论文标题

从伽马射线线测量中得出热核超新星性能

Deriving Thermonuclear Supernova Properties from Gamma-Ray Line Measurements

论文作者

Leising, Mark D.

论文摘要

我们说明了用于得出热核或类型IA,超新星的性能的方法,包括合成的$^{56} $ ni质量,总弹出质量,弹射能量和$^{56} $ ni在速度中的分布,来自伽玛射线线的类别。我们为简单的伽马射线仪器模拟了少数已发布的SN IA模型的数据,并通过直接分析来测量其潜在属性。假设球形对称性和同源扩展,我们始终计算所有$^{56} $ CO和$^{56} $ ni线的精确线配置文件,仅需要质量密度的变化和$^{56} $ ni质量分数,并具有扩展质量为输入。通过参数化这些数量,我们迭代参数以符合模拟数据。我们符合多条线的完整配置文件,或者我们在线路上集成,仅适合线路与时间相比。线轮廓拟合更强大,但是无论哪种情况,我们都可以准确地恢复模型的上述属性值,并在线路中有足够的信号噪声。未来的伽马射线任务,具有线敏感性,接近10 $^{ - 6} $ Photons cm $^{ - 2} $ s $^{ - 1} $将对许多SN IA进行测量这些属性,并且每年的精确性和准确性前所未有。我们的分析适用于SN 2014j的$^{56} $ CO行,相对于其他估计,偏爱低$^{56} $ ni质量和低弹出质量。

We illustrate methods for deriving properties of thermonuclear, or Type Ia, supernovae, including synthesized $^{56}$Ni mass, total ejecta mass, ejecta kinetic energy, and $^{56}$Ni distribution in velocity, from gamma-ray line observations. We simulate data from a small number of published SN Ia models for a simple gamma-ray instrument, and measure their underlying properties from straightforward analyses. Assuming spherical symmetry and homologous expansion, we calculate exact line profiles for all $^{56}$Co and $^{56}$Ni lines at all times, requiring only the variation of mass density and $^{56}$Ni mass fraction with expansion velocity as input. By parameterizing these quantities, we iterate the parameters to fit the simulated data. We fit the full profiles of multiple lines, or we integrate over the lines and fit line fluxes only versus time. Line profile fits are more robust, but in either case, we can recover accurately the values of the aforementioned properties of the models simulated, given sufficient signal-to-noise in the lines. A future gamma-ray mission with line sensitivity approaching 10$^{-6}$ photons cm$^{-2}$ s$^{-1}$ would measure these properties for many SN Ia, and with unprecedented precision and accuracy for a few per year. Our analyses applied to the reported $^{56}$Co lines from SN 2014J favor a low $^{56}$Ni mass and low ejecta mass, relative to other estimates.

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