Dimension of a polyhedron

Dependencies:

  1. Polyhedral set and polyhedral cone
  2. Implicit equality
  3. Affine independence (incomplete)
  4. Dimension of a set of vectors
  5. Rank of a homogenous system of linear equations
  6. Linearly independent set is not bigger than a span
  7. Interior point of polyhedron

Let $P \defeq \{x \in \mathbb{R}^n: (a_i^Tx \ge b_i, \forall i \in I) \wedge (a_i^Tx = b_i, \forall i \in E)\}$ be a non-empty polyhedron without any implicit equalities. Let $A \defeq \{a_i: i \in E\}$. Then $\dim(P) = n - \rank(A)$.

Proof

Interpret $A$ as a matrix whose rows are $\{a_i^T: i \in E\}$. Let $S \defeq \{x \in \mathbb{R}^n: Ax = 0\}$. By the rank-nullity theorem, $\dim(S) = n - \rank(A)$.

Proof that $\dim(P) \le n - \rank(A)$.

Let $X \defeq \{x^{(0)}, x^{(1)}, \ldots, x^{(m)}\}$ be the max number of affinely independent vectors in $P$. Then $\dim(P) = m$. For $i \in [m]$, let $d^{(i)} \defeq x^{(i)} - x^{(0)}$ and $D \defeq \{d^{(i)}: i \in [m]\}$. Then $D$ is linearly independent.

For any $j \in E$, we have $a_j^Td^{(i)} = a_j^Tx^{(j)} - a_j^Tx^{(0)} = b_j - b_j = 0$. Hence, $Ad^{(i)} = 0$. Hence, $D \subseteq S$. Since $D$ is linearly independent, $|D| \le \dim(S) = n - \rank(A)$. Since, $\dim(P) = |D|$, we get $\dim(P) \le n - \rank(A)$.

Proof that $\dim(P) \ge n - \rank(A)$

Let $D \defeq \{d^{(1)}, \ldots, d^{(m)}\}$ be a basis of $S$. Then $m = n - \rank(A)$. Let $\xhat \in P$ be an interior point of $P$. Let $x^{(0)} \defeq \xhat$. For $i \in [m]$, let $x^{(i)} \defeq \xhat + \eps d^{(i)}$, where $\eps$ is an arbitrarily small positive real number. For small enough $\eps$, we can guarantee that $x^{(i)} \in P$ for all $i \in [m]$. This is because $\xhat$ is an interior point of $P$, and for every $j \in E$, $a_j^Tx^{(i)} = a_j^T\xhat = b_j$. By construction, $X \defeq \{x^{(i)}: 0 \le i \le m\}$ is affinely independent. Also, $X \subseteq P$. Hence, $\dim(P) \ge |X| - 1 = m = n - \rank(A)$.

Dependency for: None

Info:

Transitive dependencies:

  1. /linear-algebra/vector-spaces/condition-for-subspace
  2. /linear-algebra/matrices/gauss-jordan-algo
  3. /sets-and-relations/equivalence-relation
  4. Group
  5. Ring
  6. Polynomial
  7. Integral Domain
  8. Comparing coefficients of a polynomial with disjoint variables
  9. Field
  10. Vector Space
  11. Linear independence
  12. Affine independence (incomplete)
  13. Span
  14. Semiring
  15. Matrix
  16. Stacking
  17. System of linear equations
  18. Product of stacked matrices
  19. Matrix multiplication is associative
  20. Reduced Row Echelon Form (RREF)
  21. Matrices over a field form a vector space
  22. Row space
  23. Elementary row operation
  24. Every elementary row operation has a unique inverse
  25. Row equivalence of matrices
  26. Row equivalent matrices have the same row space
  27. RREF is unique
  28. Identity matrix
  29. Inverse of a matrix
  30. Inverse of product
  31. Elementary row operation is matrix pre-multiplication
  32. Row equivalence matrix
  33. Equations with row equivalent matrices have the same solution set
  34. Basis of a vector space
  35. Linearly independent set is not bigger than a span
  36. Homogeneous linear equations with more variables than equations
  37. Rank of a homogenous system of linear equations
  38. Rank of a matrix
  39. Dimension of a set of vectors
  40. Cone
  41. Convex combination and convex hull
  42. Convex set
  43. Polyhedral set and polyhedral cone
  44. Implicit equality
  45. Interior point of polyhedron