arXiv subjects

P. Chote

Publications and source records attributed to P. Chote.

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

The Gravitational-wave Optical Transient Observer (GOTO) data pipeline and workflow for transient discovery

Wide-field and high-cadence sky surveys are the first step in the chain of discovery and characterisation of astrophysical transients such as supernovae, kilonovae, and tidal disruption events, each linked to the varied demise of stellar systems. The Gravitational-wave Optical Transient Observer (GOTO) is a telescope array of thirty-two 40 cm unit telescopes split over two almost antipodal sites. It performs a regular time-domain sky-survey in the optical to ~20 mag in addition to immediate scheduling of follow-up observations at the locations of external multi-wavelength and -messenger triggers. To facilitate the timely recovery of optical counterparts to these triggers, as well as the presence of serendipitous discoveries of astrophysical transients in the regular sky-survey, a low-latency data pipeline and workflow was developed. The implementation of this workflow is described herein and the quality of GOTO data delivered by it assessed, alongside its performance for prompt transient recovery. Utilising difference image analysis to identify candidate discoveries, the process is typically complete ~7 minutes after shutter close on the telescope. We further describe later processing of these candidates -- both automated and human-in-the-loop -- including reporting to the wider community and the triggering of more detailed observations, with a focus on immediate, intra-night characterisation. The workflow is meeting the needs of GOTO to promptly discover, report and characterise infant transients. Nevertheless, areas for further development and improvements are also highlighted.

astro-ph.IM↗

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↗

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

Short timescale imaging polarimetry of geostationary satellite Thor-6: the nature of micro-glints

Large constellations of orbiting communication satellites will become an important source of noise for present and future astronomical observatories. Mitigation measures rely on high quality predictive models of the position and expected brightness of these objects. Optical linear imaging polarimetry holds promise as a quantitative tool to improve our understanding of the physics of reflection of sunlight off satellite components and through which models of expected brightness can be improved. We present the first simultaneous short-timescale linear polarimetry and optical photometry observations of a geostationary satellite, using the new MOPTOP imaging polarimeter on the 2m Liverpool Telescope. Our target, telecommunication satellite Thor-6, shows prominent short timescale glint-like features in the lightcurve, some as short as seconds. Our polarimetric observations overlap with several of these micro-glints, and have the cadence required to resolve them. We find that the polarisation lightcurve is remarkably smooth, the short time scale glints are not seen to produce strong polarimetric features in our observation. We show how short timescale polarimetry can further constrain the properties of the components responsible for these micro-glints.

astro-ph.EP↗

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$\sigma$) 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 $5\sigma$ 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↗

arXiv2021

NGTS and HST insights into the long period modulation in GW Librae

Light curves of the accreting white dwarf pulsator GW Librae spanning a 7.5 month period in 2017 were obtained as part of the Next Generation Transit Survey. This data set comprises 787 hours of photometry from 148 clear nights, allowing the behaviour of the long (hours) and short period (20min) modulation signals to be tracked from night to night over a much longer observing baseline than has been previously achieved. The long period modulations intermittently detected in previous observations of GW Lib are found to be a persistent feature, evolving between states with periods ~83min and 2-4h on time-scales of several days. The 20min signal is found to have a broadly stable amplitude and frequency for the duration of the campaign, but the previously noted phase instability is confirmed. Ultraviolet observations obtained with the Cosmic Origin Spectrograph onboard the Hubble Space Telescope constrain the ultraviolet-to-optical flux ratio to ~5 for the 4h modulation, and <=1 for the 20min period, with caveats introduced by non-simultaneous observations. These results add further observational evidence that these enigmatic signals must originate from the white dwarf, highlighting our continued gap in theoretical understanding of the mechanisms that drive them.

