Description: Quasi-Monte Carlo is a numerical method that uses low-discrepancy sequences to improve the accuracy of estimates in simulations and calculations. Unlike traditional Monte Carlo methods, which rely on random number generation, Quasi-Monte Carlo employs points that are more uniformly distributed in space, allowing for faster and more efficient convergence in obtaining results. This approach is particularly useful in applications requiring high precision, such as numerical integration and optimization. Low-discrepancy sequences, such as Sobol or Halton sequences, are fundamental to this method as they ensure that sampled points cover the space more evenly, thereby reducing estimation error. Quasi-Monte Carlo can be utilized in various fields, including finance, engineering, and scientific computing, where precision in parameter estimation is crucial for achieving high-quality results.
