Suchergebnisse

Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. ; The guest star of AD 1181 is the only historical supernova of the past millennium that is without a definite counterpart. The previously proposed association with supernova remnant G130.7+3.1 (3C 58) is in strong doubt because of the inferred age of this remnant. Here we report a new identification of SN 1181 with our codiscovery of the hottest known Wolf-Rayet star of the oxygen sequence (IRAS 00500+6713 or 2MASS J00531123+6730023, here named by us as "Parker's star") and its surrounding nebula Pa 30. Our spectroscopy of the nebula shows a fast shock with extreme velocities of ≈1100 km s-1. The derived expansion age of the nebula implies an explosive event ≈1000 yr ago that agrees with the 1181 event. The on-sky location also fits the historical Chinese and Japanese reports of SN 1181 to within 3.°5. Pa 30 and Parker's star have previously been proposed to be the result of a double-degenerate merger, leading to a rare Type Iax supernova. The likely historical magnitude and the distance suggest the event was subluminous for normal supernova. This agrees with the proposed Type Iax association that would also be only the second of its kind in the Galaxy. Taken together, the age, location, event magnitude, and duration elevate Pa 30 to prime position as the counterpart of SN 1181. This source is the only Type Iax supernova where detailed studies of the remnant star and nebula are possible. It provides strong observational support for the double-degenerate merger scenario for Type Iax supernovae. © 2021. The Author(s). Published by the American Astronomical Society. ; Q.A.P. thanks the Hong Kong Research Grants Council for GRF research support under grants 17326116 and 17300417. A.R. and F.L. thank HKU for the provision of postdoctoral fellowships under Q.A.P., while F.L. also acknowledges funding from MTA Hungary (OTKA project No. K-132406). A.A.Z. thanks the Hung Hing Ying Foundation for the provision of a visiting professorship at HKU and acknowledges funding from the UK STFC under grant ST/T000414/1. M.A.G. was funded under grant number PGC2018-102184-B-I00 of the Ministerio de Educación, Innovación y Universidades cofunded with FEDER funds. ; With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709. ; Peer reviewed

[Context] Data-driven methods play an increasingly important role in the field of astrophysics In the context of large spectroscopic surveys of stars, data-driven methods are key in deducing physical parameters for millions of spectra in a short time. Convolutional neural networks (CNNs) enable us to connect observables (e.g. spectra, stellar magnitudes) to physical properties (atmospheric parameters, chemical abundances, or labels in general). ; [Aims] We test whether it is possible to transfer the labels derived from a high-resolution stellar survey to intermediate-resolution spectra of another survey by using a CNN. ; [Methods] We trained a CNN, adopting stellar atmospheric parameters and chemical abundances from APOGEE DR16 (resolution R = 22 500) data as training set labels. As input, we used parts of the intermediate-resolution RAVE DR6 spectra (R ∼ 7500) overlapping with the APOGEE DR16 data as well as broad-band ALL_WISE and 2MASS photometry, together with Gaia DR2 photometry and parallaxes. ; [Results] We derived precise atmospheric parameters Teff, log(g), and [M/H], along with the chemical abundances of [Fe/H], [α/M], [Mg/Fe], [Si/Fe], [Al/Fe], and [Ni/Fe] for 420 165 RAVE spectra. The precision typically amounts to 60 K in Teff, 0.06 in log(g) and 0.02−0.04 dex for individual chemical abundances. Incorporating photometry and astrometry as additional constraints substantially improves the results in terms of the accuracy and precision of the derived labels, as long as we operate in those parts of the parameter space that are well-covered by the training sample. Scientific validation confirms the robustness of the CNN results. We provide a catalogue of CNN-trained atmospheric parameters and abundances along with their uncertainties for 420 165 stars in the RAVE survey. ; [Conclusions] CNN-based methods provide a powerful way to combine spectroscopic, photometric, and astrometric data without the need to apply any priors in the form of stellar evolutionary models. The developed procedure can extend the scientific output of RAVE spectra beyond DR6 to ongoing and planned surveys such as Gaia RVS, 4MOST, and WEAVE. We call on the community to place a particular collective emphasis and on efforts to create unbiased training samples for such future spectroscopic surveys. ; Funding for RAVE has been provided by: the Leibniz-Institut für Astrophysik Potsdam (AIP); the Australian Astronomical Observatory; the Australian National University; the Australian Research Council; the French National Research Agency (Programme National Cosmology et Galaxies (PNCG) of CNRS/INSU with INP and IN2P3, co-funded by CEA and CNES); the German Research Foundation (SPP 1177 and SFB 881); the European Research Council (ERC-StG 240271 Galactica); the Istituto Nazionale di Astrofisica at Padova; The Johns Hopkins University; the National Science Foundation of the USA (AST-0908326); the W. M. Keck foundation; the Macquarie University; the Netherlands Research School for Astronomy; the Natural Sciences and Engineering Research Council of Canada; the Slovenian Research Agency (research core funding no. P1-0188); the Swiss National Science Foundation; the Science & Technology Facilities Council of the UK; Opticon; Strasbourg Observatory; and the Universities of Basel, Groningen, Heidelberg, and Sydney. TZ acknowledges financial support of the Slovenian Research Agency (research core funding No. P1-0188) and of the ESA project PHOTO2CHEM (C4000127986). FA is grateful for funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 800502. This work has made use of data from the European Space Agency (ESA) mission Gaia (http://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, http://www.cosmos.esa. int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This publication makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation.

