Radial interplanetary fields at Comets and Mars

太阳系中的物体嵌入太阳风中，它们如何与太阳风相互作用取决于它们的大气和磁场。没有全球磁场的天体，如火星和彗星，会形成一个感应磁层。该区域是一个理想的等离子体实验室，由不同的离子种类和尘埃颗粒组成，可以由航天器探索。了解环境对于未来人类的探索和我们对太阳系的了解至关重要，决定相互作用区域形状的主要参数之一是行星际磁场（IMF）的方向。大多数模型假设场的统一“标准”方向，这通常会给出很好的结果。然而，IMF是高度可变的，很大一部分的情况下是不包括在literations.Plasma观测在火星和彗星67 P/Churyumov-Gerasimenko最近显示不寻常的波和粒子活动，是不包括在标准模型，这是由于径向IMF配置。在这些情况下，环境可以完全改变，离子逃逸和加速率也会有很大的不同。这对行星大气模型和彗星尾部观测的影响知之甚少。这是一个知识空白，应该填补之前即将到来的使命彗星拦截器将遇到一颗彗星，并采取多点测量在这种环境中的第一次。了解在这些特殊条件下的环境的关键是将现有的数值和分析模型的观测和建立新的模型，更好地描述非标准的情况。

Objects in the solar system are embedded in the solar wind and how they interact with it depends on their atmosphere and magnetic fields. Bodies without a global magnetic field, like Mars and comets, develop an induced magnetosphere. This region is an ideal plasma laboratory consisting of different ion species and dust particles that can be explored by spacecraft. Understanding the environment is crucial for future human exploration and our understanding of the solar system.One of the main parameters determining the shape of the interaction region is the direction of the interplanetary magnetic field (IMF). Most models assume a unified "standard" direction of the field, which often gives good results. However, the IMF is highly variable, and a large part of cases is not covered in literature.Plasma observations at both Mars and comet 67P/Churyumov-Gerasimenko recently showed unusual wave and particle activity that was not covered by the standard models, and which were attributed to a radial IMF configuration. For these cases the environment can change completely, and ion escape and acceleration rates are dramatically different. This has consequences for planetary atmospheric models and cometary tail observations that are poorly understood. This is a knowledge gap that should be filled before the upcoming mission Comet Interceptor will encounter a comet and take multi-point measurements in this environment for the first time.The key to understanding the environment under these special conditions is to relate existing numerical and analytical models to the observations and build new models that better describe the non-standard cases.