The period variations of rotating, pulsating and eclipsing variable stars bear valuable astrophysical information about the presence of companions, evolutionary effects, and the inner structure of the stars. This talk described a universal method for de-trending and re-scaling precise photometric data (Kepler, MOST, CoRoT, OGLE, …) appropriate for period-change diagnostics of periodic variables. We demonstrated the potential of the method by analysing the period variability of one of the newly-identified Kepler magnetic chemically-peculiar (mCP) stars. We showed that, surprisingly, our target star displays near-sinusoidal changes in its observed light-variations, with a period of 2.85(6) years, which is apparently the result of the presence of a nearby stellar companion. The expected long-term changes of the rotational period, as have been observed in several mCP stars, have not been identified among the sample of Kepler mCP stars.

This contribution gave three examples of X-ray transients in the Magellanic Clouds and the Milky Way that have been observed as part of the SALT Transients Large Programme. The transients (SMC X-3, MAXI J1957+032 and ASASSN-16oh) have been triggered from both space-based wide-field monitoring facilities (Swift/XRT, MAXI) and ground-based ones (ASASSN, the All Sky Automated Survey for SN), providing insights into the physics of super-Eddington accretion onto neutron stars and white dwarfs, and also into the long-term properties of accreting millisecond X-ray pulsars.

Over an 11-year cycle the Sun changes its brightness by less than 0.1%. However, it is an open question how strong the Sun’s photometric variability was in the distant past. One way to answer that is to study other Sun-like stars and compare their photometric variability with that of the Sun. In a recent paper, we presented ground-based spectroscopic observations of a 7.4-year cycle in the solar analogue HD 173701. Complemented with observations from the Kepler space telescope, those data constitute the most complete set of observations of a stellar cycle ever obtained for any Sun-like star. They reveal that HD 173701 has strong solar-like differential rotation and a magnetic cycle comparable to the cycle generated by the solar dynamo, but with a resulting variability twice the amplitude of that observed in the Sun.

This general overview of our understanding of the Galaxy followed the lines of its main structures (halo, disc, bulge/bar) and emphasized some time-domain astronomy contributions. On the one hand the distance and tangential motions of the stars are essential to that understanding, and are obtained through multi-epoch surveys. On the other hand the chemistry of the stars and their radial velocities are also key elements for mapping the Galactic (sub-)structures, and unravelling their history and evolution. Contemporary surveys are revolutionizing our view of the Milky Way and of galaxies in general. Among those, the Gaia mission excels through its precise astrometry of 1.3 billion stars that populate the Milky Way and beyond, providing the first 3-D view of a major part of the Milky Way.

Clustering algorithms constitute a multi-disciplinary analytical tool commonly used to summarise large data sets. Astronomical classifications are based on similarity, where celestial objects are assigned to a specific class according to specific physical features. The aim of this project is to obtain relevant information from high-dimensional data (at least three input variables in a data-frame) derived from stellar light-curves using a number of clustering algorithms such as K-means and Expectation Maximisation. In addition to identifying the best performing algorithm, we also identify a subset of features that best define stellar groups. Three methodologies are applied to a sample of Kepler time series in the temperature range 6500–19,000 K. In that spectral range, at least four classes of variable stars are expected to be found: δ Scuti, γ Doradus, Slowly Pulsating B (SPB), and (the still equivocal) Maia stars.

The Space-based, multi-band, astronomical Variable Object Monitor (SVOM) is a collaborative project between China and France dedicated to the detection, localisation and study of about 60 Gamma Ray Bursts per year, and other high-energy transient phenomena. SVOM is planned to be launched in 2021, with a lifetime of 3–5 years. The poster described our construction and testing of a prototype to set up an interface between our data reduction sub-system, the global VOEvent network, and the French science centre.

The main purpose for holding a Workshop about the Large Synoptic Survey Telescope (LSST) was to move all participants further towards answering the question, “How will I do my science with LSST data?” Presentations included (i) the planned pipelines and products of the data management team, and (ii) the existing channels for communication within the science community and between the community and the LSST Data Management team. In between the formal presentations, small groups discussed matters such as how to select the data products or communications resources that were best suited to individual science goals. The latter discussions were designed both to facilitate engagement with the material and to foster collaboration. Participants should thus have become better equipped to continue on their respective individual paths towards science with LSST.

This talk provided an overview and update of the LSST Project and a review of the Data Management system, with a focus on the products most relevant to the researchers of transients and variables. The open opportunities for user-defined Special Programmes such as Deep Drilling Fields were also presented.

This poster reported our spectroscopy of the neutron-star X-ray binary 4U 1728-34, observed with Suzaku in 2010 October. It is classified as an atoll source. Its continuous X-ray spectrum can be fitted by a combination of a multicolour accretion-disk model for the soft energy, plus a power-law model for the hard energy. A broad emission line at 6–7 keV can be fitted well using a simple Gaussian component with an equivalent width of ∼322 eV. However, for this object the presence of that feature is disputed, even though our results from Suzaku do suggest the presence of a broad Fe emission line that is consistent with results from XMM-Newton. Nevertheless, the parameters of the line (the line centroid and the equivalent width) are a little different, but that could be due to a difference in modelling the continuum.

