#  SN 2023zaw: the low-energy explosion of an ultra-stripped star, with non-
radioactive heating

T. Moore Astrophysics Research Centre, School of Mathematics and Physics,
Queen’s University Belfast, BT7 1NN, UK  European Southern Observatory, Alonso
de Córdova 3107, Casilla 19, Santiago, Chile  J. H. Gillanders Astrophysics
sub-Department, Department of Physics, University of Oxford, Keble Road,
Oxford, OX1 3RH, UK  M. Nicholl Astrophysics Research Centre, School of
Mathematics and Physics, Queen’s University Belfast, BT7 1NN, UK  M. E. Huber
Institute for Astronomy, University of Hawai’i, 2680 Woodlawn Drive, Honolulu,
HI 96822, USA  S. J. Smartt Astrophysics sub-Department, Department of
Physics, University of Oxford, Keble Road, Oxford, OX1 3RH, UK  Astrophysics
Research Centre, School of Mathematics and Physics, Queen’s University
Belfast, BT7 1NN, UK  S. Srivastav Astrophysics sub-Department, Department of
Physics, University of Oxford, Keble Road, Oxford, OX1 3RH, UK  H. F. Stevance
Astrophysics sub-Department, Department of Physics, University of Oxford,
Keble Road, Oxford, OX1 3RH, UK  Astrophysics Research Centre, School of
Mathematics and Physics, Queen’s University Belfast, BT7 1NN, UK  Department
of Physics, The University of Auckland, Private Bag 92019, Auckland, New
Zealand  T.-W. Chen Graduate Institute of Astronomy, National Central
University, 300 Jhongda Road, 32001 Jhongli, Taiwan  K. C. Chambers  Institute
for Astronomy, University of Hawai’i, 2680 Woodlawn Drive, Honolulu, HI 96822,
USA  J. P. Anderson European Southern Observatory, Alonso de Córdova 3107,
Casilla 19, Santiago, Chile  Millennium Institute of Astrophysics (MAS),
Nuncio Monseñor Sótero Sanz 100, Providencia, Santiago, Chile  M. D. Fulton
Astrophysics Research Centre, School of Mathematics and Physics, Queen’s
University Belfast, BT7 1NN, UK  S. R. Oates Department of Physics, Lancaster
University, Lancaster, LA1 4YB, UK  C. Angus  Astrophysics Research Centre,
School of Mathematics and Physics, Queen’s University Belfast, BT7 1NN, UK  G.
Pignata  Instituto de Alta Investigación, Universidad de Tarapacá, Arica,
Casilla 7D, Chile  N. Erasmus South African Astronomical Observatory, PO Box
9, Observatory 7935, Cape Town, South Africa  H. Gao Institute for Astronomy,
University of Hawai’i, 2680 Woodlawn Drive, Honolulu, HI 96822, USA  J. Herman
Institute for Astronomy, University of Hawai’i, 2680 Woodlawn Drive, Honolulu,
HI 96822, USA  C.-C. Lin  Institute for Astronomy, University of Hawai’i, 2680
Woodlawn Drive, Honolulu, HI 96822, USA  T. Lowe  Institute for Astronomy,
University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822  E. A. Magnier
Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu,
HI 96822  P. Minguez  Institute for Astronomy, University of Hawaii, 2680
Woodlawn Drive, Honolulu, HI 96822  C.-C. Ngeow Graduate Institute of
Astronomy, National Central University, 300 Jhongda Road, 32001 Jhongli,
Taiwan  X. Sheng  Astrophysics Research Centre, School of Mathematics and
Physics, Queen’s University Belfast, BT7 1NN, UK  S. A. Sim Astrophysics
Research Centre, School of Mathematics and Physics, Queen’s University
Belfast, BT7 1NN, UK  K. W. Smith  Astrophysics Research Centre, School of
Mathematics and Physics, Queen’s University Belfast, BT7 1NN, UK  R. Wainscoat
Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu,
HI 96822  S. Yang  Henan Academy of Sciences, Zhengzhou 450046, Henan, China
D. R. Young Astrophysics Research Centre, School of Mathematics and Physics,
Queen’s University Belfast, BT7 1NN, UK  K.-J. Zeng  Graduate Institute of
Astronomy, National Central University, 300 Jhongda Road, 32001 Jhongli,
Taiwan

###### Abstract

Most stripped envelope supernova progenitors are formed through binary
interaction, losing hydrogen and/or helium from their outer layers. An
emerging class of supernovae with the highest degree of envelope-stripping are
thought to be the product of stripping by a NS companion. However, relatively
few examples are known and the outcomes of such systems can be diverse and are
poorly understood at present. Here, we present spectroscopic observations and
high cadence multi-band photometry of SN 2023zaw, a low ejecta mass and
rapidly evolving supernova. SN 2023zaw was discovered in a nearby spiral
galaxy at D = 39.7 Mpc, with significant Milky Way extinction, $E(B-V)=0.21$,
and significant (but uncertain) host extinction. Bayesian evidence comparison
reveals that nickel is not the only power source and an additional energy
source is required to explain our observations. Our models suggest an ejecta
mass of $M_{\rm ej}\sim 0.07$ M⊙and a synthesised nickel mass of $M_{\rm
ej}\sim 0.007$ M⊙is required to explain the explosion. However an additional
heating from a magnetar or interaction with circumstellar material is required
to power the early light curve.

Transient sources (1851) — Supernovae (1668) — Core-collapse supernovae (304)
– Type Ib supernovae (1729) – Circumstellar matter (241)

††facilities: Gemini:Gillett, Swift, PS1, PO:1.2m, Liverpool:2m††software:
Astropy (Astropy Collaboration et al., 2013, 2018, 2022), Numpy (Harris et
al., 2020), Matplotlib (Hunter, 2007), Mosfit (Guillochon et al., 2018), Hoki
(Stevance et al., 2020), PSF (Nicholl et al., 2023), DRAGONS (Labrie et al.,
2023, 2023)

##  1 Introduction

Modern sky surveys such as the Asteroid Terrestrial-impact Last Alert System
(ATLAS; Tonry et al. 2018), Zwicky Transient Facility (ZTF; Bellm et al.
2019), and the Panoramic Survey Telescope and Rapid Response System (Pan-
STARRS; Chambers et al. 2016) are revealing the extremes of core-collapse
supernovae (SNe) and optical transients (Inserra, 2019; Modjaz et al., 2019).
A small number of SNe, often belonging to the hydrogen poor Types Ib and Ic,
show rapid evolution and brighten and fade on timescales much faster than
typical classes of SNe (Poznanski et al., 2010; Drout et al., 2013; De et al.,
2018; Prentice et al., 2018, 2020; Chen et al., 2020; Yan et al., 2023; Ho et
al., 2023).Generally, a small ejecta mass is invoked to explain the rapid
evolution of fast transients (Moriya et al., 2017). A small ejecta mass
reduces the photon diffusion timescale allowing the light curve to peak and
begin to decline rapidly. Low ejecta mass interpretations require a physically
compatible powering source. Invoking radioactive 56Ni in fast evolving SNe
frequently produces unphysical ejecta mass to nickel mass ratios (Prentice et
al., 2018; Gillanders et al., 2020; Prentice et al., 2020; Chen et al., 2020).
Additional mechanisms have been suggested to boost the luminosity of these
supernovae e.g circumstellar material interaction, energy injection from a
magnetar, and shock cooling emission (Yao et al., 2020; Sawada et al., 2022)

