arXiv subjects

R. Starling

Publications and source records attributed to R. Starling.

At least 19 recordsLinked to original sources

arXiv2026

Searching for outbursts from Symbiotic Binaries in GOTO and ATLAS data

Symbiotic Binaries contain a white dwarf accreting material from a red giant star through a wind. We present the results of a search for outbursts from Symbiotic Binaries using photometric data obtained using the GOTO all-sky survey taken from 2023 onwards. After identifying ten candidate outbursting systems, we used ATLAS photometry to characterise their photometric behaviour before 2023, leaving five systems which showed photometric behaviour consistent with an outburst. The ATLAS data showed how important the photometric history of an object is in determining whether a photometric feature is a likely outburst event. The outburst from LMC N67 is the first reported Z And-type outburst from a Symbiotic binary in the LMC. OGLE SMC-LPV-4044 and HK Sco show previously unreported outbursts. QW Sge and V4141 Sgr show outbursts starting in 2024, which have already been reported and are ongoing. By better identifying and characterising Z And-type outbursts from many systems, it will be possible to better understand the physics of these events, which are still not fully understood.

astro-ph.SR↗

arXiv2026

GOTO identification and broadband modelling of the counterpart to the SVOM GRB 250818B

Rapid localisation and follow-up of gamma-ray bursts (GRBs) increasingly rely on low-latency triggers from new missions coupled to wide-field robotic optical facilities. We present the discovery and multi-wavelength follow-up of GRB 250818B, detected by the Space Variable Objects Monitor (SVOM) and localised optically by the Gravitational-wave Optical Transient Observer (GOTO). We compile and homogenise X-ray, optical/NIR, and radio data to build broadband light curves and spectral energy distributions. The afterglow is unusually luminous for a nominal short GRB, lying on the bright end of the short-GRB population in X-rays and optical and among the most luminous high-redshift short-GRB afterglows in the radio. MeerKAT detects the source at 3.1 GHz, while ALMA provides deep higher-frequency limits. Keck/LRIS spectroscopy shows continuum and metal absorption (Fe II, Mg II, Mg I), giving $z=1.216$. Synchrotron forward-shock modelling favours a constant-density medium and strongly prefers refreshed (energy-injection) emission, well described by a two-component jet with $E_{K,iso} \sim 4\times10^{52}$ erg, $n_0 \sim 3.6$ cm$^{-3}$, $\theta_j \simeq 0.10$ rad ($\sim 5.7$ deg), and $p \simeq 1.64$. The host association is ambiguous: the nearest LS DR10 galaxy candidate ($r_{AB} \sim 24.7$) is offset by $\sim 4$ arcsec ($\sim 34$ kpc) with chance-alignment probability $P_{cc} \sim 0.2$, and current imaging does not exclude a fainter, near-coincident host. SED fitting of the candidate host suggests a low-mass galaxy. GRB 250818B highlights the power of rapid wide-field counterpart identification in the SVOM era, while host-association uncertainty can still limit offset-based interpretation.

astro-ph.HE↗

arXiv2025

SN 2024bfu, SN 2025qe, and the early light curves of type Iax supernovae

Type Iax supernovae (SNe Iax) are one of the most common subclasses of thermonuclear supernova and yet their sample size, particularly those observed shortly after explosion, remains relatively small. In this paper we present photometric and spectroscopic observations of two SNe Iax discovered shortly after explosion, SN 2024bfu and SN 2025qe. Both SNe were observed by multiple all-sky surveys, enabling tight constraints on the moment of first light and the shape of the early light curve. Our observations of SN 2025qe begin <2d after the estimated time of first light and represent some of the earliest observations of any SN Iax. Spectra show features consistent with carbon absorption throughout the evolution of SN 2025qe, potentially indicating the presence of unburned material throughout the ejecta. We gather a sample of SNe Iax observed by ATLAS, GOTO, and ZTF shortly after explosion and measure their rise times and early light curve power-law rise indices. We compare our results to a sample of normal SNe Ia and find indications that SNe Iax show systematically shorter rise times, consistent with previous work. We also find some indication that SNe Iax show systematically lower rise indices than normal SNe Ia. The low rise indices observed among SNe Iax are qualitatively consistent with extended $^{56}$Ni distributions and more thoroughly-mixed ejecta compared to normal SNe Ia, similar to predictions from pure deflagration explosions.

