34.80 | 180 | 58606.5053 | $r$ | 18.21
Nickel | 16:49:36.70 | +09:47:18.24 | 180 | 58606.5089 | $r$ | 17.90
Nickel | 12:11:51.29 | +24:08:05.28 | 60 | 58612.2555 | $r$ | 18.12
Nickel | 12:11:51.29 | +24:08:05.28 | 60 | 58612.2566 | $i$ | 18.77
Nickel | 12:03:10.99 | +44:31:41.88 | 600 | 58612.3013 | $r$ | 19.78
Nickel | 12:03:10.99 | +44:31:41.52 | 600 | 58612.3086 | $i$ | 18.52
Nickel | 16:31:32.21 | +30:08:41.64 | 45 | 58612.3273 | $V$ | 17.96
Nickel | 16:31:32.23 | +30:08:41.64 | 45 | 58612.3292 | $i$ | 17.92
Nickel | 16:32:19.03 | +19:50:03.48 | 420 | 58612.4514 | $r$ | 19.79
Nickel | 16:32:19.03 | +19:50:03.48 | 480 | 58612.4566 | $i$ | 18.47
Nickel | 17:30:24.29 | -13:45:39.96 | 600 | 58612.4993 | $r$ | 18.40
Nickel | 17:30:24.26 | -13:45:39.96 | 600 | 58612.5066 | $i$ | 15.96
Swope | 05:48:48.14 | -25:21:50.04 | 180 | 58598.9937 | $i$ | 21.01
Swope | 16:48:15.84 | -17:25:10.56 | 180 | 58599.1293 | $i$ | 20.84
Swope | 16:52:15.50 | -16:55:18.48 | 180 | 58599.1326 | $i$ | 20.76
Swope | 16:52:07.51 | -16:25:29.28 | 180 | 58599.1364 | $i$ | 20.81
Swope | 16:54:19.06 | -16:52:38.28 | 180 | 58599.1402 | $i$ | 20.91
Swope | 16:51:47.52 | -14:56:01.68 | 180 | 58599.1444 | $i$ | 20.87
Swope | 16:55:01.87 | -09:57:58.68 | 180 | 58599.1478 | $i$ | 20.99
Swope | 17:01:30.14 | -12:27:01.08 | 180 | 58599.1511 | $i$ | 20.80
Swope | 16:54:41.69 | -07:28:57.36 | 180 | 58599.1549 | $i$ | 20.65
Swope | 16:56:39.65 | -06:59:02.04 | 180 | 58599.1579 | $i$ | 20.94
Swope | 16:56:36.22 | -06:29:16.44 | 180 | 58599.1613 | $i$ | 20.70
Swope | 16:58:31.01 | -05:29:36.96 | 180 | 58599.1648 | $i$ | 20.78
Swope | 16:54:23.78 | -03:30:23.40 | 180 | 58599.1688 | $i$ | 20.61
Swope | 16:56:21.77 | -02:00:58.32 | 180 | 58599.1720 | $i$ | 20.73
Swope | 16:56:19.51 | -01:31:10.20 | 180 | 58599.1754 | $i$ | 20.95
Swope | 17:04:24.62 | -04:30:05.40 | 180 | 58599.1788 | $i$ | 20.67
Swope | 17:13:39.50 | -09:51:43.92 | 300 | 58599.1827 | $r$ | 21.47
Swope | 17:13:39.50 | -09:51:44.64 | 300 | 58599.1867 | $i$ | 21.16
Swope | 17:13:39.53 | -09:51:43.92 | 300 | 58599.1908 | $g$ | 21.68
Swope | 17:31:27.60 | -08:20:46.68 | 600 | 58599.1982 | $r$ | 21.78
Swope | 17:31:27.62 | -08:20:47.40 | 600 | 58599.2061 | $i$ | 21.45
Swope | 17:31:27.62 | -08:20:46.68 | 600 | 58599.2136 | $g$ | 22.12
Swope | 16:04:33.07 | +23:49:04.80 | 180 | 58599.2223 | $i$ | 20.96
Swope | 16:58:21.41 | -02:00:43.20 | 180 | 58599.2258 | $i$ | 21.27
Swope | 16:52:24.98 | +02:27:39.96 | 180 | 58599.2295 | $i$ | 21.17
Swope | 16:50:30.86 | +04:26:55.32 | 180 | 58599.2326 | $i$ | 21.14
Swope | 16:04:43.13 | +17:51:32.40 | 180 | 58599.2367 | $i$ | 21.19
Swope | 16:17:17.52 | +19:21:08.64 | 180 | 58599.2402 | $i$ | 21.11
Swope | 16:15:10.08 | +19:21:02.88 | 180 | 58599.2437 | $i$ | 21.00