astro-ph.SR↗

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↗

arXiv2020

V1460 Her: A fast spinning white dwarf accreting from an evolved donor star

We present time-resolved optical and ultraviolet spectroscopy and photometry of V1460~Her, an eclipsing cataclysmic variable with a 4.99\,h orbital period and an overluminous K5-type donor star. The optical spectra show emission lines from an accretion disc along with absorption lines from the donor. We use these to measure radial velocities, which, together with constraints upon the orbital inclination from photometry, imply masses of $M_1=0.869\pm0.006\,\mathrm{M}_\odot$ and $M_2=0.295\pm0.004\,\mathrm{M}_\odot$ for the white dwarf and the donor. The radius of the donor, $R_2=0.43\pm0.002\,\mathrm{R}_\odot$, is $\approx 50$ per cent larger than expected given its mass, while its spectral type is much earlier than the M3.5 type that would be expected from a main sequence star with a similar mass. HST spectra show strong $\mathrm{N{\small V}}$ 1240 A emission but no $\mathrm{C{\small IV}}$ 1550 A emission, evidence for CNO-processed material. The donor is therefore a bloated, over-luminous remnant of a thermal-timescale stage of high mass transfer and has yet to re-establish thermal equilibrium. Remarkably, the HST ultraviolet data also show a strong 30 per cent peak-to-peak, $38.9\,$s pulsation that we explain as being due to the spin of the white dwarf, potentially putting V1460 Her in a similar category to the propeller system AE Aqr in terms of its spin frequency and evolutionary path. AE Aqr also features a post-thermal timescale mass donor, and V1460 Her may therefore be its weak magnetic field analogue since the accretion disc is still present, with the white dwarf spin-up a result of a recent high accretion rate.

astro-ph.SR↗

arXiv2020

Searching for Electromagnetic Counterparts to Gravitational-wave Merger Events with the Prototype Gravitational-wave Optical Transient Observer (GOTO-4)

We report the results of optical follow-up observations of 29 gravitational-wave triggers during the first half of the LIGO-Virgo Collaboration (LVC) O3 run with the Gravitational-wave Optical Transient Observer (GOTO) in its prototype 4-telescope configuration (GOTO-4). While no viable electromagnetic counterpart candidate was identified, we estimate our 3D (volumetric) coverage using test light curves of on- and off-axis gamma-ray bursts and kilonovae. In cases where the source region was observable immediately, GOTO-4 was able to respond to a GW alert in less than a minute. The average time of first observation was $8.79$ hours after receiving an alert ($9.90$ hours after trigger). A mean of $732.3$ square degrees were tiled per event, representing on average $45.3$ per cent of the LVC probability map, or $70.3$ per cent of the observable probability. This coverage will further improve as the facility scales up alongside the localisation performance of the evolving gravitational-wave detector network. Even in its 4-telescope prototype configuration, GOTO is capable of detecting AT2017gfo-like kilonovae beyond 200~Mpc in favourable observing conditions. We cannot currently place meaningful electromagnetic limits on the population of distant ($\hat{D}_L = 1.3$~Gpc) binary black hole mergers because our test models are too faint to recover at this distance. However, as GOTO is upgraded towards its full 32-telescope, 2 node (La Palma \& Australia) configuration, it is expected to be sufficiently sensitive to cover the predicted O4 binary neutron star merger volume, and will be able to respond to both northern and southern triggers.

