PATHFINDER: Multi-objective discovery in structural and spectral spaces

arXiv:2604.04194v1 Announce Type: cross Abstract: Automated decision-making is becoming key for automated characterization including electron and scanning probe microscopies and nano indentation. Most machine learning driven workflows optimize a single predefined objective and tend to converge prematurely on familiar responses, overlooking rare but scientifically important states. More broadly, the challenge is not only where to measure next, but how to coordinate exploration across structural,