oxygen abundance
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2022 ◽  
Vol 924 (2) ◽  
pp. 44
Author(s):  
Erin Aadland ◽  
Philip Massey ◽  
D. John Hillier ◽  
Nidia Morrell

Abstract We present a spectral analysis of four Large Magellanic Cloud (LMC) WC-type Wolf–Rayet (WR) stars (BAT99-8, BAT99-9, BAT99-11, and BAT99-52) to shed light on two evolutionary questions surrounding massive stars. The first is: are WO-type WR stars more oxygen enriched than WC-type stars, indicating further chemical evolution, or are the strong high-excitation oxygen lines in WO-type stars an indication of higher temperatures. This study will act as a baseline for answering the question of where WO-type stars fall in WR evolution. Each star’s spectrum, extending from 1100 to 25000 Å, was modeled using cmfgen to determine the star’s physical properties such as luminosity, mass-loss rate, and chemical abundances. The oxygen abundance is a key evolutionary diagnostic, and with higher resolution data and an improved stellar atmosphere code, we found the oxygen abundance to be up to a factor of 5 lower than that of previous studies. The second evolutionary question revolves around the formation of WR stars: do they evolve by themselves or is a close companion star necessary for their formation? Using our derived physical parameters, we compared our results to the Geneva single-star evolutionary models and the Binary Population and Spectral Synthesis (BPASS) binary evolutionary models. We found that both the Geneva solar-metallicity models and BPASS LMC-metallicity models are in agreement with the four WC-type stars, while the Geneva LMC-metallicity models are not. Therefore, these four WC4 stars could have been formed either via binary or single-star evolution.


2021 ◽  
Vol 13 (17) ◽  
pp. 3440
Author(s):  
Loredana Perrone ◽  
Andrey V. Mikhailov ◽  
Dario Sabbagh

For the first time thermospheric parameters (neutral composition, exospheric temperature and vertical plasma drift related to thermospheric winds) have been inferred for ionospheric G-conditions observed with Millstone Hill ISR on 11–13 September 2005; 13 June 2005, and 15 July 2012. The earlier developed method to extract a consistent set of thermospheric parameters from ionospheric observations has been revised to solve the problem in question. In particular CHAMP/STAR and GOCE neutral gas density observations were included into the retrieval process. It was found that G-condition days were distinguished by enhanced exospheric temperature and decreased by ~2 times of the column atomic oxygen abundance in a comparison to quiet reference days, the molecular nitrogen column abundance being practically unchanged. The inferred upward plasma drift corresponds to strong ~90 m/s equatorward thermospheric wind presumably related to strong auroral heating on G-condition days.


2021 ◽  
Vol 13 (8) ◽  
pp. 1514
Author(s):  
Andrey V. Mikhailov ◽  
Loredana Perrone ◽  
Anatoly A. Nusinov

European near-noontime ionosonde observations were considered during the period of deep solar minimum in 2008–2009 to analyze foF2 perturbations not related to solar and geomagnetic activity. Sudden stratospheric warming (SSWs) events in January 2008 and 2009 were analyzed. An original method was used to retrieve aeronomic parameters from observed electron concentration in the ionospheric F-region. Atomic oxygen was shown to be the main aeronomic parameter responsible both for the observed day-to-day and long-term (during SSWs) foF2 variations. Atomic oxygen rather than neutral temperature mainly controls the decrease of thermospheric neutral gas density in the course of the SSW events. Day-to-day variations of thermospheric circulation and an intensification of eddy diffusion during SSWs are suggested to be the processes changing the atomic oxygen abundance in the upper atmosphere for the periods in question. Recent Global-Scale Observations of the Limb and Disk (GOLD) observations of O/N2 column density confirm the depletion of the atomic oxygen abundance not related to geomagnetic activity during SSWs.


2021 ◽  
Vol 908 (2) ◽  
pp. 165
Author(s):  
Zachary J. Pace ◽  
Christy Tremonti ◽  
Adam L. Schaefer ◽  
David V. Stark ◽  
Catherine A. Witherspoon ◽  
...  

Author(s):  
Joice Mathew ◽  
James Gilbert ◽  
Robert Sharp ◽  
Alexey Grigoriev ◽  
Shanae King ◽  
...  

2020 ◽  
Vol 161 (1) ◽  
pp. 9
Author(s):  
Mariagrazia Franchini ◽  
Carlo Morossi ◽  
Paolo Di Marcantonio ◽  
Miguel Chavez ◽  
Vardan Adibekyan ◽  
...  

2020 ◽  
Vol 643 ◽  
pp. A142
Author(s):  
M. Cubas Armas ◽  
A. Asensio Ramos ◽  
H. Socas-Navarro

Aims. We report the results of a novel determination of the solar oxygen abundance using spatially resolved observations and inversions. We seek to derive the photospheric solar oxygen abundance with a method that is robust against uncertainties in the model atmosphere. Methods. We use observations with spatial resolution obtained at the Vacuum Tower Telescope to derive the oxygen abundance at 40 different spatial positions in granules and intergranular lanes. We first obtain a model for each location by inverting the Fe I lines with the NICOLE inversion code. These models are then integrated into a hierarchical Bayesian model that is used to infer the most probable value for the oxygen abundance that is compatible with all the observations. The abundance is derived from the [O I] forbidden line at 6300 Å taking into consideration all possible nuisance parameters that can affect the abundance. Results. Our results show good agreement in the inferred oxygen abundance for all the pixels analyzed, demonstrating the robustness of the analysis against possible systematic errors in the model. We find a slightly higher oxygen abundance in granules than in intergranular lanes when treated separately (log(ϵO) = 8.83 ± 0.02 vs. log(ϵO) = 8.76 ± 0.02), which is a difference of approximately 2-σ. This tension suggests that some systematic errors in the model or the radiative transfer still exist but are small. When taking all pixels together, we obtain an oxygen abundance of log(ϵO) = 8.80 ± 0.03, which is compatible with both granules and lanes within 1-σ. The spread of results is due to both systematic and random errors.


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