arXiv subjects

Sara Webb

Publications and source records attributed to Sara Webb.

16 recordsLinked to original sources

arXiv2026

The Deeper, Wider, Faster programme's first DECam optical data release

The transient and variable optical sky is relatively poorly characterised on fast ($<$1$\,$hr) timescales. With the Dark Energy Camera (DECam), the Deeper, Wider, Faster programme (DWF) probes a unique parameter space with its deep (median of $g\sim22.2$ AB mag), minute-cadence imaging. In this work, we present DWF's first data release which comprises high cadence photometry extracted from $\sim$12000 images and 166 hours of telescope time. We present a novel data processing pipeline, $\texttt{dwf-postpipe}$, developed to identify sources and extract their light curves. The accuracy of the photometry is assessed by cross-matching to public catalogues. In addition, we injected a population of synthetic GRB afterglows into a subset of the DWF DECam imaging to compare the efficiency of our pipeline with a standard difference imaging approach. Both pipelines show performance and reliably recover injected transients with peak magnitudes $g<22$ AB mag with an efficiency of $97.24^{+0.7}_{-1.0}$ percent for \texttt{dwf-postpipe} and $96.14^{+0.9}_{-1.1}$ percent for a difference imaging approach. However, we find that $\texttt{dwf-postpipe}$ is less likely to recover transients appearing in galaxies that are brighter or comparable in brightness to the transient itself. To demonstrate the power of the data in this release, we conduct a search for uncatalogued variable stars in a single night of DWF DECam imaging and find ten pulsating variables, two eclipsing binaries and one ZZ ceti. We also conduct a search for variable phenomena in the Chandra Deep Field South, a Rubin deep drilling field, and identify two flares from likely UV ceti type stars.

astro-ph.HE↗

arXiv2025

First Temperature Profile of a Stellar Flare using Differential Chromatic Refraction

We present the first derivation of a stellar flare temperature profile from single-band photometry. Stellar flare DWF030225.574-545707.45129 was detected in 2015 by the Dark Energy Camera as part of the Deeper, Wider, Faster Programme. The brightness ($\Delta m_g = -6.12$) of this flare, combined with the high air mass ($1.45 \lesssim X \lesssim 1.75$) and blue filter (DES $g$, 398-548 nm) in which it was observed, provided ideal conditions to measure the zenith-ward apparent motion of the source due to differential chromatic refraction (DCR) and, from that, infer the effective temperature of the event. We model the flare's spectral energy distribution as a blackbody to produce the constraints on flare temperature and geometric properties derived from single-band photometry. We additionally demonstrate how simplistic assumptions on the flaring spectrum, as well as on the evolution of flare geometry, can result in solutions that overestimate effective temperature. Exploiting DCR enables studying chromatic phenomena with ground-based astrophysical surveys and stellar flares on M-dwarfs are a particularly enticing target for such studies due to their ubiquity across the sky, and the heightened color contrast between their red quiescent photospheres and the blue flare emission. Our novel method will enable similar temperature constraints for large sample of objects in upcoming photometric surveys like the Vera C. Rubin Legacy Survey of Space and Time.

astro-ph.SR↗

arXiv2025

A Lightweight Large Vision-language Model for Multimodal Medical Images

Medical Visual Question Answering (VQA) enhances clinical decision-making by enabling systems to interpret medical images and answer clinical queries. However, developing efficient, high-performance VQA models is challenging due to the complexity of medical imagery and diverse modalities. In this paper, we introduce a lightweight, multimodal VQA model integrating BiomedCLIP for image feature extraction and LLaMA-3 for text processing. Designed for medical VQA tasks, our model achieves state-of-the-art performance on the OmniMedVQA dataset. With approximately 8 billion parameters, it requires only two NVIDIA 40 GB A100 GPUs, demonstrating superior efficiency over larger models. Our results show 73.4% accuracy for open-end questions, surpassing existing models and validating its potential for real-world medical applications. Key contributions include a specialized multimodal VQA model, a resource-efficient architecture, and strong performance in answering open-ended clinical questions.

cs.CV↗

arXiv2024

GRB$\,$220831A: a hostless, intermediate Gamma-ray burst with an unusual optical afterglow

