Graph invariant defined from axis-parallel unit cubes
A graph with cubicity 2, realized as the intersection graph of axis-parallel unit 2-cubes, i.e. axis-parallel unit squares, in the plane.
In the mathematical field of graph theory, cubicity is a graph invariant defined to be the smallest dimension such that a graph can be realized as the intersection graph of axis-parallel unit cubes in Euclidean space.[1] Cubicity was introduced by Fred S. Roberts in 1969, along with a related invariant called boxicity that considers the smallest dimension needed to represent a graph as the intersection graph of axis-parallel rectangles in Euclidean space.[2]
The cubicity of a graph , denoted by , is the smallest integer such that can be represented as the intersection graph of axis-parallel closed unit -cubes in -dimensional Euclidean space, .[5][6][7]
For , a graph can have such a representation in if and only if is the intersection of indifference graphs on the same vertex set as .[8]
For a graph on vertices, Moreover, this upper bound is best possible in terms of .[15][16]
Relations to other graph dimensions
Relations to boxicity: bounds
The cubicity of a graph is closely related to its boxicity, denoted by . The definition of boxicity is essentially the same as that of cubicity, except in terms of using axis-parallel rectangles instead of axis-parallel unit cubes.
Since a cube is a special case of a rectangle, the cubicity of a graph is always an upper bound for its boxicity, i.e.,
In the other direction, it can be shown that for a graph on vertices, where denotes the ceiling function. Moreover, this upper bound is tight.[17]
↑Roberts (1969, p.302, Section 1) uses closed cubes of side-length . Footnote 1 on p. 302: "Boxes are not necessarily closed, though it is not hard to show that if a representation [of ] is attainable with [open] boxes in , it is attainable with closed boxes in .".
↑That is, cub(K1,n) = ⌈log₂(n)⌉. Proof: ∀ n ∈ ℕ*, 1 ≤ n; so, 0 < n ≤ 2n−1. ∀ n ∈ ℕ*, ∃! c ∈ ℕ such that n ≤ 2ᶜ ≤ 2n−1 (namely, c is the least k ∈ ℕ such that n ≤ 2ᵏ); so, ∃! c ∈ ℕ such that log₂(n) ≤ c ≤ log₂(2n−1). So, ⌈log₂(n)⌉ = c = ⌊log₂(2n−1)⌋.
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