Efficient harmonic resolvent analysis via time-stepping
We present an extension of the RSVD-$\Delta t$ algorithm initially developed for resolvent analysis of statistically stationary flows to handle harmonic resolvent analysis of time-periodic flows. The harmonic resolvent operator, as proposed by \citet{Padovanetal20}, characterizes the linearized dynamics of time-periodic flows in the frequency domain, and its singular value decomposition reveals forcing and response modes with optimal energetic gain. However, computing harmonic resolvent modes poses challenges due to $(i)$ the coupling of all $N_{\omega}$ retained frequencies into a single harmonic resolvent operator and $(ii)$ the singularity or near-singularity of the operator, making harmonic resolvent analysis considerably more computationally expensive than a standard resolvent analysis. To overcome these challenges, the RSVD-$\Delta t$ algorithm leverages time stepping of the underlying time-periodic linearized Navier-Stokes operator, which is $N_{\omega}$ times smaller than the harmonic resolvent operator, to compute the action of the harmonic resolvent operator. We develop strategies to minimize the algorithm's CPU and memory consumption, and our results demonstrate that these costs scale linearly with the problem dimension. We validate the RSVD-$\Delta t$ algorithm by computing modes for a periodically varying Ginzburg-Landau equation and demonstrate its performance using the flow over an airfoil.