Quantum algorithms achieve polynomial advantage for synchronization estimation and super-polynomial advantage for no-phase-locking certification in higher-order simplicial Kuramoto models under stated assumptions.
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QCPP implements polynomial transformations of Hamiltonians via stochastic mixtures of unitary channels, achieving a tunable tradeoff between query and sample complexity.
Quantum algorithm finds eigenvalues of parameterized matrix families by minimizing singular values and applies it to Schrödinger equation collocation with O(sqrt(N)) scaling.
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Efficient Quantum Algorithms for Higher-Order Coupled Oscillators
Quantum algorithms achieve polynomial advantage for synchronization estimation and super-polynomial advantage for no-phase-locking certification in higher-order simplicial Kuramoto models under stated assumptions.
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Quantum Channel Polynomial Processing
QCPP implements polynomial transformations of Hamiltonians via stochastic mixtures of unitary channels, achieving a tunable tradeoff between query and sample complexity.
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Quantum algorithm for solving generalized eigenvalue problems with application to the Schr\"odinger equation
Quantum algorithm finds eigenvalues of parameterized matrix families by minimizing singular values and applies it to Schrödinger equation collocation with O(sqrt(N)) scaling.