Recursive optimization algorithms can be used to determine which idle photonic switching elements to configure in N×N switching fabrics to achieve crosstalk suppression. Different algorithms are used to achieve different levels of optimization. Embodiment full optimization techniques may configure all inactive cells to reduce crosstalk, and consequently may provide the best noise performance and highest power usage. Partial optimizations may configure fewer than all inactive cells to reduce crosstalk, and may provide sub-optimal noise performance at lower power usages. Differential partial optimization algorithms configure inactive cells in different stages of a photonic switching fabric. Fewer than all cells in a given stage may be configured by some algorithms.