# A Swift Fix for Nuclear Outbursts

Jason T. Hinkle Institute for Astronomy, University of Hawai‘i, 2680 Woodlawn
Drive, Honolulu, HI 96822, USA  Thomas W.-S. Holoien NHFP Einstein Fellow  The
Observatories of the Carnegie Institution for Science, 813 Santa Barbara
Street., Pasadena, CA 91101, USA  Benjamin. J. Shappee Institute for
Astronomy, University of Hawai‘i, 2680 Woodlawn Drive, Honolulu, HI 96822, USA
Katie Auchettl School of Physics, The University of Melbourne, Parkville, VIC
3010, Australia  ARC Centre of Excellence for All Sky Astrophysics in 3
Dimensions (ASTRO 3D)  Department of Astronomy and Astrophysics, University of
California, Santa Cruz, CA 95064, USA

###### Abstract

In November 2020, the Swift team announced an update to the UltraViolet and
Optical Telescope calibration to correct for the loss of sensitivity over
time. This correction affects observations in the three near ultraviolet (UV)
filters, by up to 0.3 mag in some cases. As UV photometry is critical to
characterizing tidal disruption events (TDEs) and other peculiar nuclear
outbursts, we re-computed published Swift data for TDEs and other singular
nuclear outbursts with Swift photometry in 2017 or later, as a service to the
community. Using archival UV, optical, and infrared photometry we ran host SED
fits for each host galaxy. From these, we computed synthetic host magnitudes
and host-galaxy properties. We calculated host-subtracted magnitudes for each
transient and computed blackbody fits. In addition to the nuclear outbursts,
we include the ambiguous transient ATLAS18qqn (AT2018cow), which has been
classifed as a potential TDE on an intermediate mass black hole. Finally, with
updated bolometric light curves, we recover the relationship of Hinkle et al.
(2020), where more luminous TDEs decay more slowly than less luminous TDEs
with decreased scatter as compared to the original relationship.

Active galactic nuclei(16) — Black hole physics (159) — Near ultraviolet
astronomy(1094) — Supermassive black holes (1663) — Tidal disruption (1696) —
Transient sources (1851)

††journal: AJ††facilities: Swift (UVOT) (Roming et al., 2005)††software:
linmix (Kelly, 2007)

##  1 Introduction

A tidal disruption event (TDE) occurs when a star passes too close to a
supermassive black hole (SMBH) and is torn apart by tidal forces. A fraction
of the disrupted stellar material is subsequently accreted onto the SMBH,
resulting in a short-lived, luminous flare (e.g., Lacy et al., 1982; Rees,
1988; Evans & Kochanek, 1989; Phinney, 1989). Because they can occur in
quiescent galaxies, TDEs are useful as probes of inactive black holes, and
allow the study of accretion disks as they form, evolve, and are disrupted on
observable timescales.

In recent years, wide-field, untargeted transient surveys, such as the All-Sky
Automated Survey for SuperNovae (ASAS-SN; Shappee et al., 2014; Kochanek et
al., 2017), the Asteroid Terrestrial Last-impact Alert System (ATLAS; Tonry et
al., 2018), the Panoramic Survey Telescope and Rapid Response System (Pan-
STARRS Chambers et al., 2016), and the Zwicky Transient Facility (ZTF; Bellm
et al., 2019) have put substantial effort into identifying and studying
transient outbursts thought to be TDEs. TDEs are identified as discrete flares
nuclear flares with hot ($1-5\times 10^{4}$ K) blackbody spectral energy
distributions (SEDs) and broad hydrogen and/or helium lines in their optical
spectra. Their temporal evolution is very different from the typical
stochastic variability of AGN. In the process of searching for TDEs, other
nuclear outbursts have also been discovered. Some may be unusual TDEs, such as
TDEs occurring around existing AGN (e.g., Blanchard et al., 2017; Payne et
al., 2020), TDEs caused by an intermediate or stellar-mass black hole (e.g.,
Perley et al., 2019; Kremer et al., 2020), or unrelated phenomena like “rapid
turn-on” and changing-look AGN (e.g., Shappee et al., 2014; Wyrzykowski et
al., 2017; Frederick et al., 2019; Trakhtenbrot et al., 2019a).

A common feature of these nuclear outbursts is that a significant portion of
their emission is emitted at ultraviolet (UV) wavelengths. As such,
observations from space-based UV telescopes, in particular the Neil Gehrels
Swift Observatory (Swift; Gehrels et al., 2004), are crucial for
characterizing the temperatures and luminosities of these events. Nearly all
transients identified as possible TDEs have thus been the subjects of extended
monitoring campaigns with the Swift UltraViolet and Optical Telescope (UVOT;
Roming et al., 2005).

In Novemeber 2020, the Swift team announced that due to a loss of sensitivity
over time, the photometric calibration for the three UVOT UV filters needed to
be retroactively corrected111https://www.swift.ac.uk/analysis/uvot/index.php.
This loss of sensitivity cn affect UV observations made with Swift after 2017
by up to 0.3 magnitudes. Since Swift observations are often used to estimate
blackbody temperatures in nuclear outbursts, a difference of 0.3 mag can have
a significant effect on the estimated blackbody temperatures and luminosities,
particularly for cases where the transient magnitude is close to that of its
host galaxy. The UVOT photometry correction thus has the potential to affect
not only the conclusions about individual objects, but also the conclusions of
population studies (e.g., Arcavi et al., 2014; Hung et al., 2017; Hinkle et
al., 2020; van Velzen et al., 2020).

Here we re-compute the Swift photometry for all previously published epochs of
Swift data taken of TDEs and other singular nuclear outbursts that were
observed by Swift in 2017 or later. This includes both transients discovered
after 2017 and those discovered prior to 2017 that were still being observed
after 2017. We have also used multi-wavelength archival data to model the SEDs
of the transient host galaxies and produce host-subtracted light curves and
blackbody models of these transients in a uniform way. We present the
resulting corrected Swift light curves, host-subtracted light curves, and
blackbody models, which we make publicly available.

In Section 2 we discuss the sample selection. Section 3 discusses the sources
of archival photometry and the models for the SEDs of the transient host
galaxies. Section 4 discusses our reduction of the Swift UVOT data and
presents the raw and host-subtracted Swift light curves. Section 5 covers our
blackbody models of the transient SEDs and presents the resulting
luminosities, radii, and temperatures. Section 6 discusses our re-analysis of
the peak-luminosity/decline-rate relationship we first presented in Hinkle et
al. (2020). Finally, Section 7 summarizes the results of this work. Throughout
this paper, we have used a cosmology with $H_{0}$ = 69.6 km s-1 Mpc-1,
$\Omega_{M}=0.29$, and $\Omega_{\Lambda}=0.71$.

