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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Search-based approximate diagonalization followed by analytical inversion yields high-precision multi-qubit Clifford+T circuits with 95% fewer non-Clifford gates on real-algorithm benchmarks.
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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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High-Precision Multi-Qubit Clifford+T Synthesis by Unitary Diagonalization
Search-based approximate diagonalization followed by analytical inversion yields high-precision multi-qubit Clifford+T circuits with 95% fewer non-Clifford gates on real-algorithm benchmarks.