In this paper, we present spectrophotometric follow-up observations of the
rapidly evolving SN 2023zaw.111While preparing this manuscript, another pre-
print on the same source appeared on the arXiv (Das et al., 2024). We
determine a time of maximum light of MJD $60287.1\pm 0.2$ from fitting a
polynomial to the ZTF $g$-band. Classified as a Type Ib, SN 2023zaw rises
rapidly to maximum light ($<$ 4 days) followed by a similarly fast decline,
comparable to the fastest fading Type I SN 2019bkc (Chen et al., 2020;
Prentice et al., 2020).

##  2 Discovery and Follow-up

SN 2023zaw was discovered on 2023 December 7 05:34 UT (MJD 60285.23) by ZTF
(Bellm et al., 2019) and registered on the Transient Name Server at 11:50 UT
(Sollerman, 2023) with the discovery mag $g=19.34$. We independently detected
SN 2023zaw in ATLAS data (Smith et al., 2020) a few hours later at 08:00 UT as
the field visibility moved from California to Hawaii, at mag $o=18.74$. The
transient is offset 8.97” N, 19.15” W from UGC 03048, a spiral galaxy with a
redshift from the NASA Extragalactic Database (NED) of 0.010150 $\pm$ 0.000026
(Springob et al., 2005). From NED the median redshift-independent distance to
UGC 03048 is 39.7 Mpc, based on the Tully-Fisher method (Tully et al., 2013).
The SN is offset 8.97” North and 19.15” West, or 4.1 kpc, from the galaxy
center. SN 2023zaw is located on the edge of one of the two prominent arms of
UGC 03048. The Milky Way extinction along this line of sight is AV = 0.6555
mag (Schlafly & Finkbeiner, 2011). Na I D lines in the classification spectrum
suggest additional host extinction is significant (Poznanski et al., 2012).

Four AstroNotes regarding SN 2023zaw were released on the Transient Name
Server222https://www.wis-tns.org/object/2023zaw at the time of discovery,
commenting on its early evolution. Karambelkar et al. (2023a) highlighted the
discovery and fast fading nature of SN 2023zaw, along with an observation of
the transient with NOT/ALFOSC. The Kinder project (Lee et al., 2023) reported
a color-dependent fade using observations performed on the 40-cm SLT at Lulin
Observatory, Taiwan. In Fulton et al. (2023), we reported the combined ATLAS
and ZTF data and highlighted that this source was flagged by our ‘Fastfinder’
filter and annotator on the Lasair broker333https://lasair-ztf.lsst.ac.uk
(Smith et al., 2019) to find fast evolving objects in the ZTF public alert
stream. Both Karambelkar et al. (2023a) and Fulton et al. (2023) identified SN
2023zaw as a fast-fading, sub-luminous and red transient. Spectroscopic
observations with Keck (Karambelkar et al., 2023b) reported an apparent
similarity with the candidate ‘.Ia’ SN 2010X (Kasliwal et al., 2010). Finally,
Gillanders et al. (2023) classified the object as a Type Ib SN based on
observations performed with Gemini-N/GMOS, and this spectrum was immediately
made public on the TNS.

###  2.1 Photometry

Photometry for SN 2023zaw (internal name ATLAS23wuw) were obtained from the
ATLAS forced photometry server (Shingles et al., 2021) and binned by day. The
ATLAS (Tonry et al., 2018) system is a all-sky survey for potentially
dangerous near-Earth objects. ATLAS data are processed using the ATLAS Science
Server (Smith et al., 2020) to search for stationary transients. We obtained
measurements in the $g$ and $r$-bands using the Lasair broker (Smith et al.,
2019) and public ZTF stream data444https://lasair-
ztf.lsst.ac.uk/objects/ZTF23absbqun.

We triggered follow-up observations with the 1.8m Pan-STARRS1 on the Haleakala
mountain, Hawaii (Chambers et al., 2016). The Pan-STARRS1 telescope has a 7
deg2 field of view and features a 1.4 gigapixel camera. Observations in the
$grizy_{\rm P1}$ were taken with a daily cadence between MJD 60291 and 60295.
An additional $riz_{\rm P1}$ epoch was taken on MJD 60302, all further Pan-
STARRS observations were performed using the $iz_{\rm P1}$ bands. Optical
imaging was triggered with the 2.0-m Liverpool Telescope (LT; Steele et al.,
2004) using IO:O in $riz$ bands under program PL23B26 (PI: M. Fulton).
Measurements were made by PSF fitting using Source-Extractor (Bertin &
Arnouts, 1996) without host-galaxy subtraction. We observed SN 2023zaw with
the 0.4m SLT telescope as a part of the Kinder project (Chen et al., 2021) and
measured psf $griz$-band photometry. Three epochs of photometric observations
were performed with the GMOS-N instrument at the Gemini-North 8.1-m telescope,
under program ID GN-2023B-Q-125 (PI: M. Huber). These were obtained at MJDs
60329.2 ($riz$-band), 60339.3 ($riz$-band) and 60341.2 ($ri$-band). These
observations were bias-subtracted and flat-field corrected using standard
recipes in DRAGONS (Labrie et al., 2023, 2023). We also present three epochs
of $r$-band photometry derived from the acquisition images obtained prior to
our spectroscopic observations with GMOS-N (see Section 2.2 for details).
Aperture photometry was performed using PSF (Nicholl et al., 2023) with a
small optimised aperture, an encircled energy correction, and local background
subtraction.

The Ultra-Violet and Optical Telescope (UVOT; Roming et al., 2005) onboard the
Neil Gehrels Swift Observatory (Swift; Gehrels et al., 2004) satellite
observed SN 2023zaw on MJD 60293 and MJD 60296. A single $uvm2$ exposure was
performed on MJD 60291. While observations were taken in the $u$, $b$, $v$,
$uvw1$, $uvm2$ and $uvw2$ bands on days MJD 60293 and MJD 60296. The images at
each epoch were co-added, and the count rates obtained from the stacked images
using the Swift tool uvotsource. To extract the source counts, we used a
source aperture of $5\arcsec$ radius and an aperture of $20\arcsec$ radius for
the background. The source count rates were converted to magnitudes using the
UVOT photometric zero points (Poole et al., 2008; Breeveld et al., 2011). All
Swift observations are non-detections of the transient.

