宽视场红外瞬态探测器（WINTER）
The wide-field infrared transient explorer (WINTER)
摘要：
Wide-Field Infrared Transient Explorer（WINTER）是一种新型的红外时域测量仪器，将部署在Palomar天文台的一个专用1米机器人望远镜上。WINTER将对红外（IR）天空进行一次视见受限的时域调查，特别强调识别LIGO探测到的双星中子星（BNS）合并残留物中的r过程材料。我们描述的科学目标和调查设计的冬季仪器。有了一个专用的触发器和在4小时内将整个LIGO O 4位置误差轮廓映射到190 Mpc距离的能力，WINTER将成为一个强大的千诺瓦发现引擎和多信使天体物理学研究工具。除了对合并双星进行后续观测外，WINTER还将促进广泛的时域天文观测，同时建立适合于测量科学的静态红外天空的深度叠加图像。WINTER的定制相机采用六个商用大幅面铟镓砷（InGaAs）传感器和一个平铺光学系统，覆盖$>$ 1平方度的视场，填充系数为90%。该仪器在Y，J和短H（Hs）波段进行观察，调谐到InGaAs传感器的长波截止，覆盖0.9 - 1.7微米的波长范围。我们介绍了WINTER仪器的设计以及目前在帕洛玛天文台进行最终整合的进展情况，并计划于2021年中期进行调试。
英文摘要：
The Wide-Field Infrared Transient Explorer (WINTER) is a new infrared time-domain survey instrument which will be deployed on a dedicated 1 meter robotic telescope at Palomar Observatory. WINTER will perform a seeing-limited time domain survey of the infrared (IR) sky, with a particular emphasis on identifying r-process material in binary neutron star (BNS) merger remnants detected by LIGO. We describe the scientific goals and survey design of the WINTER instrument. With a dedicated trigger and the ability to map the full LIGO O4 positional error contour in the IR to a distance of 190 Mpc within four hours, WINTER will be a powerful kilonova discovery engine and tool for multi-messenger astrophysics investigations. In addition to follow-up observations of merging binaries, WINTER will facilitate a wide range of time-domain astronomical observations, all the while building up a deep coadded image of the static infrared sky suitable for survey science. WINTER's custom camera features six commercial large-format Indium Gallium Arsenide (InGaAs) sensors and a tiled optical system which covers a $>$1-square-degree field of view with 90% fill factor. The instrument observes in Y, J and a short-H (Hs) band tuned to the long-wave cutoff of the InGaAs sensors, covering a wavelength range from 0.9 - 1.7 microns. We present the design of the WINTER instrument and current progress towards final integration at Palomar Observatory and commissioning planned for mid-2021.
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。
