# Computing inverse of matrix with very small precision values

I have a square matrix with very small values of the order of 10^-9 or 10^-20. I need to compute the inverse of this matrix. But when I try to compute the inverse of the function using Python's inbuilt numpy.linalg.inv(.) function, I get an inverse matrix with all entries 0. Is there any transformation that can be applied to the matrix to extract the inverse approximation out of the original matrix.

• Are all of the entries small (say, smaller than $10^{-9}$ in absolute value)? If so, then Morgan's trick should work Mar 30, 2019 at 16:34
• Obligatory: Are you sure you need to compute the inverse? There might be more appropriate tools for the task you have in mind. Mar 30, 2019 at 16:41
• @Lorenzo Yes it is inverse itself. However, even if not exact, any approximations will also do. Mar 30, 2019 at 23:15
• Mar 31, 2019 at 5:46