In optical dating, incomplete and heterogeneous resetting (“bleaching”) of the luminescence signal measured from mineral grains since the last episode of transport and deposition is commonly observed for sedimentary samples. As a result, different grains could have different equivalent dose (D_e) values at the time of deposition. For such samples, statistical treatment of the D_e distribution is required to estimate the burial dose. This study aims to assess the reliability of burial dose determination for heterogeneously bleached samples using the minimum age model (MAM). We modeled heterogeneous bleaching processes under various bleaching scenarios and simulated the resulting single-grain D_e distributions using a Monte Carlo method. Various factors that could potentially affect the reliability of burial dose estimates are investigated, including the distribution of residual dose, proportion of fully bleached grains, baseline dose, sample size, and unaccounted between-grain standard deviation. The simulation results reveal that the performance of the model depends primarily on the residual dose distribution. The proportion of fully bleached grains has the most influence on the reliability of MAM burial dose estimates.

在光学测年中，自从最后一次运输和沉积以来，从矿物颗粒中测得的发光信号的不完全和不均匀的复位（“漂白”）通常会出现在沉积样品中。结果，不同的晶粒在沉积时可能具有不同的等效剂量（D _e）值。对于此类样品，需要对D _e分布进行统计学处理以估计埋葬剂量。这项研究旨在评估使用最小年龄模型（MAM）进行非均相漂白样品埋葬剂量测定的可靠性。我们对各种漂白方案下的非均相漂白过程进行了建模，并模拟了所得的单颗粒D _e分布使用蒙特卡洛方法。研究了可能影响埋葬剂量估计值可靠性的各种因素，包括残留剂量的分布，完全漂白谷物的比例，基线剂量，样品量以及未解释的颗粒间标准偏差。仿真结果表明，模型的性能主要取决于残余剂量分布。完全漂白谷物的比例对MAM埋葬剂量估计值的可靠性影响最大。