The Discovery of the Most Metal-Rich White Dwarf: Composition of a Tidally Disrupted Extrasolar Dwarf Planet

Cool white dwarf stars are usually found to have an outer atmosphere that is practically pure in hydrogen or helium. However, a small fraction have traces of heavy elements that must originate from the accretion of extrinsic material, most probably circumstellar matter. Upon examining thousands of Sloan Digital Sky Survey spectra, we discovered that the helium-atmosphere white dwarf SDSS J073842.56+183509.6 shows the most severe metal pollution ever seen in the outermost layers of such stars. We present here a quantitative analysis of this exciting star by combining high S/N follow-up spectroscopic and photometric observations with model atmospheres and evolutionary models. We determine the global structural properties of our target star, as well as the abundances of the most significant pollutants in its atmosphere, i.e., H, O, Na, Mg, Si, Ca, and Fe. The relative abundances of these elements imply that the source of the accreted material has a composition similar to that of Bulk Earth. We also report the signature of a circumstellar disk revealed through a large infrared excess in JHK photometry. Combined with our inferred estimate of the mass of the accreted material, this strongly suggests that we are witnessing the remains of a tidally disrupted extrasolar body that was as large as Ceres.Comment: 7 pages in emulateapj, 5 figures, accepted for publication in Ap

Multiwavelength Observations of the Hot DB Star PG 0112+104

We present a comprehensive multiwavelength analysis of the hot DB white dwarf PG 0112+104. Our analysis relies on newly-acquired FUSE observations, on medium-resolution FOS and GHRS data, on archival high-resolution GHRS observations, on optical spectrophotometry both in the blue and around Halpha, as well as on time-resolved photometry. From the optical data, we derive a self-consistent effective temperature of 31,300+-500 K, a surface gravity of log g = 7.8 +- 0.1 (M=0.52 Msun), and a hydrogen abundance of log N(H)/N(He) < -4.0. The FUSE spectra reveal the presence of CII and CIII lines that complement the previous detection of CII transitions with the GHRS. The improved carbon abundance in this hot object is log N(C)/N(He) = -6.15 +- 0.23. No photospheric features associated with other heavy elements are detected. We reconsider the role of PG 0112+104 in the definition of the blue edge of the V777 Her instability strip in light of our high-speed photometry, and contrast our results with those of previous observations carried out at the McDonald Observatory.Comment: 10 pages in emulateapj, 9 figures, accepted for publication in Ap

Chandra grating spectroscopy of three hot white dwarfs

High-resolution soft X-ray spectroscopic observations of single hot white dwarfs are scarce. With the Chandra Low-Energy Transmission Grating, we have observed two white dwarfs, one is of spectral type DA (LB 1919) and the other is a non-DA of spectral type PG1159 (PG 1520+525). The spectra of both stars are analyzed, together with an archival Chandra spectrum of another DA white dwarf (GD 246). The soft X-ray spectra of the two DA white dwarfs are investigated in order to study the effect of gravitational settling and radiative levitation of metals in their photospheres. LB 1919 is of interest because it has a significantly lower metallicity than DAs with otherwise similar atmospheric parameters. GD 246 is the only white dwarf known that shows identifiable individual iron lines in the soft X-ray range. For the PG1159 star, a precise effective temperature determination is performed in order to confine the position of the blue edge of the GW Vir instability region in the HRD. (abridged)Comment: A&A, in pres

Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC‐based T estimates show higher correlation to sap flow‐based T than EC‐based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high‐quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data‐based estimates of ecosystem T permitting a data‐driven perspective on the role of plants’ water use for global water and carbon cycling in a changing climate.We acknowledge insightful discussions with Dario Papale and apologize for having a cappuccino after lunch. We further acknowledge Ulrich Weber for preparing the cappuccino. M.G. acknowledges funding by Swiss National Science Foundation project ICOS‐CH Phase 2 20FI20_173691. L.Š. was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the CzeCOS program, grant number LM2015061, and by SustES‐Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797). G.W. acknowledges support by the Austrian National Science Fund (FWF, project I03859) and the Province of South Tyrol (“Cycling of carbon and water in mountain ecosystems under changing climate and land use”). R.P. was supported by grants CGL2014‐55883‐JIN, RTI2018‐095297‐J‐I00 (Spain), and by a Humboldt Research Fellowship for Experienced Researchers (Germany). This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: Ameri‐Flux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet‐Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux‐TERN, TCOS‐Siberia, and USCCC. The ERA‐Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. Open access funding enabled and organized by Projekt DEAL

DA white dwarfs from the LSS-GAC survey DR1: the preliminary luminosity and mass functions and formation rate

Modern large-scale surveys have allowed the identification of large numbers of white dwarfs. However, these surveys are subject to complicated target selection algorithms, which make it almost impossible to quantify to what extent the observational biases affect the observed populations. The LAMOST (Large Sky Area Multi-Object Fiber Spectroscopic Telescope) Spectroscopic Survey of the Galactic anti-center (LSS-GAC) follows a well-defined set of criteria for selecting targets for observations. This advantage over previous surveys has been fully exploited here to identify a small yet well-characterised magnitude-limited sample of hydrogen-rich (DA) white dwarfs. We derive preliminary LSS-GAC DA white dwarf luminosity and mass functions. The space density and average formation rate of DA white dwarfs we derive are 0.83+/-0.16 x 10^{-3} pc^{-3} and 5.42 +/- 0.08 x 10^{-13} pc^{-3} yr^{-1}, respectively. Additionally, using an existing Monte Carlo population synthesis code we simulate the population of single DA white dwarfs in the Galactic anti-center, under various assumptions. The synthetic populations are passed through the LSS-GAC selection criteria, taking into account all possible observational biases. This allows us to perform a meaningful comparison of the observed and simulated distributions. We find that the LSS-GAC set of criteria is highly efficient in selecting white dwarfs for spectroscopic observations (80-85 per cent) and that, overall, our simulations reproduce well the observed luminosity function. However, they fail at reproducing an excess of massive white dwarfs present in the observed mass function. A plausible explanation for this is that a sizable fraction of massive white dwarfs in the Galaxy are the product of white dwarf-white dwarf mergers.Comment: 23 pages, 14 figures and 5 tables. Accepted for publication by MNRA

Different Verbal Learning Strategies in Autism Spectrum Disorder: Evidence from the Rey Auditory Verbal Learning Test

The Rey Auditory Verbal Learning Test, which requires the free recall of the same list of 15 items over 5 trials, was administered to a group of highfunctioning adolescents and adults with autism spectrum disorder (PDD) and a group of matched typical individuals. Overall levels of free recall were comparable in the two groups, as were the rates of learning over trials. Both groups also subjectively organised their recall to a similar extent. However, the serial position curve of the PDD participants, although similar to that of the comparison group on the first trial, became flatter on subsequent trials and was characterised by a slower growth in the primacy effect. Growth in the middle and recency portions of the curve was comparable in both groups. The findings are discussed in the light of current models of serial position effects and their implications for memory in ASD