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Phase-Drift Limits and Adaptive Quadrature Readout in Programmable Photonic Processors

Authors: G\"okhan Elmas, Igor A. Litvin, and Janis N\"otzelPublished: 2026-08-03Paper ID: 2608.02249Category: physics.opticsLicense: CC BY 4.0

Abstract

Phase fluctuations between optical inputs limit programmable photonic processors because their output powers depend on coherent interference. We study the phase-drift penalty that arises when sine and cosine quadratures are measured sequentially rather than simultaneously. The analysis is motivated by measurements from an eight-mode programmable photonic processor, including 35 free-running recordings of 300 s acquired at approximately 125 samples per second per channel. These recordings provide an empirical route for estimating the phase-increment variance at a selected reconfiguration interval. The estimate is defined at the time of the second measurement. For fixed quadrature order, perturbation of the atan2 reconstruction gives $e_{C\to S}=-\delta_\tau\sin^2\phi_0+O(\delta_\tau^2)$ and $e_{S\to C}=-\delta_\tau\cos^2\phi_0+O(\delta_\tau^2)$. Writing $Q_\tau=\operatorname{Var}(\delta_\tau)$, uniform phase averaging gives the first-order drift mean-square error $3Q_\tau/8$. A phase-predicted ordering rule measures the locally less informative quadrature first and the more informative quadrature second. Its uniform first-order penalty is $(3/8-1/\pi)Q_\tau$, which is 84.9 percent below the fixed-order value. We also derive an increment-aware estimator from a local state-space model. Marginalizing the unknown phase increment increases the variance of a stale phase observation by $Q_\tau$, reducing its Fisher information from $I$ to $I/(1+IQ_\tau)$. For ideal balanced Poisson detection, the Fisher information of each quadrature equals its detected signal-photon number. This yields dimensionless architecture boundaries in spatial information and phase-increment variance. Nonlinear Monte Carlo simulations validate the perturbative laws, quantify robustness to prediction error, and compare simultaneous, fixed-order, increment-aware, and adaptive receivers under a common noise model.

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