Breaking the coupling among N2 fully-connected linear polarization channels

Polarization multiplexing is one of the key technologies for multi-dimensional information transmission. When constructing a N ² -dimensional linear polarization multiplexing network with N input states of distinct polar angle and corresponding N outputs ( N  > 2), there are inherent couplings for all channels due to polarization decomposition and superposition, exhibiting as information crosstalk among non-orthogonal channels. Also, physical symmetric structure severely limits the full utilization of polarization multiplexing by inducing crosstalk in orthogonal polarization channels. Here by employing polarization diffraction neural network (PDNN) to minimize couplings in a global manner, we establish N ² fully-connected independent transmission channels by multiplexing N linear polar angles. Taking chiral-assisted metasurfaces as physical platform, a single-layer PDNN is verified by nine input-output channels ( N  = 3), ultra-low crosstalk in digital holographic imaging shows the effectiveness of proposed method. We also impose amplitude-feature enhancement of metasurface to further improve transformation efficiency while maintaining channel isolation. Our results exemplify the architecture’s capability for complete polarization multiplexing, with direct applicability to optical linear computing, advanced holography, and high-security optical encryption.