Supernova search with active learning in ZTF DR3

We provide the first results from the complete SNAD adaptive learning pipeline in the context of a broad scope of data from large-scale astronomical surveys. The main goal of this work is to explore the potential of adaptive learning techniques in application to big data sets. Our SNAD team used Active Anomaly Discovery (AAD) as a tool to search for new supernova (SN) candidates in the photometric data from the first 9.4 months of the Zwicky Transient Facility (ZTF) survey, namely, between March 17 and December 31 2018 (58194 < MJD < 58483). We analysed 70 ZTF fields at a high galactic latitude and visually inspected 2100 outliers. This resulted in 104 SN-like objects being found, 57 of which were reported to the Transient Name Server for the first time and with 47 having previously been mentioned in other catalogues, either as SNe with known types or as SN candidates. We visually inspected the multi-colour light curves of the non-catalogued transients and performed fittings with different supernova models to assign it to a probable photometric class: Ia, Ib/c, IIP, IIL, or IIn. Moreover, we also identified unreported slow-evolving transients that are good superluminous SN candidates, along with a few other non-catalogued objects, such as red dwarf flares and active galactic nuclei. Beyond confirming the effectiveness of human-machine integration underlying the AAD strategy, our results shed light on potential leaks in currently available pipelines. These findings can help avoid similar losses in future large-scale astronomical surveys. Furthermore, the algorithm enables direct searches of any type of data and based on any definition of an anomaly set by the expert.Comment: 22 pages with appendix, 12 figures, 2 tables, accepted for publication in Astronomy and Astrophysic

GRB 130831a: Rise and demise of a magnetar at z = 0.5

Open Access.--14th Marcel Grossman Meeting On Recent Developments in Theoretical and Experimental General Relativity, Astrophysics and Relativistic Field Theories; University of Rome "La Sapienza"Rome; Italy; 12 July 2015 through 18 July 2015; Code 142474.-- http://www.icra.it/mg/mg14/Gamma-ray bursts (GRBs) are the brightest explosions in the universe, yet the properties of their energy sources are far from understood. Very important clues, however, can be deduced by studying the afterglows of these events. We present observations of GRB 130831A and its afterglow obtained with Swift, Chandra, and multiple ground-based observatories. This burst shows an uncommon drop in the X-ray light curve at about 100 ks after the trigger, with a decay slope of α 7. The standard Forward Shock (FS) model offers no explanation for such a behaviour. Instead, a model in which a newly born magnetar outflow powers the early X-ray emission is found to be viable. After the drop, the X-ray afterglow resumes its decay with a slope typical of FS emission. The optical emission, on the other hand, displays no clear break across the X-ray drop and its decay is consistent with that of the late X-rays. Using both the X-ray and optical data, we show that the FS model can explain the emission after 100 ks. We model our data to infer the kinetic energy of the ejecta and thus estimate the efficiency of a magnetar “central engine” of a GRB. Furthermore, we break down the energy budget of this GRB into prompt emission, late internal dissipation, kinetic energy of the relativistic ejecta, and compare it with the energy of the accompanying supernova, SN 2013fu. Copyright © 2018 by the Editors.All rights reserved.Peer reviewe

Anomaly Detection in the Open Supernova Catalog

International audienceIn the upcoming decade, large astronomical surveys will discover millions of transients raising unprecedented data challenges in the process. Only the use of the machine learning algorithms can process such large data volumes. Most of the discovered transients will belong to the known classes of astronomical objects. However, it is expected that some transients will be rare or completely new events of unknown physical nature. The task of finding them can be framed as an anomaly detection problem. In this work, we perform for the first time an automated anomaly detection analysis in the photometric data of the Open Supernova Catalog (OSC), which serves as a proof of concept for the applicability of these methods to future large-scale surveys. The analysis consists of the following steps: (1) data selection from the OSC and approximation of the pre-processed data with Gaussian processes, (2) dimensionality reduction, (3) searching for outliers with the use of the isolation forest algorithm, and (4) expert analysis of the identified outliers. The pipeline returned 81 candidate anomalies, 27 (33 per cent) of which were confirmed to be from astrophysically peculiar objects. Found anomalies correspond to a selected sample of 1.4 per cent of the initial automatically identified data sample of approximately 2000 objects. Among the identified outliers we recognized superluminous supernovae, non-classical Type Ia supernovae, unusual Type II supernovae, one active galactic nucleus and one binary microlensing event. We also found that 16 anomalies classified as supernovae in the literature are likely to be quasars or stars. Our proposed pipeline represents an effective strategy to guarantee we shall not overlook exciting new science hidden in the data we fought so hard to acquire. All code and products of this investigation are made publicly available.^

The SNAD Viewer: Everything You Want to Know about Your Favorite ZTF Object

International audienceWe describe the SNAD Viewer, a web portal for astronomers which presents a centralized view of individual objects from the Zwicky Transient Facility’s (ZTF) data releases, including data gathered from multiple publicly available astronomical archives and data sources. Initially built to enable efficient expert feedback in the context of adaptive machine learning applications, it has evolved into a full-fledged community asset that centralizes public information and provides a multi-dimensional view of ZTF sources. For users, we provide detailed descriptions of the data sources and choices underlying the information displayed in the portal. For developers, we describe our architectural choices and their consequences such that our experience can help others engaged in similar endeavors or in adapting our publicly released code to their requirements. The infrastructure we describe here is scalable and flexible and can be personalized and used by other surveys and for other science goals. The Viewer has been instrumental in highlighting the crucial roles domain experts retain in the era of big data in astronomy. Given the arrival of the upcoming generation of large-scale surveys, we believe similar systems will be paramount in enabling an optimal exploitation of the scientific potential enclosed in current terabyte and future petabyte-scale data sets. The Viewer is publicly available online at https://ztf.snad.space

