arXiv subjects

T. Heikkilä

Publications and source records attributed to T. Heikkilä.

11 recordsLinked to original sources

arXiv2024

A study in scarlet -- I. Photometric properties of a sample of Intermediate Luminosity Red Transients

We investigate the photometric characteristics of a sample of Intermediate Luminosity Red Transients (ILRTs), a class of elusive objects with peak luminosity between that of classical novae and standard supernovae. We present the multi-wavelength photometric follow-up of four ILRTs, namely NGC 300 2008OT-1, AT 2019abn, AT 2019ahd and AT 2019udc. Through the analysis and modelling of their spectral energy distribution and bolometric light curves we infer the physical parameters associated with these transients. All four objects display a single peaked light curve which ends in a linear decline in magnitudes at late phases. A flux excess with respect to a single black body emission is detected in the infrared domain for three objects in our sample, a few months after maximum. This feature, commonly found in ILRTs, is interpreted as a sign of dust formation. Mid infrared monitoring of NGC 300 2008OT-1 761 days after maximum allows us to infer the presence of $\sim$10$^{-3}$-10$^{-5}$ M$_{\odot}$ of dust, depending on the chemical composition and the grain size adopted. The late time decline of the bolometric light curves of the considered ILRTs is shallower than expected for $^{56}$Ni decay, hence requiring an additional powering mechanism. James Webb Space Telescope observations of AT 2019abn prove that the object has faded below its progenitor luminosity in the mid-infrared domain, five years after its peak. Together with the disappearance of NGC 300 2008OT-1 in Spitzer images seven years after its discovery, this supports the terminal explosion scenario for ILRTs. With a simple semi-analytical model we try to reproduce the observed bolometric light curves in the context of few M$_{\odot}$ of material ejected at few 10$^{3}$ km s$^{-1}$ and enshrouded in an optically thick circumstellar medium.

astro-ph.SR↗

arXiv2024

A study in scarlet -- II. Spectroscopic properties of a sample of Intermediate Luminosity Red Transients

We investigate the spectroscopic characteristics of Intermediate Luminosity Red Transients (ILRTs), a class of elusive objects with peak luminosity between that of classical novae and standard supernovae. We present the extensive optical and near-infrared (NIR) spectroscopic monitoring of four ILRTs, namely NGC 300 2008OT-1, AT 2019abn, AT 2019ahd and AT 2019udc. First we focus on the evolution of the most prominent spectral features observed in the low resolution spectra, then we discuss more in detail the high resolution spectrum collected for NGC 300 2008OT-1 with the Very Large Telescope equipped with UVES. Finally we analyse late time spectra of NGC 300 2008OT-1 and AT 2019ahd through comparisons with both synthetic and observed spectra. Balmer and Ca lines dominate the optical spectra, revealing the presence of slowly moving circumstellar medium (CSM) around the objects. The line luminosity of H$α$, H$β$ and Ca II NIR triplet presents a double peaked evolution with time, possibly indicative of interaction between fast ejecta and the slow CSM. The high resolution spectrum of NGC 300 2008OT-1 reveals a complex circumstellar environment, with the transient being surrounded by a slow ($\sim$30 km s$^{-1}$) progenitor wind. At late epochs, optical spectra of NGC 300 2008OT-1 and AT 2019ahd show broad ($\sim$2500 km s$^{-1}$) emission features at $\sim$6170 A and $\sim$7000 A which are unprecedented for ILRTs. We find that these lines originate most likely from the blending of several narrow lines, possibly of iron-peak elements.

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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↗

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↗

arXiv2020

Observational constraints on the optical and near-infrared emission from the neutron star-black hole binary merger S190814bv

On 2019 August 14, the LIGO and Virgo interferometers detected a high-significance event labelled S190814bv. Preliminary analysis of the GW data suggests that the event was likely due to the merger of a compact binary system formed by a BH and a NS. ElectromagNetic counterparts of GRAvitational wave sources at the VEry Large Telescope (ENGRAVE) collaboration members carried out an intensive multi-epoch, multi-instrument observational campaign to identify the possible optical/near infrared counterpart of the event. In addition, the ATLAS, GOTO, GRAWITA-VST, Pan-STARRS and VINROUGE projects also carried out a search on this event. Our observations allow us to place limits on the presence of any counterpart and discuss the implications for the kilonova (KN) possibly generated by this NS-BH merger, and for the strategy of future searches. Altogether, our observations allow us to exclude a KN with large ejecta mass $M\gtrsim 0.1\,\mathrm{M_\odot}$ to a high ($>90\%$) confidence, and we can exclude much smaller masses in a subsample of our observations. This disfavours the tidal disruption of the neutron star during the merger. Despite the sensitive instruments involved in the campaign, given the distance of S190814bv we could not reach sufficiently deep limits to constrain a KN comparable in luminosity to AT 2017gfo on a large fraction of the localisation probability. This suggests that future (likely common) events at a few hundreds Mpc will be detected only by large facilities with both high sensitivity and large field of view. Galaxy-targeted observations can reach the needed depth over a relevant portion of the localisation probability with a smaller investment of resources, but the number of galaxies to be targeted in order to get a fairly complete coverage is large, even in the case of a localisation as good as that of this event.

