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Alina A. Volnova

Publications and source records attributed to Alina A. Volnova.

11 recordsLinked to original sources

What ZTF Saw Where Rubin Looked: Anomaly Hunting in DR23

We present results from the SNAD VIII Workshop, during which we conducted the first systematic anomaly search in the ZTF fields also observed by LSSTComCam during Rubin Scientific Pipeline commissioning. Using the PineForest active anomaly detection algorithm, we analysed four selected fields (two galactic and two extragalactic) and visually inspected 400 candidates. As a result, we discovered six previously uncatalogued variable stars, including RS~CVn, BY Draconis, ellipsoidal, and solar-type variables, and refined classifications and periods for six known objects. These results demonstrate the effectiveness of the SNAD anomaly detection pipeline and provide a preview of the discovery potential in the upcoming LSST data.

astro-ph.IM

Signatures to help interpretability of anomalies

Machine learning is often viewed as a black box when it comes to understanding its output, be it a decision or a score. Automatic anomaly detection is no exception to this rule, and quite often the astronomer is left to independently analyze the data in order to understand why a given event is tagged as an anomaly. We introduce here idea of anomaly signature, whose aim is to help the interpretability of anomalies by highlighting which features contributed to the decision.

cs.LG

Dataset of artefacts for machine learning applications in astronomy

Accurate photometry in astronomical surveys is challenged by image artefacts, which affect measurements and degrade data quality. Due to the large amount of available data, this task is increasingly handled using machine learning algorithms, which often require a labelled training set to learn data patterns. We present an expert-labelled dataset of 1127 artefacts with 1213 labels from 26 fields in ZTF DR3, along with a complementary set of nominal objects. The artefact dataset was compiled using the active anomaly detection algorithm PineForest, developed by the SNAD team. These datasets can serve as valuable resources for real-bogus classification, catalogue cleaning, anomaly detection, and educational purposes. Both artefacts and nominal images are provided in FITS format in two sizes (28 x 28 and 63 x 63 pixels). The datasets are publicly available for further scientific applications.

astro-ph.IM

Exploring the Universe with SNAD: Anomaly Detection in Astronomy

SNAD is an international project with a primary focus on detecting astronomical anomalies within large-scale surveys, using active learning and other machine learning algorithms. The work carried out by SNAD not only contributes to the discovery and classification of various astronomical phenomena but also enhances our understanding and implementation of machine learning techniques within the field of astrophysics. This paper provides a review of the SNAD project and summarizes the advancements and achievements made by the team over several years.

astro-ph.IM

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.

astro-ph.HE

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

We 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

astro-ph.IM

GRB 140423A: A Case of Stellar Wind to Interstellar Medium Transition in the Afterglow

We present very early ground-based optical follow-up observations of GRB~140423A, which was discovered by \emph{Swift}/BAT and by {\it Fermi}/GBM. Its broadband afterglow was monitored by {\it Swift}/XRT and ground-based optical telescopes from $T_0+$70.96~s to 4.8~d after the {\it Swift}/BAT trigger. This is one more case of prompt optical emission observation. The temporal and spectral joint fit of the multiwavelength light curves of GRB 140423A reveals that achromatic behavior is consistent with the external shock model including a transition from a stellar wind to the interstellar medium (ISM) and energy injection. In terms of the optical light curves, there is an onset bump in the early afterglow with a rising index $α_{\rm O,I} = -0.59 \pm 0.04$ (peaking at $t_{\rm peak}-T_0 \approx 206$~s). It then decays with a steep index $α_{\rm O,II} = 1.78 \pm 0.03$, and shows a steeper to flatter "transition" with $α_{\rm O,III} = 1.13 \pm 0.03$ at around $T_0 + 5000$~s. The observed X-ray afterglow reflects an achromatic behavior, as does the optical light curve. There is no obvious evolution of the spectral energy distribution between the X-ray and optical afterglow, with an average value of the photon index $Γ\approx 1.95$. This "transition" is consistent with an external shock model having the circumburst medium transition from a wind to the ISM, by introducing a long-lasting energy injection with a Lorentz factor stratification of the ejecta. The best parameters from Monte Carlo Markov Chain fitting are $E_{\rm K,iso} \approx 2.14\times10^{55}$ erg, $Γ_0 \approx 162$, $ε_e \approx 0.02$, $ε_B \approx 1.7\times10^{-6}$, $A_\ast \approx 1.0$, $R_t \approx 4.1\times10^{17}$ cm, $n \approx 11.0 \rm\ cm^{-3}$, $L_0 \approx 3.1\times10^{52} \rm\ erg\ s^{-1}$, $k \approx 1.98$, $s \approx 1.54$, and $θ_j > 0.3$ rad.

