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首页> 外文期刊>The Astrophysical journal >Quantifying the Uncertainty in the Orbits of Extrasolar Planets
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Quantifying the Uncertainty in the Orbits of Extrasolar Planets

机译:量化太阳系外行星轨道的不确定性

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Precise radial velocity measurements have led to the discovery of ~100 extrasolar planetary systems. We investigate the uncertainty in the orbital solutions that have been fitted to these observations. Understanding these uncertainties will become more and more important as the discovery space for extrasolar planets shifts to longer and longer periods. While detections of short-period planets can be rapidly refined, planets with long orbital periods will require observations spanning decades to constrain the orbital parameters precisely. Already in some cases, multiple distinct orbital solutions provide similarly good fits, particularly in multiple-planet systems. We present a method for quantifying the uncertainties in orbital fits and addressing specific questions directly from the observational data rather than relying on best-fit orbital solutions. This Markov chain Monte Carlo (MCMC) technique has the advantage that it is well suited to the high-dimensional parameter spaces necessary for the multiple-planet systems. We apply the MCMC technique to several extrasolar planetary systems, assessing the uncertainties in orbital elements for several systems. Our MCMC simulations demonstrate that for some systems there are strong correlations between orbital parameters and/or significant non-Gaussianities in parameter distributions, even though the measurement errors are nearly Gaussian. Once these effects are considered, the actual uncertainties in orbital elements can be significantly larger or smaller than the published uncertainties. We also present simple applications of our methods, such as predicting the times of possible transits for GJ 876.
机译:精确的径向速度测量导致发现了约100个太阳系外行星系统。我们调查了适合这些观测结果的轨道解的不确定性。随着太阳系外行星的发现空间越来越长,理解这些不确定性将变得越来越重要。虽然可以快速完善对短周期行星的探测,但具有长轨道周期的行星将需要跨越数十年的观测来精确地约束轨道参数。在某些情况下,多个不同的轨道解决方案已经提供了类似的良好拟合,尤其是在多行星系统中。我们提出了一种量化轨道拟合不确定性和直接从观测数据中解决特定问题的方法,而不是依赖于最佳拟合轨道解决方案。马尔可夫链蒙特卡洛(MCMC)技术的优势在于,它非常适合多行星系统所需的高维参数空间。我们将MCMC技术应用于几个太阳系外行星系统,评估几个系统的轨道要素的不确定性。我们的MCMC仿真表明,对于某些系统,即使测量误差接近高斯,在轨道参数和/或参数分布中的重要非高斯性之间也存在很强的相关性。一旦考虑了这些影响,轨道元素中的实际不确定性可能会大大大于或小于已公布的不确定性。我们还介绍了我们方法的简单应用,例如预测GJ 876可能通过的时间。

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