Source-Prior Engineering for Bayesian Optical Sensing in Time-Reversed Young Interferometry

Area of Science:

• Quantum optics
• Metrology
• Information theory

Background:

• Conventional Young interferometry relies on detector-plane measurements.
• Reconstructing interference from a fixed detector presents unique challenges.
• Bayesian inference offers a framework for sensor design.

Purpose of the Study:

• To formulate Time-reversed Young (TRY) interferometry as a source-coded Bayesian response sensor.
• To identify the key sensing resource in TRY as posterior-weighted score contrast.
• To develop practical design rules for TRY systems and analyze their tolerances.

Main Methods:

• Formulating TRY architecture as a source-coded Bayesian response sensor.
• Analyzing the detected source-label histogram as a posterior distribution.
• Deriving Fisher information from the posterior variance of a centered likelihood score.
• Proposing a passive double-slit implementation with weak perturbations.

Main Results:

• The prior in TRY reshapes the sampled response ensemble, enabling enhanced sensing.
• Posterior-weighted score contrast is identified as the crucial sensing resource.
• A two-label source code converts weak perturbations into detectable label imbalances.
• Practical tolerances and extensions to integrated photonics are analyzed.

Conclusions:

• TRY interferometry provides a source-programmable Bayesian sensing architecture.
• It complements conventional detector-plane Young interferometry.
• The framework offers resource-aware methods for near-null response enhancement and multiparameter sensing.