GRB$\,$220831A is a gamma-ray burst (GRB) with a duration and spectral peak energy that places it at the interface between the distribution of long-soft and short-hard GRBs. In this paper, we present the multi-wavelength follow-up campaign to GRB$\,$220831A and its optical, near-infrared, X-ray and radio counterparts. Our deep optical and near-infrared observations do not reveal an underlying host galaxy, and establish that GRB$\,$220831A is observationally hostless to depth, $m_i\gtrsim26.6$ AB mag. Based on the Amati relation and the non-detection of an accompanying supernova, we find that this GRB is most likely to have originated from a collapsar at $z>2$, but it could also possibly be a compact object merger at $z<0.4$ with a large separation distance from its host galaxy. Regardless of its origin, we show that its optical and near-infrared counterpart departs from the evolution expected from a forward shock dominated synchrotron afterglow, exhibiting a steep post-break temporal powerlaw index of $-3.83^{+0.62}_{-0.79}$, too steep to be the jet-break. By analysing a range of models, we find that the observed steep departure from forward shock closure relations is likely due to an internal process producing either a flare or a plateau.

astro-ph.HE↗

arXiv2024

How Do Observational Astronomers Learn to Inspect Imaging Data

Astronomy is entering an unprecedented era of data collection. Upcoming large surveys will gather more data than ever before, generated at rates requiring real-time decision making. Looking ahead, it is inevitable that astronomers will need to rely more heavily on automated processes. Indeed, some instances have already arisen wherein the majority of the inspection process is automated. Visual discovery, performed traditionally by humans, is one key area where automation is now being integrated rapidly. Visual discovery comprises two aspects: (1) visual inspection, the skill associated with examining an image to identify areas or objects of interest; and (2) visual interpretation, the knowledge associated with the classification of the objects or features. Both skills and knowledge are vital for humans to perform visual discovery, however, there appears to have been limited investigation into how the skill of visual inspection in astronomy is acquired. We report on a survey of 70 professional observational astronomers, at various career stages and from different geographical regions. We found that between 63% and 73% of the astronomers surveyed had received formal and$/$or informal training in visual inspection of images, although formal training (21%) was less common than informal training (60%). Surprisingly, out of the 37% who did not recall having received training in visual inspection, 29% (20 astronomers) indicated that they provided training to others. This suggests the emergence of `expertise without precedent' where a first expert in the field provides a new way of achieving a task. These results, paired with a set of three pilot interviews, present a touchstone against which the training of future observational astronomers can be compared.

astro-ph.IM↗

arXiv2024

A Fast-cadenced Search for Gamma-Ray Burst Orphan Afterglows with the Deeper, Wider, Faster Programme

The relativistic outflows that produce Long GRBs (LGRBs) can be described by a structured jet model where prompt $\gamma$-ray emission is restricted to a narrow region in the jet's core. Viewing the jet off-axis from the core, a population of afterglows without an associated GRB detection can be predicted. In this work, we conduct an archival search for these `orphan' afterglows (OAs) with minute-cadence, deep ($g\sim23$) data from the Dark Energy Camera (DECam) taken as part of the Deeper, Wider, Faster programme (DWF). We introduce a method to select fast-evolving OA candidates within DWF data that comprises a machine learning model, based on a realistic synthetic population of OAs. Using this classifier, we recover 51 OA candidates. Of these candidates, 42 are likely flare events from M-class stars. The remaining nine possess quiescent, coincident sources in archival data with angular profiles consistent with a star and are inconsistent with the expected population of LGRB host galaxies. We therefore conclude that these are likely Galactic events. We calculate an upper limit on the rate of OAs down to $g<22$ AB mag of 7.46\,deg$^{-2}$yr$^{-1}$ using our criteria and constrain possible jet structures. We also place an upper limit of the characteristic angle between the $\gamma$-ray emitting region and the jet's half opening angle. For a smooth power-law and a power-law with core jet model respectively, these values are $58.3^{\circ}$ and $56.6^{\circ}$, for a power-law index of 0.8 and $75.3^{\circ}$ and $76.8^{\circ}$ for a power-law index of 1.2.

astro-ph.HE↗

arXiv2021

Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data

Astronomical transients are stellar objects that become temporarily brighter on various timescales and have led to some of the most significant discoveries in cosmology and astronomy. Some of these transients are the explosive deaths of stars known as supernovae while others are rare, exotic, or entirely new kinds of exciting stellar explosions. New astronomical sky surveys are observing unprecedented numbers of multi-wavelength transients, making standard approaches of visually identifying new and interesting transients infeasible. To meet this demand, we present two novel methods that aim to quickly and automatically detect anomalous transient light curves in real-time. Both methods are based on the simple idea that if the light curves from a known population of transients can be accurately modelled, any deviations from model predictions are likely anomalies. The first approach is a probabilistic neural network built using Temporal Convolutional Networks (TCNs) and the second is an interpretable Bayesian parametric model of a transient. We show that the flexibility of neural networks, the attribute that makes them such a powerful tool for many regression tasks, is what makes them less suitable for anomaly detection when compared with our parametric model.

