Optimal transport maps and plans between two absolutely continuous measures
$\mu$ and $\nu$ can be approximated by solving semi-discrete or fully-discrete
optimal transport problems. These two problems ensue from approximating $\mu$
or both $\mu$ and $\nu$ by Dirac measures. Extending an idea from [Gigli, On
H\"older continuity-in-time of the optimal transport map towards measures along
a curve], we characterize how transport plans change under perturbation of both
$\mu$ and $\nu$. We apply this insight to prove error estimates for
semi-discrete and fully-discrete algorithms in terms of errors solely arising
from approximating measures. We obtain weighted $L^2$ error estimates for both
types of algorithms with a convergence rate $O(h^{1/2})$. This coincides with
the rate in [Berman, Convergence rates for discretized Monge--Amp\`ere
equations and quantitative stability of Optimal Transport, Theorem 5.4] for
semi-discrete methods, but the error notion is different.

本文研究了两个绝对连续测度之间的最优输运问题，提出了半离散和全离散算法，并证明了这两种算法的误差估计及其计算收敛速率。