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Dylan Magill

Publications and source records attributed to Dylan Magill.

6 recordsLinked to original sources

Aarmed with Data: Bumps, Outflows, and Disk-like Emission in TDE 2025aarm

The origin of the optical emission in tidal disruption events (TDEs) remains one of the major outstanding questions in the field, in part due to the limited number of nearby events with high-cadence monitoring to track their evolving photometric and spectroscopic properties. We present multi-wavelength observations of the nearby ($z=0.01368$) TDE\,2025aarm, including near-daily spectroscopic coverage prior to the optical peak. Its proximity makes it one of the brightest TDEs discovered, reaching a peak magnitude of $m_r\sim15.5$ ($M_r\sim-18$). The light curve deviates from a smooth evolution, exhibiting multiple rebrightening episodes visible in both the individual filter light curves and the bolometric luminosity. Blackbody modelling reveals that these rebrightenings are associated with an increase in temperature of $> 5,000-10,000$\,K, while the inferred photospheric radius remains approximately constant. Simultaneously, the H$\alpha$ line not only increases in blueshift but also broadens, suggesting a link between the continuum rebrightenings to changes in the kinematics of the line-forming gas. We identify a persistent absorption component at $\sim-3900$\,km\,s$^{-1}$ in multiple Balmer lines, providing further evidence for outflowing material. The H$\alpha$ profile also exhibits excess flux compared to a Gaussian on both sides of the line, inconsistent with simple scattering-dominated outflow models. Disk-profile modelling provides evidence for the emergence of a disk-like component least $\sim20$ days after peak, with substantial changes in the disk properties between $\sim50$ and 60 days. These observations highlight the complexity of TDE emission processes and demonstrate how dense multi-wavelength monitoring can disentangle the roles of accretion, reprocessing, and outflows in shaping TDE emission.

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Automatically distinguishing Rubin transients from AGN using variability metrics

Stochastic variability of active galactic nuclei (AGN) can produce contaminants in the search for explosive extragalactic transients (such as supernovae and tidal disruption events). In the new era of the Rubin Observatory's Legacy Survey of Space and Time (LSST), previously uncatalogued AGN, especially those with luminosity near the survey detection limits, are expected to produce a flood of detections that have the potential to contaminate surveys targeting other transients, leading to inefficient use of spectroscopic follow-up time. For surveys aiming to statistically characterise transient demographics, it is advantageous to use easily modelled and reproducible selection criteria to distinguish AGN from other transients, rather than machine learning. We test enacting cuts based on simple data-driven photometric variability parameters to distinguish non-AGN extragalactic transients from standard AGN variability on both Zwicky Transient Facility photometry and simulated LSST photometry from the MALLORN data set. We also investigate the impact of light curve history availability, redshift range and filter selection on selection efficiency. We find that a two-dimensional cut incorporating the ratio of detection flux and pre-detection standard deviation and the ratio of detection flux to pre-detection mean flux is the most effective cut. This approach is easily scalable as these values are included in the LSST alert packets. We provide estimates of the completeness and purity of the sample produced by enacting this cut, and gauge the AGN contamination avoided. The parameters utilised in this approach could also be implemented as features for identifying AGN in a photometric classifier.

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ATLAS100 -- I. A volume-limited sample of supernovae and related transients within 100 Mpc

We present ATLAS100 -- a sample of 1729 supernovae and other explosive optical transients within $\sim 100$ Mpc observed by the ATLAS survey over a span of 5.75 years from 2017 September 21 to 2023 June 21. The volume-limited sample includes transients associated with galaxies with a spectroscopic redshift of $z \leq 0.025$, and spectroscopically classified transients within this redshift threshold where a host redshift was not available in existing catalogues. Our host galaxy list is constructed from aggregating all available galaxy redshift and distance catalogues. We carefully select all transients within a projected radius of 50\,kpc of these hosts. The ATLAS100 transient sample has a host galaxy redshift completeness fraction of $83$ per cent, consistent with expectations for the redshift completeness of local galaxy catalogues. Within this volume, the spectroscopic classifications are 87 per cent complete and we reclassify many ambiguous transients with joint light curve and spectroscopic considerations. Here, we release the catalogue together with compiled, binned and cleaned ATLAS photometry for all transients. We fit the light curve data to derive peak luminosity and characteristic timescales. We explore the sample characteristics, demographics and discuss completeness and purity of the sample.

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A vision for ground-based astronomy beyond the 2030s: How to build ESO's next big telescope sustainably

Astronomy is the study of the Universe and all the objects that it comprises. Our attention is therefore usually focused beyond Earth, home to the only form of life known today. However, how can we continue to explore the secrets of the Universe, if we stand by and watch our only home burn? We know that there is no Planet B. It is therefore urgent that, as astronomers, we collectively work to protect the Earth, allowing future generations the opportunity to continue to uncover the secrets of the cosmos. As astronomical facilities account for the majority of our community's carbon footprint, we propose guidelines that we hold crucial for the European Southern Observatory (ESO) to consider in the context of the Expanding Horizons programme as it plans a next-generation, transformational facility.

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MALLORN: Many Artificial LSST Lightcurves based on Observations of Real Nuclear transients

The Vera C. Rubin Observatory's 10-Year Legacy Survey of Space and Time (LSST) is expected to produce a hundredfold increase in the number of transients we observe. However, there are insufficient spectroscopic resources to follow up on all of the wealth of targets that LSST will provide. As such it is necessary to be able to prioritise objects for followup observations or inclusion in sample studies based purely on their LSST photometry. We are particularly keen to identify tidal disruption events (TDEs) with LSST. TDEs are immensely useful for determining black hole parameters and probing our understanding of accretion physics. To assist in these efforts, we present the Many Artificial LSST Lightcurves based on the Observations of Real Nuclear transients (MALLORN) data set and the corresponding classifier challenge for identifying TDEs. MALLORN comprises 10178 simulated LSST light curves, constructed from real Zwicky Transient Facility (ZTF) observations of 64 TDEs, 727 nuclear supernovae and 1407 AGN with spectroscopic labels using Gaussian process fitting, empirically-motivated spectral energy distributions from SNCosmo and the baseline from the Rubin Survey Simulator. Our novel approach can be easily adapted to simulate transients for any photometric survey using observations from another, requiring only the limiting magnitudes and an estimate of the cadence of observations. The MALLORN Astronomical Classification Challenge, launched on Kaggle on 15/10/2025, will allow competitors to test their photometric classifiers on simulated LSST data to find TDEs and improve upon their capabilities prior to the start of LSST.

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Super-SNID : an expanded set of SNID classes and templates for the new era of wide-field surveys

We present an expanded template library for the supernova identification (SNID) software, along with updated source files that make it easy to merge our templates - and other major SNID libraries - into the base code. This expansion, dubbed 'Super-SNID', increases the number of spectra for under-represented supernova classes (e.g., SNe Ia-02cx, Ibn) and adds new classes (e.g., SLSNe, TDEs, LFBOTs). Super-SNID includes 841 spectral templates for 161 objects, primarily from the Public ESO Spectroscopic Survey of Transient Objects (PESSTO) Data Releases 1-4. The library is available on GitHub with simple installation instructions.

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