The Milky Way extinction-corrected light curve of SN 2023zaw is presented in
Figure 1. All photometry will be provided in the online version of this paper
and as a machine readable table.

Figure 1:  Multicolor light curves with corrections for Milky Way foreground
extinction and time dilation for (z = 0.010150) applied. Each telescope is
shown with a different marker and unfilled markers indicate upper limits. We
exclude Swift/UVOT non-detections for visual clarity. Additionally we show the
expected decline rate of a 56Co tail (0.98 mag / 100 day) (Woosley et al.,
1989).

###  2.2 Spectroscopy

We observed SN 2023zaw at three different phases with the Gemini-North/GMOS-N
instrument under program ID GN-2023B-Q-125 (PI: M. Huber). Our three
observations commenced on MJDs 60291.3, 60295.3 and 60313.4 (corresponding to
phases from maximum light of $\approx+4.2$, +8.2 and +26.0 days,
respectively). All observations were performed using the R400 grating,
sampling the $\approx 4200-9100$ Å wavelength range at a spectral resolution
of R $\sim 2000$.

We reduced all three epochs of Gemini observations using the DRAGONS pipeline
(Labrie et al., 2023, 2023) following standard recipes, and the spectra were
all flux-calibrated against the same standard star. The contribution of the
host galaxy was estimated and subtracted, and each reduced, co-added spectrum
agrees well with the background-subtracted Pan-STARRS photometry obtained at
the same epoch. All spectra in this work will be made publicly available on
the WISeREP repository (Yaron & Gal-Yam, 2012).

##  3 Analysis

###  3.1 Host Galaxy and Milky Way Foreground Extinction

There is a strong and narrow absorption line in the +4.2 and +8.2 day GMOS-N
spectra, consistent with Na i D absorption at the redshift of UGC 03048. The
GMOS-N spectral resolution does not allow the D1 and D2 components to be
separately measured. After normalising the spectrum, we fit a single Gaussian
to the blended absorption line, with a centre $\lambda_{c}=5953.94$ Å
($z=0.0104$), a FWHM width $=11.4$ Å, and an equivalent width, ${\rm
EW}=2.10\pm 0.22$ Å.

Measurements of the equivalent width of the Na i doublet have been shown to be
correlated with the line-of-sight extinction (Poznanski et al., 2012), and
this method has often been applied to extragalactic transients. While there is
a reasonably linear relation between line strength and $E(B-V)$, up to a total
${\rm EW}_{\rm(D_{1}+D_{2})}\simeq 0.7$ Å, the relationship then saturates. No
quantitative and unique measurement of $E(B-V)$ appears possible beyond this,
but we can say that an ${\rm EW}=2.10\pm 0.22$ Å requires a minimum of
$E(B-V)_{\rm host}\gtrsim 0.5$. The Milky Way foreground extinction is also
significant along this line of sight, with $E(B-V)_{\rm MW}=0.2$ (Schlafly &
Finkbeiner, 2011). Throughout the rest of this manuscript, we apply a total
extinction of $E(B-V)=0.7$, noting that a somewhat higher value cannot be
discounted.

###  3.2 Light Curves

The light curves of SN 2023zaw are shown in Figure 1. Shortly after discovery,
SN 2023zaw reaches a maximum brightness of r = 17.6 mag and g = 18 mag. The
rapid rising phase of the light curve is not well observed, but the time from
explosion to $g$-band peak is constrained to be less than four days by the
ATLAS $o$-band non-detections (at depths correspond to Mo of -14.5 and -14.8
mag) at 2.7 and 1.8 days pre-discovery, respectively. The photometric
evolution after maximum light is similarly rapid. Due to the short rise time
we only observe the rising portion of the light curve in the $go$-bands. SN
2023zaw evolves extremely fast when compared to the representative Type Ib SN
2007Y (Stritzinger et al., 2009) in Figure 2. Initially SN 2023zaw fades $\sim
3$ magnitudes in $\sim 10\,$days in the $r$-band, with SN 2007Y fading by less
than a magnitude during the same interval. After this early rapid fade, SN
2023zaw is comparable to SN 2019bkc which is the fastest known Type I SN. SN
2023zaw settles to an apparent radioactive tail which we observe in the
$riz$-bands.

Figure 2: Light curves of SN 2023zaw in the $griz$-bands compared to the fast
supernovae SN 2019bkc (Prentice et al., 2020; Chen et al., 2020), SN 2019dge
(Yao et al., 2020), and the representative Type SN Ib SNe 2007Y (Stritzinger
et al., 2009) and SN 2007C (Drout et al., 2011; Stritzinger et al., 2018).
Each light curve is in the rest frame and has been corrected for Milky Way and
host galaxy extinctions (Drout et al., 2011). These supernovae were chosen to
represent the population USSNe and typical Type Ib SNe.  Figure 3: Fit results
to the complete light curves using MOSFiT (Guillochon et al., 2018) for our
physical models compared to photometry, where downward arrows are upper-
limits, realisations are repented as solid lines and, band colors match those
in Figure 1. Panel (a) shows nickel-only model realisations. Panels (c), (d),
and (e) show the nickel + exp model, magnetar + nickel model, and
circumstellar material interaction + Nickel models respectively. Panel (b)
shows a fit to only the late-time light curve to estimate a synthesized
nickel-mass, and Panel (f) shows our shock-cooling emission + nickel, the
shock cooling model follows (Piro et al., 2021). The Bayesian evidence for
each model is calculated for model comparison. When quoting the evidence for
each model the name of each model in the MOSFiT code is used to ensure the
reproducability of these results. Model evidence is not included in panel (b)
as the model is only evaluated against the light curve tail. The MOSFiT input
file will be made available as a data behind the figure file with the online
article and all models are or will be made publicly available

###  3.3 Light Curve Modeling

We use the Modular Open Source Fitter for Transients
MOSFiT555https://github.com/guillochon/MOSFiT which is a Python-based modular
code which evaluates a user-defined physical model to the observed light
curves of transients. The code is described in detail by Guillochon et al.
(2018). We use the dynesty (Speagle, 2020) nested sampling package option in
MOSFiT to evaluate for a series of different models. For all models we assume
an optical opacity ($\kappa$) of 0.1 cm2 g-1 and a gamma-ray opacity
($\kappa_{\gamma}$) of 0.027 cm2 g-1. We apply a constraint to the host galaxy
H column density of n${}_{\rm H,host}(\rm cm^{-2})>3.43\times 10^{21}$ for
consistency with our adopted minimum host extinction (Section 3.1), assuming
RV = 3.1 and n${}_{\rm H}(\rm cm^{-2})/\rm A_{V}=2.21\times 10^{21}$ (Güver &
Özel, 2009). All models that are considered in this work are shown in Figure 3
together with the observed light curves of SN 2023zaw .