Swope | 16:06:46.54 | +19:50:55.32 | 180 | 58599.2469 | $i$ | 20.98
Swope | 16:15:19.03 | +21:50:09.60 | 180 | 58599.2506 | $i$ | 21.03
Swope | 16:06:45.43 | +22:19:55.20 | 180 | 58599.2538 | $i$ | 20.98
Swope | 16:02:26.26 | +23:19:39.72 | 180 | 58599.2570 | $i$ | 20.90
Swope | 16:02:24.12 | +24:19:08.40 | 180 | 58599.2602 | $i$ | 21.09
Swope | 15:55:52.44 | +24:19:06.60 | 180 | 58599.2633 | $i$ | 21.14
Swope | 16:51:52.82 | -14:55:45.84 | 180 | 58599.2672 | $i$ | 21.35
Swope | 15:46:56.30 | +25:48:27.00 | 180 | 58599.2712 | $i$ | 21.23
Swope | 15:35:30.67 | +27:17:55.32 | 180 | 58599.2745 | $i$ | 21.11
Swope | 15:42:06.12 | +27:47:40.20 | 180 | 58599.2777 | $i$ | 20.97
Swope | 15:28:27.72 | +28:17:34.80 | 180 | 58599.2820 | $i$ | 21.08
Swope | 15:32:58.22 | +28:17:29.04 | 180 | 58599.2852 | $i$ | 21.04
Swope | 15:41:58.13 | +28:17:28.68 | 180 | 58599.2881 | $i$ | 21.06
Swope | 15:46:01.42 | +30:17:00.96 | 180 | 58599.2926 | $i$ | 20.93
Swope | 15:39:41.66 | +28:17:26.16 | 180 | 58599.2961 | $i$ | 21.12
Swope | 15:48:41.38 | +29:18:08.28 | 600 | 58599.3002 | $r$ | 21.89
Swope | 16:35:51.96 | +22:27:47.88 | 600 | 58599.3119 | $r$ | 22.12
Swope | 16:55:16.87 | +04:58:04.80 | 600 | 58599.3217 | $r$ | 22.29
Swope | 17:01:40.34 | -06:53:32.64 | 600 | 58599.3429 | $r$ | 22.00
Swope | 17:10:21.26 | +07:42:18.36 | 600 | 58599.3524 | $r$ | 22.16
Swope | 17:11:59.23 | +09:54:34.56 | 600 | 58599.3627 | $r$ | 22.20
Swope | 16:25:41.09 | +19:20:58.92 | 180 | 58599.3720 | $r$ | 21.41
Swope | 16:19:18.41 | +18:20:56.40 | 180 | 58599.3758 | $r$ | 21.44
Swope | 16:23:22.03 | +16:51:48.24 | 180 | 58599.3794 | $r$ | 21.47
Swope | 16:25:24.12 | +16:22:05.16 | 180 | 58599.3828 | $r$ | 21.44
Swope | 16:29:28.56 | +15:52:15.24 | 180 | 58599.3861 | $r$ | 21.38
Swope | 16:29:24.50 | +15:22:18.84 | 180 | 58599.3891 | $r$ | 21.52
Swope | 17:20:08.66 | -01:00:54.72 | 180 | 58599.3927 | $r$ | 21.62
Swope | 16:50:50.76 | +07:55:32.52 | 180 | 58599.3965 | $r$ | 21.46
Swope | 16:46:55.97 | +08:55:05.88 | 180 | 58599.3995 | $r$ | 21.24
Swope | 16:48:43.37 | +06:25:56.28 | 180 | 58599.4034 | $r$ | 21.50
Swope | 16:44:47.59 | +07:25:46.92 | 180 | 58599.4083 | $i$ | 20.60
Swope | 17:01:39.50 | -06:53:53.16 | 600 | 58599.4128 | $i$ | 21.84
Swope | 17:01:38.38 | -06:54:24.84 | 802 | 58599.4260 | $r$ | 21.44
Swope | 13:09:27.50 | +28:22:41.88 | 450 | 58600.1866 | $B$ | 21.83
Swope | 13:09:27.50 | +28:22:41.16 | 150 | 58600.1941 | $V$ | 21.14
Swope | 13:09:27.41 | +28:22:41.52 | 150 | 58600.1982 | $g$ | 21.84
Swope | 13:09:27.46 | +28:22:40.08 | 150 | 58600.2005 | $i$ | 20.91
Swope | 13:09:27.41 | +28:22:40.80 | 150 | 58600.2028 | $r$ | 21.31
Swope | 17:05:34.56 | +08:04:54.84 | 360 | 58600.2797 | $r$ | 22.08
Swope | 17:05:34.61 | +08:04:54.12 | 360 | 58600.2844 | $i$ | 21.64
