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arXiv 1901.05972astro-ph.HEastro-ph.SR
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大质量恒星的宽双星伴星及其在约束出生踢中的应用

Wide binary companions to massive stars and their use in constraining natal kicks

Andrei P. Igoshev, Hagai B. Perets

摘要:

超宽质量双星(轨道间隔$10^3-2\times 10^5$ ~AU)的起源和它们的性质还没有很好的描述和理解。在这里,我们使用第二次盖亚数据发布,以寻找广泛的天体测量同伴银河O-B5恒星共享类似的视差和自行与小学。使用的数据,我们的特点,这样的二进制的频率和属性。我们发现了一个超宽的$4.4\pm0.5$百分比的多重性分数,我们的完整性限制(高达$\approx 17$ ~mag,下降到G-星的距离为0.3-2~kpc,不包括恒星的集群)。次级质量函数通常与克劳帕初始恒星函数一致;如果外推到质量较低的伴星,我们可能会期望得到宽双星分数的$\sim 27\pm5\%$。此外,我们使用这些数据作为验证样本,以测试是否存在超宽双星之间的中子星(NS)和黑洞(BH)。我们建议,发现这样的二进制可以提供独特的约束最弱的出生踢可能的NS/BH。如果一个紧凑的天体形成于一个超宽的双星系统中,并且接收到非常低的出生反冲,这样的双星系统应该作为一个共同的自行双星系统而存在。因此,我们使用盖亚数据来寻找超宽的伴星(正常和毫秒)和X射线双星。我们找不到可靠的配对。未来的数据可能会通过这种方法提供严格的限制。

英文摘要:

The origin of ultra-wide massive binaries (orbital separations $10^3-2\times 10^5$~AU) and their properties are not well characterized nor understood. Here we use the second Gaia data release to search for wide astrometric companions to Galactic O-B5 stars which share similar parallax and proper motion with the primaries. Using the data we characterize the frequency and properties of such binaries. We find an ultra-wide multiplicity fraction of $4.4\pm0.5$ per cent, to our completeness limit (up to $\approx 17$~mag; down to G-stars at distances of 0.3-2~kpc, excluding stars in clusters). The secondary mass-function is generally consistent with a Kroupa initial stellar function; if extrapolated to lower mass companion stars we then might expect a wide-binary fraction of $\sim 27\pm5\%$. In addition we use these data as a verification sample to test the existence of ultra-wide binaries among neutron stars (NSs) and black holes (BHs). We propose that the discovery of such binary can provide unique constraints on the weakest natal kicks possible for NSs/BHs. If a compact object is formed in an ultra-wide binary and receives a very-low natal kick, such a binary should survive as a common proper motion pair. We therefore use Gaia data to search for ultra-wide companions to pulsars (normal and millisecond ones) and X-ray binaries. We find no reliable pairs. Future data could potentially provide stringent constraints through this method.

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