Variational Quantum Transformer Architecture for Synthetic Language Generation
We propose a compact NISQ-compatible quantum transformer architecture for synthetic QNLP sequence modelling. The model preserves the autoregressive next-token interface of a classical transformer, but replaces attention and feed-forward sublayers with variational quantum encoder blocks, connector circuits, decoder blocks and a direct two-qubit measurement readout. Token contexts are angle-encoded into small quantum registers, processed by parallel variational heads and encoder integration circuits and conditioned through decoder ancillae to produce a distribution over a four-token vocabulary. We evaluate several architecture variants on deterministic and lexicographic grammar-generation t...
| Authors | Julian Hager, Michael Kölle, Gerhard Stenzel et al. |
|---|---|
| Primary category | quant-ph |
| Published | 16 September 2026 |
| Last updated at source | 16 September 2026 |
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