astro-ph.HE↗

arXiv2025

GOTO065054+593624: a 8.5 mag amplitude dwarf nova identified in real time via Kilonova Seekers

Dwarf novae are astrophysical laboratories for probing the nature of accretion, binary mass transfer, and binary evolution -- yet their diverse observational characteristics continue to challenge our theoretical understanding. We here present the discovery of, and subsequent observing campaign on GOTO065054+593624 (hereafter GOTO0650), a dwarf nova of the WZ Sge type, discovered in real-time by citizen scientists via the Kilonova Seekers citizen science project, which has an outburst amplitude of 8.5 mag. An extensive dataset charts the photometric and spectroscopic evolution of this object, covering the 2024 superoutburst. GOTO0650 shows an absence of visible emission lines during the high state, strong H and barely-detected HeII emission, and high-amplitude echo outbursts with a rapidly decreasing timescale. The comprehensive dataset presented here marks GOTO0650 as a candidate period bouncer, and highlights the important contribution that citizen scientists can make to the study of Galactic transients.

astro-ph.SR↗

arXiv2024

SN 2023tsz: A helium-interaction driven supernova in a very low-mass galaxy

SN 2023tsz is a Type Ibn supernova (SNe Ibn) discovered in an extremely low-mass host. SNe Ibn are an uncommon subtype of stripped-envelope core-collapse SNe. They are characterised by narrow helium emission lines in their spectra and are believed to originate from the collapse of massive Wolf-Rayet (WR) stars, though their progenitor systems still remain poorly understood. In terms of energetics and spectrophotometric evolution, SN 2023tsz is largely a typical example of the class, although line profile asymmetries in the nebular phase are seen, which may indicate the presence of dust formation or unshocked circumstellar material. Intriguingly, SN 2023tsz is located in an extraordinarily low-mass host galaxy that is in the 2nd percentile for SESN host masses and star formation rates (SFR). The host has a radius of 1.0 kpc, a $g$-band absolute magnitude of $-12.73$, and an estimated metallicity of $\log(Z_{*}/Z_{\odot}$) = $-1.56$. The SFR and metallicity of the host galaxy raise questions about the progenitor of SN 2023tsz. The low SFR suggests that a star with sufficient mass to evolve into a WR would be uncommon in this galaxy. Further, the very low-metallicity is a challenge for single stellar evolution to enable H and He stripping of the progenitor and produce a SN Ibn explosion. The host galaxy of SN 2023tsz adds another piece to the ongoing puzzle of SNe Ibn progenitors, and demonstrates that they can occur in hosts too faint to be observed in contemporary sky surveys at a more typical SN Ibn redshift.

astro-ph.HE↗

arXiv2024

$\textit{Kilonova Seekers}$: the GOTO project for real-time citizen science in time-domain astrophysics

Time-domain astrophysics continues to grow rapidly, with the inception of new surveys drastically increasing data volumes. Democratised, distributed approaches to training sets for machine learning classifiers are crucial to make the most of this torrent of discovery -- with citizen science approaches proving effective at meeting these requirements. In this paper, we describe the creation of and the initial results from the $\textit{Kilonova Seekers}$ citizen science project, built to find transient phenomena from the GOTO telescopes in near real-time. $\textit{Kilonova Seekers}$ launched in July 2023 and received over 600,000 classifications from approximately 2,000 volunteers over the course of the LIGO-Virgo-KAGRA O4a observing run. During this time, the project has yielded 20 discoveries, generated a `gold-standard' training set of 17,682 detections for augmenting deep-learned classifiers, and measured the performance and biases of Zooniverse volunteers on real-bogus classification. This project will continue throughout the lifetime of GOTO, pushing candidates at ever-greater cadence, and directly facilitate the next-generation classification algorithms currently in development.

astro-ph.IM↗

arXiv2022

Self-Supervised Clustering on Image-Subtracted Data with Deep-Embedded Self-Organizing Map

