Abstract. A polytope is inscribable if there is a realization where all vertices lie on the sphere. In this paper, we provide a necessary and sufficient condition for a polytope to be inscribable. Based on this condition, we characterize the problem of determining inscribability as a minimum rank optimization problem using slack matrices. We propose a semidefinite programming (SDP) approximation for the minimum rank optimization problem and prove that it is tight for certain classes of polytopes. Given a polytope, we provide three algorithms to determine its inscribability. All the optimization problems and algorithms we propose in this paper depend on the number of vertices and facets but are independent of the dimension of the polytope. Numerical results demonstrate our SDP approximation’s efficiency, accuracy, and robustness for determining inscribability of simplicial polytopes of dimensions [Formula: see text] with vertices [Formula: see text], revealing its potential in high dimensions.

In this paper we introduce a natural model for the realization space of a polytope up to projective equivalence which we call the slack realization space of the polytope. The model arises from the positive part of an algebraic variety determined by the slack ideal of the polytope. This is a saturated determinantal ideal that encodes the combinatorics of the polytope. We also derive a new model of the realization space of a polytope from the positive part of the variety of a related ideal. The slack ideal offers an effective computational framework for several classical questions about polytopes such as rational realizability, nonprescribability of faces, and realizability of combinatorial polytopes.