The rising phase of SN 2023zaw is poorly sampled compared to the peak and tail
of the light curve, which makes achieving a good fit at early time difficult.
Following Wheeler et al. (2015), we use the observed rise time $t_{\rm r}$ and
photospheric velocity $v_{\rm ph}$ to estimate an ejecta mass $M_{\rm ej}$
using the equation $M_{\rm ej}\ \approx 1/2\cdot\beta\cdot c/\kappa\cdot
v_{\rm ph}t_{\rm r}^{2}$ (Arnett, 1982), where $\beta=13.8$ is constant, $c$
is the speed of light, $t_{\rm r}$ is the rise time, and $\kappa$ is the
opacity. To approximate the rise time we adopt the midpoint between the last
non-detection and the first detection as the explosion epoch (MJD 60284.3, 0.9
days before detection) and the $g$-band peak for the time of maximum, this
gives a rise time ($t_{\rm r}$) estimate of $\sim 2.75$ days. For the
photospheric velocity $v_{\rm ph}$ we use the velocity derived from spectral
modelling in Section 4. Following this analysis we estimate an ejected mass
$M_{\rm ej}\sim 0.07$ M⊙. Considering a $\pm$1 day uncertainty on the rise
time our mass estimate could vary by +0.06 or -0.04 M⊙. To capture the
constraint in our priors we adopt a Gaussian prior on the ejecta mass $M_{\rm
ej}$ described by sigma = 0.07 and mu = 0.06 on the ejected mass $M_{\rm ej}$
parameter.

####  3.3.1 Nickel Powered Explosion

We attempt to fit the multiband light curves with 56Ni decay, using the built-
in default MOSFiT model (Nadyozhin, 1994; Guillochon et al., 2018). Despite a
reasonable agreement with $i$-band observations, overall this model does not
provide a satisfactory fit to the light curves of SN 2023zaw . During the SN
rise the model conflicts with the deep ATLAS $o$-band limits, and fails to
reproduce the maximum luminosity in the $gcr$-bands. The model clearly
diverges from the late-time $rz$-band tail and only adequately matches the
decline between MJD 60300 and MJD 60320. We find the most probable model
ejects M${}_{\rm ej}=0.06^{+0.01}_{-0.01}$ M⊙ of material with a large 56Ni
fraction $f_{\rm Ni}=0.90^{+0.06}_{-0.11}$ and a reasonable SN-like ejecta
velocity $v_{\rm ej}=6400^{+300}_{-300}$ $\rm{km}\,s^{-1}$ . This implies
M${}_{\rm Ni}\sim$ 0.05 M⊙ was synthesised in the explosion, this is
significantly less than a typical Type Ib SN (Anderson, 2019; Rodríguez et
al., 2023), and is comparable to the total ejected mass. This presents a major
problem for this model, contradicting our observed spectra. An ejecta of
mostly 56Ni and its decay products should be dominated by iron-group
absorption in the blue this is not observed in the spectra of SN 2023zaw.
Additionally, a nickel yield of MNi= 0.05 M⊙ was difficult to rationalise in
the context of the ultra-stripped SN iPTF 14gqr (Sawada et al., 2022).
Clearly, a 56Ni-only model does not reproduce our observations, requires an
unrealistic nickel-fraction, and can only adequately explain the light curve
tail. Therefore, we exclude the scenario where nickel-decay is the only
mechanism powering SN 2023zaw and seek an explanation with another mechanism
in addition to nickel decay.

The light curve tail begins approximately ten days after maximum. The decline-
rate slows and follows a power-law decline, an evolution which is similar to
the $i$-band tail of the fast-fading SN 2019bkc (Chen et al., 2020; Prentice
et al., 2020) where this was attributed to radioactivity.

Assuming the heating at late times is powered by decay of 56Co to 56Fe, we can
estimate a synthesised nickel mass for SN 2023zaw. We apply the same model as
before but with a restriction to fit only the late time $riz$-band data (MJD
$>$ 60300). The sampler only evaluates against the late-time photometry, but
we provide a prior constraining the explosion epoch between the last ATLAS
non-detection (MJD 60282.51) and the first detection (MJD = 60285.23). The
tail requires that $M_{\rm Ni}\ \sim 0.006$ M⊙ was synthesised and ejected to
power this phase of the light curve. Seeking to verify our method, we
reanalyse the tail of SN 2019bkc and find a nickel mass M${}_{\rm Ni}\ \sim
0.005$ M⊙, which is compatible with M${}_{\rm Ni}\ =0.001-0.01$ M⊙ estimated
by Chen et al. (2020).

Motivated by the poor agreement of the nickel decay model to the initial peak
but apparent agreement to the light curve tail, we consider a generalised
early-time heating source plus a nickel decay tail. Using MOSFiT we adopt a
physics-agnostic analytical prescription for an exponentially rising
additional energy source that declines from its maximum ($t_{peak}$) following
a power-law (named exppow). It is described by $L=L_{\rm
scale}\cdot(1-e^{-t/t_{peak}})^{\alpha}\cdot(t/t_{peak})^{-\beta}$, where
$L_{\rm scale}$, $\alpha$, $\beta$, and $t_{peak}$ are free parameters.
Combining the default and exppow models we created a new MOSFiT model called
exppowni.

We fit the exppowni model as before using the same constraints on opacity and
host galaxy extinction. The model realisations are shown in Figure 3. We see
good agreement with observations and consistency with the ATLAS non-
detections, the observed color, and late-time luminosities. We estimate a
nickel mass of $M_{\rm Ni}\sim 0.006$ M⊙, which is in agreement with the fit
for only the light curve tail. It is clear that an additional luminosity
source is required to simultaneously match the fast rise, the peak luminosity
and the observed 56Co tail. The parameterised nature of the exppowni model
provides insight into the timescale of the additional luminosity source, which
reaches $t_{peak}$ between $1.6-2.6$ days after explosion and dominates the
luminosity during this phase with a scale luminosity $L_{\rm scale}$ $\sim
10^{42}$ ergs s-1.

####  3.3.2 Circumstellar Material Interaction + Nickel

We evaluate interaction with nearby circumstellar material (CSM) as a possible
extra energy source for SN 2023zaw. CSM interaction can produce unusual and
rapidly evolving transients (e.g. Moore et al., 2023; Kuncarayakti et al.,
2023; Nagao et al., 2023; Perley et al., 2022). We use the CSMNI model in
MOSFiT (Villar et al., 2017; Jiang et al., 2020; Moore et al., 2023) which
combines the luminosity of 56Ni decay and heating from shock propagation
following an ejecta-CSM collision. The CSM interaction physics is implemented
following the treatment of Chatzopoulos et al. (2013). We use the adapted
model setup used by Moore et al. (2023) and Srivastav et al. (2023) where the
onset of interaction is delayed until the ejected material reaches an inner
CSM radius.

