Publications by authors named "Serdar Okuyucu"

We report femtosecond pulse generation at GHz repetition rates with the Yb:YLF gain medium for the first time. A simple, low-cost, and compact architecture is implemented for the potential usage of the system as a low-noise timing jitter source. The system is pumped by 250 mW, 960 nm single-mode diodes from both sides.

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We demonstrate a versatile dual-wavelength synchronous mode-locking of a diode-pumped Cr:LiSAF laser for the first time, to our knowledge. A two-color mode-locked operation is achieved by using intracavity birefringent filters (BRFs) or etalons as frequency-selective elements. Using filters with different thicknesses and hence different free spectral ranges (FSRs), wavelength separation in two-color mode-locking could be selected between 1 and 9 nm, with corresponding beating frequencies in the 0.

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In this work, we have investigated the continuous-wave (cw) lasing potential of thin slab-shaped Cr:LiCAF crystals with a low chromium doping level of around 1% and various lengths of 1 to 2 cm. These relatively long crystals with low Cr-doping facilitate the distribution of heat load in a larger volume and could enable power scaling of Cr:LiCAF lasers. However, long crystals tend to have larger passive losses, and it is also more challenging to achieve efficient mode-matching to the low-brightness pump mode in a longer gain element, which could hinder laser performance.

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We studied the two-color lasing performance of a Cr:LiCAF laser using crystal quartz on-surface and off-surface optical axis birefringent filters (BRFs). Four different on-surface optical axis BRFs with thicknesses of 2 mm, 4 mm, 8 mm, and 16 mm, and three different off-surface optical axis BRFs with a diving angle of 25° and thicknesses of 2 mm, 4 mm, and 8 mm have been tested. Two-color lasing operation could be achieved in tens of different pairs of wavelengths using both types of BRFs.

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Neuronal noise is a major factor affecting the communication between coupled neurons. In this work, we propose a statistical toolset to infer the coupling between two neurons under noise. We estimate these statistical dependencies from data which are generated by a coupled Hodgkin-Huxley (HH) model with additive noise.

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