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Monte Carlo methods are widely used in fields like finance (for option pricing), physics (for particle transport), engineering (for risk analysis), and machine learning (for Bayesian inference). They are particularly useful when dealing with high-dimensional integrals or complex stochastic processes. The elegance of the method lies in its simplicity and its reliance on randomness to yield statistically meaningful results through repeated simulation.
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Alexander Fernando Haro Sarango (2025) studied this question.