astro-ph.SR↗

arXiv2019

The transitional gap transient AT 2018hso: new insights on the luminous red nova phenomenon

Aims: AT 2018hso is a new transient showing transitional properties between those of LRNe and the class of intermediate luminosity red transients (ILRTs) similar to SN 2008S. Through the detailed analysis of the observed parameters, our study support that it actually belongs to the LRN class, and was likely produced by the coalescence of two massive stars. Methods: We obtained ten months of optical and near-infrared photometric monitoring, and eleven epochs of low-resolution optical spectroscopy of AT~2018hso. We compared its observed properties with those of other ILRTs and LRNe. We also inspected the archival Hubble Space Telescope (HST) images obtained about 15 years ago to constrain the progenitor's properties. Results: The light curves of AT 2018hso show a first sharp peak (Mr = -13.93 mag), followed by a broader and shallower second peak, that resembles a plateau in the optical bands. The spectra dramatically change with time. Early time spectra show prominent Balmer emission lines and a weak Ca II] doublet, which is usually observed in ILRTs. However, the major decrease in the continuum temperature, the appearance of narrow metal absorption lines, the major change in the H$α$ strength and profile, and the emergence of molecular bands support a LRN classification. The possible detection of an I ~ -8 mag source at the position of AT 2018hso in HST archive images is consistent with expectations for a pre-merger massive binary, similar to the precursor of the 2015 LRN in M101. Conclusions: We provide reasonable arguments to support a LRN classification for AT~2018hso. This study reveals growing heterogeneity in the observables of LRNe than thought in the past, making sometimes tricky the discrimination between LRNe and ILRTs. This suggests the need of monitoring the entire evolution of gap transients to avoid misclassifications.

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arXiv2018

A dust-enshrouded tidal disruption event with a resolved radio jet in a galaxy merger

Tidal disruption events (TDEs) are transient flares produced when a star is ripped apart by the gravitational field of a supermassive black hole (SMBH). We have observed a transient source in the western nucleus of the merging galaxy pair Arp 299 that radiated >1.5x10^52 erg in the infrared and radio, but was not luminous at optical or X-ray wavelengths. We interpret this as a TDE with much of its emission re-radiated at infrared wavelengths by dust. Efficient reprocessing by dense gas and dust may explain the difference between theoretical predictions and observed luminosities of TDEs. The radio observations resolve an expanding and decelerating jet, probing the jet formation and evolution around a SMBH.

astro-ph.GA↗

arXiv2016

Progenitor constraints for core-collapse supernovae from Chandra X-ray observations

The progenitors of hydrogen-poor core-collapse supernovae (SNe) of types Ib, Ic and IIb are believed to have shed their outer hydrogen envelopes either by extremely strong stellar winds, characteristic of classical Wolf-Rayet stars, or by binary interaction with a close companion star. The exact nature of the progenitors and the relative importance of these processes are still open questions. One relatively unexplored method to constrain the progenitors is to search for high-mass X-ray binaries (HMXB) at SN locations in pre-explosion X-ray observations. In a HMXB, one star has already exploded as a core-collapse SN, producing a neutron star or a stellar-mass black hole. It is likely that the second star in the system will also explode as a supernova, which should cause a detectable long-term change in the system's X-ray luminosity. In particular, a pre-explosion detection of a HMXB coincident with a SN could be informative about the progenitor's nature. In this paper we analyze pre-explosion ACIS observations of 18 nearby type Ib, Ic and IIb supernovae from the Chandra X-ray observatory public archive. Two sources that could potentially be associated with the supernova are identified in the sample. Additionally we make similar post-explosion measurements for 46 SNe. Although our modelling indicates that progenitor systems with compact binary companions are probably quite rare, studies of this type can in the future provide more stringent constraints as the number of discovered nearby SNe and suitable pre-explosion X-ray data are both increasing.

astro-ph.HE↗