Linear multistep methods are numerical techniques used to solve ordinary differential equations (ODEs) by approximating the solutions at discrete points. Unlike single-step methods (like the Euler method or Runge-Kutta methods) that only use information from the current time step to compute the next step, linear multistep methods utilize information from multiple previous time steps.
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A linear multistep method approximates an ODE using several previous solution and derivative values.