Modeling viral diffusion using quantum computational network simulation

Abstract

Summary Processes of viral diffusion are important in biological, technological, and social systems alike. Several mathematical models of infection have been developed to predict diffusion through networks, such as nonlinear dynamical systems (NLDSs). Such models generally offer accurate representations of real‐world diffusion, particularly for networks with static topologies. However, simulations of viral diffusion are computationally expensive, rendering them infeasible for large‐scale networks. Here, a new approach is shown that leverages quantum computing to make viral diffusion simulations feasible for large networks, independent of network topology. Simulations of an error‐free quantum circuit accurately modeled viral diffusion, with multivariate Euclidean distances from predicted infection probabilities capped near 8% for a network with N = 5 nodes and t = 20 time‐steps. This is sufficient accuracy to distinguish the relative susceptibility of nodes and to identify significant changes, such as periods of especially high susceptibility. The results illustrate the potential for quantum computational network simulation to provide accurate models of diffusion through large networks, an important real‐world application of quantum computing. The ability to simulate viral diffusion is invaluable for researchers across disciplines who aim to understand, anticipate, prepare for, and intervene in ongoing diffusion processes.

Studying the effect of lockdown using epidemiological modelling of COVID-19 and a quantum computational approach using the Ising spin interaction

“…Attempts have been made to use quantum computational approach to model epidemics by Britt in 2010 17 . Here, he tried to model the viral network diffusion using the Non-linear Dynamical System (NLDs) while attempting to precisely control the person (represented by ‘nodes’ in the work) to person viral infection.…”

Social Laser Model for the Bandwagon Effect: Generation of Coherent Information Waves

“…This is quite like the RDM ( random discontinuous motion ) interpretation of quantum mechanics [ 69 ], whereas quite different from other interpretations, such as the many-world interpretation [ 70 , 71 ] and the WISE ( wave function is the system entity ) interpretation [ 72 ]. It should be also pointed out that in recent years, some physics-based social or network models have been studied [ 73 , 74 ]. Some new intersection of quantum and operational research are emerging, such as quantum machine learning [ 75 , 76 ].…”

“…It should be also pointed out that in recent years, some physics-based social or network models have been studied [ 73 , 74 ]. Some new intersection of quantum and operational research are emerging, such as quantum machine learning [ 75 , 76 ].…”

Entanglement Distribution in a Quantum Network: A Multicommodity Flow-Based Approach

“…The quantum Internet will provide a facility for communicating qubits between quantum information processing devices [1]- [4]. It will enable us to implement interesting applications such as quantum key distribution [5], [6], clock synchronization [7], secure multiparty computation [8], and others [4], [9]. To implement a full quantum internet the network needs to be able to produce entanglement between any two end nodes connected to the network [10]- [13].…”