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UID:pretalx-juliacon-2026-7ZFWC8@pretalx.com
DTSTART;TZID=CET:20260813T161500
DTEND;TZID=CET:20260813T163000
DESCRIPTION:This package provides a collection of functions which can be wr
 itten in a form separated by coordinates.\nAn example is a multidimensiona
 l Gaussian\, a parabolic potential or a complex valued plane wave.\nTypica
 lly the separable functions are combined by a multiplication but there are
  also examples using other operators to combine them. Upon construction th
 e separable parts are pre-calculated and a Julia-generic `Base.Broadcast.B
 roadcasted` object\, which behaves a bit like a lazy array. It seamlessly 
 merges with other broadcasting operations. The package\, albeit being CUDA
 -agnostic\, is fully capable of working with `CuArray` objects\, creating 
 a pre-calculated 1-dimensional `CuArray` for each dimension which then tak
 es part in the broadcasting. The use of `SeparableFuctions.jl` significant
 ly speeds up calculations and saves on-board memory. It is currently used 
 in a number of other packages\, for example `StructuredIlluminationMicrosc
 opy.jl` which reconstructs optical images supported by acceleration via `C
 UDA.jl`(See also the Computational Physics Minisymposium).
DTSTAMP:20260502T104016Z
LOCATION:Room 3
SUMMARY:SeparableFunctions.jl - Rainer Heintzmann
URL:https://pretalx.com/juliacon-2026/talk/7ZFWC8/
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UID:pretalx-juliacon-2026-7AEJTQ@pretalx.com
DTSTART;TZID=CET:20260814T121500
DTEND;TZID=CET:20260814T123000
DESCRIPTION:Structured Illumination Microscopy is a method in which a fluor
 escent sample is illuminated with a number of patterns containing high spa
 tial frequencies. This encodes super-resolution information into the  clas
 sical light microscopy image which is the successively recovered by Fourie
 r-space based reconstruction methods. \nThis talk will introduce into the 
 topic and then highlight some of the concepts behind `StructuredIlluminati
 onMicroscopy.jl`\, which supports some of the fastest algorithms for recon
 structing images measured by structured illumination. The package features
  Fourier-space reconstruction approaches including upsampling\, reconstruc
 tion and  noise-reduction steps. It exploits `rFFT`s and `SeparableFunctio
 ns.jl`\, wherever possible\, minimizes the memory footprint by working on 
 pre-allocated arrays and fully supports GPU acceleration via `CUDA.jl`.
DTSTAMP:20260502T104016Z
LOCATION:Room 2
SUMMARY:StructuredIlluminationMicroscopy.jl - Rainer Heintzmann
URL:https://pretalx.com/juliacon-2026/talk/7AEJTQ/
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