cs.LG↗

arXiv2021

Real-Time Detection of Anomalies in Large-Scale Transient Surveys

New time-domain surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will observe millions of transient alerts each night, making standard approaches of visually identifying new and interesting transients infeasible. We present two novel methods of automatically detecting anomalous transient light curves in real-time. Both methods are based on the simple idea that if the light curves from a known population of transients can be accurately modelled, any deviations from model predictions are likely anomalies. The first modelling approach is a probabilistic neural network built using Temporal Convolutional Networks (TCNs) and the second is an interpretable Bayesian parametric model of a transient. We demonstrate our methods' ability to provide anomaly scores as a function of time on light curves from the Zwicky Transient Facility. We show that the flexibility of neural networks, the attribute that makes them such a powerful tool for many regression tasks, is what makes them less suitable for anomaly detection when compared with our parametric model. The parametric model is able to identify anomalies with respect to common supernova classes with high precision and recall scores, achieving area under the precision-recall curves (AUCPR) above 0.79 for most rare classes such as kilonovae, tidal disruption events, intermediate luminosity transients, and pair-instability supernovae. Our ability to identify anomalies improves over the lifetime of the light curves. Our framework, used in conjunction with transient classifiers, will enable fast and prioritised followup of unusual transients from new large-scale surveys.

astro-ph.IM↗

arXiv2021

Finding Fast Transients in Real Time Using Novel Light Curve Analysis Algorithm

The current data acquisition rate of astronomical transient surveys and the promise for significantly higher rates during in the next decade necessitate the development of novel approaches to analyze astronomical data sets and promptly detect objects of interest. The Deeper, Wider, Faster (DWF) program is a survey focused on the identification of fast evolving transients, such as fast radio bursts, gamma-ray bursts, and supernova shock breakouts. It employs a multi-frequency simultaneous coverage of the same part of the sky over several orders of magnitude. Using the Dark Energy Camera mounted on the 4-meter Blanco telescope, DWF captures a 20 second g-band exposure every minute, at a typical seeing of ~ 1" and an airmass of ~ 1.5. These optical data are collected simultaneously with observations conducted over the entire electromagnetic spectrum - from radio to gamma-rays - as well as cosmic ray observations. In this paper, we present a novel real-time light curve analysis algorithm, designed to detect transients in the DWF optical data; this algorithm functions independently from, or in conjunction with, image subtraction. We present a sample of fast transients detected by our algorithm, as well as a false-positive analysis. Our algorithm is customizable and can be tuned to be sensitive to transients evolving over different timescales and flux ranges.

astro-ph.IM↗

arXiv2021

The Deeper, Wider, Faster Program: Exploring stellar flare activity with deep, fast cadenced DECam imaging via machine learning

We present our 500 pc distance-limited study of stellar fares using the Dark Energy Camera as part of the Deeper, Wider, Faster Program. The data was collected via continuous 20-second cadence g band imaging and we identify 19,914 sources with precise distances from Gaia DR2 within twelve, ~3 square-degree, fields over a range of Galactic latitudes. An average of ~74 minutes is spent on each field per visit. All light curves were accessed through a novel unsupervised machine learning technique designed for anomaly detection. We identify 96 flare events occurring across 80 stars, the majority of which are M dwarfs. Integrated are energies range from $\sim 10^{31}-10^{37}$ erg, with a proportional relationship existing between increased are energy with increased distance from the Galactic plane, representative of stellar age leading to declining yet more energetic are events. In agreement with previous studies we observe an increase in flaring fraction from M0 -> M6 spectral types. Furthermore, we find a decrease in the flaring fraction of stars as vertical distance from the galactic plane is increased, with a steep decline present around ~100 pc. We find that ~70% of identified flares occur on short timescales of ~8 minutes. Finally we present our associated are rates, finding a volumetric rate of $2.9 \pm 0.3 \times 10^{-6}$ flares pc$^{-3}$ hr$^{-1}$.

astro-ph.SR↗

arXiv2020

Unsupervised machine learning for transient discovery in Deeper, Wider, Faster light curves