##  2 Sample

For our re-analysis, we selected 35 objects that have been classified as TDE
candidates or other nuclear outbursts in the literature. These objects are
listed in Table 1, along with the references where the Swift photometry was
originally published and the source classifications, typically either as an
AGN or a TDE. Where the nature of a source is unclear, we list the
classification as an “AGN/TDE”. All but one of our sources is consistent with
the host nucleus. The lone exception, ATLAS18qqn (AT2018cow), is the brightest
of the growing class of fast optical transients (e.g., Prentice et al., 2018;
Ho et al., 2020; Coppejans et al., 2020). It has been interpreted as either an
exotic supernova (e.g., Prentice et al., 2018; Perley et al., 2019), the tidal
disruption of a star by an intermediate mass black hole (e.g., Perley et al.,
2019; Uno & Maeda, 2020), or the tidal disruption of a star by a stellar mass
black hole in a star cluster (Kremer et al., 2020). We list it as “Ambiguous”
in Table 1 and include it in our sample due to the potential TDE
classification.

In our Swift re-analysis, we used a 5$\farcs$0 radius aperture except for
ASASSN-17cv, ASASSN-19dj, ZTF18aajupnt, ZTF19aaiqmgl, and ZTF19abzrhgq which
used 10$\farcs$0, 15$\farcs$0, 15$\farcs$0, 10$\farcs$0, and 10$\farcs$0
radius apertures respectively. These larger apertures were chosen to
incorporate the entire host galaxy. Additionally, the transient photometry for
ATLAS18qqn was measured using a 3$\farcs$0 radius aperture to minimize host
contamination as the source is non-nuclear. We chose 5$\farcs$0 as the default
for sources without clear aperture sizes in the literature because 5$\farcs$0
is the standard Swift aperture radius and has small aperture loss corrections
(Poole et al., 2008).

Table 1: Sample of Objects

Object | TNS ID | Right Ascension | Declination | Type | References
---|---|---|---|---|---
ASASSN-14li | … | 12:48:15.230 |  $+$17:46:26.44 | TDE |  Holoien et al. (2016a), Brown et al. (2017), van Velzen et al. (2019)
ASASSN-15oi | … | 20:39:09.183 |  $-$30:45:20.10 | TDE |  Holoien et al. (2016b), Gezari et al. (2017), Holoien et al. (2018)
ASASSN-17cv | AT2017bgt | 16:11:05.696 |  $+$02:34:0.52 | AGN | Trakhtenbrot et al. (2019a)
ASASSN-18el | AT2018zf | 19:27:19.551 |  $+$65:33:54.31 | AGN/TDE |  Trakhtenbrot et al. (2019b), Ricci et al. (2020)
ASASSN-18jd | AT2018bcb | 22:43:42.871 |  $-$16:59:08.49 | AGN/TDE | Neustadt et al. (2020)
ASASSN-18pg | AT2018dyb | 16:10:58.774 |  $-$60:55:23.16 | TDE |  Leloudas et al. (2019), Holoien et al. (2020)
ASASSN-18ul | AT2018fyk | 22:50:16.090 |  $-$44:51:53.50 | TDE | Wevers et al. (2019)
ASASSN-18zj | AT2018hyz | 10:06:50.871 |  $+$01:41:34.08 | TDE |  van Velzen et al. (2020), Hung et al. (2020a), Gomez et al. (2020)
ASASSN-19bt | AT2019ahk | 07:00:11.546 |  $-$66:02:24.14 | TDE | Holoien et al. (2019a)
ASASSN-19dj | AT2019azh | 08:13:16.945 |  $+$22:38:54.03 | TDE |  Liu et al. (2019), van Velzen et al. (2020), Hinkle et al. (2021)
ATLAS18qqn | AT2018cow | 16:16:00.220 |  $+$22:16:04.91 | Ambiguous |  Prentice et al. (2018), Perley et al. (2019)
ATLAS18way | AT2018hco | 01:07:33.635 |  $+$23:28:34.28 | TDE | van Velzen et al. (2020)
ATLAS18yzs | AT2018iih | 17:28:03.930 |  $+$30:41:31.42 | TDE | van Velzen et al. (2020)
ATLAS19qqu | AT2019mha | 16:16:27.799 |  $+$56:25:56.29 | TDE | van Velzen et al. (2020)
Gaia19axp | AT2019brs | 14:27:46.400 |  $+$29:30:38.27 | AGN | Frederick et al. (2020)
Gaia19bpt | AT2019ehz | 14:09:41.880 |  $+$55:29:28.10 | TDE | van Velzen et al. (2020)
iPTF16fnl | AT2016fnl | 00:29:57.042 |  $+$32:53:37.51 | TDE |  Blagorodnova et al. (2017), Brown et al. (2018)
OGLE16aaa | … | 01:07:20.880 |  $-$64:16:20.70 | TDE |  Wyrzykowski et al. (2017), Kajava et al. (2020)
OGLE17aaj | … | 01:56:24.930 |  $-$71:04:15.70 | AGN | Gromadzki et al. (2019)
PS16dtm | AT2016ezh | 01:58:04.739 |  $-$00:52:21.74 | TDEaaThese sources have been interpreted as TDEs occuring in AGN host galaxies | Blanchard et al. (2017)
PS17dhz | AT2017eqx | 22:26:48.370 |  $+$17:08:52.40 | TDE | Nicholl et al. (2019)
PS18kh | AT2018zr | 07:56:54.537 |  $+$34:15:43.61 | TDE |  Holoien et al. (2019b), van Velzen (2018)
ZTF18aahqkbt | AT2018bsi | 08:15:26.621 |  $+$45:35:31.95 | TDE | van Velzen et al. (2020)
ZTF18aajupnt | AT2018dyk | 15:33:08.015 |  $+$44:32:08.20 | LINER | Frederick et al. (2019)
ZTF18actaqdw | AT2018lni | 04:09:37.652 |  $+$73:53:41.66 | TDE | van Velzen et al. (2020)
ZTF19aabbnzo | AT2018lna | 07:03:18.649 |  $+$23:01:44.70 | TDE | van Velzen et al. (2020)
ZTF19aaiqmgl | AT2019avd | 08:23:36.767 |  $+$04:23:02.46 | AGN | Frederick et al. (2020)
ZTF19aakiwze | AT2019cho | 12:55:09.210 |  $+$49:31:09.93 | TDE | van Velzen et al. (2020)
ZTF19aakswrb | AT2019bhf | 15:09:15.975 |  $+$16:14:22.52 | TDE | van Velzen et al. (2020)
ZTF19aapreis | AT2019dsg | 20:57:02.974 |  $+$14:12:15.86 | TDE | van Velzen et al. (2020)
ZTF19aatubsj | AT2019fdr | 17:09:06.859 |  $+$26:51:20.50 | TDEaaThese sources have been interpreted as TDEs occuring in AGN host galaxies | Frederick et al. (2020)
ZTF19abhhjcc | AT2019meg | 18:45:16.180 |  $+$44:26:19.21 | TDE | van Velzen et al. (2020)
ZTF19abidbya | AT2019lwu | 23:11:12.305 |  $-$01:00:10.71 | TDE | van Velzen et al. (2020)
ZTF19abvgxrq | AT2019pev | 04:29:22.720 |  $+$00:37:07.50 | AGN | Frederick et al. (2020)
ZTF19abzrhgq | AT2019qiz | 04:46:37.880 |  $-$10:13:34.90 | TDE |  van Velzen et al. (2020), Nicholl et al. (2020), Hung et al. (2020b)

