Optimizing Startshot lightsail design: a generative network-based approach

TL;DR

This paper presents a novel generative network-based optimization framework for designing silicon-based lightsails, aiming to meet the extreme optical, mechanical, and thermal requirements for relativistic propulsion in the Starshot project.

Contribution

It introduces an adjoint topology optimization and variational autoencoder-assisted inverse design method for lightsail development, enabling multi-objective optimization of propulsion system components.

Findings

Optimized lightsail designs with improved optical and kinematic properties.

Framework demonstrates potential for multi-objective, physics-driven system optimization.

Enables pathway toward practical realization of relativistic spacecraft propulsion.

Abstract

The Starshot lightsail project aims to build an ultralight spacecraft ("nanocraft") that can reach Proxima Centauri b in approximately 20 years, requiring propulsion with a relativistic velocity of ~60 000 km/s. The spacecraft's acceleration approach currently under investigation is based on applying the radiation pressure from a high-power laser array located on Earth to the spacecraft lightsail. However, the practical realization of such a spacecraft imposes extreme requirements to the lightsail's optical, mechanical, thermal properties. Within this work, we apply adjoint topology optimization and variational autoencoder-assisted inverse design algorithm to develop and optimize a silicon-based lightsail design. We demonstrate that the developed framework can provide optimized optical and opto-kinematic properties of the lightsail. Furthermore, the framework opens up the pathways to realizing a multi-objective optimization of the entire lightsail propulsion system, leveraging the previously demonstrated concept of physics-driven compressed space engineering