GULPS partitions two-qubit unitary synthesis into depth-2 segments solved via linear programming over Littlewood-Richardson inequalities followed by least-squares optimization, yielding faster and lower-cost decompositions than prior synthesizers on heterogeneous ISAs.
Noise- aware circuit compilations for a continuously parameterized two-qubit gateset,
2 Pith papers cite this work. Polarity classification is still indexing.
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Canopus unifies qubit mapping and routing across quantum ISAs by modeling synthesis costs via canonical two-qubit gate forms, achieving 15-35% lower routing overhead than prior methods on varied backends and topologies.
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GULPS: Two-Qubit Gate Synthesis via Linear Programming for Heterogeneous Instruction Sets
GULPS partitions two-qubit unitary synthesis into depth-2 segments solved via linear programming over Littlewood-Richardson inequalities followed by least-squares optimization, yielding faster and lower-cost decompositions than prior synthesizers on heterogeneous ISAs.
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Unifying Qubit Routing Across Diverse Quantum ISAs via Canonical Representation
Canopus unifies qubit mapping and routing across quantum ISAs by modeling synthesis costs via canonical two-qubit gate forms, achieving 15-35% lower routing overhead than prior methods on varied backends and topologies.