We evaluate the csmni model against our observations and show the CSM model
realisations in Figure 3. This model fits the light curve peak very well and
matches the overall light curve evolution in all bands, including close
agreement to the late-time tail. The derived model parameters are: $M_{\rm
ej}=0.069^{+0.005}_{-0.004}$ M⊙, $f_{\rm Ni}=0.12^{+0.02}_{-0.02}$, $r_{\rm
csm}=63^{+13}_{-12}$ AU, $M_{\rm csm}=0.23^{+0.06}_{-0.05}$ M⊙, where, $M_{\rm
csm}$ is the mass of the CSM material and $r_{\rm csm}$ is the CSM radius.
This model implies $M_{\rm Ni}\sim 0.008$ M⊙, which is compatible with our
estimate from just the lightcurve tail. The posterior of the CSM density
profile reveals the model is insensitive to a wind or disc-like CSM structure
parameter $s$ and the CSM mass and radius show strong degeneracy. The derived
kinetic energy for this model is low at $E_{k}\sim$ 1049 erg. We note the +61
day spectrum of SN 2023zaw (Das et al., 2024) shows narrow helium lines,
likely from interaction. These results suggest late-stage mass loss before
explosion consistent with Wu & Fuller (2022).

####  3.3.3 Magnetar + Nickel

We investigate the feasibility of magnetar heating as the additional energy
source using the Magnetar + Nickel (‘magni’) model described by Nicholl et al.
(2017); Gomez et al. (2022), which combines the luminosity of magnetar spin-
down (Kasen & Bildsten, 2010; Woosley, 2010) and radioactive heating. This
model is significantly better than radioactive heating alone, and matches the
peak but diverges from the $riz$-band tail. Our derived Magnetar + Ni model
has the following parameters, ejecta mass $M_{\rm ej}=0.055^{+0.006}_{-0.005}$
M⊙, nickel fraction $f_{\rm Ni}=0.08^{+0.06}_{-0.09}$, and $M_{\rm Ni}\sim
0.004$ M⊙. We find magnetar parameters of $P_{\rm spin}=6.3^{+1.6}_{-1.1}$ ms
and $B_{\perp}=0.19^{+0.17}_{-0.20}\times 10^{14}$ G. The B-field required
from our models is consistent with the population of superluminous supernovae.
However the spin period, $P_{\rm spin}$ is towards the longer end of the range
of 1-6 ms (e.g. Kashiyama et al., 2016; Nicholl et al., 2017). Given the low
ejecta mass the region of the ejected material which is being heated by the
central engine should be visible. Therefore, we would expect the W-shaped O II
absorption lines to be present in the spectrum which are the characteristic
signature of central engines in Type I superluminous supernovae (Mazzali et
al., 2016; Quimby et al., 2018), unfortunately this region of the SN 2023zaw
spectrum was not observed.

####  3.3.4 Shock Cooling + Nickel

Finally, we consider the contribution of 56Ni and shock cooling emission of a
shocked stellar envelope following the analytical Piro et al. (2021) model. In
this scenario the progenitor star possesses an extended envelope which is
shocked by the expanding SN and produces observable shock cooling emission. We
have added this model to MOSFiT as the pironi model. We show our model
realisations in Figure. 3. Our models require $f_{\rm
Ni}=0.01^{+0.03}_{-0.01}$, $M_{\rm ej}=0.04^{+0.03}_{-0.02}$ M⊙, $M_{\rm
Ni}\sim 0.0004$ M⊙, $M_{\rm env}\sim 0.3$ M⊙, and $R_{\rm
star}=10^{10.5^{+0.5}_{-0.4}}\,\rm cm$. The shock cooling model shows
relatively poor agreement with the overall light curve of SN 2023zaw. The
model is too luminous and contradicts the ATLAS non-detections and does not
well reproduce the observed tail.

We note that this model has excellent agreement to observations when we adopt
the host extinction ($\rm A_{v,host}=1.12$ mag) estimate made by Das et al.
(2024) but not for our adopted value (see Section 3.1). Evaluating the pironi
model with a lower value of host extinction, $\rm A_{v,host}=1.12$ mag, we
find $f_{\rm Ni}\sim 0.009$, an envelope mass $M_{\rm env}\sim 0.31$ M⊙, an
ejected mass $M_{\rm ej}\sim 0.03$ M⊙ and a stellar radius $R_{\rm star}\sim
10^{10.3}\,\rm cm$.

For both treatments of host extinction we find envelope masses close to or
smaller than 0.2 M⊙ which is compatible with the envelope masses of an ultra-
stripped progenitor (Tauris et al., 2015).

####  3.3.5 Model Comparison

To compare the models we use the Bayesian model evidence (marginal likelihood)
scores for each model which are returned by MOSFiT when using the nested
sampler Dynesty (Speagle, 2020). From the Bayesian evidence scores a Bayes
factor (BF) can be used to compare two models. The BF comparing model $x$ and
model $y$ is given by B $\equiv$ Zx/Zy, where Zi is the Bayesian evidence for
model i. A Bayes factor B $>$ 10 indicates a strong preference, and B $>$ 100
is considered definitive.

We find a BF Zexpowni/Z${}_{\rm nickel}\ \sim 10^{21}$, where Zexppowni,
Znickel are the evidence for their respective models, this shows evidence
favouring an additional powering source. This statistical test and the poor
agreement of 56Ni only modelling with the light curves provides evidence that
SN 2023zaw requires an additional power source. Comparing our Ni model and
shock cooling model we find Zpironi/Z${}_{\rm nickel}\ \sim 10^{1}$, the shock
cooling + Ni model is preferred over Ni alone. Comparing between models in
this way our analysis favours CSM + Ni model above all others. When comparing
the alternative models we calculate Zcsmni/Zmagni $\sim 10^{10}$, favouring
CSM interaction over the spin-down of a newly born neutron star. However, we
note that the MOSFiT CSMNI model is the most complex evaluated in this work
and the most flexible while likely oversimplifying the physics involved. While
the CSM + Ni model reproduces the light curve tail luminosity better than any
other model, the blackbody spectrum assumed in MOSFiT may be unreliable at
this phase as the ejected material becomes transparent.

