arXiv subjects

S. Gurovich

Publications and source records attributed to S. Gurovich.

14 recordsLinked to original sources

arXiv2024

The VISTA Variables in the V\'ia L\'actea eXtended (VVVX) ESO public survey: Completion of the observations and legacy

The ESO public survey VISTA Variables in the V\'ia L\'actea (VVV) surveyed the inner Galactic bulge and the adjacent southern Galactic disk from $2009-2015$. Upon its conclusion, the complementary VVV eXtended (VVVX) survey has expanded both the temporal as well as spatial coverage of the original VVV area, widening it from $562$ to $1700$ sq. deg., as well as providing additional epochs in $JHK_{\rm s}$ filters from $2016-2023$. With the completion of VVVX observations during the first semester of 2023, we present here the observing strategy, a description of data quality and access, and the legacy of VVVX. VVVX took $\sim 2000$ hours, covering about 4% of the sky in the bulge and southern disk. VVVX covered most of the gaps left between the VVV and the VISTA Hemisphere Survey (VHS) areas and extended the VVV time baseline in the obscured regions affected by high extinction and hence hidden from optical observations. VVVX provides a deep $JHK_{\rm s}$ catalogue of $\gtrsim 1.5\times10^9$ point sources, as well as a $K_{\rm s}$ band catalogue of $\sim 10^7$ variable sources. Within the existing VVV area, we produced a $5D$ map of the surveyed region by combining positions, distances, and proper motions of well-understood distance indicators such as red clump stars, RR Lyrae, and Cepheid variables. In March 2023 we successfully finished the VVVX survey observations that started in 2016, an accomplishment for ESO Paranal Observatory upon 4200 hours of observations for VVV+VVVX. The VVV+VVVX catalogues complement those from the Gaia mission at low Galactic latitudes and provide spectroscopic targets for the forthcoming ESO high-multiplex spectrographs MOONS and 4MOST.

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arXiv2021

Drifting Features: Detection and evaluation in the context of automatic RRLs identification in VVV

As most of the modern astronomical sky surveys produce data faster than humans can analyze it, Machine Learning (ML) has become a central tool in Astronomy. Modern ML methods can be characterized as highly resistant to some experimental errors. However, small changes on the data over long distances or long periods of time, which cannot be easily detected by statistical methods, can be harmful to these methods. We develop a new strategy to cope with this problem, also using ML methods in an innovative way, to identify these potentially harmful features. We introduce and discuss the notion of Drifting Features, related with small changes in the properties as measured in the data features. We use the identification of RRLs in VVV based on an earlier work and introduce a method for detecting Drifting Features. Our method forces a classifier to learn the tile of origin of diverse sources (mostly stellar 'point sources'), and select the features more relevant to the task of finding candidates to Drifting Features. We show that this method can efficiently identify a reduced set of features that contains useful information about the tile of origin of the sources. For our particular example of detecting RRLs in VVV, we find that Drifting Features are mostly related to color indices. On the other hand, we show that, even if we have a clear set of Drifting Features in our problem, they are mostly insensitive to the identification of RRLs. Drifting Features can be efficiently identified using ML methods. However, in our example, removing Drifting Features does not improve the identification of RRLs.

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arXiv2019

Radio Emission from Interstellar Shocks: Young Type Ia Supernova Remnants and the Case of N 103B in the Large Magellanic Cloud

Here we present a radio continuum study based on new and archival data from the Australia Telescope Compact Array towards N 103B, a young (<=1000 yrs) spectroscopically confirmed type Ia SNR in the Large Magellanic Cloud (LMC) and proposed to have originated from a single degenerate progenitor. The radio morphology of this SNR is asymmetrical with two bright regions towards the north-west and south-west of the central location as defined by radio emission. N 103B identified features include: a radio spectral index of -0.75+-0.01 (consistent with other young type Ia SNRs in the Galaxy); a bulk SNR expansion rate as in X-rays; morphology and polarised electrical field vector measurements where we note radial polarisation peak towards the north-west of the remnant at both 5500 and 9000 MHz. The spectrum is concave-up and the most likely reason is the non-linear diffusive shock acceleration effects or presence of two different populations of ultra-relativistic electrons. We also note unpolarized clumps near the south-west region which is in agreement with this above scenario. We derive a typical magnetic field strength for N 103B, of 16.4 microG for an average rotation measurement of 200 rad m^-2. However, we estimate the equipartition field to be of the order of ~235 microG with an estimated minimum energy of Emin=6.3*10^48 erg. The close (~0.5 degree) proximity of N 103B to the LMC mid-plane indicates that an early encounter with dense interstellar medium may have set an important constrain on SNR evolution. Finally, we compare features of N 103B, to six other young type Ia SNRs in the LMC and Galaxy, with a range of proposed degeneracy scenarios to highlight potential differences due to a different models. We suggest that the single degenerate scenario might point to morphologically asymmetric type Ia supernova explosions.

