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

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Authors: Max Foreback, Evan Imata, Vincent R. Ragusa, Jacob Weiler, Jonathan Sy, C. Shao, J. Wagner, Dylan Wells, Rick Marcusen, Katherine G. Skocelas, Aman Hafez, Amy Conolly
+9 more Kyle R. Helson, Rajiv Ramnath, Wolfgang Banzhaf, Charles Ofria, Marcin Pilinski, Bryan Reynolds, Anselmo C. Pontes, Emily Dolson, Julie Rolla
Cited by: 1

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. EC typically requires numerous design evaluations, making the integration of slow, low-throughput simulators 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 this domain. We evolve solutions for two novel space-science applications: 3D antennas optimized for directional sensitivity and spacecraft geometries optimized for drag reduction. Notably, we identify antennas with directional sensitivity roughly comparable to the expected sensitivity of two-antenna interferometric arrays, representing potential cost-savings. ECLIPSE enables interdisciplinary teams of physicists, engineers, and EC researchers to collaboratively explore designs for scientific hardware while leveraging existing domain-specific simulation software.

Fields of Study & Subjects

Advanced Multi-Objective Optimization Algorithms Evolutionary Algorithms and Applications Metaheuristic Optimization Algorithms Research

Publication details

Journal / source
arXiv (Cornell University)
Publication date
8 January 2026
Document type
Preprint