343 research outputs found

    VEXAS: VISTA EXtension to Auxiliary Surveys -- Data Release 2: Machine-learning based classification of sources in the Southern Hemisphere

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    We present the second public data release (DR) of the VISTA EXtension to Auxiliary Surveys (VEXAS), where we classify objects into stars, galaxies and quasars based on an ensemble of machine learning algorithms. The aim of VEXAS is to build the widest multi-wavelength catalogue, providing reference magnitudes, colours and morphological information for a large number of scientific uses. We apply an ensemble of 32 different machine learning models, based on three different algorithms and on different magnitude sets, training samples and classification problems on the three VEXAS DR1 optical+infrared (IR) tables. The tables were created in DR1 cross-matching VISTA near-IR data with WISE far-IR data and with optical magnitudes from the Dark Energy Survey (VEXAS-DESW), the Sky Mapper Survey (VEXAS-SMW), and the PanSTARRS (VEXAS-PSW). We assemble a large table of spectroscopically confirmed objects (415 628 unique objects), based on the combination of 6 different spectroscopic surveys that we use for training. We develop feature imputation to classify also objects for which magnitudes in one or more bands are missing. We classify in total ~90 million objects in the Southern Hemisphere. Among these,~62.9M (~52.6M) are classified as 'high confidence' ('secure') stars, ~920k (~750k) as 'high confidence' ('secure') quasars and ~34.8M (~34.1M) as 'high confidence' ('secure') galaxies, with probabilities pclass0.7p_{\rm class}\ge 0.7 (pclass0.9p_{\rm class}\ge 0.9). The density of high-confidence extragalactic objects varies strongly with the survey depth: at pclass0.7p_{\rm class}\ge 0.7, there are 111/deg2^2 quasars in the VEXAS-DESW footprint and 103/deg2^2 in the VEXAS-PSW footprint, while only 10.7/deg2^2 in the VEXAS-SM footprint. Improved depth in the midIR and coverage in the optical and nearIR are needed for the SM footprint that is not already covered by DESW and PSW.Comment: 25 pages, 18 figures, 8 tables. Accepted for publication on A&A. The VEXAS tables are publicly available through the ESO Phase 3 here: https://archive.eso.org/scienceportal/home?data_collection=VEXAS. The DR2 tables update the DR1 with the addition of imputed magnitudes and membership probabilities to each of the three classe

    Theory of highly loaded coal-water slurries

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    There has been analyzed the existing schemes of strapping of circulated system of drilling set during drilling with well washing by the foam and argued the necessity of its efficient raising; there has been chosen the scheme of strapping of circulated system during drilling with well washing by the foam for the possibility of the most rational usage of existing foamgenerating equipment.В статті проаналізовані існуючі схеми обв'язки циркуляційної системи бурової установки при бурінні з промиванням свердловини піною та обґрунтована необхідність підвищення їх ефективності; для можливості найбільш раціонального використання існуючого піногенеруючого устаткування передбачена схема обв'язки циркуляційної системи при бурінні з промиванням свердловини піною

    Rogue waves and mode locking driven by Vector Resonance Multimode instability

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    Modulation instabilities discovered more than fifty and hundred fifty years ago created since then a framework for study complexity of different wave phenomena including turbulence and rogue waves. Using Erbium-doped fiber laser without any previously studied mode-locking mechanisms, here for the first time we demonstrate both experimentally and theoretically a new type of modulation instability, namely Vector Resonance Multimode Instability, leading to tunability of the laser dynamics from turbulence including rogue waves to the stable pulse train similar to the laser mode-locking regime

    Temporal scaling of optical rogue waves in unidirectional ring fiber laser

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    A fiber mode-lock laser allows generation of the optical rogue wave (ORW) at different time scales. The criteria for distinguishing between them is a comparison of the event lifetime with the main characteristic time of the system. The characteristic time can be estimated from the decay of an autocorrelation function (AF). Thus, in comparison with AF characteristic time, fast optical rogue wave (FORW) events have duration less than the AF decay time and it appeared due to pulse-pulse interaction and nonlinear pulses dynamics. While slow optical rogue wave (SORW) have a duration much more longer than the decay time of the AF which it papered due to hopping between different attractors. Switching between regimes can be managed by change the artificial birefringence that induced in a laser cavity. For understanding the role playing by the periodical amplification and the resonator, we have performed an unidirectional fiber laser experiments without a saturable absorber. This laser experiment allowed to generate of most of the RW patterns which were either observed experimentally or predicted theoretically. In this way, we have observed the generation of an FORW along with SORW under similar conditions. Most of the patterns were found to be mutually exclusive which means that only one RW mechanism was realized in each regime of generation

    Upconversion assisted self-pulsing in a high-concentration erbium doped fiber laser

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    We report results on experimental and theoretical characterisation of self-pulsing in high concentration erbium doped fibre laser which is free from erbium clusters. Unlike previous models of self-pulsing accounting for pair-induced quenching (PIQ) on the clustered erbium ions, new model has been developed with accounting for statistical nature of the excitation migration and upconversion and resonance-like pumpto-signal intensity noise transfer. The obtained results are in a good agreement with the experimental data

    KiDS0239-3211: A new gravitational quadruple lens candidate

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    We report the discovery of a candidate to quadrupole gravitationally lensed system KiDS0239-3211 based on the public data release 3 of the KiDS survey and machine learning techniques
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