Supernovae (SNe) are cosmic explosions which are usually represented in a small region of the luminosity–time-scale diagram when discussing the variable sky. However, there are different time-scales involved in the evolution of SNe that are not reflected by that representation. This talk reviewed some of the physical mechanisms driving the SN light-curve diversity, especially at early times. It then discussed our efforts in the astroinformatics laboratory at CMM and at MAS to discover very young SNe using large etendue telescopes such as Blanco/DECam; those efforts led to the real-time discovery of more than one hundred SNe, some of them very young, under the High cadence Transient Survey (HiTS). We showed that, by comparing hydrodynamical models in the literature with HiTS SNe using Markov Chain Monte Carlo to sample from the posterior in a Bayesian approach, we can constrain the physical parameters that are driving the early time-evolution of these events. We also discussed how these data are being used for different projects, such as the discovery of asteroids and variable stars, and for testing different machine-learning algorithms in an interdisciplinary approach.

Octocam is an 8-channel VIS and NIR imager and spectrograph to be installed at Gemini South in 2022. It provides simultaneous imaging in g’,r’,i’,z,Y,J,H,KS bands or simultaneous spectroscopy at a resolution of ∼4000, together with high time-resolution options. Additional capabilities such as spectropolarimetry or an Integral Field Unit could be added as an upgrade later. These properties makes it very well suited as a follow-up instrument for transient searches. It is planned as a dedicated follow-up instrument for LSST, and will start operations at the same time as the LSST main survey. Octocam was conceived as a consortium consisting of South-West Research Institute in San Antonio, Texas, IAA-CSIC in Granada, FRACTAL SLNE in Madrid, and George Washington University.

Radio emission from astrophysical transients allows us to derive calorimetry of kinetic feedback and detailed imaging in ways that are not possible at other wavelengths, and as such it forms an important part of the multi-messenger follow-ups of these events. The field is burgeoning, with a renaissance of interest in accretion, stellar explosions and jetted supernovæ, alongside newer classes of phenomena such as fast radio bursts and tidal disruption events. The purpose of this workshop was to discuss the infrastructure and techniques for detecting, identifying and probing radio transients, with a particular focus on how best to exploit transient alerts from multi-messenger facilities. We examined the type of transient alerts those facilities will broadcast, and methods for following them up, such as rapid-response triggering and shadowing. In break-out groups, participants chose a science question related to a particular radio transient type or class and discussed whether the planned transient strategies and observing techniques on the Square Kilometre Array will be adequate to address the particular question. The classes they chose included fast radio bursts, supernovæ, cataclysmic variable and unknown transients. Any proposed adaptation or suggestion was relayed to a panel of experts for further discussion. The second part of the workshop concentrated on the application of long baseline interferometry for detecting and measuring radio transients.

Measurements of current rates of core-collapse supernovæ (CCSNe) suffer from significant uncertainties, probably due to the large fraction of CCSNe that explode in crowded regions which have bright background emission and significant dust extinction. Conventional optical (seeing-limited) SN surveys generally fail to detect them, but including them is crucial to the accurate determination of CCSN rates. Project SUNBIRD aims to tighten the present constraints on the fraction of CCSNe that are missed by conventional SN surveys. We are monitoring more than 25 dusty luminous infrared galaxies that are actively star-forming, for evidence of dust-obscured CCSNe, in an effort to characterise the population of CCSNes exploding in those nuclear regions of dusty LIRGs. We observe in the near-infrared, which is less affected by dust extinction compared to the optical; we are using Gemini South and Keck, and we make use of state-of-the-art laser guide-star adaptive optics instruments to achieve a spatial resolution <0’.1, which is sufficient to resolve close to the galactic nucleus.

During the project’s first year we discovered three CCSNe and one candidate one, with nuclear offsets as small as 200 pc, as cited in the poster. Aggregating the new discoveries with the CCSNe found in previous programmes employing AO, we compared the distribution of nuclear offsets of AO CCSN discoveries with all other documented CCSNe discovered in LIRGs. The poster showed that our method is singularly effective at uncovering CCSNe in the nuclear regions of LIRGs, and that while optical surveys dominate SNe discoveries far from a galaxy’s centre, near infra-red AO observations are needed to probe the regions within 1 kpc of the nucleus.

The SkyMapper Transient survey (SMT) is exploring variability in the southern sky by performing (a) a rolling search to discover and study supernovæ, and (b) a Target of Opportunity programme that uses the robotic SkyMapper Telescope at Siding Spring Observatory. The supernova survey is obtaining a non-targeted sample of Type Ia supernovæ (SNe Ia) at low redshifts, z < 0.1, and studying other interesting transients found with the search strategy. We have a Target of Opportunity programme with an automatic response mechanism to search for optical counterparts to gravitational-wave and fast radio-burst events; it benefits from SkyMapper’s large field of view of 5.7 sq. deg. and a rapid data reduction pipeline.

