From complex-step differentiation to a general reconstruction framework
Rafael Abreu, Chahana Nagesh
Abstract
The complex-step method is traditionally derived from the Taylor expansion of an analytic function and is widely used as a numerical technique for derivative approximation. We present an alternative formulation based on the Cauchy--Riemann equations and show that the classical complex-step relation arises naturally from the harmonic structure of holomorphic functions. In particular, the complex-step method admits two complementary harmonic interpretations: as a Cauchy problem, in which the derivative is identified with the normal datum of the imaginary component on the real axis, and as a reconstruction problem in a strip, in which the finite imaginary perturbation provides the upper-boundary data. The latter formulation leads explicitly to the strip Poisson and conjugate Poisson kernels and their derivatives. A related harmonic reconstruction framework in the upper half-plane leads to the Poisson, conjugate Poisson, and Cauchy kernels as elementary reconstruction operators for harmonic and holomorphic functions. Extending this reconstruction from ordinary boundary functions to finite measures yields the classical Stieltjes transform and its inversion formula. The same measure-theoretic structure appears in spectral theory, where scalar matrix elements of the resolvent are Stieltjes transforms of the associated spectral measures. These results establish a common complex-analytic structure connecting complex-step differentiation, harmonic reconstruction, Stieltjes inversion, and spectral reconstruction, while distinguishing the boundary-value problems through which the corresponding information is recovered.
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