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

TL;DR

This paper evaluates space radiation shielding materials using OLTARIS simulations and introduces quantum algorithms like QAOA and VQE to optimize material selection, demonstrating potential for improved protection in space missions.

Contribution

It combines space radiation modeling with quantum optimization techniques to identify effective shielding materials, a novel integration of quantum computing in space radiation protection.

Findings

Beryllium borohydride performs best in SPE environments.

Lithium hydride results in the lowest GCR dose.

Quantum algorithms agree with classical simulations in optimizing shielding.

Abstract

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.