Note. — The 35 transients we re-analyze in this manuscript. TNS ID is the ID
given for objects reported on the Transient Name Server. References include
the discovery papers and papers using Swift data taken in 2017 or later. The
type given reflects the classifications in the listed references. If using the
revised photometry presented here, please cite both this paper and the
original paper(s) in which Swift photometry was published.

##  3 Host Galaxy SED Fits

In order to accurately measure the UV and optical photometry of each
transient, we must first subtract the emission of the host galaxy. Two of our
sources, ASASSN-19bt and ATLAS18qqn have Swift images of the host galaxy
during quiescence (see Holoien et al. (2019a) and Perley et al. (2019)
respectively), from which we directly obtained host fluxes. In the case of
ATLAS18qqn, we measured the flux at the location of the transient, offset from
the host galaxy nucleus. For most of our sources, there was no archival Swift
coverage of the host galaxy. For these sources, we fit archival multi-
wavelength photometry of the host galaxy using the Fitting and Assessment of
Synthetic Templates code (FAST; Kriek et al., 2009) to obtain a spectral
energy distribution (SED) of the host galaxy, from which we can estimate the
UV flux.

Table 2: Archival Host Photometry

Object | TNS ID | Filter | Magnitude | Uncertainty
---|---|---|---|---
… | … | … | … | …
ASASSN-19dj | AT2019azh | NUV | 18.71 | 0.05
ASASSN-19dj | AT2019azh | u(SDSS) | 16.80 | 0.10
ASASSN-19dj | AT2019azh | g(SDSS) | 15.12 | 0.04
ASASSN-19dj | AT2019azh | r(SDSS) | 14.59 | 0.03
ASASSN-19dj | AT2019azh | i(SDSS) | 14.35 | 0.03
ASASSN-19dj | AT2019azh | z(SDSS) | 14.13 | 0.03
ASASSN-19dj | AT2019azh | J | 13.94 | 0.04
ASASSN-19dj | AT2019azh | H | 13.99 | 0.09
ASASSN-19dj | AT2019azh | Ks | 14.34 | 0.05
ASASSN-19dj | AT2019azh | W1 | 15.07 | 0.03
ASASSN-19dj | AT2019azh | W2 | 15.70 | 0.03
… | … | … | … | …

Note. — Archival UV, optical, and infrared photometry used in the FAST SED
fits for our objects. All magnitudes are presented in the AB system, using
published conversions for systems naturally in the Vega system. For
ASASSN-19bt and ATLAS18qqn, the UVOT magnitudes listed were used to subtract
the Swift photometry and the other photometry was used for the host SED fit.
The TDE ASASSN-19dj is shown here to illustrate the format, while the full
table is available as an ancillary file.

For objects without Swift images in quiescence, we used published host galaxy
magnitudes to fit the host galaxy SED with FAST when available. For sources
without literature magnitudes222The sources with host magnitudes in the
literature are ASASSN-14li, ASASSN-15oi, ASASSN-18jd, ASASSN-18pg,
ASASSN-18ul, ASASSN-18zj, ASASSN-19bt, ASASSN-19dj, iPTF16fnl, OGLE17aaj, and
PS18kh we obtained $JHK_{S}$ images from the Two Micron All-Sky Survey (2MASS;
Skrutskie et al., 2006) for near infrared (NIR) constraints and $ugriz$ or
$grizY$ images from the from Sloan Digital Sky Survey (SDSS) Data Release 16
(Ahumada et al., 2020) or Pan-STARRS (Chambers et al., 2016) for optical
constraints. We then measured aperture magnitudes of the host galaxy in the
2MASS and SDSS/Pan-STARRS data using the same aperture size as was used for
the follow-up photometry (see Section 4), using nearby stars to calibrate the
galaxy magnitudes. The TDEs ASASSN-19bt and OGLE16aaa were too far south to be
observed by either SDSS or Pan-STARRS, so we obtained catalog magnitudes from
the AAVSO Photometric All-Sky Survey (APASS; Henden et al., 2015) and the Dark
Energy Survey (Abbott et al., 2018), respectively. We additionally obtained UV
magnitudes from the Galaxy Evolution Explorer (GALEX; Martin et al., 2005)
All-sky Imaging Survey (AIS) catalog and $W1$ and $W2$ magnitudes from the
Wide-field Infrared Survey Explorer (WISE; Wright et al., 2010) AllWISE
catalog for all hosts in our sample. The archival photometry is shown in Table
2.