Developing an effective automatic classifier to separate genuine sources from artifacts is essential for transient follow-ups in wide-field optical surveys. The identification of transient detections from the subtraction artifacts after the image differencing process is a key step in such classifiers, known as real-bogus classification problem. We apply a self-supervised machine learning model, the deep-embedded self-organizing map (DESOM) to this "real-bogus" classification problem. DESOM combines an autoencoder and a self-organizing map to perform clustering in order to distinguish between real and bogus detections, based on their dimensionality-reduced representations. We use 32x32 normalized detection thumbnails as the input of DESOM. We demonstrate different model training approaches, and find that our best DESOM classifier shows a missed detection rate of 6.6% with a false positive rate of 1.5%. DESOM offers a more nuanced way to fine-tune the decision boundary identifying likely real detections when used in combination with other types of classifiers, for example built on neural networks or decision trees. We also discuss other potential usages of DESOM and its limitations.

cs.CV↗

arXiv2022

A blast from the infant Universe: the very high-z GRB 210905A

We present a detailed follow-up of the very energetic GRB 210905A at a high redshift of z = 6.312 and its luminous X-ray and optical afterglow. We obtained a photometric and spectroscopic follow-up in the optical and near-infrared (NIR), covering both the prompt and afterglow emission from a few minutes up to 20 Ms after burst. With an isotropic gamma-ray energy release of Eiso = 1.27E54 erg, GRB 210905A lies in the top ~7% of gamma-ray bursts (GRBs) in terms of energy released. Its afterglow is among the most luminous ever observed. It starts with a shallow evolution that can be explained by energy injection, and it is followed by a steeper decay, while the spectral energy distribution is in agreement with slow cooling in a constant-density environment within the standard fireball theory. A jet break at ~ 46.2+-16.3 d (~6.3 d rest-frame) has been observed in the X-ray light curve; however, it is hidden in the H band due to the contribution from the likely host galaxy, the fourth GRB host at z > 6 known to date. We derived a half-opening angle of 8.4+-1.0 degrees, which is the highest ever measured for a z>6 burst, but within the range covered by closer events. The resulting collimation-corrected gamma-ray energy release of 1E52 erg is also among the highest ever measured. The moderately large half-opening angle argues against recent claims of an inverse dependence of the half-opening angle on the redshift. The total jet energy is likely too large to be sustained by a standard magnetar, and it suggests that the central engine of this burst was a newly formed black hole. Despite the outstanding energetics and luminosity of both GRB 210905A and its afterglow, we demonstrate that they are consistent with those of less distant bursts, indicating that the powering mechanisms and progenitors do not evolve significantly with redshift.

astro-ph.HE↗

arXiv2021

The Gravitational-wave Optical Transient Observer (GOTO): prototype performance and prospects for transient science

The Gravitational-wave Optical Transient Observer (GOTO) is an array of wide-field optical telescopes, designed to exploit new discoveries from the next generation of gravitational wave detectors (LIGO, Virgo, KAGRA), study rapidly evolving transients, and exploit multi-messenger opportunities arising from neutrino and very high energy gamma-ray triggers. In addition to a rapid response mode, the array will also perform a sensitive, all-sky transient survey with few day cadence. The facility features a novel, modular design with multiple 40-cm wide-field reflectors on a single mount. In June 2017 the GOTO collaboration deployed the initial project prototype, with 4 telescope units, at the Roque de los Muchachos Observatory (ORM), La Palma, Canary Islands. Here we describe the deployment, commissioning, and performance of the prototype hardware, and discuss the impact of these findings on the final GOTO design. We also offer an initial assessment of the science prospects for the full GOTO facility that employs 32 telescope units across two sites.

astro-ph.IM↗

arXiv2021

Searching For Fermi GRB Optical Counterparts With The Prototype Gravitational-Wave Optical Transient Observer (GOTO)

