论文标题
很少有两个（或更多）星体观测值的观察二进制轨道求解器（FOBO）
Few Observation Binary Orbit Solver (FOBOS) from two (or more) astrometric observations
论文作者
论文摘要
我们开发了一种新的快速方法，用于估算二进制或三重系统的轨道性质，使用了少于两个时期的天体数据。 FOBOS（很少的观察二进制轨道求解器）使用平坦的先前的蛮力蒙特卡洛法来产生可能的轨道参数的概率密度函数。我们在假观测上测试了代码，并表明它可以（经常）将半轴轴限制为2-3倍以内，而倾斜度仅在$ \ sim $ 20 $ 20 $^{\ circ} $之内，只有两个星体观测值。我们还表明，68％和95％的置信区间在统计上是可靠的。将此方法应用于三重系统，可以限制二级和三级恒星轨道的相对倾斜。 FOBO通常可以在二进制系统中为CPU分钟找到统计学数量的可能匹配，而三重系统的CPU小时。
We have developed a new, fast method of estimating the orbital properties of a binary or triple system using as few as two epochs of astrometric data. FOBOS (Few Observation Binary Orbit Solver) uses a flat prior brute force Monte Carlo method to produce probability density functions of the likely orbital parameters. We test the code on fake observations and show that it can (fairly often) constrain the semi-major axis to within a factor of 2-3, and the inclination to within $\sim$20$^{\circ}$ from only two astrometric observations. We also show that the 68 and 95 per cent confidence intervals are statistically reliable. Applying this method to triple systems allows the relative inclination of the secondary and tertiary star orbits to be constrained. FOBOS can usually find a statistically significant number of possible matches in CPU minutes for binary systems, and CPU hours for triple systems.