Identification of anomalous light curves within time-domain surveys is often challenging. In addition, with the growing number of wide-field surveys and the volume of data produced exceeding astronomers ability for manual evaluation, outlier and anomaly detection is becoming vital for transient science. We present an unsupervised method for transient discovery using a clustering technique and the Astronomaly package. As proof of concept, we evaluate 85553 minute-cadenced light curves collected over two 1.5 hour periods as part of the Deeper, Wider, Faster program, using two different telescope dithering strategies. By combining the clustering technique HDBSCAN with the isolation forest anomaly detection algorithm via the visual interface of Astronomaly, we are able to rapidly isolate anomalous sources for further analysis. We successfully recover the known variable sources, across a range of catalogues from within the fields, and find a further 7 uncatalogued variables and two stellar flare events, including a rarely observed ultra fast flare (5 minute) from a likely M-dwarf.

astro-ph.IM↗

arXiv2020

Kilonova Luminosity Function Constraints based on Zwicky Transient Facility Searches for 13 Neutron Star Mergers

We present a systematic search for optical counterparts to 13 gravitational wave (GW) triggers involving at least one neutron star during LIGO/Virgo's third observing run. We searched binary neutron star (BNS) and neutron star black hole (NSBH) merger localizations with the Zwicky Transient Facility (ZTF) and undertook follow-up with the Global Relay of Observatories Watching Transients Happen (GROWTH) collaboration. The GW triggers had a median localization of 4480 deg^2, median distance of 267 Mpc and false alarm rates ranging from 1.5 to 1e-25 per yr. The ZTF coverage had a median enclosed probability of 39%, median depth of 20.8mag, and median response time of 1.5 hr. The O3 follow-up by the GROWTH team comprised 340 UVOIR photometric points, 64 OIR spectra, and 3 radio. We find no promising kilonova (radioactivity-powered counterpart) and we convert the upper limits to constrain the underlying kilonova luminosity function. Assuming that all kilonovae are at least as luminous as GW170817 at discovery (-16.1mag), we calculate our joint probability of detecting zero kilonovae is only 4.2%. If we assume that all kilonovae are brighter than -16.6mag (extrapolated peak magnitude of GW170817) and fade at 1 mag/day (similar to GW170817), the joint probability of zero detections is 7%. If we separate the NSBH and BNS populations, the joint probability of zero detections, assuming all kilonovae are brighter than -16.6mag, is 9.7% for NSBH and 7.9% for BNS mergers. Moreover, <57% (<89%) of putative kilonovae could be brighter than -16.6mag assuming flat (fading) evolution, at 90% confidence. If we further account for the online terrestrial probability for each GW trigger, we find that <68% of putative kilonovae could be brighter than -16.6mag. Comparing to model grids, we find that some kilonovae must have Mej < 0.03 Msun or Xlan>1e-4 or phi>30deg to be consistent with our limits. (Abridged)

astro-ph.HE↗

arXiv2019

GROWTH on S190814bv: Deep Synoptic Limits on the Optical/Near-Infrared Counterpart to a Neutron Star-Black Hole Merger

On 2019 August 14, the Advanced LIGO and Virgo interferometers detected the high-significance gravitational wave (GW) signal S190814bv. The GW data indicated that the event resulted from a neutron star--black hole (NSBH) merger, or potentially a low-mass binary black hole merger. Due to the low false alarm rate and the precise localization (23 deg$^2$ at 90\%), S190814bv presented the community with the best opportunity yet to directly observe an optical/near-infrared counterpart to a NSBH merger. To search for potential counterparts, the GROWTH collaboration performed real-time image subtraction on 6 nights of public Dark Energy Camera (DECam) images acquired in the three weeks following the merger, covering $>$98\% of the localization probability. Using a worldwide network of follow-up facilities, we systematically undertook spectroscopy and imaging of optical counterpart candidates. Combining these data with a photometric redshift catalog, we ruled out each candidate as the counterpart to S190814bv and we placed deep, uniform limits on the optical emission associated with S190814bv. For the nearest consistent GW distance, radiative transfer simulations of NSBH mergers constrain the ejecta mass of S190814bv to be $M_\mathrm{ej} < 0.04$~$M_{\odot}$ at polar viewing angles, or $M_\mathrm{ej} < 0.03$~$M_{\odot}$ if the opacity is $\kappa < 2$~cm$^2$g$^{-1}$. Assuming a tidal deformability for the neutron star at the high end of the range compatible with GW170817 results, our limits would constrain the BH spin component aligned with the orbital momentum to be $ \chi < 0.7$ for mass ratios $Q < 6$, with weaker constraints for more compact neutron stars. We publicly release the photometry from this campaign at http://www.astro.caltech.edu/~danny/static/s190814bv.