The typical detection rate of $\sim1$ gamma-ray burst (GRB) per day by the \emph{Fermi} Gamma-ray Burst Monitor (GBM) provides a valuable opportunity to further our understanding of GRB physics. However, the large uncertainty of the \emph{Fermi} localization typically prevents rapid identification of multi-wavelength counterparts. We report the follow-up of 93 \emph{Fermi} GRBs with the Gravitational-wave Optical Transient Observer (GOTO) prototype on La Palma. We selected 53 events (based on favourable observing conditions) for detailed analysis, and to demonstrate our strategy of searching for optical counterparts. We apply a filtering process consisting of both automated and manual steps to 60\,085 candidates initially, rejecting all but 29, arising from 15 events. With $\approx3$ GRB afterglows expected to be detectable with GOTO from our sample, most of the candidates are unlikely to be related to the GRBs. Since we did not have multiple observations for those candidates, we cannot confidently confirm the association between the transients and the GRBs. Our results show that GOTO can effectively search for GRB optical counterparts thanks to its large field of view of $\approx40$ square degrees and its depth of $\approx20$ mag. We also detail several methods to improve our overall performance for future follow-up programs of \emph{Fermi} GRBs.

astro-ph.HE↗

arXiv2021

Light curve classification with recurrent neural networks for GOTO: dealing with imbalanced data

The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machine learning (ML) and deep learning (DL) algorithms to sift through the vast incoming data stream. A problem that arises in real-world applications of learning algorithms for classification is imbalanced data, where a class of objects within the data is underrepresented, leading to a bias for over-represented classes in the ML and DL classifiers. We present a recurrent neural network (RNN) classifier that takes in photometric time-series data and additional contextual information (such as distance to nearby galaxies and on-sky position) to produce real-time classification of objects observed by the Gravitational-wave Optical Transient Observer (GOTO), and use an algorithm-level approach for handling imbalance with a focal loss function. The classifier is able to achieve an Area Under the Curve (AUC) score of 0.972 when using all available photometric observations to classify variable stars, supernovae, and active galactic nuclei. The RNN architecture allows us to classify incomplete light curves, and measure how performance improves as more observations are included. We also investigate the role that contextual information plays in producing reliable object classification.

astro-ph.IM↗

arXiv2021

Processing GOTO data with the Rubin Observatory LSST Science Pipelines II: Forced Photometry and light curves

We have adapted the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Science Pipelines to process data from the Gravitational-Wave Optical Transient Observer (GOTO) prototype. In this paper, we describe how we used the Rubin Observatory LSST Science Pipelines to conduct forced photometry measurements on nightly GOTO data. By comparing the photometry measurements of sources taken on multiple nights, we find that the precision of our photometry is typically better than 20~mmag for sources brighter than 16 mag. We also compare our photometry measurements against colour-corrected PanSTARRS photometry, and find that the two agree to within 10~mmag (1$σ$) for bright (i.e., $\sim14^{\rm th}$~mag) sources to 200~mmag for faint (i.e., $\sim18^{\rm th}$~mag) sources. Additionally, we compare our results to those obtained by GOTO's own in-house pipeline, {\sc gotophoto}, and obtain similar results. Based on repeatability measurements, we measure a $5σ$ L-band survey depth of between 19 and 20 magnitudes, depending on observing conditions. We assess, using repeated observations of non-varying standard SDSS stars, the accuracy of our uncertainties, which we find are typically overestimated by roughly a factor of two for bright sources (i.e., $<15^{\rm th}$~mag), but slightly underestimated (by roughly a factor of 1.25) for fainter sources ($>17^{\rm th}$~mag). Finally, we present lightcurves for a selection of variable sources, and compare them to those obtained with the Zwicky Transient Factory and GAIA. Despite the Rubin Observatory LSST Science Pipelines still undergoing active development, our results show that they are already delivering robust forced photometry measurements from GOTO data.

astro-ph.IM↗

arXiv2021

Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks -- sifting the GOTO candidate stream

Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional neural network that provides nuanced, uncertainty-aware classification of transient candidates in difference imaging, and demonstrate its application to the datastream from the GOTO wide-field optical survey. Not only are candidates assigned a well-calibrated probability of being real, but also an associated confidence that can be used to prioritise human vetting efforts and inform future model optimisation via active learning. To fully realise the potential of this architecture, we present a fully-automated training set generation method which requires no human labelling, incorporating a novel data-driven augmentation method to significantly improve the recovery of faint and nuclear transient sources. We achieve competitive classification accuracy (FPR and FNR both below 1%) compared against classifiers trained with fully human-labelled datasets, whilst being significantly quicker and less labour-intensive to build. This data-driven approach is uniquely scalable to the upcoming challenges and data needs of next-generation transient surveys. We make our data generation and model training codes available to the community.