We then fit this archival host-galaxy photometry using FAST and assuming a
Cardelli et al. (1988) extinction law with $\text{R}_{\text{V}}=3.1$ and
Galactic extinction at the coordinates of the host galaxy (Schlafly &
Finkbeiner, 2011), a Salpeter IMF (Salpeter, 1955), an exponentially declining
star-formation rate, and the Bruzual & Charlot (2003) stellar population
models. We estimated the host flux in the UVOT filters for each FAST iteration
by convolving the best-fit host SED from FAST with the filter response curve
for each filter, obtained from the Spanish Virtual Observatory (SVO) Filter
Profile Service (Rodrigo et al., 2012). In addition to the UVOT filters, we
used the Bessel filter responses (Bessell, 1990) to obtain Johnson-Cousins
magnitudes. To estimate the uncertainties on the estimated host-galaxy fluxes,
we performed a Monte Carlo sampling by perturbing the archival host fluxes
assuming Gaussian errors and running 1000 different FAST iterations for each
host galaxy. We took the median value as the magnitude and calculated
$1\sigma$ errors by taking the difference between the 16th and 84th percentile
values from the median and taking the larger value as the error. We then
subtracted these synthetic host fluxes from the Swift photometry. In most
cases, these synthetic magnitudes are well-constrained, but for host galaxies
without GALEX magnitudes, such as the hosts of ASASSN-18pg, PS17dhz and
ZTF19abidbya, the UV synthetic magnitudes often have large uncertainties as
the star formation rates (SFRs), and thus UV emission, are poorly constrained.
The synthetic magnitudes computed for each object, spanning from GALEX $FUV$
to 2MASS $K_{s}$ are shown in Table 3. In general, the archival and synthetic
magnitudes agree within the uncertainties indicating a reasonable fit. For the
objects with synthetic host magnitudes in the literature, such as PS18kh and
ASASSN-18ul, our host values are largely consistent within the uncertainties.
Any discrepancies are likely due to fitting different archival photometry
and/or different choices made when fitting the host SEDs.

Because the TDE ASASSN-19bt (Holoien et al., 2019a) has Swift UVOT images with
no transient source, we are able to test the accuracy of our synthetic Swift
magnitudes. We fit GALEX $NUV$, APASS $gri$, 2MASS $JHK_{s}$, WISE $W1$ and
$W2$ photometry of the host galaxy, excluding the UVOT data, and then computed
synthetic UVOT magnitudes. We find that for each of the six UVOT bands, the
measured and synthetic photometry are consistent given the uncertainties. If
we repeat this process without the GALEX $NUV$ constraint, the differences are
larger but the models are still consistent with the data given the larger
uncertainties.

Table 3: Synthetic Host-Galaxy Magnitudes

Object | TNS ID | Filter | Magnitude | Uncertainty |
---|---|---|---|---|---
… | … | … | … | … |
ASASSN-19dj | AT2019azh | FUV(GALEX) | 20.449 | 0.863 |
ASASSN-19dj | AT2019azh | NUV(GALEX) | 18.768 | 0.125 |
ASASSN-19dj | AT2019azh | UVW2(UVOT) | 19.320 | 0.238 |
ASASSN-19dj | AT2019azh | UVM2(UVOT) | 18.827 | 0.127 |
ASASSN-19dj | AT2019azh | UVW1(UVOT) | 18.196 | 0.108 |
ASASSN-19dj | AT2019azh | U(UVOT) | 16.721 | 0.048 |
ASASSN-19dj | AT2019azh | B(UVOT) | 15.445 | 0.079 |
ASASSN-19dj | AT2019azh | V(UVOT) | 14.884 | 0.040 |
ASASSN-19dj | AT2019azh | U(J-C) | 16.574 | 0.055 |
ASASSN-19dj | AT2019azh | B(J-C) | 15.439 | 0.076 |
ASASSN-19dj | AT2019azh | V(J-C) | 14.830 | 0.039 |
ASASSN-19dj | AT2019azh | R(J-C) | 14.580 | 0.022 |
ASASSN-19dj | AT2019azh | I(J-C) | 14.331 | 0.022 |
ASASSN-19dj | AT2019azh | u(SDSS) | 16.623 | 0.049 |
ASASSN-19dj | AT2019azh | g(SDSS) | 15.203 | 0.064 |
ASASSN-19dj | AT2019azh | r(SDSS) | 14.630 | 0.026 |
ASASSN-19dj | AT2019azh | i(SDSS) | 14.405 | 0.019 |
ASASSN-19dj | AT2019azh | z(SDSS) | 14.211 | 0.029 |
ASASSN-19dj | AT2019azh | J(2MASS) | 13.995 | 0.041 |
ASASSN-19dj | AT2019azh | H(2MASS) | 13.798 | 0.050 |
ASASSN-19dj | AT2019azh | Ks(2MASS) | 13.989 | 0.049 |
… | … | … | … | … |

Note. — Synthetic host photometry computed from the Monte Carlo sampling of
host galaxy SED fits with FAST. We used the Bessel filter responses (Bessell,
1990) for our Johnson-Cousins synthetic magnitude calculations. All magnitudes
are presented in the AB system, using published conversions for systems
naturally in the Vega system. Note that the synthetic photometry listed in
this table for ATLAS18qqn represents the entire host galaxy, not the region
where the transient occurred and thus the UVOT magnitudes are significantly
brighter. The values used for the subtraction of ATLAS18qqn are measured at
the region of the transient from Swift images. The TDE ASASSN-19dj is shown
here to illustrate the format and the full table is available as an ancillary
file.

In addition to providing synthetic photometry for host flux subtraction, the
FAST models constrain the age of the stellar population, the stellar mass, and
the star formation rate of the host. Uncertainties on the host properties are
computed in the same fashion as the synthetic magnitudes. In some cases our
reported one-sided uncertainties are zero, which is a consequence of the grid
spacing used in the FAST fitting procedure. In such cases, the median and
either 16th or 84th percentile values are identical due to the discrete
spacing of the grid in that parameter. This is most notable in the stellar
population ages where the grid spacing was log(age) = 0.05. The SED fit to the
host galaxy of ZTF19aabbnzo is particularly poorly constrained, with no limit
on the SFR given the sampling. If we use the 99.7th percentile value, we
obtain a weak upper limit of log[SFR (M$\odot$ yr-1)] $<-1.86$.

Table 4 provides these host parameters for each of our host galaxies. FAST
only fits stellar population synthesis models, so the fits for the galaxies
known to host AGN have not taken into account a non-stellar component.
Additionally for some of the larger galaxies, the default 5$\farcs$0 radius
used to match the Swift photometry does not encapsulate the full host galaxy.
Finally, as expected, many of the TDE host galaxies are relatively low mass,
consistent with hosting SMBHs less massive than $\sim 10^{7}$ M$\odot$ (van
Velzen, 2018; Wevers et al., 2019; Mockler et al., 2019).

