Proton auroras are widely observed on the day side of Mars, identified as a significant intensity enhancement in the hydrogen Ly alpha (121.6 nm) emission between 120 and 150~km altitudes. Solar wind protons penetrating as energetic neutral atoms into the Martian thermosphere are thought to be responsible for these auroras. Understanding proton auroras is therefore important for characterizing the solar wind interaction with the atmosphere of Mars. Recent observations of spatially localized "patchy" proton auroras suggest a possible direct deposition of protons into the atmosphere of Mars during unstable solar wind conditions. Here, we develop a purely data-driven model of proton auroras using Mars Atmosphere and Volatile EvolutioN (MAVEN) in situ observations and limb scans of Ly alpha emissions between 2014 and 2022. We train an artificial neural network that reproduces individual Ly alpha intensities with a Pearson correlation of 0.95 along with a faithful reconstruction of the observed Ly alpha emission altitude profiles. By performing a SHapley Additive exPlanations (SHAP) analysis, we find that Solar Zenith Angle, seasonal CO2 atmosphere variability, solar wind temperature, and density are the most important features for the modelled proton auroras. We also demonstrate that our model can serve as an inexpensive tool for simulating and characterizing Ly alpha response under a variety of seasonal and upstream solar wind conditions.

翻译：质子极光广泛存在于火星昼侧，表现为氢莱曼α（121.6纳米）辐射在120至150公里高度范围内的显著强度增强。一般认为，太阳风质子以高能中性原子形式进入火星热层是产生这类极光的原因。因此，理解质子极光对于表征太阳风与火星大气的相互作用具有重要意义。近期观测到的空间局域化"斑块状"质子极光表明，在不稳定的太阳风条件下，质子可能直接沉降进入火星大气。本文基于火星大气与挥发性演化探测器（MAVEN）2014至2022年间的在位观测数据及莱曼α辐射临边扫描数据，构建了一个纯数据驱动的质子极光模型。我们训练的人工神经网络能够以0.95的皮尔逊相关系数重现单个莱曼α强度，并忠实还原观测到的莱曼α辐射高度廓线。通过夏普利加法解释（SHAP）分析，我们发现太阳天顶角、季节性二氧化碳大气变化、太阳风温度和密度是模型化质子极光的最重要特征。研究还表明，该模型可作为模拟和表征不同季节及上游太阳风条件下莱曼α辐射响应的低成本工具。