One molecule, many outputs; many molecules, one output: exact diagnostics for atom-level compositional quantum encoders

arXiv:2611.15092v1 Announce Type: new Abstract: Quantum natural language processing (QNLP) turns the grammar of a sentence into a tensor network and then into a quantum circuit with trainable angles. We build such a model for molecules: each heavy atom is a word with one wire per bond, and each bond is a ``cup'' joining two wires, so the circuit's wiring is the molecular graph. We work out exactly what these circuits keep. With the typed angle sharing of lambeq, the circuits separate every isomer pair we tested. Yet for isomers that simpler sharing confuses, the output states stay almost the same, before and after training. On 7 Tox21 pairs and 1,988 MOSES pairs, nearly all the difference lies in how often the measurements succeed, which a standard readout ignores.