astro-ph.HE↗

arXiv2019

GROWTH on S190510g: DECam Observation Planning and Follow-Up of a Distant Binary Neutron Star Merger Candidate

The first two months of the third Advanced LIGO and Virgo observing run (2019 April-May) showed that distant gravitational wave (GW) events can now be readily detected. Three candidate mergers containing neutron stars (NS) were reported in a span of 15 days, all likely located more than 100 Mpc away. However, distant events such as the three new NS mergers are likely to be coarsely localized, which highlights the importance of facilities and scheduling systems that enable deep observations over hundreds to thousands of square degrees to detect the electromagnetic counterparts. On 2019-05-10 02:59:39.292 UT the GW candidate S190510g was discovered and initially classified as a BNS merger with 98% probability. The GW event was localized within an area of 3462 deg2, later refined to 1166 deg2 (90%) at a distance of 227 +- 92 Mpc. We triggered Target of Opportunity observations with the Dark Energy Camera (DECam), a wide-field optical imager mounted at the prime focus of the 4m Blanco Telescope at CTIO in Chile. This Letter describes our DECam observations and our real-time analysis results, focusing in particular on the design and implementation of the observing strategy. Within 24 hours of the merger time, we observed 65% of the total enclosed probability of the final skymap with an observing efficiency of 94%. We identified and publicly announced 13 candidate counterparts. S190510g was re-classified 1.7 days after the merger, after our observations were completed, with a "binary neutron star merger" probability reduced from 98% to 42% in favor of a "terrestrial" classification.

astro-ph.HE↗

arXiv2019

A strategy for LSST to unveil a population of kilonovae without gravitational-wave triggers

We present a cadence optimization strategy to unveil a large population of kilonovae using optical imaging alone. These transients are generated during binary neutron star and potentially neutron star-black hole mergers and are electromagnetic counterparts to gravitational-wave signals detectable in nearby events with Advanced LIGO, Advanced Virgo, and other interferometers that will come online in the near future. Discovering a large population of kilonovae will allow us to determine how heavy element production varies with the intrinsic parameters of the merger and across cosmic time. The rate of binary neutron star mergers is still uncertain, but only few (less than 15) events with associated kilonovae may be detectable per year within the horizon of next-generation ground-based interferometers. The rapid evolution (hours to days) at optical/infrared wavelengths, relatively low luminosity, and the low volumetric rate of kilonovae makes their discovery difficult, especially during blind surveys of the sky. We propose future large surveys to adopt a rolling cadence in which g-i observations are taken nightly for blocks of 10 consecutive nights. With the current baseline2018a cadence designed for the Large Synoptic Survey Telescope (LSST), less than 7.5 poorly-sampled kilonovae are expected to be detected in both the Wide Fast Deep (WFD) and Deep Drilling Fields (DDF) surveys per year, under optimistic assumptions on their rate, duration, and luminosity. We estimate the proposed strategy to return up to about 272 GW170817-like kilonovae throughout the LSST WFD survey, discovered independently from gravitational-wave triggers.

astro-ph.IM↗

arXiv2019

Probing the extragalactic fast transient sky at minute timescales with DECam

Searches for optical transients are usually performed with a cadence of days to weeks, optimised for supernova discovery. The optical fast transient sky is still largely unexplored, with only a few surveys to date having placed meaningful constraints on the detection of extragalactic transients evolving at sub-hour timescales. Here, we present the results of deep searches for dim, minute-timescale extragalactic fast transients using the Dark Energy Camera, a core facility of our all-wavelength and all-messenger Deeper, Wider, Faster programme. We used continuous 20s exposures to systematically probe timescales down to 1.17 minutes at magnitude limits $g > 23$ (AB), detecting hundreds of transient and variable sources. Nine candidates passed our strict criteria on duration and non-stellarity, all of which could be classified as flare stars based on deep multi-band imaging. Searches for fast radio burst and gamma-ray counterparts during simultaneous multi-facility observations yielded no counterparts to the optical transients. Also, no long-term variability was detected with pre-imaging and follow-up observations using the SkyMapper optical telescope. We place upper limits for minute-timescale fast optical transient rates for a range of depths and timescales. Finally, we demonstrate that optical $g$-band light curve behaviour alone cannot discriminate between confirmed extragalactic fast transients such as prompt GRB flashes and Galactic stellar flares.

astro-ph.HE↗