arXiv subjects

Andrew Milligan

Publications and source records attributed to Andrew Milligan.

4 recordsLinked to original sources

arXiv2026

A Faint Progenitor System for the Faint Supernova 2024vjm

Type Ia Supernovae (SNe Ia) are well known for their role as standardizable cosmological candles. Their uniformity is credited to their single origin as thermonuclear explosions of White dwarf (WD) stars. Nevertheless, some SNe Ia break this regularity. Prominently, the Iax subclass are less energetic and remarkably diverse, raising questions about their progenitor systems. While no progenitor system of a normal SN Ia has ever been detected, a luminous blue star was identified in pre-explosion images of the site of the bright SN Iax SN 2012Z, suggested to be a helium giant companion star acting as a mass donor to a WD SN progenitor. This is in line with models of weak mass accretion of a WD from a binary companion, producing an explosion that does not fully disrupt the star. However, these models fail to explain the properties of the faintest Type Iax explosions, suggesting either they originate from other WD binary systems, or even from massive progenitor stars. Here, we present the faint SN Iax SN 2024vjm - possibly the faintest supernova observed to date. Using a deep pre-explosion image taken by the recently launched Euclid space mission, we show that its progenitor system must be fainter than the helium giant SN Iax progenitor candidate of SN 2012Z, as well as that of the luminous red companion or remnant of the faint SN 2008ha, and may require a subdwarf helium star as a mass donor. The deep image also provides strong arguments against a massive star origin for this faint supernova. Our observations argue that SN 2024vjm is a WD explosion, but we find that remarkably faint SNe Iax fade more slowly than bright ones, i.e., they evolve in an opposite manner from the famous Phillips relation that makes regular SNe Ia cosmological candles.

astro-ph.HE↗

arXiv2026

AT2024wpp: An Extremely Luminous Fast Ultraviolet Transient Powered by Accretion onto a Black Hole

We present the discovery of AT 2024wpp ("Whippet"), a fast and luminous 18cow-like transient. At a redshift of z=0.0868, revealed by Keck Cosmic Web Imager spectroscopy of its faint star-forming host, it is the fourth-nearest example of its class to date. Rapid identification of the source in the Zwicky Transient Facility data stream permitted ultraviolet-through-optical observations to be obtained prior to peak, allowing the first determination of the peak bolometric luminosity (2x10^45 erg/s), maximum photospheric radius (10^15 cm), and total radiated energy (10^51 erg) of an 18cow-like object. We present results from a comprehensive multiwavelength observing campaign, including a far-UV spectrum from the Cosmic Origins Spectrograph on the Hubble Space Telescope and deep imaging extending >100 days post-explosion from the Very Large Telescope, Hubble Space Telescope, Very Large Array, and Atacama Large Millimetre Array. We interpret the observations under a model in which a rapidly-accreting central engine blows a fast (~0.2c) wind into the surrounding medium and irradiates it with X-rays. The high Doppler velocities and intense ionization within this wind prevent identifiable spectroscopic features from appearing in the ejecta or in the surrounding circumstellar material. Weak H and He signatures do emerge in the spectra after 35 days in the form of double-peaked narrow lines. Each peak is individually narrow (full width ~3000 km/s) but the two components are separated by ~6600 km/s, indicating stable structures of denser material, possibly representing streams of tidal ejecta or an ablated companion star.

astro-ph.HE↗

arXiv2025

Testing and Combining Transient Spectral Classification Tools on 4MOST-like Blended Spectra

With the 4-meter Multi-Object Spectroscopic Telescope (4MOST) expected to provide an influx of transient spectra when it begins observations in early 2026 we consider the potential for real-time classification of these spectra. We investigate three extant spectroscopic transient classifiers: the Deep Automated Supernova and Host classifier (DASH), Next Generation SuperFit (NGSF) and SuperNova IDentification (SNID), with a focus on comparing the completeness and purity of the transient samples they produce. We manually simulate fibre losses critical for accurately determining host-contamination and use the 4MOST Exposure Time Calculator to produce realistic, 4MOST-like, host-galaxy contaminated spectra. We investigate the three classifiers individually and in all possible combinations. We find that a combination of DASH and NGSF can produce a SN Ia sample with a purity of 99.9% while successfully classifying 70% of SNe Ia. However, it struggles to classify non-SN Ia transients. We investigate photometric cuts to transient magnitude and the transient's fraction of total fibre flux, finding that both can be used to improve non-SN Ia transient classification completeness by 8--44% with SNe Ibc benefitting the most and superluminous (SL) SNe the least. Finally, we present an example classification plan for live classification and the predicted purities and completeness across five transient classes: Ia, Ibc, II, SL and non-SN transients. We find that it is possible to classify 75% of input spectra with >70% purity in all classes except non-SN transients. Precise values can be varied using different classifiers and photometric cuts to suit the needs of a given study.

astro-ph.SR↗

arXiv2024

How accurate are transient spectral classification tools? -- A study using 4,646 SEDMachine spectra

Accurate classification of transients obtained from spectroscopic data are important to understand their nature and discover new classes of astronomical objects. For supernovae (SNe), SNID, NGSF (a Python version of SuperFit), and DASH are widely used in the community. Each tool provides its own metric to help determine classification, such as rlap of SNID, chi2/dof of NGSF, and Probability of DASH. However, we do not know how accurate these tools are, and they have not been tested with a large homogeneous dataset. Thus, in this work, we study the accuracy of these spectral classification tools using 4,646 SEDMachine spectra, which have accurate classifications obtained from the Zwicky Transient Facility Bright Transient Survey (BTS). Comparing our classifications with those from BTS, we have tested the classification accuracy in various ways. We find that NGSF has the best performance (overall Accuracy 87.6% when samples are split into SNe Ia and Non-Ia types), while SNID and DASH have similar performance with overall Accuracy of 79.3% and 76.2%, respectively. Specifically for SNe Ia, SNID can accurately classify them when rlap > 15 without contamination from other types, such as Ibc, II, SLSN, and other objects that are not SNe (Purity > 98%). For other types, determining their classification is often uncertain. We conclude that it is difficult to obtain an accurate classification from these tools alone. This results in additional human visual inspection effort being required in order to confirm the classification. To reduce this human visual inspection and to support the classification process for future large-scale surveys, this work provides supporting information, such as the accuracy of each tool as a function of its metric.

astro-ph.IM↗