astro-ph.HE

Active Anomaly Detection for time-domain discoveries

We present the first evidence that adaptive learning techniques can boost the discovery of unusual objects within astronomical light curve data sets. Our method follows an active learning strategy where the learning algorithm chooses objects which can potentially improve the learner if additional information about them is provided. This new information is subsequently used to update the machine learning model, allowing its accuracy to evolve with each new information. For the case of anomaly detection, the algorithm aims to maximize the number of scientifically interesting anomalies presented to the expert by slightly modifying the weights of a traditional Isolation Forest (IF) at each iteration. In order to demonstrate the potential of such techniques, we apply the Active Anomaly Discovery (AAD) algorithm to 2 data sets: simulated light curves from the PLAsTiCC challenge and real light curves from the Open Supernova Catalog. We compare the AAD results to those of a static IF. For both methods, we performed a detailed analysis for all objects with the ~2% highest anomaly scores. We show that, in the real data scenario, AAD was able to identify ~80\% more true anomalies than the IF. This result is the first evidence that AAD algorithms can play a central role in the search for new physics in the era of large scale sky surveys.

astro-ph.IM

Anomaly Detection in the Open Supernova Catalog

In 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, 4) expert analysis of the identified outliers. The pipeline returned 81 candidate anomalies, 27 (33%) of which were confirmed to be from astrophysically peculiar objects. Found anomalies correspond to a selected sample of 1.4% of the initial automatically identified data sample of ~2000 objects. Among the identified outliers we recognised 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.

astro-ph.HE

GRB170817A associated with GW170817: multifrequency observations and modeling of prompt gamma-ray emission

We present our observations of electromagnetic transients associated with GW170817/GRB 170817A using optical telescopes of Chilescope observatory and Big Scanning Antenna (BSA) of Pushchino Radio Astronomy Observatory at 110MHz. The Chilescope observatory detected an optical transient of $\sim19^m$ on the third day in the outskirts of the galaxy NGC 4993; we continued observations following its rapid decrease. We put an upper limit of $1.5\times10^{4}$ Jy on any radio source with a duration of 10-60 s which may be associated with GW170817/GRB 170817A. The prompt gamma-ray emission consists of two distinctive components - a hard short pulse delayed by $\sim2$ seconds with respect to the LIGO signal and softer thermal pulse with $T\sim 10 $ keV lasting for another $\sim2$ seconds. The appearance of a thermal component at the end of the burst is unusual for short GRBs. Both the hard and the soft components do not satisfy the Amati relation, making GRB 170817A distinctively different from other short GRBs. Based on gamma-ray and optical observations, we develop a model for the prompt high-energy emission associated with GRB 170817A. The merger of two neutron stars creates an accretion torus of $\sim10^{-2} M_\odot$, which supplies the black hole with magnetic flux and confines the Blandford-Znajek-powered jet. We associate the hard prompt spike with the quasispherical breakout of the jet from the disk wind. As the jet plows through the wind with subrelativistic velocity, it creates a radiation-dominated shock that heats the wind material to tens of kiloelectron volts, producing the soft thermal component.

astro-ph.HE

Repetitive Patterns in Rapid Optical Variations in the Nearby Black-hole Binary V404 Cygni

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 disc, 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. These large-amplitude, relatively slow timescale, phenomena are thought to have physical origins distinct from X-ray or optical variations with small amplitudes and fast ($\lesssim$10 sec) timescales often observed in other black hole binaries (e.g., XTE J1118+480 and GX 339-4). 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 conpanion star) at a distance of 2.4 kiloparsecs. 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-disc 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 disc in binaries with long orbital periods will have surface densities too low to maintain sustained mass accretion to the inner part of the disc. The lack of sustained accretion -- not the actual rate -- would then be the critical factor causing large-amplitude oscillations in long-period systems.

astro-ph.HE