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Structure-preserving quantum algorithms for linear and nonlinear Hamiltonian systems
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Structure-preserving quantum algorithms for linear and nonlinear Hamiltonian systems
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Hamiltonian systems of ordinary and partial differential equations are fundamental mathematical models spanning virtually all physical scales. A critical property for the robustness and stability of computational methods in such systems is the underlying symplectic structure, which preserves geometric properties like phase-space volume over time and energy conservation over an extended period. In this paper, we present quantum algorithms that incorporate symplectic integrators, ensuring the preservation of this key structure. We demonstrate how these algorithms maintain the symplectic properties for both linear and nonlinear Hamiltonian systems. Additionally, we provide a comprehensive theoretical analysis of the computational complexity, showing that our approach offers both accuracy and improved efficiency over classical algorithms. These results highlight the potential application of quantum algorithms for solving large-scale Hamiltonian systems while preserving essential physical properties.
Forward citations
Cited by 2 Pith papers
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Transmutation based Quantum Simulation for Non-unitary Dynamics
The Kannai transform turns dissipative quantum simulation for A = L†L into a Gaussian-weighted sum of unitary wave propagators, giving query complexity Õ(√(‖A‖T log(1/ε))) and a κ^{3/2} linear-solver corollary.
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Symplectic perspective to quantum computing for Hamiltonian systems
A symplectic framework links quantum evolution to classical Hamiltonian dynamics on Kähler manifolds, yielding exponentially compressed quantum representations for integrable systems and approximate versions for other...
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