Mitchell Physics Building
College Station, Texas 77843-4242
Artificial neural network (ANN) is a framework for many different machine algorithms to work together and process complex data inputs. The rapid growth of applications that rely on ANN concepts gives rise to a staggering increase in the demand for hardware implementations of neural networks. New types of hardware that can support the requirements of high-speed associative computing while maintaining low power consumption are sought, and optical artificial neural networks fit the task well.
Intense femtosecond laser pulses are prone to undergo nonlinear effects in media. The increasing use of high intensity femtosecond laser systems underscores the need to understand the retinal hazards generated by nonlinear optical effects, like the generation of supercontinuum. Current laser safety standards such as ANSI Z136.1 for pulse wavelengths of 1200 nm - 1400 nm have been determined from experimental studies using pulse durations longer than 100 fs and linear pulse simulations. The combination of strong absorption, broad bandwidth, and dispersive effects makes standard nonlinear pulse simulation methods, based on the slowly varying envelope approximation, unsuitable for the study of near-infrared pulses in biological tissues. To model retinal hazards, we leverage an existing linear ultrafast pulse propagation model that does not rely on an envelope approximation and simulate supercontinuum broadening in water. Using a one-dimensional simulation of self-phase modulation, and incorporating self-focusing, we validate the model using a previous experiment in water. We then simulate propagation of 10 fs - 1 ps, 1200 nm - 1400 nm pulses at the current ANSI MPE limit for pulses under 10 ps. We then expand our simulation to consider the effect of chirping or pre-focusing the pulse before entering the eye.
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