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arXiv 2303.12432astro-ph.HEastro-ph.SR
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从星云光谱推断剥离包层核心坍缩超新星的前身星质量–动能关系

Inferring the progenitor mass-kinetic energy relation of stripped-envelope core-collapse supernovae from nebular spectroscopy

Qiliang Fang, Keiichi Maeda

AI总结:

本文利用星云光谱中[O I]/[Ca II]与[O I]宽度的相关性,推导剥离包层核心坍缩超新星的CO核质量–动能关系,发现富氦与缺氦亚型遵循同一标度律。

摘要:

前身星质量与爆炸动能之间的关系,是揭示剥离包层(SE)核心坍缩(CC)超新星(SNe)爆炸机制的关键。本文提出一种利用SESNe星云光谱推导该关系的方法,其依据是作为前身星质量指标的[O I]/[Ca II],与用于测量富氧物质膨胀速度的[O I]宽度之间的相关性。为解释这一相关性,动能($E_{\ m K}$)必须与以CO核质量($M_{\ m CO}$)表示的前身星质量呈正相关。我们证明,SNe IIb/Ib与SNe Ic/Ic-BL遵循相同的$M_{\ m CO}$–$E_{\ m K}$标度关系,这表明富氦和缺氦超新星具有相同的爆炸机制。本文得到的$M_{\ m CO}$–$E_{\ m K}$关系与早期阶段观测所得关系进行了比较,结果在很大程度上吻合良好。结合早期阶段观测,本文提出的方法使人们有机会从最外层区域到致密内核扫描整个抛射物,这对于揭示抛射物的整体性质并约束核心坍缩超新星的爆炸机制具有重要意义。

英文摘要:

The relation between the progenitor mass and the kinetic energy of the explosion is a key toward revealing the explosion mechanism of stripped-envelope (SE) core-collapse (CC) supernovae (SNe). Here, we present a method to derive this relation using the nebular spectra of SESNe, based on the correlation between the [O~I]/[Ca~II], which is an indicator of the progenitor mass, and the width of [O~I], which measures the expansion velocity of the oxygen-rich material. To explain the correlation, the kinetic energy ($E_{\rm K}$) is required to be positively correlated with the progenitor mass as represented by the CO core mass ($M_{\rm CO}$). We demonstrate that SNe IIb/Ib and SNe Ic/Ic-BL follow the same $M_{\rm CO}$-$E_{\rm K}$ scaling relation, which suggests the helium-rich and helium-deficient SNe share the same explosion mechanism. The $M_{\rm CO}$-$E_{\rm K}$ relation derived in this work is compared with the ones from early phase observations. The results are largely in good agreement. Combined with early phase observation, the method presented in this work provides a chance to scan through the ejecta from the outermost region to the dense inner core, which is important to reveal the global properties of the ejecta and constrain the explosion mechanism of core-collapse supernovae.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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