QNLP Quantum Natural Language Processing

Quantinuum released λambeq Gen II, an open-source quantum natural language processing (QNLP) software that translates text into quantum circuits for real quantum hardware

λambeq Gen II introduces the DisCoCirc formalism, enabling richer linguistic compositionality and scalability to entire texts, not just sentences

DisCoCirc ensures canonical, well-defined, and learnable quantum models, supporting language neutrality and flexibility across linguistic domains

The new version addresses previous QNLP challenges in interpretability and trainability, offering explainable AI (XAI) features and compositional generalization

λambeq Gen II integrates with Quantinuum’s quantum stack and uses Python and variational quantum classifier (VQC) techniques for circuit generation

Quantinuum demonstrated the first scalable, error-corrected, end-to-end quantum computational chemistry workflow using logical qubits and quantum phase estimation (QPE)

This chemistry workflow was executed on Quantinuum’s System Model H2 quantum computer via the InQuanto platform, showcasing real-time quantum error correction