Table 4: Host-Galaxy Properties

Object | TNS ID | Redshift | AV | log[Age (yr)] | log[Mass (M$\odot$)] | log[SFR (M$\odot$ yr-1)]
---|---|---|---|---|---|---
ASASSN-14li | … | 0.0206 | 0.070 | $9.40_{-0.15}^{+0.00}$ | $9.72_{-0.12}^{+0.01}$ | $-1.48_{-0.15}^{+0.01}$
ASASSN-15oi | … | 0.0479 | 0.185 | $9.35_{-0.05}^{+0.05}$ | $9.99_{-0.04}^{+0.03}$ | $<-3.60$
ASASSN-17cv | AT2017bgt | 0.0640 | 0.213 | $9.95_{-0.15}^{+0.00}$ | $11.06_{-0.07}^{+0.01}$ | $0.32_{-0.08}^{+0.02}$
ASASSN-18el | AT2018zf | 0.0190 | 0.236 | $9.65_{-0.05}^{+0.10}$ | $9.59_{-0.06}^{+0.02}$ | $-0.81_{-0.06}^{+0.03}$
ASASSN-18jd | AT2018bcb | 0.1192 | 0.098 | $9.90_{-0.10}^{+0.05}$ | $11.22_{-0.08}^{+0.01}$ | $-0.18_{-0.26}^{+0.02}$
ASASSN-18pg | AT2018dyb | 0.0179 | 0.624 | $9.90_{-0.20}^{+0.10}$ | $10.16_{-0.11}^{+0.05}$ | $<-1.13$
ASASSN-18ul | AT2018fyk | 0.0590 | 0.037 | $9.80_{-0.05}^{+0.05}$ | $10.70_{-0.02}^{+0.04}$ | $-1.50_{-0.98}^{+0.40}$
ASASSN-18zj | AT2018hyz | 0.0457 | 0.094 | $9.10_{-0.00}^{+0.05}$ | $9.71_{-0.05}^{+0.01}$ | $<-2.04$
ASASSN-19bt | AT2019ahk | 0.0262 | 0.336 | $9.85_{-0.20}^{+0.15}$ | $10.29_{-0.12}^{+0.08}$ | $-0.60_{-0.03}^{+0.04}$
ASASSN-19dj | AT2019azh | 0.0223 | 0.122 | $9.10_{-0.05}^{+0.05}$ | $9.95_{-0.02}^{+0.03}$ | $-1.56_{-0.17}^{+0.42}$
ATLAS18qqn | AT2018cow | 0.0141 | 0.238 | $9.95_{-0.10}^{+0.05}$ | $9.81_{-0.06}^{+0.01}$ | $-0.69_{-0.03}^{+0.01}$
ATLAS18way | AT2018hco | 0.0880 | 0.109 | $9.15_{-0.10}^{+0.25}$ | $9.69_{-0.06}^{+0.17}$ | $<-0.95$
ATLAS18yzs | AT2018iih | 0.2120 | 0.135 | $9.10_{-0.00}^{+0.40}$ | $10.56_{-0.06}^{+0.26}$ | $<-2.07$
ATLAS19qqu | AT2019mha | 0.1480 | 0.022 | $8.95_{-0.05}^{+0.20}$ | $9.75_{-0.07}^{+0.08}$ | $<-1.63$
Gaia19axp | AT2019brs | 0.3736 | 0.043 | $9.45_{-0.85}^{+0.45}$ | $11.08_{-0.52}^{+0.35}$ | $0.57_{-2.15}^{+0.05}$
Gaia19bpt | AT2019ehz | 0.0740 | 0.048 | $9.10_{-0.10}^{+0.15}$ | $9.37_{-0.05}^{+0.13}$ | $<-2.07$
iPTF16fnl | AT2016fnl | 0.0163 | 0.226 | $9.25_{-0.00}^{+0.05}$ | $9.49_{-0.00}^{+0.04}$ | $-1.73_{-0.01}^{+0.15}$
OGLE16aaa | … | 0.1655 | 0.057 | $9.20_{-0.00}^{+0.05}$ | $10.54_{-0.01}^{+0.02}$ | $-0.46_{-0.01}^{+0.28}$
OGLE17aaj | … | 0.1160 | 0.077 | $9.70_{-0.85}^{+0.20}$ | $10.41_{-0.33}^{+0.13}$ | $<0.13$
PS16dtm | AT2016ezh | 0.0804 | 0.070 | $9.50_{-0.20}^{+0.35}$ | $9.93_{-0.14}^{+0.20}$ | $-0.55_{-0.05}^{+0.03}$
PS17dhz | AT2017eqx | 0.1089 | 0.175 | $9.30_{-1.05}^{+0.70}$ | $9.12_{-0.76}^{+0.38}$ | $<-0.13$
PS18kh | AT2018zr | 0.0710 | 0.128 | $9.50_{-0.05}^{+0.00}$ | $9.97_{-0.04}^{+0.02}$ | $<-2.94$
ZTF18aahqkbt | AT2018bsi | 0.0510 | 0.170 | $9.80_{-0.10}^{+0.00}$ | $10.72_{-0.08}^{+0.01}$ | $-0.86_{-0.01}^{+0.02}$
ZTF18aajupnt | AT2018dyk | 0.0367 | 0.055 | $9.85_{-0.00}^{+0.10}$ | $11.00_{-0.01}^{+0.07}$ | $0.05_{-0.02}^{+0.01}$
ZTF18actaqdw | AT2018lni | 0.1380 | 0.661 | $10.00_{-0.05}^{+0.00}$ | $10.23_{-0.05}^{+0.06}$ | $-0.28_{-0.14}^{+0.10}$
ZTF19aabbnzo | AT2018lna | 0.0910 | 0.130 | $9.00_{-0.00}^{+0.00}$ | $9.76_{-0.02}^{+0.03}$ | $-99.00_{-0.00}^{+0.00}$
ZTF19aaiqmgl | AT2019avd | 0.0296 | 0.072 | $9.90_{-0.10}^{+0.05}$ | $10.42_{-0.06}^{+0.02}$ | $-0.77_{-0.03}^{+0.04}$
ZTF19aakiwze | AT2019cho | 0.1930 | 0.038 | $9.20_{-0.30}^{+0.60}$ | $9.82_{-0.18}^{+0.31}$ | $<-0.42$
ZTF19aakswrb | AT2019bhf | 0.1206 | 0.068 | $9.50_{-0.20}^{+0.30}$ | $10.34_{-0.14}^{+0.20}$ | $-0.71_{-0.41}^{+0.16}$
ZTF19aapreis | AT2019dsg | 0.0512 | 0.280 | $9.85_{-0.05}^{+0.05}$ | $10.57_{-0.02}^{+0.02}$ | $-0.75_{-0.26}^{+0.12}$
ZTF19aatubsj | AT2019fdr | 0.2666 | 0.145 | $9.45_{-0.20}^{+0.25}$ | $10.93_{-0.13}^{+0.17}$ | $0.22_{-0.17}^{+0.18}$
ZTF19abhhjcc | AT2019meg | 0.1520 | 0.153 | $9.93_{-0.23}^{+0.07}$ | $10.16_{-0.11}^{+0.07}$ | $-0.79_{-0.26}^{+0.10}$
ZTF19abidbya | AT2019lwu | 0.1170 | 0.101 | $10.00_{-0.90}^{+0.00}$ | $9.98_{-0.38}^{+0.31}$ | $<-0.20$
ZTF19abvgxrq | AT2019pev | 0.0970 | 0.225 | $9.05_{-0.05}^{+0.10}$ | $10.33_{-0.03}^{+0.05}$ | $0.09_{-0.15}^{+0.07}$
ZTF19abzrhgq | AT2019qiz | 0.0151 | 0.302 | $9.50_{-0.00}^{+0.15}$ | $9.89_{-0.02}^{+0.08}$ | $<-2.28$

