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arXiv · 2208.11394

Simulating the Spread of Infection in Networks with Quantum Computers

Xiaoyang Wang·Yinchenguang Lyu·Changyu Yao·Xiao Yuan
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Abstract

We propose to use quantum computers to simulate infection spreading in networks. We first show the analogy between the infection distribution and spin-lattice configurations with Ising-type interactions. Then, since the spreading process can be modeled as a classical Markovian process, we show that the spreading process can be simulated using the evolution of a quantum thermal dynamic model with a parameterized Hamiltonian. In particular, we analytically and numerically analyze the evolution behavior of the Hamiltonian, and prove that the evolution simulates a classical Markovian process, which describes the well-known epidemiological stochastic susceptible and infectious (SI) model. A practical method to determine the parameters of the thermal dynamic Hamiltonian from epidemiological inputs is exhibited. As an example, we simulate the infection spreading process of the SARS-Cov-2 variant Omicron in a small-world network.

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Xiaoyang Wang, Yinchenguang Lyu, Changyu Yao, Xiao Yuan. 2022-08-24. Simulating the Spread of Infection in Networks with Quantum Computers. https://doi.org/10.1103/physrevapplied.19.064035

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