Gaia Data Release 2
Gaia Data Release 2
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DOI：
10.1051/0004-6361/201833357
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发表时间：
2018-05
影响因子：
6.5
通讯作者：
L. Eyer;L. Rimoldini;M. Audard;R. I. Anderson;K. Nienartowicz;F. Glass;O. Marchal;M. Grenon;
中科院分区：
文献类型：
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作者：
L. Eyer;L. Rimoldini;M. Audard;R. I. Anderson;K. Nienartowicz;F. Glass;O. Marchal;M. Grenon;
目标。我们描述了所使用的方法和进行的分析框架中的盖亚数据处理活动，以产生盖亚数据发布2（DR 2）的候选样本与相关参数的短时间尺度的变化。方法.盖亚DR 2样本的候选者具有短时间尺度的可变性，来自盖亚G per-CCD，GBP和GRP测光的前22个月的研究，用于盖亚暗端（G ~ 16.5−20等）的子样本源。对于利用盖亚数据的第一次短时间尺度变化搜索，我们将自己限制在可疑的快速周期性变化的情况下。我们的研究结合了通过变差函数分析进行的快速变差检测，通过最小二乘周期图进行的高频搜索，以及基于对通过盖亚眼睛看到的特定来源的调查的经验选择（例如，已知的变量或在其光变曲线中具有特殊特征的视觉识别对象）。这一选择标准的逐步定义、改进和验证也得益于2017年8月至11月在西班牙加那利群岛拉帕尔马的佛兰芒墨卡托望远镜对几十个具有短期变化的初步候选者进行的补充地面光度监测。结果作为盖亚DR 2的一部分，我们发布了一份包含3018个候选者的名单，这些候选者具有短时间尺度的变化，分布在整个天空中，麦哲伦云的假阳性率高达10-20%，并且根据天空的面积，19%到50%之间的较长周期变量的污染更显着但合理。虽然它的完整性被限制在0.05%左右，但盖亚短时间尺度变星的第一个样本恢复了一些非常有趣的已知短周期变星，例如后共同包络双星或灾难变星，并揭示了一些迷人的，新发现的变星源。在未来的盖亚数据发布的角度来看，几个改进的短时间尺度的变异性处理被认为是通过增强现有的变差函数和周期搜索算法或通过分类确定的变异候选人。尽管如此，我们的盖亚DR 2分析的令人鼓舞的结果证明了这种快速变化研究的使命的力量，并为天体物理学的这一领域开辟了广阔的前景。
Aims. We describe the methods used and the analysis performed in the frame of the Gaia data processing activities to produce the Gaia Data Release 2 (DR2) sample candidates with short-timescale variability together with associated parameters. Methods. The Gaia DR2 sample of candidates with short-timescale variability results from the investigation of the first 22 months of Gaia G per-CCD, GBP, and GRP photometry for a subsample of sources at the Gaia faint end (G ~ 16.5−20 mag). For this first short-timescale variability search exploiting Gaia data, we limited ourselves to the case of suspected rapid periodic variability. Our study combines fast-variability detection through variogram analysis, a high-frequency search by means of least-squares periodograms, and an empirical selection based on the investigation of specific sources seen through the Gaia eyes (e.g., known variables or visually identified objects with peculiar features in their light curves). The progressive definition, improvement, and validation of this selection criterion also benefited from supplementary ground-based photometric monitoring of a few tens of preliminary candidates with short-timescale variability, performed at the Flemish Mercator telescope in La Palma (Canary Islands, Spain) between August and November 2017. Results. As part of Gaia DR2, we publish a list of 3018 candidates with short-timescale variability, spread throughout the sky, with a false-positive rate of up to 10–20% in the Magellanic Clouds, and a more significant but justifiable contamination from longer-period variables between 19% and 50%, depending on the area of the sky. Although its completeness is limited to about 0.05%, this first sample of Gaia short-timescale variables recovers some very interesting known short-period variables, such as post-common envelope binaries or cataclysmic variables, and brings to light some fascinating, newly discovered variable sources. In the perspective of future Gaia data releases, several improvements of the short-timescale variability processing are considered, by enhancing the existing variogram and period-search algorithms or by classifying the identified variability candidates. Nonetheless, the encouraging outcome of our Gaia DR2 analysis demonstrates the power of this mission for such fast-variability studies, and opens great perspectives for this domain of astrophysics.