Adam A. Miller

There is a general consensus that Type Ia supernovae (SNe Ia) comprise the thermonuclear explosions of a C/O white dwarf (WD) in a binary system. However, the nature of their progenitors and explosion mechanism still remains elusive. Their early light curves can offer strong constraints on these parameters, as they trace the outermost layers and provide evidence of their initial conditions. In this work, we study the Zwicky Transient Facility (ZTF) data release 2 sample of SNe Ia in search for objects with early flux excess (EEx SNe Ia). Two main approaches were used: i) finding deviations between early-time observations and models without early excess and ii) finding an agreement between observations and models with early excess. For the former approach, different methods, such as power-law and SALT2 fits, were used to identify EEx SN Ia candidates. For the second approach, we used double-detonation (DD) and companion-interaction (CI) models, finding 145 and 199 candidates, respectively. In general, there is a disagreement between the methods in the exact objects identified as EEx SNe Ia as well as in their number. By combining multiple methods, we found 17 strong EEx SN Ia candidates, 6 of which are of the overluminous subtype (five 91T-like and one 03 fg-like). The most prominent excesses reach ∼10–17% of peak flux (up to ∼−17 mag). We found that the best EEx SN Ia candidates have higher stretch on average compared to the rest of the SNe Ia. They also seem to prefer lower mass and bluer host galaxies, potentially linked to younger stellar populations. Additionally, we estimated the fraction of EEx SNe Ia to be ≲25% of all SNe Ia, in agreement with previous works, with overluminous subtypes having a higher relative fraction compared to normal SNe Ia. When studying the parameter distribution of the DD models for the EEx SN Ia candidates, we see a preference for intermediate WD core mass (1 M _⊙ ), a lower fraction of shell burning (20%), and heavier He-burning products ( ⁵⁶ Ni). For the CI models, we see no trends with any of the parameters. We are unable to draw strong conclusions on whether one model is preferred over the other as a viable description of SN Ia explosions Finally, we highlight the challenge of identifying EEx SNe Ia in real time, making the triggering of early-time spectroscopic observations for these objects a difficult task.

We present panchromatic observations of the Type Ia supernova (SN Ia) 2023qov, ranging from ∼2 weeks before to ∼1 yr after maximum light. JWST near- and mid-infrared spectra at +276 and +363 days show ∼400 K dust emission that cools by ∼75 K between epochs, the first unambiguous spectroscopic detection of dust emission in a normal SN Ia. We find that the emission is well described by models of carbonaceous dust placed within ∼1 lt-yr of the SN, with a dust mass of ∼10 ⁻⁴ M _⊙ . We do not see evidence of active dust creation, suggesting an infrared light echo by preexisting circumstellar dust as the likely source of the emission. The JWST nebular line profiles suggest asymmetric, stratified ejecta, similar to other normal SNe Ia, though a slight double-horn structure in the argon lines indicates a toroidal enhancement. SN 2023qov exhibits a slightly red, fast-declining early light curve (Δ m ₁₅ ( B ) = 1.47 ± 0.05 mag), from which we determine a ⁵⁶ Ni mass of M ₅₆ = 0.21 ± 0.04 M _⊙ , and a distance of d = 36.0 ± 1.8 Mpc to the SN and its host, NGC 7029. The presence of circumstellar dust around a normal SN Ia has implications both for the progenitor system, suggesting a less than pristine environment, and for cosmology, as a possible source of reddening and extinction that can affect distance inferences.

We present optical + near-infrared + mid-infrared (MIR) observations of the normal Type Ia supernovae (SNe Ia) 2022aaiq and 2024gy in the nebular phase, continuously spanning 0.35–28 μ m. Medium-resolution JWST spectroscopy reveals novel narrow ( v _FWHM < 1500 km s ⁻¹ ) [Ni ii ] 1.94 and 6.64 μ m cores in both events. The MIR [Ni ii ] 6.64 μ m line exhibits a distinct narrow core atop a broader base, indicating a central enhancement of stable Ni. This structure points to high central densities consistent with a near-Chandrasekhar-mass ( M _Ch ) progenitor or a high-metallicity sub- M _Ch progenitor. From detailed line-profile inversions of SN 2024gy, we derive emissivity profiles for stable iron-group elements, radioactive material, and intermediate-mass elements, revealing spatially distinct ejecta zones. The [Ni iii ] 7.35 μ m line shows a shallow-to-steep slope transition—a “broken-slope” morphology—that matches predictions for delayed detonation explosions with separated deflagration and detonation ashes. We also reanalyze and compare to archival JWST spectra of SN 2021aefx and the subluminous SN 2022xkq. From the stable Ni luminosities, we infer that SN 2024gy produced ∼5–10 times more stable Ni mass than SN 2022xkq, favoring a near- M _Ch scenario for SN 2024gy and a sub- M _Ch scenario for SN 2022xkq. These results demonstrate that resolved line profiles, now accessible with JWST, provide powerful diagnostics of explosion geometry, central density, and progenitor mass in SNe Ia.

