TuniQ uses RL with a dual-encoder, shaped rewards, and action masking to autotune quantum compilation passes, improving fidelity and speed over Qiskit while generalizing across backends and scaling to large circuits.
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Encodes M by N matrix into quantum state using Θ(log(MN)) qubits in O(log²(MN)) time via segment tree embedded in bucket brigade QRAM with constant ancillas and O(MN) memory cells.
citing papers explorer
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TuniQ: Autotuning Compilation Passes for Quantum Workloads at Scale for Effectiveness and Efficiency
TuniQ uses RL with a dual-encoder, shaped rewards, and action masking to autotune quantum compilation passes, improving fidelity and speed over Qiskit while generalizing across backends and scaling to large circuits.
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Efficient Quantum State Preparation with Bucket Brigade QRAM
Encodes M by N matrix into quantum state using Θ(log(MN)) qubits in O(log²(MN)) time via segment tree embedded in bucket brigade QRAM with constant ancillas and O(MN) memory cells.