astro-ph.HE↗

arXiv2018

Fast spectrophotometry of WD 1145+017

WD 1145+017 is currently the only white dwarf known to exhibit periodic transits of planetary debris as well as absorption lines from circumstellar gas. We present the first simultaneous fast optical spectrophotometry and broad-band photometry of the system, obtained with the Gran Telescopio Canarias (GTC) and the Liverpool Telescope (LT), respectively. The observations spanned $5.5$ h, somewhat longer than the $4.5$-h orbital period of the debris. Dividing the GTC spectrophotometry into five wavelength bands reveals no significant colour differences, confirming grey transits in the optical. We argue that absorption by an optically thick structure is a plausible alternative explanation for the achromatic nature of the transits that can allow the presence of small-sized ($\sim\mu$m) particles. The longest ($87$ min) and deepest ($50$ per cent attenuation) transit recorded in our data exhibits a complex structure around minimum light that can be well modelled by multiple overlapping dust clouds. The strongest circumstellar absorption line, Fe II $\lambda$5169, significantly weakens during this transit, with its equivalent width reducing from a mean out-of-transit value of $2$ \AA\ to $1$ \AA\ in-transit, supporting spatial correlation between the circumstellar gas and dust. Finally, we made use of the Gaia Data Release 2 and archival photometry to determine the white dwarf parameters. Adopting a helium-dominated atmosphere containing traces of hydrogen and metals, and a reddening $E(B-V)=0.01$ we find $T_\mathrm{eff}=15\,020 \pm 520$ K, $\log g=8.07\pm0.07$, corresponding to $M_\mathrm{WD}=0.63\pm0.05\ \mbox{$\mathrm{M}_{\odot}$}$ and a cooling age of $224\pm30$ Myr.

astro-ph.SR↗

arXiv2018

VLA Radio Observations of AR Sco

AR Scorpii is unique amongst known white dwarf binaries in showing powerful pulsations extending to radio frequencies. Here we aim to investigate the multi-frequency radio emission of AR Sco in detail, in order to constrain its origin and emission mechanisms. We present interferometric radio frequency imaging of AR Sco at 1.5, 5 and 9 GHz, analysing the total flux and polarization behaviour of this source at high time resolution (10, 3 and 3 s), across a full 3.6 hr orbital period in each band. We find strong modulation of the radio flux on the orbital period and the orbital sideband of the white dwarf's spin period (also known as the "beat" period). This indicates that, like the optical flux, the radio flux arises predominantly from on or near the inner surface of the M-dwarf companion star. The beat-phase pulsations of AR Sco decrease in strength with decreasing frequency. They are strongest at 9 GHz and at an orbital phase ~0.5. Unlike the optical emission from this source, radio emission from AR Sco shows weak linear polarization but very strong circular polarization, reaching ~30% at an orbital phase ~0.8. We infer the probable existence of a non-relativistic cyclotron emission component, which dominates at low radio frequencies. Given the required magnetic fields, this also likely arises from on or near the M-dwarf.

astro-ph.SR↗

arXiv2017

White Dwarf Rotation as a Function of Mass and a Dichotomy of Mode Linewidths: Kepler Observations of 27 Pulsating DA White Dwarfs Through K2 Campaign 8

We present photometry and spectroscopy for 27 pulsating hydrogen-atmosphere white dwarfs (DAVs, a.k.a. ZZ Ceti stars) observed by the Kepler space telescope up to K2 Campaign 8, an extensive compilation of observations with unprecedented duration (>75 days) and duty cycle (>90%). The space-based photometry reveals pulsation properties previously inaccessible to ground-based observations. We observe a sharp dichotomy in oscillation mode linewidths at roughly 800 s, such that white dwarf pulsations with periods exceeding 800 s have substantially broader mode linewidths, more reminiscent of a damped harmonic oscillator than a heat-driven pulsator. Extended Kepler coverage also permits extensive mode identification: We identify the spherical degree of 61 out of 154 unique radial orders, providing direct constraints of the rotation period for 20 of these 27 DAVs, more than doubling the number of white dwarfs with rotation periods determined via asteroseismology. We also obtain spectroscopy from 4m-class telescopes for all DAVs with Kepler photometry. Using these homogeneously analyzed spectra we estimate the overall mass of all 27 DAVs, which allows us to measure white dwarf rotation as a function of mass, constraining the endpoints of angular momentum in low- and intermediate-mass stars. We find that 0.51-to-0.73-solar-mass white dwarfs, which evolved from 1.7-to-3.0-solar-mass ZAMS progenitors, have a mean rotation period of 35 hr with a standard deviation of 28 hr, with notable exceptions for higher-mass white dwarfs. Finally, we announce an online repository for our Kepler data and follow-up spectroscopy, which we collect at http://www.k2wd.org.

astro-ph.SR↗