Abstract

We present a simple and robust method for brightness enhancement, efficiently transforming a radially polarized LG (0,1)* mode into a nearly Gaussian beam of much higher quality. We use for this a spatially variable retardation plate and a spatial filter. The analysis shows that the transformation yields an increase in brightness by a factor of 3.4. In the experiment, we transformed a high-power Nd:YAG radially polarized (0,1)* LG beam with power of 70W and M2=2.6 into a nearly Gaussian beam with M2=1.36. This resulted in brightness enhancement by a factor of 2.6.

© 2007 Optical Society of America

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References

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Figures (3)

Fig. 1
Fig. 1

(a) Calculated polarization distribution just after passing a radially polarized LG ( 0 , 1 ) * beam through the SVR. (b) Calculated far-field intensity distribution. (c) Far-field intensity cross section (solid), with the intensity cross section obtained with an ideal continuous SVR device (dashed). (d) Beam quality factor M 2 of the beam obtained after the spatial filtering, as a function of the spatial filter radius, normalized to the waist parameter w. (e) Spatial-filtering efficiency, as a function of the normalized spatial-filter radius. (f) Ratio of the beam brightness, obtained after the spatial-filtering, to that of the input LG ( 0 , 1 ) * beam, as a function of the normalized spatial-filter radius. Solid curves are for transformation with an eight-sectored SVR; dashed curves are for transformation with an ideal continuous SVR.

Fig. 2
Fig. 2

(a), (b) Near-field and far-field intensity distributions of the input LG ( 0 , 1 ) * mode, obtained from the high-power Nd:YAG radially polarized resonator. (c)–(f) Near-field distributions obtained after passing the beam through an analyzing polarizer in (c) horizontal, (d) 45°, (e) vertical, and (f) 135° orientations.

Fig. 3
Fig. 3

(a) Image of the input radially polarized beam in the SVR plane; (b) far-field intensity distribution; (c), (d) near-field and far-field intensity distributions of the output beam, obtained after the spatial filtering.

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