Swope | 17:05:34.58 | +08:04:54.84 | 360 | 58600.2891 | $g$ | 21.95
Swope | 17:05:34.56 | +08:04:55.56 | 600 | 58600.2939 | $u$ | 21.49
Swope | 17:05:34.37 | +08:04:53.40 | 360 | 58600.3037 | $V$ | 22.01
Swope | 17:05:34.34 | +08:04:54.12 | 570 | 58600.3090 | $B$ | 22.37
Swope | 16:16:28.56 | +22:21:58.32 | 1200 | 58601.3103 | $r$ | 22.50
Swope | 05:48:48.65 | -25:21:59.40 | 180 | 58601.9885 | $i$ | 20.74
Swope | 12:12:20.28 | +24:14:27.60 | 45 | 58602.1652 | $r$ | 21.09
Swope | 12:12:20.26 | +24:14:25.80 | 45 | 58602.1662 | $i$ | 20.46
Swope | 12:12:20.18 | +24:14:27.60 | 45 | 58602.1672 | $g$ | 21.64
Swope | 12:12:20.11 | +24:14:29.04 | 300 | 58602.1682 | $u$ | 21.25
Swope | 12:12:20.14 | +24:14:24.36 | 45 | 58602.1726 | $V$ | 21.13
Swope | 12:12:20.16 | +24:14:25.80 | 120 | 58602.1737 | $B$ | 21.99
Swope | 15:48:44.62 | +29:18:35.64 | 600 | 58602.2468 | $r$ | 22.54
Swope | 16:35:55.87 | +22:28:16.68 | 600 | 58602.2563 | $r$ | 22.59
Swope | 16:55:19.58 | +04:58:21.72 | 600 | 58602.2665 | $r$ | 22.11
Swope | 17:01:43.18 | -06:53:18.96 | 600 | 58602.2860 | $r$ | 20.91
Swope | 17:10:23.95 | +07:42:32.40 | 600 | 58602.3042 | $r$ | 21.44
Swope | 17:12:02.26 | +09:54:52.56 | 600 | 58602.3150 | $r$ | 21.84
Swope | 17:13:47.50 | -09:50:56.76 | 300 | 58602.3248 | $r$ | 21.67
Swope | 17:13:47.52 | -09:50:57.12 | 300 | 58602.3288 | $i$ | 20.95
Swope | 17:13:47.50 | -09:50:56.76 | 300 | 58602.3327 | $g$ | 22.21
Swope | 17:31:34.39 | -08:20:18.60 | 600 | 58602.3392 | $r$ | 22.23
Swope | 17:31:34.42 | -08:20:18.96 | 600 | 58602.3467 | $i$ | 21.48
Swope | 17:31:34.34 | -08:20:18.24 | 600 | 58602.3541 | $g$ | 22.67
Swope | 16:25:41.38 | +19:20:14.64 | 180 | 58602.3870 | $r$ | 21.72
Swope | 16:19:19.10 | +18:20:38.76 | 180 | 58602.3907 | $r$ | 21.64
Swope | 16:23:23.35 | +16:51:09.72 | 180 | 58602.3940 | $r$ | 21.62
Swope | 16:25:25.70 | +16:21:21.60 | 180 | 58602.3973 | $r$ | 21.51
Swope | 16:29:29.38 | +15:51:33.84 | 180 | 58602.4004 | $r$ | 21.63
Swope | 16:29:25.66 | +15:21:34.92 | 180 | 58602.4037 | $r$ | 21.47
Swope | 17:20:09.79 | -01:01:39.00 | 180 | 58602.4074 | $r$ | 21.08
Swope | 16:50:51.94 | +07:54:58.68 | 180 | 58602.4111 | $r$ | 21.74
Swope | 16:46:57.19 | +08:54:40.32 | 180 | 58602.4148 | $r$ | 21.59
Swope | 16:48:44.71 | +06:25:23.88 | 180 | 58602.4184 | $r$ | 21.72
Swope | 16:44:48.84 | +07:25:10.20 | 180 | 58602.4216 | $i$ | 20.56
Swope | 05:22:58.08 | -11:23:30.12 | 600 | 58602.9589 | $r$ | 21.39
Swope | 05:22:58.15 | -11:23:30.12 | 600 | 58602.9667 | $i$ | 21.11
Swope | 05:22:58.06 | -11:23:29.04 | 600 | 58602.9742 | $g$ | 22.72
Swope | 12:12:25.44 | +24:14:24.72 | 90 | 58603.0706 | $B$ | 21.66
Swope | 12:12:25.44 | +24:14:23.28 | 45 | 58603.0721 | $V$ | 21.08
