Abstract The integration of Tensor Networks into quantum computing has unlocked new possibilities, particularly for efficiently loading complex datasets onto quantum systems. In this talk, we examine the tensor-train cross approximation (TT-cross) algorithm as an effective solution to the probability loading challenge in Quantum Monte Carlo (QMC). By applying TT-cross to high-dimensional financial distributions, we…