Through MOSFiT modelling we have shown that the total emission of SN 2023zaw
cannot be explained with radioactivity alone. We have found evidence that
suggests another energy source is required which peaks early in the evolution
of SN 2023zaw and dominates the emission at this phase. We disfavour shock
cooling emission as this additional source due to poor agreement to the multi-
color photometry, in particular our ATLAS non-detections. A BF analysis
favours CSM + nickel with a CSM mass which is extreme but not beyond
theoretical predictions (Wu & Fuller, 2022). However, a magnetar + nickel
explanation for SN 2023zaw should not be ruled out. We consider both models as
viable explanations for SN 2023zaw.

###  3.4 Spectral Modelling and Analysis

We present post-peak spectra taken +4, +8 and +26 days after maximum light.
All spectra used in this work are shown in Figure 4. Our first spectrum taken
+4.2 days after maximum light shows well developed absorption features and a
prominent Ca II NIR triplet. Weak Fe II features may exist around 4500–5000 Å,
we find that a 5700 K blackbody produces a continuum in agreement with the
observed spectrum. As noted in Section 3.1 the spectra show a prominent Na I D
line blend.

The spectra show little evolution between the +4 day and +8 day observations
considering the rapidly evolving light curve. At +8 days the spectroscopic
features have more developed line profiles and a broad emission feature at
7100 Å is apparent. Our final observation 26 days after maximum light contains
little information about SN 2023zaw and we exclude it from further
quantitative analysis.

SN 2023zaw was compared to a ’.Ia’ SN candidate SN 2010X (Karambelkar et al.,
2023b), suggesting a .Ia origin for this SN. .Ia SNe are the theorised
explosion of a helium shell on the surface of a white dwarf (Shen & Bildsten,
2009; Shen et al., 2010). In Figure 5 we present a spectroscopic comparison to
He shell detonation models (Sim et al., 2012). Although the model provides
some agreement to the SED of the observed spectrum at +4.2 days, it predicts
emission where in the observed spectrum we see a deep He I absorption feature
at $\sim$5700 Å. At +8.2 days from explosion the differences between the model
and our observations become clear, the He detonation models show strong
emission peaks for lines not present in data. With such clear divergence from
the He detonation model we rule out a .Ia origin for SN 2023zaw , in agreement
with Das et al. (2024).

Figure 4:  Optical spectroscopy of SN 2023zaw. The phase in days relative to
maximum light are indicated. These spectra have been telluric and Galactic
line of sight extinction corrected, and corrected for host galaxy recessional
velocity. The inset plot shows the blended Na I D lines in the + 4.2 and + 8.2
day spectra. We also include spectra from SN 2019wxt (Agudo et al., 2023a), SN
2007C (Modjaz et al., 2014), SN 2019bkc (Chen et al., 2020; Prentice et al.,
2020).

Given the striking similarity to both the SEDs and spectral features of the SN
2019wxt spectra, here we undertake a similar process to that presented by
Agudo et al. (2023b) of using tardis to model the photospheric-phase spectra.
tardis (Kerzendorf & Sim, 2014) is a one-dimensional, time-independent, Monte
Carlo radiative transfer spectral synthesis code capable of simulating the
spectra of an array of different explosive transients. The code assumes an
inner region of completely opaque inner ejecta, beneath which all energy
injection into the system is assumed to be thermalised. This inner boundary is
surrounded by a number of optically thin shells that represent the line-
forming region of the ejecta (these shells encompass the computational domain
of the simulation). A (user-defined) number of photon quanta (dubbed
$r$-packets) are created at the inner boundary, and are assigned properties
randomly sampled from a single-temperature blackbody. The trajectory of these
$r$-packets are simulated as they traverse the computational domain, with any
interaction (either free $e^{-}$ scattering, or bound–bound transitions)
simulated. The $r$-packets that escape the outer boundary of the simulation
are used to generate a synthetic spectrum, which can be compared (usually via
$\chi$-by-eye; see e.g., Stehle et al., 2005) to the observed spectrum, and
iterated upon to improve agreement.

While tardis is a time-independent code, it is possible to evolve the input
parameters to obtain a sequence of self-consistent models, as we do here for
the +4.2 and +8.2 day spectra of SN 2023zaw. These user-defined input
parameters include specifying the time since explosion, $t_{\rm exp}$ (which
we set to be 2 days pre-maximum), the inner and outer boundary of the
computational domain (defined in velocity-space, where $v_{\rm
inner}^{+4.2\,{\rm d}}=12500$ km s-1, $v_{\rm inner}^{+8.2\,{\rm d}}=5000$ km
s-1, and $v_{\rm outer}=20000$ km s-1), the abundance and density of the
ejecta material – here we utilise a uniform abundance across the entire ejecta
and across both epochs (see Table 1), and we invoke an exponential profile,
where:

$\begin{split}\rho\left(v,t_{\rm exp}\right)=2\times
10^{-12}&\times\exp\left[\frac{-v}{6000\ {\rm km\,s}^{-1}}\right]\\\
&\times\left(\frac{2\ {\rm day}}{t_{\rm exp}}\right)^{3}{\rm
g\,cm}^{-3}.\end{split}$ (1)

We utilise the dilute-lte, nebular and scatter approximations for excitation,
ionisation and line treatment, respectively, as well as including the recomb-
nlte He treatment (as presented by Boyle et al., 2017), to better capture NLTE
excitation effects for He I.

Table 1:  tardis model compositions.  Element | Mass fraction
---|---
He | 0.50
O | 0.30
Si | 0.20
Ca | $5\times 10^{-6}$
Figure 5:  Best-fitting tardis models (red), compared to the +4.2 and +8.2 d
observed spectra of SN 2023zaw (black). The +4.2 d observed spectrum (and
associated model spectra) have been vertically offset for clarity (by $6\times
10^{-17}{\rm erg}\,{\rm s}^{-1}\,{\rm cm}^{-2}\,{\rm\AA}^{-1}$). Also plotted
are two model spectra from a helium shell detonation simulation (blue)
presented by Sim et al. (2012). These models have phases comparable to those
of the observed spectra ($\Delta t<0.13$ d), and have been re-scaled and
arbitrarily offset to roughly match the continua of the observed spectra.

We present our model fits in Figure 5. The observations possess a number of
prominent absorption features, located at $\sim 5700$, 6100, 6400, 6800, 7400
and 8200 Å. We find that we can reproduce the +4.2 d spectrum with a
relatively simple composition, made up of He, O, Si and Ca, where the 6100 Å
feature is produced by Si II, the 7400 Å feature by O I, the 8200 Å feature by
Ca II, and all others (i.e., 5700, 6400 and 6800 Å) by He I. We over-produce
the 5700 Å He absorption feature, and do not perfectly match the continuum
blueward of $\lesssim 5400$ Å, but overall the fit to the data is good.

