Uploaded October 2025 | Updated September 2026, 2 weeks ago

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A Utility Scale Perspective on Reactivity Prediction:

In the NISQ era, simulating complex molecular systems like sulfonyl fluoride-containing drug candidates requires quantum algorithms that minimize circuit depth to suit current hardware limitations. By integrating Hamiltonian truncation, Clifford Decomposition and Transformation (CDAT), and optimized transpilation, we achieved up to a 28.5-fold reduction in circuit depth, enabling one of the largest electronic structure Hamiltonian dynamics simulations on IBMQ’s Heron architecture with direct relevance to pharmaceutical development.

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