Session

DescriptionScalable quantum computing requires coordinated advances in circuit synthesis, compilation, and algorithmic optimization. This session features exact T and CNOT gate synthesis engines, hypergraph-based circuit optimizers, and architecture aware compilation for neutral atom systems, all aimed at improving scalability and qubit locality. It also highlights hardware calibrated cost models for hybrid neural architecture search, Hamiltonian guided pretraining for variational algorithms, and efficient time dependent Hamiltonian solvers. Together, these works show how rigorous synthesis, intelligent search, and hardware aware optimization combine into a unified automation stack that accelerates scalable, performance driven quantum circuit and algorithm design. Ultimately, these advances point toward a future where quantum software design becomes not only automated and scalable, but capable of unlocking algorithmic possibilities far beyond today’s imagination.