4 resultados para sample rate

em Universidade Complutense de Madrid


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We studied the global and local ℳ-Z relation based on the first data available from the CALIFA survey (150 galaxies). This survey provides integral field spectroscopy of the complete optical extent of each galaxy (up to 2−3 effective radii), with a resolution high enough to separate individual H II regions and/or aggregations. About 3000 individual H II regions have been detected. The spectra cover the wavelength range between [OII]3727 and [SII]6731, with a sufficient signal-to-noise ratio to derive the oxygen abundance and star-formation rate associated with each region. In addition, we computed the integrated and spatially resolved stellar masses (and surface densities) based on SDSS photometric data. We explore the relations between the stellar mass, oxygen abundance and star-formation rate using this dataset. We derive a tight relation between the integrated stellar mass and the gas-phase abundance, with a dispersion lower than the one already reported in the literature (σ_Δlog (O/H) = 0.07 dex). Indeed, this dispersion is only slightly higher than the typical error derived for our oxygen abundances. However, we found no secondary relation with the star-formation rate other than the one induced by the primary relation of this quantity with the stellar mass. The analysis for our sample of ~3000 individual H II   regions confirms (i) a local mass-metallicity relation and (ii) the lack of a secondary relation with the star-formation rate. The same analysis was performed with similar results for the specific star-formation rate. Our results agree with the scenario in which gas recycling in galaxies, both locally and globally, is much faster than other typical timescales, such like that of gas accretion by inflow and/or metal loss due to outflows. In essence, late-type/disk-dominated galaxies seem to be in a quasi-steady situation, with a behavior similar to the one expected from an instantaneous recycling/closed-box model.

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We present measurements of the mean mid-infrared to submillimetre flux densities of massive (M_*≳ 10^11 M_⊙) galaxies at redshifts 1.7 < z < 2.9, obtained by stacking positions of known objects taken from the GOODS NICMOS Survey (GNS) catalogue on maps at 24 μm (Spitzer/MIPS); 70, 100 and 160 μm (Herschel/PACS); 250, 350 and 500 μm (BLAST); and 870 μm (LABOCA). A modified blackbody spectrum fit to the stacked flux densities indicates a median [interquartile] star formation rate (SFR) of SFR = 63[48, 81] M_⊙ yr^−1. We note that not properly accounting for correlations between bands when fitting stacked data can significantly bias the result. The galaxies are divided into two groups, disc-like and spheroid-like, according to their Sérsic indices, n. We find evidence that most of the star formation is occurring in n≤ 2 (disc-like) galaxies, with median [interquartile] SFR = 122[100, 150] M_⊙ yr^−1, while there are indications that the n > 2 (spheroid-like) population may be forming stars at a median [interquartile] SFR = 14[9, 20] M_⊙ yr^−1, if at all. Finally, we show that star formation is a plausible mechanism for size evolution in this population as a whole, but find only marginal evidence that it is what drives the expansion of the spheroid-like galaxies.

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Aims. Long gamma-ray bursts (LGRBs) are associated with the deaths of massive stars and might therefore be a potentially powerful tool for tracing cosmic star formation. However, especially at low redshifts (z< 1.5) LGRBs seem to prefer particular types of environment. Our aim is to study the host galaxies of a complete sample of bright LGRBs to investigate the effect of the environment on GRB formation. Methods. We studied host galaxy spectra of the Swift/BAT6 complete sample of 14 z< 1 bright LGRBs. We used the detected nebular emission lines to measure the dust extinction, star formation rate (SFR), and nebular metallicity (Z) of the hosts and supplemented the data set with previously measured stellar masses M_*. The distributions of the obtained properties and their interrelations (e.g. mass-metallicity and SFR-M_* relations) are compared to samples of field star-forming galaxies. Results. We find that LGRB hosts at z< 1 have on average lower SFRs than if they were direct star formation tracers. By directly comparing metallicity distributions of LGRB hosts and star-forming galaxies, we find a good match between the two populations up to 12 +log (O/H)~8.4−8.5, after which the paucity of metal-rich LGRB hosts becomes apparent. The LGRB host galaxies of our complete sample are consistent with the mass-metallicity relation at similar mean redshift and stellar masses. The cutoff against high metallicities (and high masses) can explain the low SFR values of LGRB hosts. We find a hint of an increased incidence of starburst galaxies in the Swift/BAT6 z< 1 sample with respect to that of a field star-forming population. Given that the SFRs are low on average, the latter is ascribed to low stellar masses. Nevertheless, the limits on the completeness and metallicity availability of current surveys, coupled with the limited number of LGRB host galaxies, prevents us from investigating more quantitatively whether the starburst incidence is such as expected after taking into account the high-metallicity aversion of LGRB host galaxies.

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This paper empirically investigates volatility transmission among stock and foreign exchange markets in seven major world economies during the period July 1988 to January 2015. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each market. To gain further insights, we examine the time-varying behaviour of net pair-wise directional connectedness during the financial turmoil periods experienced in the sample period Our results suggest that slightly more than half of the total variance of the forecast errors is explained by shocks across markets rather than by idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.