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LASCAD-The Laser Cavity Analysis and

LASCAD - The Laser Cavity Analysis a

GLAD-Laser and Physical Optics Simul

SeeFiberLaser- Optical Fiber Laser S

Position : Home > PRODUCTS > Laser Design >
GLAD-Laser and Physical Optics Simulation Software
Time: 2022-10-12 22:45Source: infocrops.comWriter: infocrops


GLAD is the state-of-the-art in physical optics and laser analysis software.

GLAD is an acronym for General Laser Analysis and Design. The objective in developing GLAD has been to develop an easy-to-use program which can model every type of system which uses coherent light.

Modeling of GLAD
Simple conventional systems or complex multiple laser beam trains
Coherent and incoherent interactions
Nonlinear gain models
Lenses and mirrors: spherical, toroidal or cylindrical
General aperture shapes
Near- and far-field diffraction propagation
Stable and unstable resonator modeling
Aberration effects including: Seidel, Zernike, phase grating, and smoothed random wavefronts
Lens and mirror arrays
Variable size arrays to 32,768 x 32,768 (GLAD 64 bit) and beyond
Rectangular arrays and separable diffraction theory
Propagation of multiple, independent laser beam trains
Automatic propagation technique control (may be overridden)
Special features for resonator design
High Fresnel numbers
Kolmogorov model of atmospheric aberration
Thermal blooming
Self-focusing effects
Zonal adaptive optics model
Phase conjugation
Polarization modeling
Partially coherent modeling
Variable index of refraction modeling
ABCD propagators
Fiber optics and 3-D waveguides
Binary optics and gratings
Vector diffraction for high NA objective lenses
M^2 characterization
Phase retrieval method
Finite-element thermal modeling
Phase retrieval and simulated annealing optimization
Gain sheets, rate equation kinetics
Global coordinate system and geometrical aberrations
Arbitrary mirror locations and rotations
Raman, four-wave mixing, frequency doubling
 
Optimization
1. Least squares optimization of any configuration
2. User-defined merit functions
3. All system parameters may be used as optimizing variables
 

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