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arXiv2019

A Color-Excess Extinction map of the Southern Galactic disk from the VVV and GLIMPSE Surveys

An improved high-resolution and deep A$_{Ks}$ foreground dust extinction map is presented for the Galactic disk area within $295^{\circ} \lesssim l \lesssim 350^{\circ}$, $-1.0^{\circ} \lesssim b \lesssim +1.0^{\circ}$. At some longitudes the map reaches up to $|b|\sim2.25^{\circ}$, for a total of $\sim$148 deg$^2$. The map was constructed via the Rayleigh-Jeans Color Excess (RJCE) technique based on deep near-infrared (NIR) and mid-infrared (MIR) photometry. The new extinction map features a maximum bin size of 1', and relies on NIR observations from the Two Micron All-Sky Survey (2MASS) and new data from ESO's Vista Variables in the Vía Láctea (VVV) survey, in concert with MIR observations from the Galactic Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE). The VVV photometry penetrates $\sim$4 magnitudes fainter than 2MASS, and provides enhanced sampling of the underlying stellar populations in this heavily obscured region. Consequently, the new results supersede existing RJCE maps tied solely to brighter photometry, revealing a systematic underestimation of extinction in prior work that was based on shallower data. The new high-resolution and large-scale extinction map presented here is readily available to the community through a web query interface.

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arXiv2019

Machine Learning on Difference Image Analysis: A comparison of methods for transient detection

We present a comparison of several Difference Image Analysis (DIA) techniques, in combination with Machine Learning (ML) algorithms, applied to the identification of optical transients associated with gravitational wave events. Each technique is assessed based on the scoring metrics of Precision, Recall, and their harmonic mean F1, measured on the DIA results as standalone techniques, and also in the results after the application of ML algorithms, on transient source injections over simulated and real data. This simulations cover a wide range of instrumental configurations, as well as a variety of scenarios of observation conditions, by exploring a multi dimensional set of relevant parameters, allowing us to extract general conclusions related to the identification of transient astrophysical events. The newest subtraction techniques, and particularly the methodology published in Zackay et al. (2016) are implemented in an Open Source Python package, named properimage, suitable for many other astronomical image analyses. This together with the ML libraries we describe, provides an effective transient detection software pipeline. Here we study the effects of the different ML techniques, and the relative feature importances for classification of transient candidates, and propose an optimal combined strategy. This constitutes the basic elements of pipelines that could be applied in searches of electromagnetic counterparts to GW sources.

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arXiv2019

Discovery of a Pulsar-powered Bow Shock Nebula in the Small Magellanic Cloud Supernova Remnant DEMS5

We report the discovery of a new Small Magellanic Cloud Pulsar Wind Nebula (PWN) at the edge of the Supernova Remnant (SNR)-DEM S5. The pulsar powered object has a cometary morphology similar to the Galactic PWN analogs PSR B1951+32 and 'the mouse'. It is travelling supersonically through the interstellar medium. We estimate the Pulsar kick velocity to be in the range of 700-2000 km/s for an age between 28-10 kyr. The radio spectral index for this SNR PWN pulsar system is flat (-0.29 $\pm$ 0.01) consistent with other similar objects. We infer that the putative pulsar has a radio spectral index of -1.8, which is typical for Galactic pulsars. We searched for dispersion measures (DMs) up to 1000 cm/pc^3 but found no convincing candidates with a S/N greater than 8. We produce a polarisation map for this PWN at 5500 MHz and find a mean fractional polarisation of P $\sim 23$ percent. The X-ray power-law spectrum (Gamma $\sim 2$) is indicative of non-thermal synchrotron emission as is expected from PWN-pulsar system. Finally, we detect DEM S5 in Infrared (IR) bands. Our IR photometric measurements strongly indicate the presence of shocked gas which is expected for SNRs. However, it is unusual to detect such IR emission in a SNR with a supersonic bow-shock PWN. We also find a low-velocity HI cloud of $\sim 107$ km/s which is possibly interacting with DEM S5. SNR DEM S5 is the first confirmed detection of a pulsar-powered bow shock nebula found outside the Galaxy.