Note. — Host-galaxy properties computed from the FAST SED models in addition
to the host-galaxy redshift and Galactic visual extinction (Schlafly &
Finkbeiner, 2011). It is important to note that the radii used to measure the
host photometry were chosen to match the Swift aperture radius and therefore
for some objects do not encompass the entire host galaxy.

##  4 Swift UVOT Reductions

The UVOT has six typically used filters for photometric follow-up programs
(Poole et al., 2008): $V$ (5425.3 Å), $B$ (4349.6 Å), $U$ (3467.1 Å), $UVW1$
(2580.8 Å), $UVM2$ (2246.4 Å), and $UVW2$ (2054.6 Å). The wavelengths quoted
here are the pivot wavelengths calculated by the SVO Filter Profile Service
(Rodrigo et al., 2012), which we use throughout the remainder of this work.

Most epochs of UVOT data include multiple observations in each filter. We
separately combined the images in each filter for each unique observation
identification number using the HEASoft uvotimsum package. We then used the
uvotsource package to extract source counts in a region centered on the
position of the transient and background counts using a source-free region
with radius of $\sim$30-40$\farcs$ Our default source radius was 5$\farcs$0 to
minimize UVOT aperture corrections, but we matched the source radii used in
the literature whenever possible, as described in Section 2. We then converted
the UVOT count rates into fluxes and magnitudes using the most recent
calibrations (Poole et al., 2008; Breeveld et al., 2010). For each UVOT image,
we confirmed that the source did not lie on a region of the detector with
known sensitivity
issues333https://swift.gsfc.nasa.gov/analysis/uvot_digest/sss_check.html (also
see the Appendix of Edelson et al. 2015).

As the UVOT uses unique $B$ and $V$ filters, we converted the UVOT $B$ and $V$
data into the Johnson-Cousins system using color
corrections444https://heasarc.gsfc.nasa.gov/docs/heasarc/caldb/swift/docs/uvot/uvot_caldb_coltrans_02b.pdf.
For these filters, we used pivot wavelengths of $V$ (5477.7 Å) and $B$ (4371.1
Å), corresponding to the Bessel filter responses used in the synthetic
magnitude calculations. Table 5 provides the Swift photometry in both
magnitude and flux density without host subtraction or extinction correction.

Table 5: Unsubtracted Swift Photometry

Object | TNS ID | MJD | Filter | Magnitude | Uncertainty | Flux Density | Uncertainty
---|---|---|---|---|---|---|---
|  |  |  |  |  | (erg s-1 cm-2 Å-1) | erg s-1 cm-2 Å-1)
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.762 | V | 14.50 | 0.03 | 5.83E-15 | 1.77E-15
ASASSN-19dj | AT2019azh | 58553.457 | V | 14.46 | 0.04 | 6.10E-15 | 0.24E-15
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.758 | B | 14.68 | 0.04 | 7.71E-15 | 0.32E-15
ASASSN-19dj | AT2019azh | 58553.454 | B | 14.53 | 0.04 | 8.85E-15 | 0.37E-15
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.757 | U | 15.00 | 0.03 | 9.04E-15 | 0.25E-15
ASASSN-19dj | AT2019azh | 58553.453 | U | 14.88 | 0.04 | 1.01E-14 | 0.04E-14
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.755 | UVW1 | 15.00 | 0.04 | 1.63E-14 | 0.06E-14
ASASSN-19dj | AT2019azh | 58553.451 | UVW1 | 14.92 | 0.04 | 1.76E-14 | 0.06E-14
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.763 | UVM2 | 14.92 | 0.04 | 2.32E-14 | 0.06E-14
ASASSN-19dj | AT2019azh | 58553.458 | UVM2 | 14.88 | 0.04 | 2.41E-14 | 0.09E-14
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.759 | UVW2 | 14.75 | 0.04 | 3.24E-14 | 0.12E-14
ASASSN-19dj | AT2019azh | 58553.454 | UVW2 | 14.67 | 0.04 | 3.49E-14 | 0.13E-14
… | … | … | … | … | … | … | …

Note. — Swift photometry of the transients without the host flux subtracted
and with no correction for Galactic extinction. The $BV$ photometry has been
converted to the Johnson-Cousins system using the color-corrections described
in the text. All magnitudes are presented in the AB system, using published
conversions for systems naturally in the Vega system. The data for each source
are grouped by filter and sorted by increasing MJD. The TDE ASASSN-19dj is
shown here to illustrate the format and the full table is available as an
ancillary file.

After computing the raw Swift photometry, and correcting the $BV$ data to the
Johnson-Cousins system, we corrected each epoch of UVOT photometry for
Galactic extinction (Schlafly & Finkbeiner, 2011) (see Table 2) and removed
the host contamination by subtracting the corresponding host flux in each
filter. To compute the uncertainties, we added the uncertainty in the Swift
photometry and the uncertainty in the host flux in that filter in quadrature.
These results are provided in Table 6. Where the transient flux was less than
a 3$\sigma$ detection, we give a 3$\sigma$ upper limit on the transient
magnitude.

