Optical Equalization using Spectral Phase Shaping
Year: 2026
Type: preprint
Abstract: We present a signal-processing framework that performs optical dynamic range compression via programmable spectral phase modulation followed by coherent detection. Motivated by the Physics-inspired Computer Vision (PhyCV) family of algorithms (itself inspired by photonics time stretch), the method exploits the natural equalization that arises from near-field spectral phase modulation followed by coherent detection. In this representation, the resulting in-phase (I) channel closely preserves the original signal profile, while the quadrature (Q) channel provides a spectrally filtered response that functions as a dark-field measurement. The phase obtained from the I and Q channels exhibits a nonlinear amplitude-to-phase mapping that exhibits dynamic range compression. To evaluate whether this concept can be realized in hardware, we emulate an LCOS-based programmable waveshaper as the spectral phase modulator. The model incorporates hardware-informed characteristics of the COHERENT WaveShaper 1000A, including spectral-phase discretization imposed by the LCOS pixel grid, finite frequency resolution and accuracy. Applying this module to simulated LiDAR waveforms shows that the spectral phase engineering provides a natural equalization of the LiDAR signal while preserving temporal structure and enhancing low-amplitude returns. These results suggest that the proposed technique is a promising physical-computing primitive for real-time preprocessing in high dynamic range systems such as LiDAR.
Language: English
Subfield: Instrumentation
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7150794822