Influence maximization under the linear threshold model on a CMOS Ising solver.

ABSTRACT: Influence Maximization (IM) is a fundamental problem in network science with applications in viral marketing, information dissemination, cybersecurity, and epidemiology. Classical IM solvers often trade off solution quality for runtime efficiency due to the NP-hardness of typical models such as Linear Threshold, Independent Cascade, and Triggering. Among these, the Linear Threshold model stands out by avoiding costly Monte Carlo simulations, enabling a more tractable Ising formulation. In this study, we propose a novel workflow for solving the Linear Threshold IM problem on directed acyclic graphs using a CMOS Ising solver through an Ising formulation. Our approach combines an integer linear programming-based Ising formulation with hardware-aware decomposition and preprocessing steps that

SUBMITTER: Zeng Z 

PROVIDER: S-EPMC12698711 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature