The row span of a matrix over arbitrary index types #
A matrix whose rows and columns are indexed by arbitrary types has no
rank in the sense of linear algebra. Two standard substitutes are the
dimension of the span of its rows and the supremum of the ranks of its
finite submatrices; this module proves them interchangeable in the
bounded form that a rank hypothesis uses, so that no cardinal
supremum is needed: the row span has dimension at most n exactly
when every finite submatrix has rank at most n
(rank_span_rows_le_iff). The same criterion is restated for the row
span presented as the range of Finsupp.lift
(rank_range_lift_le_iff), which is how the connection matrices of
RS/Novel/Skein/ConnectionRank.lean present theirs.
The point of substance is that a finite-dimensional space of functions
on κ is separated by finitely many coordinates
(exists_finset_separating): that is what makes the row rank of an
infinite matrix visible on a single finite submatrix.
Separating a space of functions on finitely many coordinates #
A finite-dimensional space of functions on κ is separated by
finitely many coordinates: some finite T is such that a vector of the
space vanishing throughout T is zero.
Finite submatrices and the row span #
The submatrix of M on the rows S and the columns T.
Equations
- RS.submatrixOn M S T = (Matrix.of M).submatrix Subtype.val Subtype.val
Instances For
The row span and the finite submatrices agree in bounded form.
The span of the rows of M has dimension at most n exactly when
every finite submatrix of M has rank at most n.
The range of Finsupp.lift at M is the span of the rows of
M.
The bounded row-rank criterion, for the row span presented as
the range of Finsupp.lift.