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arXiv2019

The First Galaxy Cluster Discovered by the VISTA Variables in the Vía Láctea Survey

We report the first confirmed detection of the galaxy cluster VVV-J144321-611754 at very low latitudes (l = 315.836$^{\circ}$, b = -1.650$^{\circ}$) located in the tile d015 of the VISTA Variables in the Vía Láctea (VVV) survey. We defined the region of 30$\times$ 30 $arcmin^2$ centered in the brightest galaxy finding 25 galaxies. For these objects, extinction-corrected median colors of (H - K$_{s}$) = 0.34 $\pm$ 0.05 mag, (J - H) = 0.57 $\pm$ 0.08 mag and (J - K$_{s}$) = 0.87 $\pm$ 0.06 mag, and R$_{1/2}$ = 1.59 $\pm$ 0.16 $arcsec$; C = 3.01 $\pm$ 0.08; and Sersic index, n = 4.63 $\pm$ 0.39 were estimated. They were visually confirmed showing characteristics of early-type galaxies in the near-IR images. An automatic clustering analysis performed in the whole tile found that the concentration of galaxies VVV-J144321-611754 is a real, compact concentration of early-type galaxies. Assuming a typical galaxy cluster with low X-ray luminosity, the photometric redshift of the brightest galaxy is $z = $ 0.196 $\pm$ 0.025. Follow-up near-IR spectroscopy with FLAMINGOS-2 at the Gemini-South telescope revealed that the two brighter cluster galaxies have typical spectra of early-type galaxies and the estimated redshift for the brightest galaxy VVV-J144321.06-611753.9 is $z =$ 0.234$\pm$0.022 and for VVV-J144319.02-611746.1 is $z =$ 0.232$\pm$0.019. Finally, these galaxies clearly follow the cluster Red Sequence in the rest-frame near-IR color--magnitude diagram with the slope similar to galaxy cluster at redshift of 0.2. These results are consistent with the presence of a bona fide galaxy cluster beyond the Milky Way disk.

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arXiv2018

From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning

Machine learning algorithms are highly useful for the classification of time series data in astronomy in this era of peta-scale public survey data releases. These methods can facilitate the discovery of new unknown events in most astrophysical areas, as well as improving the analysis of samples of known phenomena. Machine learning algorithms use features extracted from collected data as input predictive variables. A public tool called Feature Analysis for Time Series (FATS) has proved an excellent workhorse for feature extraction, particularly light curve classification for variable objects. In this study, we present a major improvement to FATS, which corrects inconvenient design choices, minor details, and documentation for the re-engineering process. This improvement comprises a new Python package called "feets", which is important for future code-refactoring for astronomical software tools.

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arXiv2017

Observations of the first electromagnetic counterpart to a gravitational wave source by the TOROS collaboration

We present the results of prompt optical follow-up of the electromagnetic counterpart of the gravitational-wave event GW170817 by the Transient Optical Robotic Observatory of the South Collaboration (TOROS). We detected highly significant dimming in the light curves of the counterpart (Delta g=0.17+-0.03 mag, Delta r=0.14+-0.02 mag, Delta i=0.10 +- 0.03 mag) over the course of only 80 minutes of observations obtained ~35 hr after the trigger with the T80-South telescope. A second epoch of observations, obtained ~59 hr after the event with the EABA 1.5m telescope, confirms the fast fading nature of the transient. The observed colors of the counterpart suggest that this event was a "blue kilonova" relatively free of lanthanides.

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arXiv2013

Milky Way Demographics with the VVV Survey II. Color Transformations and Near-Infrared Photometry for 136 Million Stars in the Southern Galactic Disk

The new multi-epoch near-infrared VVV survey (VISTA Variables in the Via Lactea) is sampling 562 sq. deg of the Galactic bulge and adjacent regions of the disk. Accurate astrometry established for the region surveyed allows the VVV data to be merged with overlapping surveys (e.g., GLIMPSE, WISE, 2MASS, etc.), thereby enabling the construction of longer baseline spectral energy distributions for astronomical targets. However, in order to maximize use of the VVV data, a set of transformation equations are required to place the VVV JHKs photometry onto the 2MASS system. The impetus for this work is to develop those transformations via a comparison of 2MASS targets in 152 VVV fields sampling the Galactic disk. The transformation coefficients derived exhibit a reliance on variables such as extinction. The transformed data were subsequently employed to establish a mean reddening law of E_{J-H}/E_{H-Ks}=2.13 +/- 0.04, which is the most precise determination to date and merely emphasizes the pertinence of the VVV data for determining such important parameters.

