19,253 research outputs found

    Seismic analysis of 70 Ophiuchi A: A new quantity proposed

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    The basic intent of this paper is to model 70 Ophiuchi A using the latest asteroseismic observations as complementary constraints and to determine the fundamental parameters of the star. Additionally, we propose a new quantity to lift the degeneracy between the initial chemical composition and stellar age. Using the Yale stellar evolution code (YREC7), we construct a series of stellar evolutionary tracks for the mass range MM = 0.85 -- 0.93 MM_{\odot} with different composition YiY_{i} (0.26 -- 0.30) and ZiZ_{i} (0.017 -- 0.023). Along these tracks, we select a grid of stellar model candidates that fall within the error box in the HR diagram to calculate the theoretical frequencies, the large- and small- frequency separations using the Guenther's stellar pulsation code. Following the asymptotic formula of stellar pp-modes, we define a quantity r01r_{01} which is correlated with stellar age. Also, we test it by theoretical adiabatic frequencies of many models. Many detailed models of 70 Ophiuchi A have been listed in Table 3. By combining all non-asteroseismic observations available for 70 Ophiuchi A with these seismological data, we think that Model 60, Model 125 and Model 126, listed in Table 3, are the optimum models presently. Meanwhile, we predict that the radius of this star is about 0.860 -- 0.865 RR_{\odot} and the age is about 6.8 -- 7.0 Gyr with mass 0.89 -- 0.90 MM_{\odot}. Additionally, we prove that the new quantity r01r_{01} can be a useful indicator of stellar age.Comment: 23 pages, 5 figures, accepted by New Astronom

    Asteroseismic study of solar-like stars: A method of estimating stellar age

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    Asteroseismology, as a tool to use the indirect information contained in stellar oscillations to probe the stellar interiors, is an active field of research presently. Stellar age, as a fundamental property of star apart from its mass, is most difficult to estimate. In addition, the estimating of stellar age can provide the chance to study the time evolution of astronomical phenomena. In our poster, we summarize our previous work and further present a method to determine age of low-mass main-sequence star.Comment: 2 pages, 1 figures, submitted to IAUS25

    Reversible dynamic isomerism change in the solid state, from Bi4I16 clusters to BiI4 1D chains in L-cystine based hybrids: templating effect of cations in iodobismuthate network formation

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    The dehydration of a iodobismuthate hybrid built up from Bi4I16 clusters and protonated L-cystine molecules involves an unprecedented reversible dynamic structural change in the solid state leading to 1D BiI4 chains and 1D helical molecular chains, highlighting the templating effect of cations in the formation of iodobismuthate network

    Is the cosmic UV background fluctuating at redshift z ~ 6 ?

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    We study the Gunn-Peterson effect of the photo-ionized intergalactic medium(IGM) in the redshift range 5< z <6.4 using semi-analytic simulations based on the lognormal model. Assuming a rapidly evolved and spatially uniform ionizing background, the simulation can produce all the observed abnormal statistical features near redshift z ~ 6. They include: 1) rapidly increase of absorption depths; 2) large scatter in the optical depths; 3) long-tailed distributions of transmitted flux and 4) long dark gaps in spectra. These abnormal features are mainly due to rare events, which correspond to the long-tailed probability distribution of the IGM density field, and therefore, they may not imply significantly spatial fluctuations in the UV ionizing background at z ~ 6.Comment: 12 pages, 4 figs, accepted by ApJ

    Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs)

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    Positron emission tomography (PET) image synthesis plays an important role, which can be used to boost the training data for computer aided diagnosis systems. However, existing image synthesis methods have problems in synthesizing the low resolution PET images. To address these limitations, we propose multi-channel generative adversarial networks (M-GAN) based PET image synthesis method. Different to the existing methods which rely on using low-level features, the proposed M-GAN is capable to represent the features in a high-level of semantic based on the adversarial learning concept. In addition, M-GAN enables to take the input from the annotation (label) to synthesize the high uptake regions e.g., tumors and from the computed tomography (CT) images to constrain the appearance consistency and output the synthetic PET images directly. Our results on 50 lung cancer PET-CT studies indicate that our method was much closer to the real PET images when compared with the existing methods.Comment: 9 pages, 2 figure
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