We present preexplosion optical and infrared (IR) imaging at the site of the type II supernova (SN II) 2023ixf in Messier 101 at 6.9 Mpc. We astrometrically registered a ground-based image of SN 2023ixf to archival Hubble Space Telescope (HST), Spitzer Space Telescope (Spitzer), and ground-based near-IR images. A single point source is detected at a position consistent with the SN at wavelengths ranging from HST R band to Spitzer 4.5 μm. Fitting with blackbody and red supergiant (RSG) spectral energy distributions (SEDs), we find that the source is anomalously cool with a significant mid-IR excess. We interpret this SED as reprocessed emission in a 8600 R ⊙ circumstellar shell of dusty material with a mass ∼5 × 10−5 M ⊙ surrounding a log ( L / L ⊙ ) = 4.74 ± 0.07 and T eff = 3920 − 160 + 200 K RSG. This luminosity is consistent with RSG models of initial mass 11 M ⊙, depending on assumptions of rotation and overshooting. In addition, the counterpart was significantly variable in preexplosion Spitzer 3.6 and 4.5 μm imaging, exhibiting ∼70% variability in both bands correlated across 9 yr and 29 epochs of imaging. The variations appear to have a timescale of 2.8 yr, which is consistent with κ-mechanism pulsations observed in RSGs, albeit with a much larger amplitude than RSGs such as α Orionis (Betelgeuse).

Type IIn supernovae (SNe IIn) are a relatively infrequently observed subclass of SNe whose photometric and spectroscopic properties are varied. A common thread among SNe IIn are the complex multiple-component hydrogen Balmer lines. Owing to the heterogeneity of SNe IIn, online databases contain some outdated, erroneous, or even contradictory classifications. SN IIn classification is further complicated by SN “impostors” and contamination from underlying H ii regions. We have compiled a catalogue of systematically classified nearby (redshift z < 0.02) SNe IIn using the Open Supernova Catalogue (OSC). We present spectral classifications for 115 objects previously classified as SNe IIn. Our classification is based upon results obtained by fitting multiple Gaussians to the Hα profiles. We compare classifications reported by the OSC and Transient Name Server (TNS) along with the best matched templates from SNID. We find that 28 objects have been misclassified as SNe IIn. TNS and OSC can be unreliable; they disagree on the classifications of 51 of the objects and contain a number of erroneous classifications. Furthermore, OSC and TNS hold misclassifications for 34 and twelve (respectively) of the transients we classify as SNe IIn. In total, we classify 87 SNe IIn. We highlight the importance of ensuring that online databases remain up to date when new or even contemporaneous data become available. Our work shows the great range of spectral properties and features that SNe IIn exhibit, which may be linked to multiple progenitor channels and environment diversity. We set out a classification sche me for SNe IIn based on the Hα profile which is not greatly affected by the inhomogeneity of SNe IIn.

We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host–galaxy associations, redshifts, spectroscopic and/or photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z ≈ 0.5. We present relative SN rates from YSE’s magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multisurvey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms; when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high (>90%) individual completeness and purity, which will help build an anchor photometric SNe Ia sample for cosmology. We then use our photometric classifier to characterize our photometric sample of 1483 SNe, labeling 1048 (∼71%) SNe Ia, 339 (∼23%) SNe II, and 96 (∼6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time.

We present optical and near-infrared (NIR) observations of the Type Icn supernova (SN Icn) 2022ann, the fifth member of its newly identified class of SNe. Its early optical spectra are dominated by narrow carbon and oxygen P-Cygni features with absorption velocities of ∼800 km s−1; slower than other SNe Icn and indicative of interaction with a dense, H/He-poor circumstellar medium (CSM) that is outflowing slower than typical Wolf-Rayet wind velocities of >1000 km s−1. We identify helium in NIR spectra two weeks after maximum and in optical spectra at three weeks, demonstrating that the CSM is not fully devoid of helium. Unlike other SNe Icn, the spectra of SN 2022ann never develop broad features from SN ejecta, including in the nebular phase. Compared to other SNe Icn, SN 2022ann has a low luminosity (o-band absolute magnitude of ∼−17.7), and evolves slowly. The bolometric light curve is well-modelled by 4.8 M⊙ of SN ejecta interacting with 1.3 M⊙ of CSM. We place an upper limit of 0.04 M⊙ of 56Ni synthesized in the explosion. The host galaxy is a dwarf galaxy with a stellar mass of 107.34 M⊙ (implied metallicity of log(Z/Z⊙) ≈ 0.10) and integrated star-formation rate of log (SFR) = −2.20 M⊙ yr−1; both lower than 97% of galaxies observed to produce core-collapse supernovae, although consistent with star-forming galaxies on the galaxy Main Sequence. The low CSM velocity, nickel and ejecta masses, and likely low-metallicity environment disfavour a single Wolf-Rayet progenitor star. Instead, a binary companion is likely required to adequately strip the progenitor and produce a low-velocity outflow.

Type IIn supernovae (SNe IIn) are an uncommon and highly heterogeneous class of SN where the SN ejecta interact with pre-existing circumstellar media (CSM). Previous studies have found a mass ladder in terms of the association of the SN location with Hα emission and the progenitor masses of SN classes. In this paper, we present the largest environmental study of SNe IIn. We analyse the Hα environments of 77 type IIn supernovae using continuum subtracted Hα images. We use the pixel statistics technique, normalised cumulative ranking (NCR), to associate SN pixels with Hα emission. We find that our 77 SNe IIn do not follow the Hα emission. This is not consistent with the proposed progenitors of SNe IIn, luminous blue variables (LBVs) as LBVs are high mass stars that undergo dramatic episodic mass loss. However, a subset of the NCR values follow the Hα emission, suggesting a population of high mass progenitors. This suggests there may be multiple progenitor paths with ∼60 per cent having non-zero NCR values with a distribution consistent with high mass progenitors such as LBVs and ∼40 per cent of these SNe not being associated with Hα emission. We discuss the possible progenitor routes of SNe IIn, especially for the zero NCR value population. We also investigate the radial distribution of the SNe in their hosts in terms of Hα and r′-band flux.