Divide by Matrix: Is it Possible?

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In post #7 of https://www.physicsforums.com/showthread.php?t=532666" thread, the OP asked whether one could meaningfully divide by a matrix. Certainly this is possible for invertible matrices, but I'm wondering if it's possible to define something similar even for singular matrices.

For instance, suppose I have a singular matrix [itex]A[/itex]. If [itex]B = \lambda A[/itex], it seems natural to define [itex]\frac{B}{A} := \lambda I[/itex]. However, I don't think this operation is well-defined. Since [itex]A[/itex] is singular, left multiplication by [itex]A[/itex] has a nontrivial kernel, so there is some nonzero vector [itex]v[/itex] such that [itex]Av = 0[/itex]. Letting [itex]V[/itex] be the matrix with columns [itex]v[/itex], then [itex]B = A \cdot \lambda I = A \cdot (\lambda I + V)[/itex], so [itex]\frac{B}{A}[/itex] could just as well be equal to [itex]\lambda I + V[/itex].

My question is, is there a way to make this division well-defined? Would working over a ring with specific properties help?
 
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Firstly, if you can't do it over a field, you probably can't do it over a ring. The field is the best case for scalars.

What you are looking for is what we call http://en.wikipedia.org/wiki/Von_Neumann_regular_ring" which has uniqueness.

There is also the http://en.wikipedia.org/wiki/Drazin_inverse" . The Drazin inverse has a further generalization called the g-Drazin inverse aka Drazin-Koliha inverse, but this is more C*-algebra stuff, rather than matrix theory proper.
 
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Thanks for the reply--the links were very interesting.

I guess what makes [itex]\lambda I[/itex] the "natural" choice for [itex]\frac{B}{A}[/itex] if [itex]B = \lambda A[/itex] is that [itex]\lambda I[/itex] is a scalar matrix and lies in the center of the ring. I guess these various pseudoinverses all have some nice properties and I'll have to work out some examples.