论文标题
在$ {\ it gaia}中搜索使用小波转换的矮星系
Searching for Dwarf Galaxies in ${\it Gaia}$ DR2 Phase-Space Data Using Wavelet Transforms
论文作者
论文摘要
我们提出了一种基于小波的算法，以$ {\ it gaia} $ dr2数据以银河系识别矮星系。我们的算法检测到4D位置的过度繁殖 - 培训空间，使其首次搜索明确使用速度信息来搜索矮星系候选者。我们通过搜索注入$ {\ it gaia} $ DR2数据的模拟矮人和已知的银河系卫星星系来优化算法并量化其性能。将我们的结果与以前的光度搜索进行比较，我们发现我们的搜索对未发现的系统敏感〜$ \ $ \ lvert b \ rvert> 20^{\ circ} $，半光线radii大于50％的检测效率阈值，pan-starrs1（ps1 $ {$ {$ { $ 32 $ kpc $ <d <64 $ kpc的距离和（$ {\ it ii} $）$ m_v <-4 $和$ 64 $ kpc $ <d <d <128 $ kpc。基于这些结果，我们预计我们的搜索有望发现$ 5 \ pm 2 $新的卫星星系：PS1足迹中的四个，在黑暗能源调查和PS1足迹之外。我们将算法应用于$ {\ it gaia} $ dr2数据集并恢复$ \ sim 830 $ high-Sigripicance候选人，我们在其中确定了$ \ sim 200 $候选人的“金标准”列表，基于与潜在的候选者进行交叉匹配的候选人，该候选者使用$ {\ IT Gaia $ edr3 data。我们所有的候选人名单均已公开分发，以供将来的后续研究。我们表明，由$ {\ it gaia} $ edr3提供的天文测量改进提高了该技术的敏感性；我们计划继续使用未来的数据发布来完善我们的候选列表。
We present a wavelet-based algorithm to identify dwarf galaxies in the Milky Way in ${\it Gaia}$ DR2 data. Our algorithm detects overdensities in 4D position--proper motion space, making it the first search to explicitly use velocity information to search for dwarf galaxy candidates. We optimize our algorithm and quantify its performance by searching for mock dwarfs injected into ${\it Gaia}$ DR2 data and for known Milky Way satellite galaxies. Comparing our results with previous photometric searches, we find that our search is sensitive to undiscovered systems at Galactic latitudes~$\lvert b\rvert>20^{\circ}$ and with half-light radii larger than the 50% detection efficiency threshold for Pan-STARRS1 (PS1) at (${\it i}$) absolute magnitudes of =$-7<M_V<-3$ and distances of $32$ kpc $< D < 64$ kpc, and (${\it ii}$) $M_V< -4$ and $64$ kpc $< D < 128$ kpc. Based on these results, we predict that our search is expected to discover $5 \pm 2$ new satellite galaxies: four in the PS1 footprint and one outside the Dark Energy Survey and PS1 footprints. We apply our algorithm to the ${\it Gaia}$ DR2 dataset and recover $\sim 830$ high-significance candidates, out of which we identify a "gold standard" list of $\sim 200$ candidates based on cross-matching with potential candidates identified in a preliminary search using ${\it Gaia}$ EDR3 data. All of our candidate lists are publicly distributed for future follow-up studies. We show that improvements in astrometric measurements provided by ${\it Gaia}$ EDR3 increase the sensitivity of this technique; we plan to continue to refine our candidate list using future data releases.