We present optical and near-infrared (NIR) observations of the fast-declining Type Ia supernova (SN Ia) 2022an. The photometric and spectroscopic properties identify it as a standard 91bg-like event; however, our data reveal a relatively narrow absorption feature with a full width at half-maximum (FWHM) of 75 Å near 1.037 μ m in the rest frame of the observed spectra that persists from around 30 days to nearly 90 days after maximum light. We attribute this feature to the He i 1.083 μ m line with a blueshifted velocity of 1.3 × 10 ⁴ km s ⁻¹ and a FWHM of 2.1 × 10 ³ km s ⁻¹ , supported by the detection of multiple optical He i transitions at earlier epochs with a higher velocity of around 1.5 × 10 ⁴ km s ⁻¹ . The high velocity of the helium cannot be explained by helium external to the progenitor at the time of explosion, such as stripped surface helium from a companion star. The properties of the helium absorption in the spectra of SN 2022an instead point to unburned material in the outer ejecta, thus providing the most compelling evidence to date for helium-bearing ejecta in a 91bg-like SN Ia. Such helium has been predicted in sub-Chandrasekhar-mass double-detonation explosions involving a surface helium shell. No theoretical calculations of modern helium-shell double detonations have been performed at epochs similar to those observed for SN 2022an to study the effects of helium on their spectra, revealing a gap between observations and theoretical calculations in our understanding of how helium manifests in SNe Ia. Nevertheless, the discovery of persistent helium absorption in SN 2022an demonstrates the diagnostic power of NIR spectroscopy for understanding thermonuclear supernova explosions by probing the abundance and structure of their ejecta.

Simulations predict that supermassive black hole binaries (SMBHBs) will exhibit periodic brightness variations that may exceed the stochastic variability intrinsic to active galactic nuclei (AGN). In this paper, we simulate SMBHBs with damped random walk (DRW) AGN variability and an added sinusoidal signal from the orbital motion, and test three methods—a generalized Lomb–Scargle periodogram (GLSP), a nested Bayesian sampler (NBS), and a weighted wavelet z -transform (or WWZ)—to determine which is best at recovering the periodicity. Our simulated light curves follow the properties of the Catalina Real-Time Transient Survey (or CRTS), Legacy Survey of Space and Time (LSST), and Zwicky Transient Facility (ZTF) to best inform current and future SMBHB searches. We map a broad range of parameter space and identify which DRW-only light curves best mimic periodicity and pass each method’s model selection. The NBS performs best at detecting periodicity and filtering out DRW-only light curves. Combined candidate selection with both the NBS and GLSP significantly reduces false-positive rates (FPRs) with marginal impact on true-positive rates (TPRs). With this joint model selection pipeline, we find the lowest FPRs in ZTF-like simulations and the highest detection rates in LSST-like simulations. Using a modified computation of the false-alarm probability with GLSP, we efficiently triage LSST AGN light curves (∼10 ⁷ light curves in ∼10–30 hr) and achieve TPRs and FPRs of ∼40% and ∼0.5%, respectively.

We present extensive ultraviolet to optical photometric and optical to near-infrared (NIR) spectroscopic follow-up observations of the nearby intermediate-luminosity ( M _V = −16.81 ± 0.19 mag) Type Iax supernovae (SNe Iax) 2024pxl in NGC 6384. SN 2024pxl exhibits a faster light curve than the high-luminosity members of this class, and slower than low-luminosity events. The observationally well-constrained rise time of ∼11 days and an estimated synthesized ⁵⁶ Ni mass of 0.03 M _⊙ , based on analytical modeling of the integrated spectral energy distribution light curve, are consistent with models of the weak deflagration of a carbon-oxygen white dwarf. Our optical spectral sequence of SN 2024pxl shows weak Si ii lines and spectral evolution similar to other high-luminosity SNe Iax, but also a prominent early-time C ii line, like lower-luminosity SNe Iax. The late-time optical spectrum of SN 2024pxl closely matches that of SN 2014dt, and its NIR spectral evolution aligns with that of other well-studied, high-luminosity SNe Iax. The spectral-line expansion velocities of SN 2024pxl are at the lower end of the SNe Iax velocity distribution, and the velocity distribution of iron-group elements compared to intermediate-mass elements suggests that the ejecta are mixed on large scales, as expected in pure deflagration models. SN 2024pxl exhibits characteristics intermediate between those of high-luminosity and low-luminosity SNe Iax, further establishing a link across this diverse class.

Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.