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Monte Carlo for risk estimation: from sampling to quantum
A risk-analysis survey of how Monte Carlo turned risk into something estimable rather than guessed at — from the Metropolis–Ulam estimator through CVaR and rare-event variance reduction, then where amortized variational methods (VAE) and quantum amplitude estimation actually fit. Field-first; thirteen 5-field reference cards at the end.