  We develop a new tool to generate statistically precise dark matter maps from
the cosmic magnification of galaxies with distance estimates. We show how to
overcome the intrinsic clustering problem using the slope of the luminosity
function, because magnificability changes strongly over the luminosity
function, while intrinsic clustering only changes weakly. This may allow
precision cosmology beyond most current systematic limitations. SKA is able to
reconstruct projected matter density map at smoothing scale $\sim 10^{'}$ with
S/N$\geq 1$, at the rate of 200-4000 deg$^2$ per year, depending on the
abundance and evolution of 21cm emitting galaxies. This power of mapping dark
matter is comparable to, or even better than that of cosmic shear from deep
optical surveys or 21cm surveys.
