“…Dynamical low-rank approximation of time-dependent matrices [37] has proven to be an efficient model order reduction technique for applications from widely varying fields including plasma physics [24,26,20,8,22,14,27,15,23,56], radiation transport [49,16,47,41,48,57,21,4], radiation therapy [40], chemical kinetics [32,50,25], wave propagation [31,58], kinetic shallow water models [38], uncertainty quantification [51,3,28,43,44,46,39,33,17,2], and machine learning [54,59,52,53]. These problems can be written as a prohibitively large matrix differential equation for A(t) ∈ R m×n , .…”