3U Transat：一个用于推动多信使天文学发展的立方星星座
3U Transat: a cubesat constellation to boost the multi-messenger astronomy
AI总结：
本文提出3U Transat纳卫星星座项目，通过低成本实现全天高能电磁监测，以提升引力波与中微子事件的多信使电磁对应体探测率，并介绍其科学目标、现状及模拟优化性能。
摘要：
得益于灵敏的引力波（GW）和中微子探测器的问世，多信使（MM）天文学将深刻改变我们对宇宙内容及其在宇宙学时间尺度上演化的理解。为了充分利用即将到来的引力波和中微子发现，尽可能多地探测电磁（EM）对应体至关重要，但迄今为止，只有一个事件被引力波探测器（Ligo/Virgo）和电磁探测器（Fermi/GBM（伽马射线暴监视器）和 Integral）同时探测到，即与双中子星并合相关的短伽马射线暴 GRB 170817A/GW 170817。为了帮助提高联合多信使事件的发生率，对于空间中的高能电磁探测器来说，以良好的灵敏度观测整个天空至关重要。为此，我们提出开发 3U Transat（TRANsient sky SATellites，瞬变天空卫星）项目。3U Transat 是一个纳卫星星座，以有限的投入提供全天覆盖。本文的目标是介绍 3U Transat 项目及其主要科学驱动因素和当前状态。我们还将描述我们用于优化星座科学性能的动态模拟器。我们将展示作为星座中卫星数量函数的预期探测和定位能力亮点。
英文摘要：
Thanks to the advent of sensitive gravitational wave (GW) and neutrino detectors, multi-messenger (MM) astronomy will deeply transform our understanding of the Universe contents and evolution over cosmological times. To fully exploit the forthcoming GW and neutrino discoveries, it is crucial to detect as many electromagnetic (EM) counterparts as possible, but up to now, only one event has been detected by both GW detectors (Ligo/Virgo) and electromagnetic detectors (Fermi/GBM (Gamma ray Burst Monitor) and Integral), the short gamma-ray burst GRB 170817A/GW 170817 associated with the merger of a binary neutron star. To help improving the rate of joint MM events, it is crucial for the EM detectors in particular at high-energy in space to observe all the sky with a decent sensitivity. To do so, we propose the development of 3U Transat (TRANsient sky SATellites) project. 3U Transat is a constellation of nano-satellites offering a full sky coverage with a limited investment. The goal of this article is to present the 3U Transat project and its main scientific drivers as well as its current status. We will also describe our dynamic simulator used to optimise the scientific performances of the constellation. We will show highlights of the expected performances in term of detection and localisation capabilities as a function of the number of satellites in the constellation.
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。