astro-ph.IM↗

arXiv2020

Processing GOTO data with the Rubin Observatory LSST Science Pipelines I : Production of coadded frames

The past few decades have seen the burgeoning of wide field, high cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted by the Vera C. Rubin Observatory. So new is the field of systematic time-domain survey astronomy, however, that major scientific insights will continue to be obtained using smaller, more flexible systems than the LSST. One such example is the Gravitational-wave Optical Transient Observer (GOTO), whose primary science objective is the optical follow-up of Gravitational Wave events. The amount and rate of data production by GOTO and other wide-area, high-cadence surveys presents a significant challenge to data processing pipelines which need to operate in near real-time to fully exploit the time-domain. In this study, we adapt the Rubin Observatory LSST Science Pipelines to process GOTO data, thereby exploring the feasibility of using this "off-the-shelf" pipeline to process data from other wide-area, high-cadence surveys. In this paper, we describe how we use the LSST Science Pipelines to process raw GOTO frames to ultimately produce calibrated coadded images and photometric source catalogues. After comparing the measured astrometry and photometry to those of matched sources from PanSTARRS DR1, we find that measured source positions are typically accurate to sub-pixel levels, and that measured L-band photometries are accurate to $\sim50$ mmag at $m_L\sim16$ and $\sim200$ mmag at $m_L\sim18$. These values compare favourably to those obtained using GOTO's primary, in-house pipeline, GOTOPHOTO, in spite of both pipelines having undergone further development and improvement beyond the implementations used in this study. Finally, we release a generic "obs package" that others can build-upon should they wish to use the LSST Science Pipelines to process data from other facilities.

astro-ph.IM↗

arXiv2019

New constraints on the physical conditions in H$_2$-bearing GRB-host damped Lyman-$α$ absorbers

We report the detections of molecular hydrogen (H$_2$), vibrationally-excited H$_2$ (H$^*_2$), and neutral atomic carbon (CI), in two new afterglow spectra of GRBs\,181020A ($z=2.938$) and 190114A ($z=3.376$), observed with X-shooter at the Very Large Telescope (VLT). Both host-galaxy absorption systems are characterized by strong damped Lyman-$α$ absorbers (DLAs) and substantial amounts of molecular hydrogen with $\log N$(HI, H$_2$) = $22.20\pm 0.05,~20.40\pm 0.04$ (GRB\,181020A) and $\log N$(HI, H$_2$) = $22.15\pm 0.05,~19.44\pm 0.04$ (GRB\,190114A). The DLA metallicites, depletion levels and dust extinctions are [Zn/H] = $-1.57\pm 0.06$, [Zn/Fe] = $0.67\pm 0.03$, and $A_V = 0.27\pm 0.02$\,mag (GRB\,181020A) and [Zn/H] = $-1.23\pm 0.07$, [Zn/Fe] = $1.06\pm 0.08$, and $A_V = 0.36\pm 0.02$\,mag (GRB\,190114A). We then examine the molecular gas content of all known H$_2$-bearing GRB-DLAs and explore the physical conditions and characteristics of these systems. We confirm that H$_2$ is detected in all CI- and H$^*_2$-bearing GRB absorption systems, but that these rarer features are not necessarily detected in all GRB H$_2$ absorbers. We find that a large molecular fraction of $f_{\rm H_2} \gtrsim 10^{-3}$ is required for CI to be detected. The defining characteristic for H$^*_2$ to be present is less clear, though a large H$_2$ column density is an essential factor. We then derive the H$_2$ excitation temperatures of the molecular gas and find that they are relatively low with $T_{\rm ex} \approx 100 - 300$\,K, however, there could be evidence of warmer components populating the high-$J$ H$_2$ levels in GRBs\,181020A and 190114A. Finally, we demonstrate that the otherwise successful X-shooter GRB afterglow campaign is hampered by a significant dust bias excluding the most dust-obscured H$_2$ absorbers from identification [Abridged].

