Optimal spectral filtering in soliton self-frequency shift for deep-tissue multiphoton microscopy.

Abstract

Tunable optical solitons generated by soliton self-frequency shift (SSFS) have become valuable tools for multiphoton microscopy (MPM). Recent progress in MPM using 1700 nm excitation enabled visualizing subcortical structures in mouse brain in vivo for the first time. Such an excitation source can be readily obtained by SSFS in a large effective-mode-area photonic crystal rod with a 1550-nm fiber femtosecond laser. A longpass filter was typically used to isolate the soliton from the residual in order to avoid excessive energy deposit on the sample, which ultimately leads to optical damage. However, since the soliton was not cleanly separated from the residual, the criterion for choosing the optimal filtering wavelength is lacking. Here, we propose maximizing the ratio between the multiphoton signal and the n'th power of the excitation pulse energy as a criterion for optimal spectral filtering in SSFS when the soliton shows dramatic overlapping with the residual. This optimization is based on the most efficient signal generation and entirely depends on physical quantities that can be easily measured experimentally. Its application to MPM may reduce tissue damage, while maintaining high signal levels for efficient deep penetration.