1. Fast and accurate algorithm for the computation of complex linear canonical transforms
- Author
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Haldun M. Ozaktas, Aykut Koc, Lambertus Hesselink, and Haldun M. Özaktaş
- Subjects
Computer science ,Gaussian ,Computation ,Fast Fourier transform ,Lossless ,Space-bandwidth product ,Fractional Fourier transforms ,Linear canonical transform ,symbols.namesake ,Bandwidth ,Graded index ,Number of samples ,Optical systems ,Input sample ,Paraxial optical systems ,Fast Fourier transforms ,Eigenvalues and eigenfunctions ,Free space ,Lossy systems ,Numerical analysis ,Complex parameter ,Thin lens ,Complex number ,Linear canonical transformation ,Binary logarithm ,Atomic and Molecular Physics, and Optics ,matrix ,Phase systems ,Electronic, Optical and Magnetic Materials ,Fourier transform ,Gaussians ,Gaussian apertures ,Input-output ,symbols ,Mathematical transformations ,Computer Vision and Pattern Recognition ,Numerical computations ,Algorithm ,Algorithms - Abstract
A fast and accurate algorithm is developed for the numerical computation of the family of complex linear canonical transforms (CLCTs), which represent the input-output relationship of complex quadratic-phase systems. Allowing the linear canonical transform parameters to be complex numbers makes it possible to represent paraxial optical systems that involve complex parameters. These include lossy systems such as Gaussian apertures, Gaussian ducts, or complex graded-index media, as well as lossless thin lenses and sections of free space and any arbitrary combinations of them. Complex-ordered fractional Fourier transforms (CFRTs) are a special case of CLCTs, and therefore a fast and accurate algorithm to compute CFRTs is included as a special case of the presented algorithm. The algorithm is based on decomposition of an arbitrary CLCT matrix into real and complex chirp multiplications and Fourier transforms. The samples of the output are obtained from the samples of the input in approximately N log N time, where N is the number of input samples. A space-bandwidth product tracking formalism is developed to ensure that the number of samples is information-theoretically sufficient to reconstruct the continuous transform, but not unnecessarily redundant.
- Published
- 2010