Table 6: Host-Subtracted Swift Photometry

Object | TNS ID | MJD | Filter | Magnitude | Uncertainty | Flux Density | Uncertainty
---|---|---|---|---|---|---|---
|  |  |  |  |  | (erg s-1 cm-2 Å-1) | erg s-1 cm-2 Å-1)
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.762 | V | 15.85 | 0.17 | 1.66E-15 | 0.26E-15
ASASSN-19dj | AT2019azh | 58553.457 | V | 15.67 | 0.17 | 1.95E-15 | 0.31E-15
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.758 | B | 15.27 | 0.12 | 4.46E-15 | 0.48E-15
ASASSN-19dj | AT2019azh | 58553.454 | B | 14.98 | 0.10 | 5.77E-15 | 0.52E-15
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.757 | U | 15.05 | 0.04 | 8.61E-15 | 0.31E-15
ASASSN-19dj | AT2019azh | 58553.453 | U | 14.90 | 0.05 | 9.87E-15 | 0.45E-15
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.755 | UVW1 | 14.79 | 0.04 | 1.98E-14 | 0.08E-14
ASASSN-19dj | AT2019azh | 58553.451 | UVW1 | 14.71 | 0.04 | 2.13E-14 | 0.08E-14
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.763 | UVM2 | 14.58 | 0.04 | 3.17E-14 | 0.12E-14
ASASSN-19dj | AT2019azh | 58553.458 | UVM2 | 14.54 | 0.04 | 3.30E-14 | 0.13E-14
… | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.759 | UVW2 | 14.40 | 0.04 | 4.48E-14 | 0.17E-14
ASASSN-19dj | AT2019azh | 58553.454 | UVW2 | 14.32 | 0.04 | 4.83E-14 | 0.18E-14
… | … | … | … | … | … | … | …

Note. — Swift photometry of the transients with the host flux subtracted
corrected for Galactic extinction. The uncertainties incorporate both the
error on the photometry and from the host SED fits. For epochs where the
transient flux was less than a 3$\sigma$ detection, the magnitude column shows
a 3$\sigma$ upper limit on the transient magnitude. All magnitudes are
presented in the AB system, using published conversions for systems naturally
in the Vega system. The data for each source are grouped by filter and sorted
by increasing MJD. The TDE ASASSN-19dj is shown here to illustrate the format
and the full table is available as an ancillary file.

##  5 Blackbody Fits

The host-subtracted UV/optical SEDs of TDEs (e.g., Holoien et al., 2014,
2016a) and some AGN flares (e.g., Neustadt et al., 2020) are well-fit as
blackbodies. While in AGN the geometry of the emitting region is likely non-
spherical and the emission is at least partly non-thermal, a simple blackbody
fit should provide a reasonable estimate of the size and luminosity of the
optically thick, continuum-emitting region. Therefore, we include blackbody
fits for each of the objects in our sample for completeness. For each epoch of
host-subtracted UV photometry, we used Markov Chain Monte Carlo (MCMC) methods
to fit a blackbody model, as used in Holoien et al. (2014, 2016a). The date
listed for each epoch is the mean MJD of the data used in the fit. Unlike our
$3\sigma$ detection limit for our reported Swift magnitudes, we employ a more
liberal 2$\sigma$ detection threshold for our blackbody fits as the models are
fit in flux space and this allows for marginal detections of the transient at
late times. We do not include blackbody fits for the TDEs ZTF18actaqdw,
ZTF19aabbnzo, and ZTF19aakiwze, as their Swift light curves only have coverage
in a single filter and we cannot constrain the temperature.

Table 7: Blackbody Fits

Object | TNS ID | MJD | log(L) | dlog(Ll) | dlog(Lu) | log(R) | dlog(Rl) | dlog(Ru) | log(T) | dlog(Tl) | dlog(Tu)
---|---|---|---|---|---|---|---|---|---|---|---
|  |  | log([erg s-1]) | log([cm]) | log([K])
… | … | … | … | … | … | … | … | … | … | … | …
ASASSN-19dj | AT2019azh | 58544.76 | 44.45 | 0.07 | 0.08 | 14.64 | 0.04 | 0.04 | 4.58 | 0.03 | 0.04
ASASSN-19dj | AT2019azh | 58553.45 | 44.36 | 0.06 | 0.07 | 14.72 | 0.04 | 0.04 | 4.52 | 0.03 | 0.04
ASASSN-19dj | AT2019azh | 58556.11 | 44.41 | 0.05 | 0.06 | 14.77 | 0.04 | 0.03 | 4.50 | 0.03 | 0.03
ASASSN-19dj | AT2019azh | 58562.95 | 44.28 | 0.04 | 0.04 | 14.83 | 0.03 | 0.03 | 4.44 | 0.02 | 0.02
ASASSN-19dj | AT2019azh | 58565.94 | 44.32 | 0.04 | 0.05 | 14.79 | 0.03 | 0.03 | 4.47 | 0.02 | 0.03
ASASSN-19dj | AT2019azh | 58568.23 | 44.21 | 0.03 | 0.03 | 14.82 | 0.02 | 0.02 | 4.43 | 0.02 | 0.02
ASASSN-19dj | AT2019azh | 58574.79 | 44.24 | 0.04 | 0.04 | 14.80 | 0.03 | 0.03 | 4.44 | 0.02 | 0.02
ASASSN-19dj | AT2019azh | 58577.10 | 44.24 | 0.04 | 0.04 | 14.79 | 0.03 | 0.02 | 4.45 | 0.02 | 0.02
ASASSN-19dj | AT2019azh | 58580.62 | 44.25 | 0.04 | 0.05 | 14.75 | 0.03 | 0.03 | 4.47 | 0.02 | 0.03
… | … | … | … | … | … | … | … | … | … | … | …

Note. — Bolometric luminosity, effective radius, and temperature estimated
from the blackbody fits to the host-subtracted and extinction-corrected Swift
data. The TDE ASASSN-19dj is shown here to illustrate the format and the full
table is available as an ancillary file.

The Swift UVOT calibration correction only affected the UV filters, making
them fainter than previously measured. This caused most objects to become
cooler and therefore $\sim$15% - 30% less luminous than estimated from earlier
reductions of Swift data. The evolution of blackbody parameters for the TDEs
in this sample are shown in Figure 1. Even with corrections to the Swift UV
data, all of the TDEs are hot, with temperatures of $\sim 15,000-50,000$ K.
The temperatures are roughly constant with time, although some objects show
trends in their temperatures, both consistent with previous results (e.g.,
Hinkle et al., 2020; van Velzen et al., 2020). As noted in Hinkle et al.
(2020), the more luminous TDEs appear to decay more slowly than their less
luminous counterparts (see top panel of Figure 1).

