For Hamiltonian families with known generators and hidden parameters, the exact query cost of implementing the inverse is determined by spectral sumset relations and representation-theoretic reduction, yielding polynomial or constant bounds for several many-body families.
Efficient Inversion of Unknown Unitary Operations with Structured Hamiltonians
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abstract
Unknown unitary inversion is a fundamental primitive in quantum computing and physics. Although recent work has demonstrated that quantum algorithms can invert arbitrary unknown unitaries without accessing their classical descriptions, improving the efficiency of such protocols remains an open question. In this work, we present efficient quantum algorithms for inverting unitaries with specific Hamiltonian structures, achieving significant reductions in both ancilla qubit requirements and unitary query complexity. We identify cases where unitaries encoding exponentially many parameters can be inverted using only a single query. We further extend our framework to implement unitary complex conjugation and transposition operations, and develop modified protocols capable of inverting more general classes of Hamiltonians. We have also demonstrated the efficacy and robustness of our algorithms via numerical simulations under realistic noise conditions of superconducting quantum hardware. Our results establish more efficient protocols that improve the resources required for quantum unitary inversion when prior information about the quantum system is available, and provide practical methods for implementing these operations on near-term quantum devices.
fields
quant-ph 1years
2026 1verdicts
ACCEPT 1representative citing papers
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Algebraic Speedups for Exact Inversion of Hamiltonian Evolutions
For Hamiltonian families with known generators and hidden parameters, the exact query cost of implementing the inverse is determined by spectral sumset relations and representation-theoretic reduction, yielding polynomial or constant bounds for several many-body families.