We note here that the NLTE He treatment within tardis is a simple,
empirically-derived approximation designed to account for the effects of
recombination from He II $\xrightarrow{}$ He I. As such, it is possible that
the estimated level populations within our tardis simulation have deviated
from the true level populations. This possible issue has been noted before,
and was proposed as the reason behind the disagreement between the relative
strengths of He features in the case of SN 2019wxt (Agudo et al., 2023b).
There, they manually altered the relative level populations of He I to better
match the observed relative strengths of the He I features. Here we opt to not
explore such variations, as our focus is on constraining the elements that
dominate the composition in the line-forming region of the ejecta material of
SN 2023zaw.

Attempts to fit the observations in a more detailed manner than presented here
should be approached with extreme caution, given we have no reliable
constraint on the true level of extinction. As a result, the true continuum of
these observed spectra could be much bluer than what we present here (see
Section 3.1 for details on our extinction estimates), which would
significantly alter the agreement of our models to the data.

Although our model composition is quite rudimentary, it aligns with our SN Ib
classification, and not .Ia. Going beyond classification arguments, we are
able to constrain the composition to be $\sim 80$% He and O, and $\sim 20$% Si
(in the line-forming region). Our inner velocity estimates derived from this
modelling ($v_{\rm inner}^{+4.2\,{\rm d}}=12500$ km s-1 and $v_{\rm
inner}^{+8.2\,{\rm d}}=5000$ km s-1) indicates the photosphere is receding
quickly into the ejecta material, consistent with a small mass of ejected
material.

###  3.5 Volumetric Rates

Here we present a preliminary volumetric rate estimate for SN 2023zaw-like
rapidly evolving stripped-envelope SNe (SESNe). We use the methodology
described by Srivastav et al. (2022) for estimating rates of SNe Iax. We
consider rapidly evolving SESNe detected by the ATLAS survey that occurred
within a distance of 100 Mpc during a 5 year window spanning 2017 September 21
and 2022 September 20 (Srivastav et al., 2022). To estimate the recovery
efficiency of SN 2023zaw-like transients within 100 Mpc, we use the ATLAS
survey simulator (McBrien, 2021). We use Gaussian Processes interpolated ATLAS
$c$ and $o$-band light curves of SN 2023zaw, produced by interpolating the
light curves using the public extrabol (Thornton et al., 2023) code. These
were then injected 10,000 times at a range of times, sky locations and
redshift bins spanning up to D = 100 Mpc in the simulation. A simulated
transient was considered to be recovered as a detection if it produced a
minimum of 6 to 8 detections of $5\sigma$ (or greater) significance. Although
difference detections in the ATLAS data stream are flagged as candidate
transients if they produce 3 individual $5\sigma$ detections on any given
night, this criterion is more realistic since human scanners will be confident
about promoting candidates to the TNS if they have detections over at least
two distinct nights.

The volumetric rate is thus estimated using

$R=\frac{N}{\eta VT},$

where $T$ is the time duration of the mock survey, $N$ is the number of ultra-
stripped SNe detected within the considered time duration, $\eta$ represents
the recovery efficiency from the ATLAS survey simulator and $V$ is the volume
probed within 100 Mpc. We consider $N=3$, representing SN 2019bkc (Prentice et
al., 2020; Chen et al., 2020), SN 2019dge (Yao et al., 2020) and SN 2021agco
(Yan et al., 2023). The recovery efficiency obtained from the survey simulator
is $\eta\approx 0.06\pm 0.02$.

From the above, we estimate a rate of $R\approx 2.5^{+2.5}_{-1.4}\pm 0.9\times
10^{-6}$ Mpc-3 yr-1 $h^{3}_{70}$ for rapidly evolving SN 2023zaw-like SESNe,
where $h_{70}=H_{0}/70$. The statistical uncertainty derives from $1\sigma$
Gaussian errors from single-sided upper and lower limits for Poisson
statistics (Gehrels, 1986) and the systematic uncertainty is based on the
error on the recovery efficiency $\eta$. The above rate estimate for SN
2023zaw-like SESNe accounts for $\sim 1-6\%$ of the CCSN rate and $\sim
5-20\%$ of the SESN rate computed by Frohmaier et al. (2021). We note here
that $\sim 15\%$ of transients in the 100 Mpc ATLAS sample do not have a
spectroscopic classification (Srivastav et al., 2022), and it is possible that
the representation of SN 2023zaw-like rapidly evolving SESNe is
disproportionately higher within the unclassified sample. Nonetheless, at a
few per cent of the CCSN rate, these transients clearly constitute a rare
class of stellar explosions.

###  3.6 Potential Evolutionary Route

Using the physical characteristics inferred from our analysis we can look for
potential progenitor systems in the Binary Population and Spectral Synthesis
data release (BPASSv2.2.2 Eldridge et al. 2017; Stanway & Eldridge 2018;
Stevance et al. 2020). Assuming a solar metallicity (Z=0.02) we look for
models with M${}_{\rm H}<0.01$ M⊙ and hydrogen mass fraction $X<0.001$
(Dessart et al., 2012). An infered low ejecta mass in Section 3.3 further
constrains our search to models with ejecta mass $<0.1$ M⊙. Given the low
kinetic energy and ejecta mass of SN 2023zaw we report below the results
obtained by assuming the lower supernova explosion energy ($10^{50}$ ergs). In
addition we apply a condition for explodability of the progenitor star,
commonly a threshold on the mass of the Oxygen Neon core ($>$1.38 M⊙) is used
to determine if a model is a candidate for core collapse. When this condition
is applied no models in BPASSv2.2.2 are found to match all of our conditions;
but relaxing the condition to an ONe core mass greater than 1.30 M⊙ (removing
one significant figure from the threshold), we find 10 models that fit our
criteria. When we include weights dependent on the Initial Mass Function as
well as the binary fractions and period distributions (our fiducial IMF –
Kroupa 2001 – and our binary fractions and period distributions are based on
Moe & Di Stefano 2017), this corresponds to 28 such systems per million solar
masses at solar metallicity.

BPASS data are a grid of stellar evolution models and does not contain all
possible observable outcomes. However, natively finding candidate progenitor
stars just at the threshold of explodability is interesting when considering
the observed rarity of SN 2023zaw-like explosions. The progenitor of SN
2023zaw is very likely a lower mass star: the initial masses of our 6 systems
on the cusp of explodability range from 7.5 to 9 M⊙, which due to the initial
mass function are some of the most common massive stars in the Universe. The
low rate of SN 2023zaw-like SNe and BPASS results are naturally reconciled if
potential progenitors of these SNe fail to explode most of the time, as their
cores do not reach the necessary physical conditions. The 10 models we find
with ONe core mass $>1.3$ M⊙ represent only 2.6 percent of the massive stars
(M${}_{\rm ZAMS}>7.5$ M⊙) that fit our stripping and ejecta mass criteria, and
it is unlikely all of these would explode. This is in agreement with the
calculated rates in Section 3.5 of a few percent of the CCSN rate.

