997 resultados para stars: cataclysmic variables


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We present the Coordinated Synoptic Investigation of NGC 2264, a continuous 30 day multi-wavelength photometric monitoring campaign on more than 1000 young cluster members using 16 telescopes. The unprecedented combination of multi-wavelength, high-precision, high-cadence, and long-duration data opens a new window into the time domain behavior of young stellar objects. Here we provide an overview of the observations, focusing on results from Spitzer and CoRoT. The highlight of this work is detailed analysis of 162 classical T Tauri stars for which we can probe optical and mid-infrared flux variations to 1% amplitudes and sub-hour timescales. We present a morphological variability census and then use metrics of periodicity, stochasticity, and symmetry to statistically separate the light curves into seven distinct classes, which we suggest represent different physical processes and geometric effects. We provide distributions of the characteristic timescales and amplitudes and assess the fractional representation within each class. The largest category (>20%) are optical "dippers" with discrete fading events lasting ~1-5 days. The degree of correlation between the optical and infrared light curves is positive but weak; notably, the independently assigned optical and infrared morphology classes tend to be different for the same object. Assessment of flux variation behavior with respect to (circum)stellar properties reveals correlations of variability parameters with Hα emission and with effective temperature. Overall, our results point to multiple origins of young star variability, including circumstellar obscuration events, hot spots on the star and/or disk, accretion bursts, and rapid structural changes in the inner disk. Based on data from the Spitzer and CoRoT missions. The CoRoT space mission was developed and is operated by the French space agency CNES, with participation of ESA's RSSD and Science Programmes, Austria, Belgium, Brazil, Germany, and Spain.

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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 h of observations with the 4-m VISTA telescope during 5 years (2010-2014), covering similar to 10(9) point sources across an area of 520 deg(2), including 33 known globular clusters and similar to 350 open clusters. The final product will be a deep near-IR atlas in five passbands (0.9-2.5 mu m) and a catalogue of more than 106 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. (C) 2009 Elsevier B.V. All rights reserved.

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Context. 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 about five years. Aims. We describe the progress of the survey observations in the first observing season, the observing strategy, and quality of the data obtained. Methods. The observations are carried out on the 4-m VISTA telescope in the ZYJHK(s) filters. In addition to the multi-band imaging the variability monitoring campaign in the K-s 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. Results. The first data release contains the aperture photometry and astrometric catalogues for 348 individual pointings in the ZYJHK(s) filters taken in the 2010 observing season. The typical image quality is similar to 0 ''.9-1 ''.0. The stringent photometric and image quality requirements of the survey are satisfied in 100% of the JHK(s) images in the disk area and 90% of the JHK(s) 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 1.28 x 10(8) stellar sources in the bulge and 1.68 x 10(8) in the disk area detected in at least one of the photometric bands. The combined, multi-band catalogues contain more than 1.63 x 10(8) stellar sources. About 10% of these are double detections because of overlapping adjacent pointings. These overlapping multiple detections are used to characterise the quality of the data. The images in the JHK(s) bands extend typically similar to 4 mag deeper than 2MASS. The magnitude limit and photometric quality depend strongly on crowding in the inner Galactic regions. The astrometry for K-s = 15-18 mag has rms similar to 35-175 mas. Conclusions. The VVV Survey data products offer a unique dataset to map the stellar populations in the Galactic bulge and the adjacent plane and provide an exciting new tool for the study of the structure, content, and star-formation history of our Galaxy, as well as for investigations of the newly discovered star clusters, star-forming regions in the disk, high proper motion stars, asteroids, planetary nebulae, and other interesting objects.

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Context. Luminous blue variables (LBVs) are a class of highly unstable stars that have been proposed to play a critical role in massive stellar evolution as well as being the progenitors of some of the most luminous supernovae known. However the physical processes underlying their characteristic instabilities are currently unknown. Aims. In order to provide observational constraints on this behaviour we have initiated a pilot study of the population of (candidate) LBVs in the Local Group galaxy M 33. Methods. To accomplish this we have obtained new spectra of 18 examples within M 33. These provide a baseline of ≥ 4 yr with respect to previous observations, which is well suited to identifying LBV outbursts. We also employed existing multi-epoch optical and mid-IR surveys of M 33 to further constrain the variability of the sample and search for the presence of dusty ejecta. Results. Combining the datasets reveals that spectroscopic and photometric variability appears common, although in the majority of cases further observations will be needed to distinguish between an origin for this behavour in short lived stochastic wind structure and low level photospheric pulsations or coherent long term LBV excursions. Of the known LBVs we report a hitherto unidentified excursion of M 33 Var C between 2001-5, while the transition of the WNLh star B517 to a cooler B supergiant phase between 1993−2010 implies an LBV classification. Proof-of-concept quantitative model atmosphere analysis is provided for Romano’s star; the resultant stellar parameters being consistent with the finding that the LBV excursions of this star are accompanied by changes in bolometric luminosity. The combination of temperature and luminosity of two stars, the BHG [HS80] 110A and the cool hypergiant B324, appear to be in violation of the empirical Humphreys-Davidson limit. Mid-IR observations demonstrate that a number of candidates appear associated with hot circumstellar dust, although no objects as extreme as η Car are identified. The combined dataset suggests that the criteria employed to identify candidate LBVs results in a heterogeneous sample, also containing stars demonstrating the B[e] phenomenon. Of these, a subset of optically faint, low luminosity stars associated with hot dust are of particular interest since they appear similar to the likely progenitor of SN 2008S and the 2008 NGC 300 transient (albeit suffering less intrinsic extinction). Conclusions. The results of such a multiwavelength observational approach, employing multiplexing spectrographs and supplemented with quantitative model atmosphere analysis, appears to show considerable promise in both identifying and characterising the physical properties of LBVs as well as other short lived phases of massive stellar evolution.

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Bibliography: p.7,14.

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Mode of access: Internet.

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The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.

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An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

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Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.