Learn2Design 2026: A physics experiment design competition for gravitational wave detectors

Learn2Design is a competition on the automated design of highly sensitive gravitational-wave detectors under realistic experimental constraints. Participants submit optimization algorithms, not fixed designs: given a detector topology, each algorithm tunes roughly 200 continuous parameters within a fixed compute budget to minimize a simulator-defined loss combining detector sensitivity and feasibility penalties. We provide the auto-differentiable simulator Differometor and approximately 30,000 high-quality designs generated through a 360,000 GPU-hour exploration campaign, which will allow for highly diverse optimization and exploration algorithms. Algorithms will be ranked by average performance on hidden topologies evaluated by the organizers, with EUR~25,000 in prize money. Beyond gravitational-wave detection, the competition asks whether AI systems can discover scientific instruments that go beyond human intuition while remaining physically meaningful.