What Are the Challenges in Using Stochastic Models for Catalysis?
Despite their advantages, stochastic models come with challenges:
1. Computational intensity: Stochastic simulations can be computationally demanding, especially for systems involving a large number of particles. 2. Parameter estimation: Accurately estimating the parameters required for stochastic models can be difficult and often requires extensive experimental data. 3. Interpretation: The probabilistic results generated by stochastic models can be harder to interpret and apply compared to deterministic results.
