Physical survival and provenance limits on watermarking AI-generated crystals

When crystals are generated, they are relaxed and standardized before scientific use. This processing can erase or alter structural evidence of how they were produced. We ask what a structure-only watermark can preserve through this process, how an auditor should calibrate the surviving evidence, and which provenance claims the resulting decision supports. BasinMark connects a deposited structure to a collection-level audit by selecting generated candidates according to keyed structural fingerprints. Exact relaxation to the same basin minimum erases coordinate marks, so the protocol selects among alternatives whose fingerprint distinctions may survive deposition. Across the evaluated generators and interatomic potentials, cell-shape bins account for much of the observed fingerprint instability. Removing these bins in two generator populations substantially improves fingerprint-label survival while preserving structural diversity. Under a key-independent null, counting each unique fingerprint class once provides exact false-positive control. Detection operates at the structural-class level, however, so collections with identical fingerprints remain indistinguishable. Watermark evidence can therefore be copied or reused across datasets. Physical processing, fingerprint design, and the handling of structural duplicates determine how much watermark evidence survives and what that evidence can establish.