1,525 research outputs found
The inverse moment problem for convex polytopes
The goal of this paper is to present a general and novel approach for the
reconstruction of any convex d-dimensional polytope P, from knowledge of its
moments. In particular, we show that the vertices of an N-vertex polytope in
R^d can be reconstructed from the knowledge of O(DN) axial moments (w.r.t. to
an unknown polynomial measure od degree D) in d+1 distinct generic directions.
Our approach is based on the collection of moment formulas due to Brion,
Lawrence, Khovanskii-Pukhikov, and Barvinok that arise in the discrete geometry
of polytopes, and what variously known as Prony's method, or Vandermonde
factorization of finite rank Hankel matrices.Comment: LaTeX2e, 24 pages including 1 appendi
Solving Sparse Integer Linear Systems
We propose a new algorithm to solve sparse linear systems of equations over
the integers. This algorithm is based on a -adic lifting technique combined
with the use of block matrices with structured blocks. It achieves a sub-cubic
complexity in terms of machine operations subject to a conjecture on the
effectiveness of certain sparse projections. A LinBox-based implementation of
this algorithm is demonstrated, and emphasizes the practical benefits of this
new method over the previous state of the art
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