  Time-independent quantum response calculations are performed using Tensor
cores. This is achieved by mapping density matrix perturbation theory onto the
computational structure of a deep neural network. The main computational cost
of each deep layer is dominated by tensor contractions, i.e. dense
matrix-matrix multiplications, in mixed precision arithmetics which achieves
close to peak performance. Quantum response calculations are demonstrated and
analyzed using self-consistent charge density-functional tight-binding theory
as well as coupled-perturbed Hartree-Fock theory. For linear response
calculations, a novel parameter-free convergence criterion is presented that is
well-suited for numerically noisy low precision floating point operations and
we demonstrate a peak performance of almost 200 Tflops using the Tensor cores
of two Nvidia A100 GPUs.
