标题： 太阳粒子事件对空间辐射屏蔽的影响：使用QAOA和VQE算法的OLTARIS模拟和材料选择的量子优化 显示英文标题

标题： Impact of Solar Particle Events on Space Radiation Shielding: OLTARIS Simulation and Quantum Optimization of Material Selection using QAOA and VQE Algorithms

摘要： 太空辐射对长期载人航天任务构成重大挑战，其来源包括银河宇宙射线、太阳粒子事件以及范艾伦带中的 trapped 粒子。 这些高能辐射会对宇航员造成严重的生物效应，并退化航天器系统，因此有效的屏蔽至关重要。 传统上使用如铝等被动屏蔽材料，但它们的局限性，尤其是在产生次级辐射方面，需要更好的替代方案。 在本研究中，使用 NASA 开发的工具 OLTARIS，在 GCR 和 SPE 环境中评估了锂氢化物、聚乙烯、锂硼氢化物、铍硼氢化物和氨硼烷等屏蔽材料的性能。 1989 年 10 月的 SPE 被用于研究粒子通量和剂量分布。 屏蔽效果因环境而异。 在 SPE 中，铍硼氢化物表现最好，而在 GCR 中，锂氢化物给出最低的剂量。 在 SPE 中，性能与氢含量有关。 还研究了太阳调制对 GCR 剂量的影响。 较高的调制会降低 GCR 强度和剂量。 高能空间辐射和材料组合的复杂性带来了计算挑战。 为了解决这个问题，将材料选择问题建模为无约束二次二进制优化问题，并使用变分量子本征求解器和量子近似优化算法进行求解。 将 OLTARIS 数据映射到伊辛模型，并应用这些量子经典方法有助于确定最小化辐射剂量的屏蔽设置。 结果表明，OLTARIS 和量子优化在两种环境中均取得一致的结果。 显示英文摘要

摘要： Space radiation poses a significant challenge for long duration human space missions, with sources including Galactic Cosmic Rays, Solar Particle Events, and trapped particles in the Van Allen belts. These high-energy radiations cause severe biological effects on astronauts and degrade spacecraft systems, making effective shielding critical. Traditionally, passive shielding materials like aluminum have been used, but their limitations, particularly in generating secondary radiation, necessitate better alternatives. In this study, the performance of shielding materials such as lithium hydride, polyethylene, lithium borohydride, beryllium borohydride, and ammonia borane are evaluated in GCR and SPE environments using OLTARIS, a NASA developed tool. The October 1989 SPE is used to study particle flux and dose distributions. Shielding effectiveness varies by environment. Beryllium borohydride performs best in SPE, while lithium hydride gives the lowest dose in GCR. In SPE, performance is linked to hydrogen content. Effect of Solar modulation on GCR dose is also studied. Higher modulation lowers GCR intensity and dose. The complex nature of high energy space radiation and material combinations creates computational challenges. To address this, the material selection problem is modeled as a Quadratic Unconstrained Binary Optimization and solved using the Variational Quantum Eigensolver and Quantum Approximate Optimization Algorithm. Mapping OLTARIS data to the Ising model and applying these quantum classical methods helped identify shielding setups that minimize radiation dose. Results show agreement between OLTARIS and quantum optimization for both environments.