astro-ph.GA↗

arXiv2018

THESEUS: a key space mission concept for Multi-Messenger Astrophysics

The recent discovery of the electromagnetic counterpart of the gravitational wave source GW170817, has demonstrated the huge informative power of multi-messenger observations. During the next decade the nascent field of multi-messenger astronomy will mature significantly. Around 2030, third generation gravitational wave detectors will be roughly ten times more sensitive than the current ones. At the same time, neutrino detectors currently upgrading to multi km^3 telescopes, will include a 10 km^3 facility in the Southern hemisphere that is expected to be operational around 2030. In this review, we describe the most promising high frequency gravitational wave and neutrino sources that will be detected in the next two decades. In this context, we show the important role of the Transient High Energy Sky and Early Universe Surveyor (THESEUS), a mission concept proposed to ESA by a large international collaboration in response to the call for the Cosmic Vision Programme M5 missions. THESEUS aims at providing a substantial advancement in early Universe science as well as playing a fundamental role in multi-messenger and time-domain astrophysics, operating in strong synergy with future gravitational wave and neutrino detectors as well as major ground- and space-based telescopes. This review is an extension of the THESEUS white paper (Amati et al. 2017), also in light of the discovery of GW170817/GRB170817A that was announced on October 16th, 2017.

astro-ph.HE↗

arXiv2014

Herschel/PACS Observations of the Host Galaxy of GRB 031203

We present Herschel/PACS observations of the nearby (z=0.1055) dwarf galaxy that has hosted the long gamma ray burst (LGRB) 031203. Using the PACS data we have been able to place constraints on the dust temperature, dust mass, total infrared luminosity and infrared-derived star-formation rate (SFR) for this object. We find that the GRB host galaxy (GRBH) 031203 has a total infrared luminosity of 3x10^10 L_sun placing it in the regime of the IR-luminous galaxy population. Its dust temperature and specific SFR are comparable to that of many high-redshift (z=0.3-2.5) infrared (IR)-detected GRB hosts (T_dust>40K ; sSFR>10 Gyr^-1), however its dust-to-stellar mass ratio is lower than what is commonly seen in IR-luminous galaxies. Our results suggest that GRBH 031203 is undergoing a strong starburst episode and its dust properties are different to those of local dwarf galaxies within the same metallicity and stellar mass range. Furthermore, our measurements place it in a distinct class to the well studied nearby host of GRB 980425 (z=0.0085), confirming the notion that GRB host galaxies can span a large range in properties even at similar cosmological epochs, making LGRBs an ideal tool in selecting samples of star-forming galaxies up to high redshift.

astro-ph.GA↗

arXiv2009

Low-Resolution Spectroscopy of Gamma-ray Burst Optical Afterglows: Biases in the Swift Sample and Characterization of the Absorbers

(Abridged). We present a sample of 77 optical afterglows (OAs) of Swift detected GRBs for which spectroscopic follow-up observations have been secured. We provide linelists and equivalent widths for all detected lines redward of Ly-alpha. We discuss to what extent the current sample of Swift bursts with OA spectroscopy is a biased subsample of all Swift detected GRBs. For that purpose we define an X-ray selected sample of Swift bursts with optimal conditions for ground-based follow up from the period March 2005 to September 2008; 146 bursts fulfill our sample criteria. We derive the redshift distribution for this sample and conclude that less than 19% of Swift bursts are at z>7. We compare the high energy properties for three sub-samples of bursts in the sample: i) bursts with redshifts measured from OA spectroscopy, ii) bursts with detected OA, but no OA-based redshift, and iii) bursts with no detection of the OA. The bursts in group i) have significantly less excess X-ray absorption than bursts in the other two groups. In addition, the fraction of dark bursts is 14% in group i), 38% in group ii) and > 39% in group iii). From this we conclude that the sample of GRBs with OA spectroscopy is not representative for all Swift bursts, most likely due to a bias against the most dusty sight-lines. Finally, we characterize GRB absorption systems as a class and compare them to QSO absorption systems, in particular DLAs. On average GRB absorbers are characterized by significantly stronger EWs for HI as well as for both low and high ionization metal lines than what is seen in intervening QSO absorbers. Based on the z>2 bursts in the sample we place a 95% confidence upper limit of 7.5% on the mean escape fraction of ionizing photons from star-forming galaxies.

astro-ph.CO↗