aiqbench analysis
This research proposes using continuous-variable quantum annealing based on bosonic systems to solve linear differential equations, effectively bypassing the qubit overhead required by traditional discretization methods. Numerical simulations confirm that this approach can accurately reproduce analytical solutions for second-order linear differential equations without converting variables into discrete states. The work establishes a viable pathway for leveraging bosonic modes in quantum optimization tasks involving continuous dynamical systems.
Solving Differential Equations Using Continuous-Variable Quantum Annealing
arXiv:2608.04601v1 Announce Type: new Abstract: Most existing quantum annealing approaches are formulated for qubit-based architectures. Consequently, applying them to continuous-variable optimization problems requires discretizing the variables, which can incur substantial qubit overhead. Continuous-variable quantum annealing based on bosonic systems has recently been proposed as an alternative framework, in which each optimization variable is directly encoded in a bosonic mode, such as a cavity mode. In this work, we develop a continuous-variable quantum annealing formulation for solving linear differential equations. By recasting the determination of the solution as a continuous-variable optimization problem, the differential equation can be mapped onto an objective function compatible with bosonic quantum annealing. Numerical simulations of second-order linear differential equations demonstrate that, under the conditions considered, the proposed formulation reproduces the corresponding analytical solutions. These results establish a potential route toward solving differential equations without the discretization overhead inherent in qubit-based implementations.
Abstract:Most existing quantum annealing approaches are formulated for qubit-based architectures. Consequently, applying them to continuous-variable optimization problems requires discretizing the variables, which can incur substantial qubit overhead. Continuous-variable quantum annealing based on bosonic systems has recently been proposed as an alternative framework, in which each optimization variable is directly encoded in a bosonic mode, such as a cavity mode. In this work, we develop a continuous-variable quantum annealing formulation for solving linear differential equations. By recasting the determination of the solution as a continuous-variable optimization problem, the differential equation can be mapped onto an objective function compatible with bosonic quantum annealing. Numerical simulations of second-order linear differential equations demonstrate that, under the conditions considered, the proposed formulation reproduces the corresponding analytical solutions. These results establish a potential route toward solving differential equations without the discretization overhead inherent in qubit-based implementations.
arXiv:2608.04601 [quant-ph]
(or arXiv:2608.04601v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2608.04601 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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