Reproduced by permission of the AAS ; We present an overview of the initial results from the Chandra Planetary Nebula Survey (ChanPlaNS), the first systematic (volume-limited) Chandra X-Ray Observatory survey of planetary nebulae (PNe) in the solar neighborhood. The first phase of ChanPlaNS targeted 21 mostly high-excitation PNe within ∼1.5 kpc of Earth, yielding four detections of diffuse X-ray emission and nine detections of X-ray-luminous point sources at the central stars (CSPNe) of these objects. Combining these results with those obtained from Chandra archival data for all (14) other PNe within ∼1.5 kpc that have been observed to date, we find an overall X-ray detection rate of ∼70% for the 35 sample objects. Roughly 50% of the PNe observed by Chandra harbor X-ray-luminous CSPNe, while soft, diffuse X-ray emission tracing shocks—in most cases, "hot bubbles"—formed by energetic wind collisions is detected in ∼30%; five objects display both diffuse and point-like emission components. The presence (or absence) of X-ray sources appears correlated with PN density structure, in that molecule-poor, elliptical nebulae are more likely to display X-ray emission (either point-like or diffuse) than molecule-rich, bipolar, or Ring-like nebulae. All but one of the point-like CSPNe X-ray sources display X-ray spectra that are harder than expected from hot (∼100 kK) central stars emitting as simple blackbodies; the lone apparent exception is the central star of the Dumbbell nebula, NGC 6853. These hard X-ray excesses may suggest a high frequency of binary companions to CSPNe. Other potential explanations include self-shocking winds or PN mass fallback. Most PNe detected as diffuse X-ray sources are elliptical nebulae that display a nested shell/halo structure and bright ansae; the diffuse X-ray emission regions are confined within inner, sharp-rimmed shells. All sample PNe that display diffuse X-ray emission have inner shell dynamical ages 5 × 103 yr, placing firm constraints on the timescale for strong shocks due to wind interactions in PNe. The high-energy emission arising in such wind shocks may contribute to the high excitation states of certain archetypical "hot bubble" nebulae (e.g., NGC 2392, 3242, 6826, and 7009) ; This research was supported via award number GO1-12025A to RIT issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS803060. M.A.G. acknowledges partial support by grant AYA2011-29754-C03-02 of the Spanish MEC (co-funded by FEDER funds). The Digitized Sky Surveys were produced at STScI under U.S. Government Grant NAG W-2166