Preparing to Discover the Unknown with Rubin LSST: Time Domain

Li, Xiaolong; Ragosta, Fabio; Clarkson, W. I.; Bianco, Federica

doi:10.3847/1538-4365/ac3bca

Cited by 14 publications

(12 citation statements)

References 39 publications

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“…Article number, page 14 of 17 Y.-Z. Cai et al: Luminous Red Nova AT 2021biy Future facilities, such as the China Space Station Telescope (CSST; Cao et al 2022a,b), the Vera C. Rubin Observatory (e.g., Li et al 2022;Bianco et al 2022), and the Nancy Grace Roman Space Telescope (e.g., Rubin et al 2021;Gezari et al 2022) will be essential for substantially increasing the population of LRNe. Joint observational and theoretical efforts will allow us to place tight constraints on the nature of LRNe.…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Observations of the luminous red nova AT 2021biy in the nearby galaxy NGC 4631

Cai¹,

Pastorello²,

Fraser³

et al. 2022

Preprint

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We present an observational study of the luminous red nova (LRN) AT 2021biy in the nearby galaxy NGC 4631. The field of the object was routinely imaged during the pre-eruptive stage by synoptic surveys, but the transient was detected only at a few epochs from ∼ 231 days before maximum brightness. The LRN outburst was monitored with unprecedented cadence both photometrically and spectroscopically. AT 2021biy shows a short-duration blue peak, with a bolometric luminosity of ∼ 1.6 × 10 41 erg s −1 , followed by the longest plateau among LRNe to date, with a duration of 210 days. A late-time hump in the light curve was also observed, possibly produced by a shell-shell collision. AT 2021biy exhibits the typical spectral evolution of LRNe. Early-time spectra are characterised by a blue continuum and prominent H emission lines. Then, the continuum becomes redder, resembling that of a K-type star with a forest of metal absorption lines during the plateau phase. Finally, late-time spectra show a very red continuum (T BB ≈ 2050 K) with molecular features (e.g., TiO) resembling those of M-type stars. Spectropolarimetric analysis indicates that AT 2021biy has local dust properties similar to those of V838 Mon in the Milky Way Galaxy. Inspection of archival Hubble Space Telescope data taken on 2003 August 3 reveals a ∼ 20 M progenitor candidate with log (L/L ) = 5.0 dex and T eff = 5900 K at solar metallicity. The above luminosity and colour match those of a luminous yellow supergiant. Most likely, this source is a close binary, with a 17-24 M primary component.

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Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Observations of the luminous red nova AT 2021biy in the nearby galaxy NGC 4631

Cai¹,

Pastorello²,

Fraser³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Future facilities, such as the China Space Station Telescope (CSST; Cao et al 2022a,b), the Vera C. Rubin Observatory (e.g., Li et al 2022;Bianco et al 2022), and the Nancy Grace Roman Space Telescope (e.g., Rubin et al 2021;Gezari et al 2022) will be essential for substantially increasing the population of LRNe. Joint observational and theoretical efforts will allow us to place tight constraints on the nature of LRNe.…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Forbidden hugs in pandemic times

Cai

Pastorello

Fraser

et al. 2022

A&A

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We present an observational study of the luminous red nova (LRN) AT 2021biy in the nearby galaxy NGC 4631. The field of the object was routinely imaged during the pre-eruptive stage by synoptic surveys, but the transient was detected only at a few epochs from ∼231 days before maximum brightness. The LRN outburst was monitored with unprecedented cadence both photometrically and spectroscopically. AT 2021biy shows a short-duration blue peak, with a bolometric luminosity of ∼1.6 × 1041 erg s−1, followed by the longest plateau among LRNe to date, with a duration of 210 days. A late-time hump in the light curve was also observed, possibly produced by a shell-shell collision. AT 2021biy exhibits the typical spectral evolution of LRNe. Early-time spectra are characterised by a blue continuum and prominent H emission lines. Then, the continuum becomes redder, resembling that of a K-type star with a forest of metal absorption lines during the plateau phase. Finally, late-time spectra show a very red continuum (TBB ≈ 2050 K) with molecular features (e.g., TiO) resembling those of M-type stars. Spectropolarimetric analysis indicates that AT 2021biy has local dust properties similar to those of V838 Mon in the Milky Way Galaxy. Inspection of archival Hubble Space Telescope data taken on 2003 August 3 reveals a ∼20 M⊙ progenitor candidate with log (L/L⊙) = 5.0 dex and Teff = 5900 K at solar metallicity. The above luminosity and colour match those of a luminous yellow supergiant. Most likely, this source is a close binary, with a 17–24 M⊙ primary component.

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“…The forthcoming LSST survey will observe all the Southern Hemisphere sky every ∼2 − 3 nights, producing an unprecedented real time movie of the night sky. The community expects to discover a significant amount of new types of variable objects using this dataset (Li et al 2022). Therefore there have been over the past years a number of works exploring deep learning and machine learning in general, to identify anomalous light curves in preparation of LSST We emphasise again that deep learning is not the unique machine learning approach to identify anomalies.…”

Section: Transient Astronomymentioning

confidence: 99%

The Dawes Review 10: The impact of deep learning for the analysis of galaxy surveys

Huertas-Company

Lanusse²

2023

Publ. Astron. Soc. Aust.

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The amount and complexity of data delivered by modern galaxy surveys has been steadily increasing over the past years. New facilities will soon provide imaging and spectra of hundreds of millions of galaxies. Extracting coherent scientific information from these large and multi-modal data sets remains an open issue for the community and data-driven approaches such as deep learning have rapidly emerged as a potentially powerful solution to some long lasting challenges. This enthusiasm is reflected in an unprecedented exponential growth of publications using neural networks, which have gone from a handful of works in 2015 to an average of one paper per week in 2021 in the area of galaxy surveys. Half a decade after the first published work in astronomy mentioning deep learning, and shortly before new big data sets such as Euclid and LSST start becoming available, we believe it is timely to review what has been the real impact of this new technology in the field and its potential to solve key challenges raised by the size and complexity of the new datasets. The purpose of this review is thus two-fold. We first aim at summarising, in a common document, the main applications of deep learning for galaxy surveys that have emerged so far. We then extract the major achievements and lessons learned and highlight key open questions and limitations, which in our opinion, will require particular attention in the coming years. Overall, state-of-the-art deep learning methods are rapidly adopted by the astronomical community, reflecting a democratisation of these methods. This review shows that the majority of works using deep learning up to date are oriented to computer vision tasks (e.g. classification, segmentation). This is also the domain of application where deep learning has brought the most important breakthroughs so far. However, we also report that the applications are becoming more diverse and deep learning is used for estimating galaxy properties, identifying outliers or constraining the cosmological model. Most of these works remain at the exploratory level though which could partially explain the limited impact in terms of citations. Some common challenges will most likely need to be addressed before moving to the next phase of massive deployment of deep learning in the processing of future surveys; for example, uncertainty quantification, interpretability, data labelling and domain shift issues from training with simulations, which constitutes a common practice in astronomy.

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Preparing to Discover the Unknown with Rubin LSST: Time Domain

Cited by 14 publications

References 39 publications

Observations of the luminous red nova AT 2021biy in the nearby galaxy NGC 4631

Observations of the luminous red nova AT 2021biy in the nearby galaxy NGC 4631

Forbidden hugs in pandemic times

The Dawes Review 10: The impact of deep learning for the analysis of galaxy surveys

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