We present first results of the SMT survey. The SMT pipeline can process and obtain potential candidates within 12 hours of observation. It disentangles real transients from processing artefacts using a machine-learning algorithm. To date, SMT has discovered over 60 spectroscopically confirmed supernovæ, several peculiar objects, and over 40 SNe Ia including one (SNIa 2016hhd) which was found within the first few days of explosion. We have also participated in searches for optical counterparts of gravitational waves, fast radio bursts and other transients, and have published observations of the optical counterpart of the gravitational-wave event GW170817. We also participate in coordinated observations with the Deeper Wider Faster programme, and the Kepler K2 cosmology project.

We organized Workshop 13, Machine learning for transient classification, into two distinct question-and-answer parts. The first was a so-called ‘idiot session’, in which basic questions about machine learning and artificial intelligence were elicited from the audience. The second focussed discussions on the application of artificial intelligence to transient astronomy.

The workshop proved highly successful. The room was packed, and the many interesting questions and discussions were good preparation for the presentation to be made on ‘machine learning’ during the plenary session the following day.

The workshop clearly reflected the general awareness and excitement in the community for the potential of machine learning in regard to transient detections in astronomy in the era of ZTF, LSST, LIGO and the SKA. Several of the presentations at this Symposium had already been exhibiting specific attention to the roles of machine-learning techniques and products. The extent to which the younger generations were being involved was clearly noticeable, and that augured well for research into workable solutions for astronomy’s ‘Big Data’ problems which – as stated frequently at this conference – are only just around the corner.

This poster presented results from the Large Magellanic Cloud Near-Infrared Synoptic Survey (LMCNISS) for classical and Type II Cepheid variables that were identified in the Optical Gravitational Lensing Experiment (OGLE-III) catalogue. Multi-wavelength time-series data for classical Cepheid variables are used to study light-curve structures as a function of period and wavelength. We exploited a sample of ∼1400 classical and ∼80 Type II Cepheid variables to derive Period–Wesenheit relations that combine both optical and near-infrared data. The new Period–Luminosity and Wesenheit relations were used to estimate distances to several Local-Group galaxies (using classical Cepheids) and to Galactic globular clusters (using Type II Cepheids). By appealing to a statistical framework, we found that fundamental-mode classical Cepheid Period–Luminosity relations are non-linear around 10–18 days at optical and near-IR wavelengths. We also suggested that a non-linear relation provides a better constraint on the Cepheid Period–Luminosity relation in Type Ia Supernovæ host galaxies, though it has a negligible effect on the systematic uncertainties affecting the local measurement of the Hubble constant.

LSST will uncover a few million time-domain alerts per night with a latency of a minute. This will provide a huge discovery space, where previously undiscovered rare phenomena may be revealed. The early detection of such previously unknown events from a minimal set of measurements is critical for discovery and follow-up. Analysis methods to recognise such events are being investigated and developed. A discussion of those approaches was presented.

Time-domain astronomy is a key theme on research roadmaps worldwide, as was amply demonstrated by the energy which the participants (coming from 33 different countries) brought to this Symposium, as they shared their experience and expertise through various time-domain projects and discussed the challenges and strategies for the road ahead. This short summary is simply a personal view of the many key topics that were discussed.

We explore the properties of sound and human sound recognition as a means to enhance and accelerate visual-only data analysis methods. The aim of this work is to enable and improve the analysis of large data sets, data requiring rapid analysis, multi-dimensional data, and signal detection in data with low signal-to-noise ratio. We present a prototype tool, StarSound, to sonify data such as astronomical transient light curves, spectra, and power spectra. Stereophonic sound is used to ‘visualise’ and localise the data under examination, and 3-D sound is discussed in conjunction with virtual reality technology, as a means to enhance analysis efficiency and efficacy, including rapid data assessment and training machine learning software. In addition, we explore the use of higher-order harmonics as a means to examine simultaneously multi-dimensional data sets. Such an approach can allow the data to be interpreted in a holistic manner and facilitates the discovery of previously unseen connections and relationships. Furthermore, we exploit the capability of the human brain for selective or focused hearing that enables the identification of desired signals in noisy data, or amidst similar or more significant signals. Finally, we provide research examples that benefit directly from data sonification. The work presented here aims to help tackle the challenges of the upcoming era of Big Data and help optimise, speed up and expand aspects of data analysis requiring human interaction.

This talk discussed the basics of gravito-inertial asteroseismology as recently developed for stars born with a convective core. Photometric space missions originally built for exoplanet hunting, notably Kepler, have opened up the low-frequency regime of stellar oscillations and revealed a larger diversity in variability than anticipated prior to the era of high-precision space photometry. The talk explained the basics of forward seismic modelling based on gravito-inertial modes, which probe the deep stellar interior. It described how a hierarchical fitting approach allows us to derive the near-core rotation period, the amount and shape of convective core overshooting, and the level of chemical mixing in the radiative envelope for stars born with a convective core and burning hydrogen in their core. A summary of the current status, covering the mass range 1.4 ≲ M ≲ 5 M⊙, is provided here through references to numerous recent papers.