Linear dependence among the diagonal components of Hamiltonian derivatives creates a slow parameter direction with O(t^0) scaling, obstructing simultaneous t^{-2} multiparameter quantum estimation.
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Integrating quantum catalysis, entanglement, and squeezing in a distributed quantum network yields better multiphase sensing precision than any two alone, approaching the Heisenberg limit, with partial catalysis outperforming global catalysis in both ideal and lossy cases.
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Geometric obstructions to quadratic time scaling in multiparameter quantum estimation
Linear dependence among the diagonal components of Hamiltonian derivatives creates a slow parameter direction with O(t^0) scaling, obstructing simultaneous t^{-2} multiparameter quantum estimation.
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Quantum-enhanced distributed network sensing using multiple quantum resources
Integrating quantum catalysis, entanglement, and squeezing in a distributed quantum network yields better multiphase sensing precision than any two alone, approaching the Heisenberg limit, with partial catalysis outperforming global catalysis in both ideal and lossy cases.