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arXiv2012

Galaxies behind the Galactic plane: First results and perspectives from the VVV Survey

Vista Variables in The Via Lactea (VVV) is an ESO variability survey that is performing observations in near infrared bands (ZYJHKs) towards the Galactic bulge and part of the disk with the completeness limits at least 3 mag deeper than 2MASS. In the present work, we searched in the VVV survey data for background galaxies near the Galactic plane using ZYJHKs photometry that covers 1.636 square degrees. We identified 204 new galaxy candidates by analyzing colors, sizes, and visual inspection of multi-band (ZYJHKs) images. The galaxy candidates colors were also compared with the predicted ones by star counts models considering a more realistic extinction model at the same completeness limits observed by VVV. A comparison of the galaxy candidates with the expected one by Milennium simulations is also presented. Our results increase the number density of known galaxies behind the Milky Way by more than one order of magnitude. A catalog with galaxy properties including ellipticity, Petrosian radii and ZYJHKs magnitudes is provided, as well as comparisons of the results with other surveys of galaxies towards Galactic plane.

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arXiv2011

VVV DR1: The First Data Release of the Milky Way Bulge and Southern Plane from the Near-Infrared ESO Public Survey VISTA Variables in the Via Lactea

The ESO Public Survey VISTA Variables in the Via Lactea (VVV) started in 2010. VVV targets 562 sq. deg in the Galactic bulge and an adjacent plane region and is expected to run for ~5 years. In this paper we describe the progress of the survey observations in the first observing season, the observing strategy and quality of the data obtained. The observations are carried out on the 4-m VISTA telescope in the ZYJHKs filters. In addition to the multi-band imaging the variability monitoring campaign in the Ks filter has started. Data reduction is carried out using the pipeline at the Cambridge Astronomical Survey Unit. The photometric and astrometric calibration is performed via the numerous 2MASS sources observed in each pointing. The first data release contains the aperture photometry and astrometric catalogues for 348 individual pointings in the ZYJHKs filters taken in the 2010 observing season. The typical image quality is ~0.9-1.0". The stringent photometric and image quality requirements of the survey are satisfied in 100% of the JHKs images in the disk area and 90% of the JHKs images in the bulge area. The completeness in the Z and Y images is 84% in the disk, and 40% in the bulge. The first season catalogues contain 1.28x10^8 stellar sources in the bulge and 1.68x10^8 in the disk area detected in at least one of the photometric bands. The combined, multi-band catalogues contain more than 1.63x10^8 stellar sources. About 10% of these are double detections due to overlapping adjacent pointings. These overlapping multiple detections are used to characterise the quality of the data. The images in the JHKs bands extend typically ~4 mag deeper than 2MASS. The magnitude limit and photometric quality depend strongly on crowding in the inner Galactic regions. The astrometry for Ks=15-18 mag has rms ~35-175 mas.

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arXiv2009

VISTA Variables in the Via Lactea (VVV): The public ESO near-IR variability survey of the Milky Way

We describe the public ESO near-IR variability survey (VVV) scanning the Milky Way bulge and an adjacent section of the mid-plane where star formation activity is high. The survey will take 1929 hours of observations with the 4-metre VISTA telescope during five years (2010-2014), covering ~10^9 point sources across an area of 520 deg^2, including 33 known globular clusters and ~350 open clusters. The final product will be a deep near-IR atlas in five passbands (0.9-2.5 microns) and a catalogue of more than 10^6 variable point sources. Unlike single-epoch surveys that, in most cases, only produce 2-D maps, the VVV variable star survey will enable the construction of a 3-D map of the surveyed region using well-understood distance indicators such as RR Lyrae stars, and Cepheids. It will yield important information on the ages of the populations. The observations will be combined with data from MACHO, OGLE, EROS, VST, Spitzer, HST, Chandra, INTEGRAL, WISE, Fermi LAT, XMM-Newton, GAIA and ALMA for a complete understanding of the variable sources in the inner Milky Way. This public survey will provide data available to the whole community and therefore will enable further studies of the history of the Milky Way, its globular cluster evolution, and the population census of the Galactic Bulge and center, as well as the investigations of the star forming regions in the disk. The combined variable star catalogues will have important implications for theoretical investigations of pulsation properties of stars.

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arXiv2006

The Northern HIPASS catalogue - Data presentation, completeness and reliability measures

The Northern HIPASS catalogue (NHICAT) is the northern extension of the HIPASS catalogue, HICAT (Meyer et al. 2004). This extension adds the sky area between the declination range of +2 deg < dec. < +25.5 deg to HICAT's declination range of -90 deg < dec. < +2 deg. HIPASS is a blind HI survey using the Parkes Radio Telescope covering 71% of the sky (including this northern extension) and a heliocentric velocity range of -1,280 km/s to 12,700 km/s . The entire Virgo Cluster region has been observed in the Northern HIPASS. The galaxy catalogue, NHICAT, contains 1002 sources with v_hel > 300 km/s . Sources with -300 km/s < v_hel < 300 km/s were excluded to avoid contamination by Galactic emission. In total, the entire HIPASS survey has found 5317 galaxies identified purely by their HI content. The full galaxy catalogue is publicly-available at .

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