arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2609.10675astro-ph.IM

基于 $\texttt{mirar}$ 框架的 WINTER 近红外巡天数据处理流水线

A data processing pipeline for the WINTER near-infrared surveyor using the $\texttt{mirar}$ framework

Viraj Karambelkar, Robert Stein, Danielle Frostig, Saarah Hall, Mansi M. Kasliwal, Tomás Ahumada, Michael W. Coughlin, Thomas Culino, Kishalay De, Sulekha Kisho… 展开作者

Viraj Karambelkar, Robert Stein, Danielle Frostig, Saarah Hall, Mansi M. Kasliwal, Tomás Ahumada, Michael W. Coughlin, Thomas Culino, Kishalay De, Sulekha Kishore, Theophile Jegou du Laz, Nathan P. Lourie, Geoffrey Mo, Tanishk Mohan, Sam Rose, Benjamin R. Roulston, Aditya Pawan Saikia, Mallika Sheshadri, Robert A. Simcoe, Jamie Soon, Aswin Suresh

首次发表
浏览论文内容

中文总结 AI 辅助

本文介绍基于 mirar 框架的 WINTER 近红外巡天数据处理流水线,实现端到端数据归约与瞬变源探测,并报告了其在天性能及早期科学成果。

中文摘要 AI 辅助

我们介绍了宽视场红外瞬变探测器(WINTER)巡天的数据处理与瞬变源探测流水线,并报告了其在天观测性能。WINTER 相机采用高性价比的 InGaAs 传感器替代传统红外传感器,安装在帕洛马天文台一台专用的 1 米机器人望远镜上。WINTER 相机拥有六个探测器,组合视场为 1.2 平方度,配备 y、J 和缩短 H 波段。WINTER 于 2023 年 6 月首次开光,此后一直以机器人模式运行。WINTER 数据处理流水线($\texttt{winterdrp}$)已在更广泛的框架 $\texttt{mirar}$ 内实现:$\texttt{mirar}$ 是一个模块化的开源 $\texttt{python}$ 包,专为时域巡天图像的实时处理而开发。$\texttt{winterdrp}$ 执行端到端的数据处理,实现数据归约和图像相减,将原始抖动 WINTER 图像转换为 $\texttt{avro}$ 格式的瞬变源警报,随后发送至 $\texttt{SkyPortal}$ 进行审查和后续观测。在 2024 年为期一年的观测中,作为巡天的一部分,WINTER 在 960 秒积分时间内,其六个探测器上的 J 波段中位 5-$\sigma$ 深度范围为 $18.1-18.8$ 星等(AB),天体测量精度约为 $0.2$ 角秒(五分之一像素),探测器性能限制的光度精度在其六个探测器上约为 $0.09-0.18$ 星等。我们展示了 WINTER 的早期科学成果,包括识别出 M31 中的恒星并合事件、银河系盘面中尘埃遮蔽的爆发型年轻恒星天体和经典新星、已知超新星的红外后续观测,以及中微子、引力波、快速 X 射线瞬变源和伽马射线暴的多信使后续观测。

英文摘要

We present the data reduction and transient detection pipeline for the Wide-field Infrared Transient Explorer (WINTER) surveyor and report its on-sky performance. The WINTER camera utilizes cost-effective InGaAs sensors as alternatives to traditional IR sensors, and is mounted on a dedicated 1-m robotic telescope at Palomar Observatory. The WINTER camera has six detectors producing a combined field-of-view of 1.2 sq. deg. equipped with y, J, and shortened-H bands. WINTER saw first light in June 2023 and has been operating robotically since. The WINTER data processing pipeline ($\texttt{winterdrp}$) has been implemented within the broader framework $\texttt{mirar}$: a modular, open-source $\texttt{python}$ package developed for realtime processing of images from time-domain surveys. $\texttt{winterdrp}$ performs end-to-end data processing implementing data reduction and image subtraction to go from raw dithered WINTER images to transient alerts in the $\texttt{avro}$ format, which are then sent to $\texttt{SkyPortal}$ for vetting and follow-up. During a year of observations in 2024, WINTER achieved J-band median 5-$σ$ depths ranging from $18.1-18.8$ mag (AB) on its six detectors in 960 second integrations as part of its survey, with an astrometric accuracy of $\approx0.2$ arcsec (a fifth of a pixel) and a detector-performance limited photometric accuracy ranging from $\approx0.09-0.18$ mag for its six detectors. We present early science results from WINTER, which include the identification of a stellar merger in M31, dust-enshrouded outbursting young stellar objects and classical novae in the Galactic plane, NIR followup of known supernovae, and multi-messenger follow-up of neutrinos, gravitational waves, fast X-ray transients and gamma-ray bursts.

发表机构

  • Columbia University(哥伦比亚大学)
  • University of Maryland, College Park(马里兰大学帕克分校)
  • Joint Space-Science Institute, University of Maryland(马里兰大学联合空间科学研究所)
  • NASA Goddard Space Flight Center(美国宇航局戈达德太空飞行中心)
  • Northwestern University(西北大学)
  • California Institute of Technology(加州理工学院)
  • Cerro Tololo Inter-American Observatory/NSF NOIRLab(北美洲-南美洲天文台/美国国家科学基金会NOIRLab)
  • University of Minnesota(明尼苏达大学)

机构由 AI 辅助整理,请以论文原文为准。

补充信息

↑