PROGRAM SUMMARY
Title of program:
Glass Onion
Catalogue identifier:
ADRY
Ref. in CPC:
154(2003)76
Distribution format: zip file
Operating system: Windows 98, Windows 2000, Windows NT
High speed store required:
18MK words
Number of bits in a word:
32
Number of lines in distributed program, including test data, etc:
59391
Keywords:
Photofragment image, Onion peeling, Anisotropy parameters,
Photoionization, Photodissociation, Velocity-map imaging, Molecule,
Experimental analysis.
Programming language used: Delphi 4.0
Computer:
IBM PC .
Nature of physical problem:
Information about velocity and angular distributions of photofragments
is the basis on which the analysis of the photolysis process resides.
Reconstructing the three-dimensional distribution from the photofragment
image is the first step, further processing involving angular and radial
integration of the inverted image to obtain velocity and angular
distributions. Provisions have to be made to correct for slight
distortions of the image, and to verify the accuracy of the analysis
process.
Method of solution:
The "Onion Peeling" algorithm described by HelM [Rev. Sci. Instrum.
67 (6) (1966)] is used to perform the image reconstruction. Angular
integration with a subsequent multi-Gaussian fit supplies information
about the vElocity distribution of the photofragments, whereas radial
integration with subsequent expansion of the angular distributions over
Legendre Polynomials gives the spatial anisotropy parameters. Fitting
algorithms have been developed to centre the image and to correct for
image distortion.
Restrictions:
The maximum image size (1280 x 1280) and resolution (16 bit) are
restricted by available memory and can be changed in the source code.
Initial centre coordinates within 5 pixels may be required for the
correction and the centering algorithm to converge. Peaks on the
velocity profile separated by less than the peak width may not be
deconvolved. In the charged particle image reconstruction, it is
assumed that the kinetic energy released in the dissociation process is
small compared to the energy acquired in the electric field. For the
fitting parameters to be physically meaningful, cylindrical symmetry of
the image has to be assumed but the actual inversion algorithm is
stable to distortions of such symmetry in experimental images.
Typical running time:
The analysis procedure can be divided into three parts: inversion,
fitting, and geometry correction. The inversion time grows
approximately as R^3, where R is the radius of the region of interest;
for R = 200 pixels it is less than a minute, for R = 400 pixels less
than 6 min on a 400 MHz IBM personal computer. The time for the
velocity fitting procedure to converge depends strongly on the number
of peaks in the velocity profile and the convergence criterion. It
ranges between less than a second for simple curves and a few minutes
for profiles with up to twenty peaks. The time taken for the image
correction scales as R^2 and depends on the curve profile. It is of
the order of a few minutes for images with R = 500 pixels.
Unusual features:
Our centering and image correction algorithm is based on Fourier
analysis of the radial distribution to insure the sharpest velocity
profile and is insensitive to an uneven intensity distribution. There
exists an angular averaging option to stabilize the inversion algorithm
and not to lose the resolution at the same time.