$\tt{KOBEsim}$：一种用于径向速度盲查行星探测的贝叶斯观测策略算法
$\tt{KOBEsim}$: a Bayesian observing strategy algorithm for planet detection in radial velocity blind-search surveys
摘要：
在系外行星跟踪和定性时代，地面观测时间非常宝贵，特别是在高精度径向速度仪器方面。因此，盲目搜索径向速度调查需要一个专门的观测战略，以优化观测时间，这对于在大轨道周期探测小岩石世界特别重要。我们开发了一种算法，其目的是提高效率的径向速度观测的背景下，系外行星搜索，我们将其应用于K-矮星轨道的可居住系外行星（神户）实验。我们的目标是加速系外行星的确认，或者尽早拒绝错误信号，以节省望远镜的时间，提高盲目搜索调查和过境候选人后续行动的效率。一旦达到径向速度数据点的最小初始数量，以这样一种方式，即周期性开始出现根据广义Lomb-Scargle（GLS）周期图，该周期的目标是与所提出的算法，命名为$\texttt{KOBEsim}$。该算法选择的下一个观测日期，最大限度地提高贝叶斯证据的这种周期性相比，没有开普勒轨道的模型。通过模拟数据，我们证明了该算法与传统的单调节奏策略相比，具有更少的观测数据和更少的低质量行星完整数据集（$41 - 47\,\%$）的时间跨度，从而加速了系外行星的探测。$20\,M_{\oplus}$行星数据点数量的增加也是明显的，$16\,\%$。我们还测试了$\texttt{KOBEsim}$与实际数据的一个特定的神户目标，并确认行星$HD~102365\,b$。这两个结果都表明，该策略能够将检测速度提高到$2$的一个因子。
英文摘要：
Ground-based observing time is precious in the era of exoplanet follow-up and characterization, especially in high-precision radial velocity instruments. Blind-search radial velocity surveys thus require a dedicated observational strategy in order to optimize the observing time, which is particularly crucial for the detection of small rocky worlds at large orbital periods. We develop an algorithm with the purpose of improving the efficiency of radial velocity observations in the context of exoplanet searches, and we apply it to the K-dwarfs Orbited By habitable Exoplanets (KOBE) experiment. We aim at accelerating exoplanet confirmations or, alternatively, rejecting false signals as early as possible in order to save telescope time and increase the efficiency of both blind-search surveys and follow-up of transiting candidates. Once a minimum initial number of radial velocity datapoints is reached in such a way that a periodicity starts to emerge according to generalized Lomb-Scargle (GLS) periodograms, that period is targeted with the proposed algorithm, named $\texttt{KOBEsim}$. The algorithm selects the next observing date that maximizes the Bayesian evidence for such periodicity in comparison with a model with no Keplerian orbits. By means of simulated data, we prove that the algorithm accelerates the exoplanet detection, needing $29 - 33\,\%$ less observations and $41 - 47\,\%$ less timespan of the full dataset for low-mass planets ($m_{\rm p}\,<\,10\,M_{\oplus}$) in comparison with a conventional monotonic cadence strategy. The enhancement in the number of datapoints for $20\,M_{\oplus}$ planets is also appreciable, $16\,\%$. We also test $\texttt{KOBEsim}$ with real data for a particular KOBE target, and for the confirmed planet $HD~102365\,b$. Both of them demonstrate that the strategy is capable of speeding up the detection up to a factor of $2$.
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