Suppose I have a rectangular matrix $M(x)$ depending on a real parameter $x$. I want to find out for which $x$ are the columns of $M(x)$ linearly dependent (or equivalently, when $M(x)$ has a nontrivial kernel). I thought about using NullSpace as in
NullSpace[M[x]]
but it stubbornly outputs an empty vector, I don't think it's able to tell me when there are nontrivial solutions. If for some reason I know of a solution $x_0$, NullSpace[M[x0]] outputs the correct nullspace, but how do I find $x_0$? If $M$ was square I could simply solve $\mathrm {Det}(M(x))=0$, but I don't have such luck.
How can I do this?
x, which is equivalent to having an analytic form for it. You might want to approach this from some other perspective at least to get some insights, say via the pseudo-inverse or something. – b3m2a1 Apr 09 '20 at 17:32RowReduce? (2) If you edit the post to provide an explicit example, I might be able to demonstrate what I had in mind. – Daniel Lichtblau Apr 10 '20 at 14:27