Figure 1: Evolution of the UV/optical blackbody luminosity (top panel),
effective radius (middle panel), and temperature (bottom panel) for the TDEs
analyzed in this work. The shading corresponds to the uncertainty. Time is in
observer-frame days relative to the earliest Swift epoch. We have not shown
the very-late time ASASSN-14li blackbody properties, which are included in
Table 7, to allow the evolution of the other TDEs to be seen more clearly.

Figure 2 shows the blackbody fits for the other nuclear outbursts. The
luminosity range of these objects is much larger than for the TDEs because
they span several source classes. The blackbody temperatures are still hot,
consistent with the lower temperature range of TDEs. For many objects, the
evolution in luminosity, radius, and temperature is much slower than for the
TDEs, potentially due to these AGN hosting more massive SMBHs than the TDE
hosts, although there is significant scatter in the various estimates of SMBH
mass for some of these sources (e.g., Frederick et al., 2020). Additionally,
unlike the TDEs, there seems to be no trend between peak luminosity and
decline rate, consistent with the analysis of comparison objects in Hinkle et
al. (2020).

Figure 2: Evolution of the UV/optical blackbody luminosity (top panel),
effective radius (middle panel), and temperature (bottom panel) for the non-
TDE transients or sources interpreted as TDEs in AGN host galaxies. The
shading corresponds to the uncertainty. Time is in observer-frame days
relative to the earliest Swift epoch.

##  6 Peak-luminosity/Decline-rate Relationship

In Figure 1, the most luminous TDEs appear to have flatter slopes near peak,
and decay more slowly than the less luminous TDEs, consistent with the
relationship presented in (Hinkle et al., 2020). Given the importance of UV
photometry to the bolometric UV/optical lightcurves on which this relationship
is based, we re-analyzed this relationship with our updated Swift data.
Similar to Hinkle et al. (2020), we have bolometrically corrected epochs
without Swift UV data using nearby Swift epochs. Because the process of
bolometrically correcting ground-based data involves heterogeneous data, we do
not include the results of these bolometric corrections in Figure 1, rather
only the blackbody fits to the Swift epochs re-analyzed here.

Some of the objects used for the relationship of Hinkle et al. (2020) had
Swift data prior to 2017, at which time the UVOT calibrations were correct and
thus have not been re-analyzed in this paper. For these objects, we use the
pre-2017 photometry from Hinkle et al. (2020). However, for each of the
objects that have been re-analyzed in this work, we followed the procedure of
Hinkle et al. (2020) to place them on the peak-luminosity/decline-rate
relationship plot. In brief, this includes measuring the peak luminosity and
time of peak as well as the decline in log luminosity between the peak and 40
days after peak. Using the updated bolometric light curves, we again find that
40 days minimizes the intrinsic scatter in the relationship. For complete
details on the analysis and uncertainty computations see Hinkle et al. (2020).
We have also updated the classifications of the sources Gaia19bpt, iPTF16fnl,
and ZTF19aapreis. Following the procedure of Kelly (2007), we fit this
relationship with a linear function, and obtain a best fit of

$\begin{split}\log_{10}(L_{peak}/(\text{erg s}^{-1}))=(43.9^{+0.1}_{-0.1})+\\\
(1.5^{+0.3}_{-0.2})(\Delta L_{40}+0.5)\end{split}$ (1)

which is consistent with the result of Hinkle et al. (2020). The estimated
intrinsic scatter in the peak luminosities of $0.20^{+0.18}_{-0.14}$ dex is
significantly decreased from the scatter of $0.29^{+0.23}_{-0.17}$ dex in
Hinkle et al. (2020). To examine the statistical significance of this
correlation, we performed the Kendall tau test and found a moderately strong
correlation of $\tau=0.55$ with a p-value of $2.8\times 10^{-4}$. We therefore
recover the correlation of Hinkle et al. (2020) with decreased scatter and
higher significance. We attribute the reduced scatter to the corrected UV
photometry, uniform host subtraction procedures, and consistent distances.

Figure 3: Peak bolometric UV/optical luminosity as compared to the decline
rate $\Delta L_{40}=$ log${}_{10}(L_{40}/L_{peak})$, where $L_{40}$ is the
luminosity of the TDE at 40 days after peak. The colors are the same as Hinkle
et al. (2020) for ease of direct comparison. Following Hinkle et al. (2020),
the filled squares with a black border are the “A” sample, filled circles with
a black border are the “B” TDEs, open squares are the “C” TDEs, and the gray
open circles are the “D” TDEs. The solid black line is the line of best fit
and the dashed black lines represent plus/minus $1\sigma$ from the best-fit
line. The Class “D” objects were not included in the fit.

##  7 Summary

Following the November 2020 announcement of an updated UVOT calibration to
correct for the loss of sensitivity over time, we re-analyzed the published
photometry for 34 nuclear outbursts and the ambiguous source ATLAS18qqn.
Starting from UVOT images, we re-computed Swift photometry, uniformly modeled
the host galaxy SEDs with FAST, corrected the transient photometry for host
flux and Galactic extinction, and fit the data with blackbody models. We
provide tables of the raw and corrected Swift photometry of the transient, the
observed and modeled host-galaxy photometry, the host-galaxy model parameters,
and the blackbody models of the transients.

With our updated bolometric UV/optical light curves, we verify the
relationship found by Hinkle et al. (2020), that more luminous TDEs decay more
slowly than less luminous TDEs. With our uniform data analysis, the scatter in
the relationship is significantly reduced.

Given the increased detection rate of TDEs and other exotic transients in
recent years, the UV remains a vital wavelength range for studying the
transient universe. In particular, UV photometry is a powerful tool for
probing the regions close to SMBHs as sources evolve. As more and more similar
events are found, Swift will continue to be a key tool in understanding their
high-energy emission.

We thank Christopher Kochanek for helpful discussions. J.H. and this work was
supported by NASA award 80NSSC21K0136. Support for T.W.-S.H. was provided by
NASA through the NASA Hubble Fellowship grant HST-HF2-51458.001-A awarded by
the Space Telescope Science Institute, which is operated by the Association of
Universities for Research in Astronomy, Inc., for NASA, under contract
NAS5-26555. B.J.S is supported by NSF grants AST-1908952, AST-1920392,
AST-1911074, and NASA award 80NSSC19K1717. Parts of this research were
supported by the Australian Research Council Centre of Excellence for All Sky
Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013.
This research has made use of the SVO Filter Profile Service
(http://svo2.cab.inta-csic.es/theory/fps/) supported from the Spanish MINECO
through grant AYA2017-84089.

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