Reconfigurable design of a thermo-optically addressed liquid-crystal phase modulator by a neural network.

We present a machine learning approach to program the light phase modulation function of an innovative thermo-optically addressed, liquid-crystal based, spatial light modulator (TOA-SLM). The designed neural network is trained with a little amount of experimental data and is enabled to efficiently generate prescribed low-order spatial phase distortions. These results demonstrate the potential of neural network-driven TOA-SLM technology for ultrabroadband and large aperture phase modulation, from adaptive optics to ultrafast pulse shaping.

Femtosecond laser-induced damage threshold of nematic liquid crystals at 1030 nm.

The laser-induced damage threshold (LIDT) of nematic liquid crystals is investigated in the femtosecond regime at ≃1030nm. The thickness and breakdown of freely suspended thin films (≃100nm) of different mixtures (MLC2073, MLC2132, and E7) is monitored in real time by spectral-domain interferometry. The duration of laser pulses was varied from 180 fs to 1.8 ps for repetition rates ranging from single shot to 1 MHz. The dependence of the LIDT with pulse duration suggests a damage mechanism dominated by ionization mechanisms at low repetition rate and by linear absorption at high repetition rate. In the single-shot regime, LIDTs exceeding 1J/cm2 are found for the three investigated mixtures. The LIDT of polyvinyl alcohol is also investigated by the same method.