A quantum algorithm for advection-diffusion equation by a probabilistic imaginary-time evolution operator
ORAL
Abstract
In this work, we propose a new quantum algorithm for solving the linear advection-diffusion reaction equations by employing a novel approximate probabilistic imaginary-time evolution (PITE) operator. This algorithm based on the approximate PITE operator can be easily extended to evolution equations. In more detail, we first verify the effectiveness of the proposed approximate PITE operator by the theoretical evaluation of the error. Next, we construct the explicit quantum circuit for realizing the imaginary-time evolution of the Hamiltonian coming from the advection-diffusion equation, whose gate complexity is logarithmic regarding the size of the discretized Hamiltonian matrix. To verify our algorithm, numerical simulations using gate-based quantum emulator Qiskit for 1D/2D examples are also provided. Moreover, we compare our proposed algorithm to some other previous works and find that our algorithm gives comparable result to the Harrow-Hassidim-Lloyd (HHL) algorithm with similar gate complexity, although we use much less ancillary qubits. Besides, our algorithm outperforms a specific HHL algorithm and a variational quantum algorithm based on the finite difference method. Finally, we extend our algorithm to the coupled system of advection-diffusion reaction equations, and we also demonstrate some simulation results for nonlinear reaction-diffusion systems, including Burgers' equation, provided that time-step-wise measurements are allowed.
*This work was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI under Grant-in-Aid for Scientific Research No.21H04553, No.20H00340, and No.22H01517. This work was partially supported by the Center of Innovations for Sustainable Quantum AI (JST Grant number JPMJPF2221).
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Publication: X. Huang et al. A quantum algorithm for advection-diffusion equation by a probabilistic imaginary-time evolution operator. Preprint. arXiv:2409.18559
Presenters
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Xinchi Huang
- The University of Tokyo; Quemix Inc.