arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1801.01902astro-ph.IMastro-ph.EP
收藏

双子座行星成像仪系外行星巡天的自动数据处理结构

Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey

Jason Wang, Marshall Perrin, Dmitry Savransky, Pauline Arriaga, Jeffrey Chilcote, Robert De Rosa, Maxwell Millar-Blanchaer, Christian Marois, Julien Rameau, Sch… 展开作者

Jason Wang, Marshall Perrin, Dmitry Savransky, Pauline Arriaga, Jeffrey Chilcote, Robert De Rosa, Maxwell Millar-Blanchaer, Christian Marois, Julien Rameau, Schuyler Wolff, Jacob Shapiro, Jean-Baptiste Ruffio, Jérôme Maire, Franck Marchis, James Graham, Bruce Macintosh, S. Mark Ammons, Vanessa Bailey, Travis Barman, Sebastian Bruzzone, Joanna Bulger, Tara Cotten, René Doyon, Gaspard Duchêne, Michael Fitzgerald, Katherine Follette, Stephen Goodsell, Alexandra Greenbaum, Pascale Hibon, Li-Wei Hung, Patrick Ingraham, Paul Kalas, Quinn Konopacky, James Larkin, Mark Marley, Stanimir Metchev, Eric Nielsen, Rebecca Oppenheimer, David Palmer, Jennifer Patience, Lisa Poyneer, Laurent Pueyo, Abhijith Rajan, Fredrik Rantakyrö, Adam Schneider, Anand Sivaramakrishnan, Inseok Song, Remi Soummer, Sandrine Thomas, J. Kent Wallace, Kimberly Ward-Duong, Sloane Wiktorowicz

摘要:

双子座行星成像仪系外行星巡天(GPIES)是一项对600颗恒星进行的多年直接成像巡天,旨在发现和描述年轻的木星系外行星及其环境。我们开发了一个自动化的数据架构,统一处理和索引与调查有关的所有数据。一个自动化和灵活的数据处理框架,我们称之为Data Cruncher,将多个数据简化管道结合在一起,以处理GPIES采集的所有光谱,偏振和校准数据。在没有人为干预的情况下,在获取数据后不到一小时就可以提供经过充分简化和校准的数据产品,以加快对潜在感兴趣物体的后续行动。数据压缩器可以在超级计算机上运行,在一天内重新处理所有GPIES数据,因为我们对数据简化管道进行了改进。后端MySQL数据库索引所有文件,这些文件同步到云,前端Web服务器允许轻松浏览与GPIES相关的所有文件。为了帮助观察者,快速查看显示器在实时处理时显示减少的数据,Slack上的聊天机器人发布观察信息以及减少的数据产品。GPIES自动化数据处理架构减少了我们的工作量,提供了实时数据简化,优化了我们的观测策略,并维护了一个均匀简化的数据集,以研究行星的出现和仪器性能。

英文摘要:

The Gemini Planet Imager Exoplanet Survey (GPIES) is a multi-year direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the Data Cruncher, combines multiple data reduction pipelines together to process all spectroscopic, polarimetric, and calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow-up on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our data reduction pipelines. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real-time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