Spektraldiffusion

Spektraldiffusion is a concept used in photonics and signal processing to describe a diffusion-like evolution of a signal’s spectral content over time. It refers to the spreading or redistribution of energy in the frequency domain, arising from stochastic environmental fluctuations, interactions within a medium, or non-linear mixing processes. The term is often used to distinguish spectral dynamics from spatial diffusion, focusing on how a spectrum changes rather than how light spreads through space.

In physical systems, spektraldiffusion can result from random fluctuations in local fields, temperature, or charge states that cause dephasing and energy-level wandering. This leads to spectral diffusion or wandering, where the center and width of spectral features change over time. A simple way to describe the dynamics is through a diffusion-like equation for the spectral density S(f, t): ∂S/∂t = ∂/∂f [D(f) ∂S/∂f] plus possible drift terms, where D(f) is a frequency-dependent diffusion coefficient. Boundary conditions enforce non-negativity and normalization of the spectrum.

Applications of spektraldiffusion include understanding and modeling time-resolved, spectrally resolved measurements in quantum optics, spectroscopy of solid-state emitters, and signal processing in dense optical channels. It also informs approaches to mitigate spectral instability, enable high-resolution metrology, and guide diffusion-based modeling of spectral data in machine learning and data analysis.

Relation to related concepts includes spectral diffusion, diffusion equations, and stochastic processes. Analysis typically relies on time-resolved and frequency-resolved measurements to separate diffusion effects from intrinsic broadening and instrumental response.