Local Variance-Based Calibration of Programmable Photonic Interferometer Meshes

• URL: http://arxiv.org/abs/2607.14759v1
• Date: Thu, 16 Jul 2026 09:45:13 GMT
• Title: Local Variance-Based Calibration of Programmable Photonic Interferometer Meshes
• Abstract summary: We introduce a local variance-based self-calibration method using intensity-only measurements.<n>For Mach-Zehnder interferometers, the variance follows a characteristic |sin(theta)| dependence.<n>We validate the method experimentally on an 8 x 8 silicon nitride programmable photonic processor.
• Score: 2.4050736024350994
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Programmable photonic interferometer meshes enable reconfigurable linear optical transformations, but their performance depends critically on accurate calibration of Mach-Zehnder interferometers and phase shifters. Conventional methods often require node isolation, dedicated routing paths, orthogonal training states, reference channels, or prior phase-voltage characterization, which become increasingly difficult in large thermally tuned meshes. We introduce a local variance-based self-calibration method using intensity-only measurements. Controlled phase perturbations are applied, and calibration points are identified from minima of the measured output-power variance. For Mach-Zehnder interferometers, the variance follows a characteristic |sin(theta)| dependence, allowing bar and cross operating points to be found without conventional node isolation. For phase shifters, balanced interference produces a complementary |cos(phi)| variance signature, enabling quadrature calibration through the same statistical principle. We validate the method experimentally on an 8 x 8 silicon nitride programmable photonic processor using a fully automated two-stage procedure. Starting from random phase settings, all Mach-Zehnder interferometers are calibrated first, followed by phase-shifter calibration under balanced-interference conditions. As a system-level test, we implement an embedded 4 x 4 Hadamard transformation on the 8 x 8 processor using a Clements decomposition. These results establish local output variance as a simple calibration observable for programmable photonic meshes. The method is compatible with discrete random phase ensembles and requires neither conventional node isolation nor orthogonal training fields, making it a practical calibration primitive for scalable self-stabilizing photonic processors.

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