Tikhonov regularization of spherical far-field continuation ($g_{\alpha ,n}^m=d_n{b}_n^m/(1+\alpha |d_n{|}^2)$)

Let $d_n=k{i}^{n+1}{h}_n^{(1)}(kR)$ and map the near-field trace to the far field by $Ag=(g_n^m/d_n{)}_{n,m}$. Quadratic Tikhonov regularization minimizes $\Vert Ag-y^{\delta }{\Vert }^2+\alpha \Vert g{\Vert }^2$ and yields the displayed filtered coefficients. Its data-error gain is at most $1/(2\sqrt{\alpha })$. Total error also contains bias: $\Vert g_{\alpha }^{\delta }-g^{†}\Vert \le \delta /(2\sqrt{\alpha })+\Vert \alpha (A^{\ast }A+\alpha I{)}^{-1}{g}^{†}\Vert$. A convergent parameter rule has $\alpha \to 0$ and $\delta /\sqrt{\alpha }\to 0$. Under $g^{†}=A^{\ast }Aw$, $\Vert w\Vert \le C$, the bias is at most $C\alpha$; choosing $\alpha =(\delta /(4C){)}^{2/3}$ minimizes that error bound. Making $\alpha$ indefinitely large removes noise by shrinking the reconstruction to zero, not by recovering the true field.