Swope | 12:12:25.42 | +24:14:27.60 | 240 | 58603.0733 | $u$ | 20.98
Swope | 12:12:25.42 | +24:14:25.80 | 45 | 58603.0767 | $g$ | 21.63
Swope | 12:12:25.44 | +24:14:24.72 | 45 | 58603.0777 | $i$ | 20.25
Swope | 12:12:25.42 | +24:14:25.44 | 45 | 58603.0787 | $r$ | 20.79
Swope | 13:09:32.93 | +28:22:49.80 | 150 | 58603.1127 | $g$ | 22.03
Swope | 13:09:32.90 | +28:22:49.44 | 150 | 58603.1172 | $r$ | 21.31
Swope | 16:48:25.25 | -17:25:10.56 | 180 | 58603.1540 | $i$ | 21.36
Swope | 16:52:28.66 | -16:55:21.00 | 180 | 58603.1576 | $i$ | 20.87
Swope | 16:56:32.86 | -01:31:23.16 | 180 | 58603.1623 | $i$ | 21.44
Swope | 17:04:38.23 | -04:30:09.36 | 180 | 58603.1675 | $i$ | 21.44
Swope | 16:58:32.11 | -02:01:00.12 | 180 | 58603.1857 | $i$ | 21.40
Swope | 16:56:32.30 | -02:00:54.36 | 180 | 58603.1888 | $i$ | 21.44
Swope | 16:54:36.96 | -03:30:26.28 | 180 | 58603.1921 | $i$ | 21.40
Swope | 16:58:44.81 | -05:29:35.16 | 180 | 58603.1955 | $i$ | 21.44
Swope | 16:56:48.94 | -06:29:14.28 | 180 | 58603.1987 | $i$ | 21.29
Swope | 16:56:52.61 | -06:59:01.68 | 180 | 58603.2019 | $i$ | 21.31
Swope | 17:01:43.92 | -12:26:56.76 | 180 | 58603.2057 | $i$ | 21.19
Swope | 16:54:56.40 | -07:28:42.60 | 180 | 58603.2091 | $i$ | 21.38
Swope | 16:55:14.81 | -09:57:52.92 | 180 | 58603.2126 | $i$ | 21.45
Swope | 16:52:01.56 | -14:55:51.96 | 180 | 58603.2317 | $i$ | 21.39
Swope | 16:54:32.14 | -16:55:17.40 | 180 | 58603.2349 | $i$ | 21.23
Swope | 16:52:19.70 | -16:25:25.68 | 180 | 58603.2627 | $i$ | 21.55
Swope | 15:35:39.22 | +27:17:56.76 | 180 | 58603.2673 | $i$ | 21.35
Swope | 15:28:36.22 | +28:17:23.28 | 180 | 58603.2707 | $i$ | 21.37
Swope | 15:33:06.96 | +28:17:26.52 | 180 | 58603.2739 | $i$ | 21.37
Swope | 15:39:51.67 | +28:17:28.68 | 180 | 58603.2769 | $i$ | 21.39
Swope | 15:46:09.84 | +30:16:49.80 | 180 | 58603.2802 | $i$ | 21.33
Swope | 15:42:05.02 | +28:17:24.00 | 180 | 58603.2834 | $i$ | 21.30
Swope | 15:42:13.37 | +27:47:34.44 | 180 | 58603.2867 | $i$ | 21.32
Swope | 15:47:05.74 | +25:48:18.72 | 180 | 58603.2902 | $i$ | 21.18
Swope | 15:56:01.15 | +24:19:01.20 | 180 | 58603.2936 | $i$ | 21.09
Swope | 16:02:33.74 | +24:19:05.16 | 180 | 58603.2968 | $i$ | 20.83
Swope | 16:02:34.85 | +23:19:22.80 | 180 | 58603.3035 | $i$ | 20.43
Swope | 16:06:56.62 | +22:19:56.28 | 180 | 58603.3067 | $i$ | 21.01
Swope | 16:15:27.05 | +21:49:48.72 | 180 | 58603.3100 | $i$ | 21.15
Swope | 16:06:57.34 | +19:50:28.32 | 180 | 58603.3130 | $i$ | 21.17
Swope | 16:15:21.43 | +19:20:57.48 | 180 | 58603.3162 | $i$ | 21.09
Swope | 16:17:28.32 | +19:21:05.04 | 180 | 58603.3195 | $i$ | 21.33
Swope | 16:04:54.79 | +17:51:38.52 | 180 | 58603.3227 | $i$ | 21.27
Swope | 16:50:43.61 | +04:26:56.04 | 180 | 58603.3267 | $i$ | 21.35
Swope | 16:52:37.82 | +02:27:38.52 | 180 | 58603.3298 | $i$ | 21.29