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We study the complexity of computing the projection of an arbitrary $d$-polytope along $k$ orthogonal vectors for various input and output forms. We show that if $d$ and $k$ are part of the input (i.e. not a constant) and we are interested in output-sensitive algorithms, then in most forms the problem is equivalent to enumerating vertices of polytopes, except in two where it is NP-hard. In two other forms the problem is trivial. We also review the complexity of computing projections when the projection directions are in some sense non-degenerate. For full-dimensional polytopes containing origin in the interior, projection is an operation dual to intersecting the polytope with a suitable linear subspace and so the results in this paper can be dualized by interchanging vertices with facets and projection with intersection. To compare the complexity of projection and vertex enumeration, we define new complexity classes based on the complexity of Vertex Enumeration.
It is well known that any graph admits a crossing-free straight-line drawing in $mathbb{R}^3$ and that any planar graph admits the same even in $mathbb{R}^2$. For a graph $G$ and $d in {2,3}$, let $rho^1_d(G)$ denote the minimum number of lines in $m
We give a pseudorandom generator that fools $m$-facet polytopes over ${0,1}^n$ with seed length $mathrm{polylog}(m) cdot log n$. The previous best seed length had superlinear dependence on $m$. An immediate consequence is a deterministic quasipolynom
We study the combinatorial Reeb flow on the boundary of a four-dimensional convex polytope. We establish a correspondence between combinatorial Reeb orbits for a polytope, and ordinary Reeb orbits for a smoothing of the polytope, respecting action an
The disjointness problem - where Alice and Bob are given two subsets of ${1, dots, n}$ and they have to check if their sets intersect - is a central problem in the world of communication complexity. While both deterministic and randomized communicati
This paper establishes some of the fundamental barriers in the theory of computations and finally settles the long-standing computational spectral problem. That is to determine the existence of algorithms that can compute spectra $mathrm{sp}(A)$ of c