##  4 Summary and Conclusions

In this section we summarize the properties of SN 2023zaw.

  1. 1.

SN 2023zaw shows a rapid rise ($<$ 4 rest-frame days), and initial decline
from maximum light which settles to a radioactive tail 10 days after peak.
Comparisons to USSNe and rapidly evolving supernovae shows that SN 2023zaw is
among the fastest fading SNe yet discovered, comparable to SN 2019bkc (Chen et
al., 2020; Prentice et al., 2020). We consider radioactive nickel as the power
source for SN 2023zaw , finding that nickel alone cannot power both the peak
and the tail of the lightcurve, unlike SN 2019dge and SN 2019wxt (Yao et al.,
2020; Agudo et al., 2023a). An additional power source is required.

  2. 2.

We consider several additional powering mechanisms and use a Bayes factor
analysis to select a preferred model. This analysis favors interaction with a
CSM ($M_{\rm csm}=0.23^{+0.06}_{-0.05}$ M⊙ $r_{\rm csm}=63^{+13}_{-12}$ AU) to
boost the initial luminosity of SN 2023zaw. We note that spectroscopic
signatures of interaction were not observed in the spectra and suggest that
the CSM envelope was swept up by the photosphere before our first
spectroscopic observation.

  3. 3.

Through spectroscopic comparison we show SN 2023zaw is similar to type Ib SNe
and shows lines and line strengths similar to SN 2007C (Modjaz et al., 2014)
and SN 2019wxt (Agudo et al., 2023a). Monte Carlo radiative transfer modelling
with tardis shows SN 2023zaw has a composition dominated by He, O and Si. The
spectroscopic evolution is not compatible with He shell detonation models.

  4. 4.

A simulated ATLAS survey and estimate of the spectroscopic completeness of the
ATLAS Volume Limited Survey (D $<$ 100 Mpc) yields a rates estimate of
$R\approx 2.5^{+2.5}_{-1.4}\pm 0.9\times 10^{-6}$ Mpc-3 yr-1 $h^{3}_{70}$. SN
2023zaw-like transients could be as common as $\sim 1-6\%$ of the CCSN rate.
Searching for potential progenitor stars in BPASS models we propose that SN
2023zaw-like events are the result of lower mass progentitors (MZAMS = 7.5 – 9
M⊙ ) whose cores are at the threshold of explodability. The low observed rate
of these SNe is then a result of the fact that only a few percent of these
stars end with a core mass sufficient to result in core collapse.

We have shown SN 2023zaw to be part of a small group of rapidly evolving SNe
with a low ejecta mass ($M\simeq 0.07$M⊙ ) and estimated a total nickel mass
synthesised in the explosion $M_{\rm Ni}\simeq\,0.006$ M⊙. Furthermore,
through BF analysis we find evidence in favour of an extra luminosity source
in addition to the radioactive decay of 56Ni. With our estimate of host galaxy
extinction and significant Milky Way extinction in the line of sight we cannot
reproduce the observe light curve with shock cooling emission as favoured by
(Das et al., 2024) and favour interaction with a detached CSM to boost the
luminosity of SN 2023zaw or magnetar energy injection.

## acknowledgments

SJS, SS, KWS and DRY acknowledge funding from STFC Grants ST/Y001605/1,
ST/X001253/1, ST/X006506/1 and ST/T000198/1. SJS acknowledges a Royal Society
Research Professorship. MN is supported by the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No. 948381) and by UK Space Agency Grant No. ST/Y000692/1.
TWC acknowledges the Yushan Young Fellow Program by the Ministry of Education,
Taiwan for the financial support. SY acknowledges the funding from the
National Natural Science Foundation of China under Grant No. 12303046. HFS is
supported by the Eric and Wendy Schmidt A.I. in Science Fellowship. Pan-STARRS
is primarily funded to search for near-earth asteroids through NASA grants
NNX08AR22G and NNX14AM74G. The Pan-STARRS science products for transient
follow-up are made possible through the contributions of the University of
Hawaii Institute for Astronomy and Queen’s University Belfast. ATLAS is
primarily funded through NASA grants NN12AR55G, 80NSSC18K0284, and
80NSSC18K1575. The ATLAS science products are provided by the University of
Hawaii, Queen’s University Belfast, STScI, SAAO and Millennium Institute of
Astrophysics in Chile. We thank Lulin staff H.-Y. Hsiao, W.-J. Hou, C.-S. Lin,
H.-C. Lin, and J.-K. Guo for observations and data management. Based on
observations obtained at the international Gemini Observatory (under program
ID GN-2023B-Q-125), a program of NSF NOIRLab, which is managed by the
Association of Universities for Research in Astronomy (AURA) under a
cooperative agreement with the U.S. National Science Foundation on behalf of
the Gemini Observatory partnership: the U.S. National Science Foundation
(United States), National Research Council (Canada), Agencia Nacional de
Investigación y Desarrollo (Chile), Ministerio de Ciencia, Tecnología e
Innovación (Argentina), Ministério da Ciência, Tecnologia, Inovações e
Comunicações (Brazil), and Korea Astronomy and Space Science Institute
(Republic of Korea). This work was enabled by observations made from the
Gemini North telescope, located within the Maunakea Science Reserve and
adjacent to the summit of Maunakea. We are grateful for the privilege of
observing the Universe from a place that is unique in both its astronomical
quality and its cultural significance. Lasair is supported by the UKRI Science
and Technology Facilities Council and is a collaboration between the
University of Edinburgh (grant ST/N002512/1) and QUB (grant ST/N002520/1)
within the LSST:UK Science Consortium. ZTF is supported by National Science
Foundation grant AST-1440341 and a collaboration including Caltech, IPAC, the
Weizmann Institute for Science, the Oskar Klein Center at Stockholm
University, the University of Maryland, the University of Washington,
Deutsches Elektronen-Synchrotron and Humboldt University, Los Alamos National
Laboratories, the TANGO Consortium of Taiwan, the University of Wisconsin at
Milwaukee, and Lawrence Berkeley National Laboratories.

##  Appendix A MOSFiT Model Posterior

Figure 6:  Physical parameter posterior distribution of the circumstellar
material + nickel model. Where the important physical parameters are nickel
fraction ($f_{\rm Ni}$), kinetic energy ($E_{\rm k}$), CSM mass ($M_{\rm
csm}$), ejecta mass ($M_{\rm ej}$), the CSM radius ($R_{\rm 0}$) in units of
AU, CSM density ($\rho$), $t_{\rm exp}$ is relative to the first photometric
detection (MJD 60285.23) of SN 2023zaw.

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