Supernova search with active learning in ZTF DR3

In order to explore the potential of adaptive learning techniques to big data sets, the SNAD team used Active Anomaly Discovery (AAD) as a tool to search for new supernova (SN) candidates in the photometric data from the first 9.4 months of the Zwicky Transient Facility survey - between 2018 March 17 and December 31 (58194 < MJD < 58483). We analysed 70 ZTF fields with high galactic latitude and visually inspected 2100 outliers. This resulted in 104 supernova-like objects found, 57 of them were reported to the Transient Name Server for the first time and 47 were previously mentioned in other catalogues either as supernovae with known types or as supernova candidates. We visually inspected the multi-colour light curves of the non-catalogued transients and performed their fit with different supernova models to assign it to a proper class: Ia, Ib/c, IIP, IIL, IIn. Moreover, we also identified unreported slow-evolving transients which are good superluminous SN candidates, and a few others non-catalogued objects, such as red dwarf flares and active galactic nuclei. Beyond confirming the effectiveness of human-machine integration underlying the AAD strategy, our results shed light on potential leaks in currently available pipelines and can help avoid similar losses in future large scale astronomical surveys. The algorithm enables directed search of any type of data and definition of anomaly chosen by the expert

Supernova search with active learning in ZTF DR3

In order to explore the potential of adaptive learning techniques to big data sets, the SNAD team used Active Anomaly Discovery (AAD) as a tool to search for new supernova (SN) candidates in the photometric data from the first 9.4 months of the Zwicky Transient Facility survey - between 2018 March 17 and December 31 (58194 < MJD < 58483). We analysed 70 ZTF fields with high galactic latitude and visually inspected 2100 outliers. This resulted in 104 supernova-like objects found, 57 of them were reported to the Transient Name Server for the first time and 47 were previously mentioned in other catalogues either as supernovae with known types or as supernova candidates. We visually inspected the multi-colour light curves of the non-catalogued transients and performed their fit with different supernova models to assign it to a proper class: Ia, Ib/c, IIP, IIL, IIn. Moreover, we also identified unreported slow-evolving transients which are good superluminous SN candidates, and a few others non-catalogued objects, such as red dwarf flares and active galactic nuclei. Beyond confirming the effectiveness of human-machine integration underlying the AAD strategy, our results shed light on potential leaks in currently available pipelines and can help avoid similar losses in future large scale astronomical surveys. The algorithm enables directed search of any type of data and definition of anomaly chosen by the expert

Supernova search with active learning in ZTF DR3

In order to explore the potential of adaptive learning techniques to big data sets, the SNAD team used Active Anomaly Discovery (AAD) as a tool to search for new supernova (SN) candidates in the photometric data from the first 9.4 months of the Zwicky Transient Facility survey - between 2018 March 17 and December 31 (58194 < MJD < 58483). We analysed 70 ZTF fields with high galactic latitude and visually inspected 2100 outliers. This resulted in 104 supernova-like objects found, 57 of them were reported to the Transient Name Server for the first time and 47 were previously mentioned in other catalogues either as supernovae with known types or as supernova candidates. We visually inspected the multi-colour light curves of the non-catalogued transients and performed their fit with different supernova models to assign it to a proper class: Ia, Ib/c, IIP, IIL, IIn. Moreover, we also identified unreported slow-evolving transients which are good superluminous SN candidates, and a few others non-catalogued objects, such as red dwarf flares and active galactic nuclei. Beyond confirming the effectiveness of human-machine integration underlying the AAD strategy, our results shed light on potential leaks in currently available pipelines and can help avoid similar losses in future large scale astronomical surveys. The algorithm enables directed search of any type of data and definition of anomaly chosen by the expert

Repetitive patterns in rapid optical variations in the nearby black-hole binary V404 Cygni

ブラックホール近傍から出る規則的なパターンを持つ光の変動を可視光で初めて捉えることに成功 -ブラックホールの「またたき」を直接目で観測できる機会に期待-. 京都大学プレスリリース. 2016-01-07.How black holes accrete surrounding matter is a fundamental yet unsolved question in astrophysics. It is generally believed that matter is absorbed into black holes via accretion disks, the state of which depends primarily on the mass-accretion rate. When this rate approaches the critical rate (the Eddington limit), thermal instability is supposed to occur in the inner disk, causing repetitive patterns of large-amplitude X-ray variability (oscillations) on timescales of minutes to hours. In fact, such oscillations have been observed only in sources with a high mass-accretion rate, such as GRS 1915+105 (refs 2, 3). These large-amplitude, relatively slow timescale, phenomena are thought to have physical origins distinct from those of X-ray or optical variations with small amplitudes and fast timescales (less than about 10 seconds) often observed in other black-hole binaries--for example, XTE J1118+480 (ref. 4) and GX 339−4 (ref. 5). Here we report an extensive multi-colour optical photometric data set of V404 Cygni, an X-ray transient source containing a black hole of nine solar masses (and a companion star) at a distance of 2.4 kiloparsecs (ref. 8). Our data show that optical oscillations on timescales of 100 seconds to 2.5 hours can occur at mass-accretion rates more than ten times lower than previously thought. This suggests that the accretion rate is not the critical parameter for inducing inner-disk instabilities. Instead, we propose that a long orbital period is a key condition for these large-amplitude oscillations, because the outer part of the large disk in binaries with long orbital periods will have surface densities too low to maintain sustained mass accretion to the inner part of the disk. The lack of sustained accretion--not the actual rate--would then be the critical factor causing large-amplitude oscillations in long-period systems