Abstract
Powder auto-indexing is the crystallographic problem of lattice determination
from an average theta series. There, in addition to all the multiplicities, the
lengths of part of lattice vectors cannot be obtained owing to systematic
absences. As a consequence, solutions are not always unique. We develop a new
algorithm to enumerate powder auto-indexing solutions. This is a novel
application of the reduction theory of positive-definite quadratic forms to a
problem of crystallography. Our algorithm is proved to be effective for all
types of systematic absences, using their newly obtained common properties. The
properties are stated as distribution rules for lattice vectors corresponding
to systematic absences on a topograph. Conway defined topographs for
2-dimensional lattices as graphs whose edges are associated with \$l\_1^2\$,
\$l\_2^2\$, \$l\_1+l\_2^2\$, \$l\_1-l\_2^2\$. In our enumeration
algorithm, topographs are utilized as a network of lattice vector lengths. As a
crystal structure is a lattice of rank 3, the definition of topographs is
generalized to any higher dimensional lattices using Voronoi's second reduction
theory. The use of topographs allows us to speed up the algorithm. The
computation time is reduced to 1/250--1/32, when it is applied to real powder
diffraction patterns. Another advantage of our algorithm is its robustness to
missing or false elements in the set of lengths extracted from a powder
diffraction pattern. Conograph is the powder indexing software which implements
the algorithm. We present results of Conograph for 30 diffraction patterns,
including some very difficult cases.
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