ECLIPSE: An Evolutionary Computation Library for Instrumentation Prototyping in Scientific Engineering

TL;DR

The paper presents ECLIPSE, a Python-based evolutionary computation framework designed to plug into domain-specific physics simulators for scientific hardware prototyping. It introduces a modular architecture with three core components—Individuals, Evaluators, and Evolvers—allowing domain-aware representations, external simulation interfaces, and high-cost optimization strategies, including ALPS-based steady-state GA and a hill-climber. The authors demonstrate ECLIPSE on antenna design and VLEO satellite topology problems, achieving meaningful design diversity and significant throughput improvements. They also discuss practical challenges such as interoperability, parallelization limits, and costly evaluations, and outline future work toward surrogate models, downsampling, and richer representations to accelerate discovery.

Abstract

Designing scientific instrumentation often requires exploring large, highly constrained design spaces using computationally expensive physics simulations. These simulators pose substantial challenges for integrating evolutionary computation (EC) into scientific design workflows. Evolutionary computation typically requires numerous design evaluations, making the integration of slow, low-throughput simulators particularly challenging, as they are optimized for accuracy and ease of use rather than throughput. We present ECLIPSE, an evolutionary computation framework built to interface directly with complex, domain-specific simulation tools while supporting flexible geometric and parametric representations of scientific hardware. ECLIPSE provides a modular architecture consisting of (1) Individuals, which encode hardware designs using domain-aware, physically constrained representations; (2) Evaluators, which prepare simulation inputs, invoke external simulators, and translate the simulator's outputs into fitness measures; and (3) Evolvers, which implement EC algorithms suitable for high-cost, limited-throughput environments. We demonstrate the utility of ECLIPSE across several active space-science applications, including evolved 3D antennas and spacecraft geometries optimized for drag reduction in very low Earth orbit. We further discuss the practical challenges encountered when coupling EC with scientific simulation workflows, including interoperability constraints, parallelization limits, and extreme evaluation costs, and outline ongoing efforts to combat these challenges. ECLIPSE enables interdisciplinary teams of physicists, engineers, and EC researchers to collaboratively explore unconventional designs for scientific hardware while leveraging existing domain-specific simulation software.

Figures (1)

• Figure 1: An overview of the ECLIPSE Framework. The algorithm begins and ends with the Evolver, which interfaces with an Evaluator module to get fitness scores, and an Individual module to receive new candidate solutions.