The nonnegative rank of a nonnegative matrix — the smallest number of nonnegative rank-one matrices summing to — satisfies , and the upper bound is trivially attained. Shitov (2014) proved the first nontrivial upper bound in terms of ordinary rank: every nonnegative matrix of ordinary rank 3 has nonnegative rank at most , equivalently every convex -gon has extension complexity (the minimum number of facets of a higher-dimensional polytope that projects onto it) at most ; this ceiling was later lowered to . For matrices of ordinary rank 4 and higher, however, no nontrivial upper bound of any kind is known, and it is equally open whether matrices of ordinary rank 4 with full nonnegative rank exist for arbitrarily large sizes. The problem asks to settle the existence, form, and order of growth of nontrivial upper bounds on the worst-case nonnegative rank of matrices of any fixed ordinary rank — equivalently, for , whether every pair of nested 3-dimensional polytopes admits an intermediate polytope with fewer vertices than the trivial count (the polytope rendering of the matrix bound ), where and denote vertex and facet counts.
Background
The nonnegative rank of a nonnegative matrix , written , is the smallest integer for which with and entrywise nonnegative — equivalently, the smallest number of nonnegative rank-one matrices summing to . Such decompositions are the subject of nonnegative matrix factorization (NMF), a standard dimensionality-reduction model in data analysis. One always has , where denotes the ordinary rank over the reals, and whenever the ordinary rank is at most 2 (Cohen and Rothblum 1993; Beasley and Laffey 2009). The gap between the two ranks is therefore invisible below ordinary rank 3 and unbounded in general, which makes the worst-case size of this gap, as a function of the ordinary rank and of the matrix dimensions, a basic structural question about nonnegative factorizations.
A second origin of the same quantity is polyhedral optimization. An extended formulation of a polytope is a description of a polytope , in possibly higher dimension, by linear equations and inequalities, such that is a linear projection of ; the extension complexity is the minimum number of inequalities over all such descriptions. Yannakakis (1991) proved that equals the nonnegative rank of any slack matrix of — the nonnegative matrix whose entry measures how far the -th vertex is from saturating the -th facet inequality — and the slack matrix of a -dimensional polytope has ordinary rank . Hence nontrivial upper bounds on the nonnegative rank of fixed-rank matrices are exactly nontrivial upper bounds on the extension complexity of fixed-dimensional polytopes, that is, on the size of their linear-programming formulations.
For ordinary rank 3 the worst case is a well-studied quantity, , the largest extension complexity of a convex -gon (slack matrices of -gons have ordinary rank 3). Beasley and Laffey (2009) asked whether a rank-3 matrix with nonnegative rank exists. Gillis and Glineur (2012) characterized geometrically as the minimum number of vertices of a polytope nested between an inner and an outer polytope determined by , and settled the question positively for ; Gouveia, Parrilo and Thomas (2013) settled via a sufficiently irregular hexagon. Shitov (2014) proved that every nonnegative rank-3 matrix obeys and consequently , giving a negative answer for . Shitov's later work ('Sublinear extensions of polygons', 2020 preprint, published 2026) identified , for , with the largest nonnegative rank of a matrix with at most rows and ordinary rank 3, proved — refuting widely held expectations of (near-)linear growth, such as the affirmative answer conjectured by several authors to the question of Braun and Pokutta (2016) whether for a fixed — and left the asymptotics open: dimension counting gives (Fiorini, Rothvoß and Tiwary 2012), Padrol (2016) improved this to , and for regular polygons Goucha, Gouveia and Silva (2017) proved a lower bound of about on the nonnegative rank of the slack matrix.
For ordinary rank — corresponding to polytopes of dimension 3 and higher — the picture is empty: no nontrivial upper bound on nonnegative rank is known for any , and the trivial bound is the only general one. On the lower-bound side, generic 3-dimensional polytopes with facets provide rank-4 slack matrices with nonnegative rank at least about (Padrol 2016), and full extension complexity in dimension 3 is known to occur generically only up to 8 vertices or facets. Worst-case results do exist for neighboring invariants and cones — positive-semidefinite formulations (descriptions by linear matrix inequalities, a strictly more expressive model than linear inequalities) of size at most exist for every -gon (Gouveia, Robinson and Thomas 2015), and every -dimensional 0/1-polytope has linear extension complexity (Averkov, Kaibel and Weltge 2018) — but neither transfers to the nonnegative rank of general matrices or to linear extension complexity of fixed-dimension polytopes.
Problem Statement
Let denote the largest nonnegative rank attained by a nonnegative matrix of ordinary rank at most whose smaller dimension (the minimum of its numbers of rows and columns) is at most . The known landmarks are: for ; , the worst-case extension complexity of a convex -gon, which lies between and ; trivially; and via slack matrices of generic 3-dimensional polytopes (Padrol 2016).
The problem is to settle, for fixed ordinary rank , whether the trivial bound can be improved in the worst case — with being the first open rung. The question has two possible resolutions for a given :
(1) Prove a nontrivial upper bound: establish a function with for all sufficiently large such that every nonnegative matrix of ordinary rank at most and smaller dimension at most has nonnegative rank at most , and identify the form and order of growth of the bound so established; determining the true asymptotics of itself is not required for this option.
(2) Disprove the possibility of such a bound: construct, for infinitely many , explicit nonnegative matrices of ordinary rank whose nonnegative rank equals their smaller dimension — equivalently, by the nested-polytope interpretation of nonnegative rank, pairs of nested -dimensional polytopes that admit no intermediate polytope with fewer vertices.
For , statement (2) asks whether a rank-4 analogue of the Beasley–Laffey full-rank matrices exists, and statement (1) asks whether the sublinearity phenomenon Shitov established for ordinary rank 3 persists one rank higher; equivalently, whether every pair of nested 3-dimensional polytopes admits an intermediate polytope with fewer vertices than the trivial count . The common objective is the order of growth of for fixed ; a result covering every fixed , in either direction, resolves the problem in full generality. Within the per- formulation above, is the smallest admissible instance: since a matrix of ordinary rank 4 also has rank at most for every , a rank-4 full-rank construction as in (2) refutes any eventual nontrivial upper bound for all , whereas an upper bound established only for leaves the higher ranks open.
References
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