Space and planetary physics 2022-2025

我们将开展一项广泛的工作计划，研究太阳、星际空间以及太阳系中的几个行星和卫星。我们选择的项目涉及存在于太空中的一些最基本的过程：因此，我们工作的许多方面可以应用于其他太阳系或整个宇宙的其他空间环境。我们还研究星际空间的一些方面，这些方面最终将有助于我们更好地预测那里的条件，特别是那些靠近地球的地方，在那里，它们可能会伤害宇航员，破坏卫星，甚至地面的电力系统。通过这种方式，我们有助于预测这样的“太空天气”，并改善整个社会。空间充满了少量的带电粒子，称为等离子体，以及磁场和电场。空间等离子体中发生的一个基本过程是磁重联，它发生在非常小的尺度上，但释放出磁能，并在大尺度上加速粒子。我们将研究航天器重新连接的测量结果，并确定能量是如何在重新连接地点周围转换和传输的。在非常大的尺度上，日冕物质抛射从太阳释放出来，当它们到达地球附近时，可能会引起空间天气影响。我们将使用许多航天器的测量结果来研究这些结构在穿过太阳系时如何演变，以更好地了解太空天气风险。我们将使用相同的一套航天器，其中一些非常接近太阳，来研究从它流出的太阳风等离子体中的小尺度结构。这些“折返”将能量带到太空，但它们在太阳上的来源尚不清楚。我们还将分析太阳风中一些非常小的尺度，质子在磁场中旋转，并模拟它们的行为，以了解粒子离开太阳时粒子的分布是如何演变的。我们还对太阳系中行星和卫星周围的环境感兴趣。木卫三是太阳系中最大的行星木星的卫星。木卫三是一个高度优先的科学目标，因为它是已知的唯一有磁场的卫星，也是极少数可能有次表层海洋的卫星之一。它与木星的等离子体和磁场相互作用，我们将开发一个先进的模型来模拟这种相互作用。距离太阳最近的行星水星也有磁场，当它与流经的太阳风相互作用时，会产生许多波。我们将研究这些波如何加速行星周围的粒子。我们在研究太阳系外的气态巨行星方面有很长的历史。在土星，我们将研究其大气中的高波；这种波也存在于地球上，通过研究土星上的波，我们将了解土星大气的全球循环，以及它是如何耦合到行星周围的太空中的。最后，我们将改进对外行星周围空间进行计算机模拟的方式。与建模师合作，我们将利用我们的理论知识在模型中加入几个关键的物理效应，以便我们能够提高它们的质量和预测能力。

We will undertake a broad programme of work studying the Sun, interplanetary space and several of the planets and moons in our Solar System. We choose projects that address some of the most fundamental processes that exist in space: as a result, many aspects of our work can be applied to other solar systems, or other space environments throughout the Universe. We also study aspects of interplanetary space that will ultimately help us better predict conditions there, and especially those near the Earth, where they can harm astronauts and damage satellites and even electrical systems on the ground. In this way, we help to predict such "space weather" and improve society at large. Space is filled with small amounts of charged particles, called a plasma, along with magnetic and electric fields. One fundamental process that occurs in space plasmas is magnetic reconnection, which occurs on very small scales but releases magnetic energy and accelerates particles on large scales. We will study spacecraft measurements of reconnection and determine how energy is converted and transported around reconnection sites.At the very large scale, coronal mass ejections are released from the Sun and can cause space weather effects when they arrive near the Earth. We will use measurements from many spacecraft to study how these structures evolve as they travel through the solar system to better understand the space weather risk.We will use the same set of spacecraft, some of which travel very close to the Sun, to study small scale structures in the solar wind plasma that flows away from it. These "switchbacks" carry energy into space, but their source on the Sun is unknown.We will also analyse some of the very smallest scales in the solar wind, over which protons gyrate around the magnetic field, and simulate their behaviour in order to understand how the distribution of particles evolves as the they travel away from the Sun.We are also interested in the environment around planets and moons in the solar system. Ganymede is a moon of Jupiter, the largest planet in the solar system. Ganymede is a high priority science target because it is the only moon known to have a magnetic field and one of very few to probably have a subsurface ocean. It interacts with Jupiter's plasma and magnetic field and we will develop an advanced model to simulate this interaction.The closest planet to the Sun, Mercury, also has a magnetic field and as it interacts with the solar wind flowing past, many waves are generated. We will study how these waves can accelerate particles around the planet.We have a long history of studying the gas giant planets of the outer solar system. At Saturn, we will study waves high in its atmosphere; such waves also exist at the Earth and by studying those at Saturn, we will learn about the global circulation of Saturn's atmosphere and how it couples into space around the planet.Finally, we will improve the way that we can run computer simulations of space around the outer planets. Working with modellers we will use our theoretical knowledge to include several key physical effects into the models so that we can improve their quality and predictive power.