Quantum-Enhanced Single-Parameter Phase Estimation with Adaptive NOON States

TL;DR

This paper develops a differentiable quantum-optical framework to optimize NOON states for phase estimation, significantly improving Fisher information and measurement efficiency at photon numbers 2 to 5.

Contribution

It introduces an end-to-end learnable model that optimizes circuit parameters for quantum phase estimation, surpassing previous experimental benchmarks.

Findings

Raw CFI improvements up to 1775% for N=5

Measurement event efficiency increased by up to 133 times

Initial NOON states are suboptimal for N≥3, with optimized states approaching 82% of the Heisenberg limit

Abstract

Quantum metrology promises phase sensitivity surpassing the shot-noise limit by exploiting entanglement and photon-number correlations. NOON states-maximally path-entangled $N$-photon superpositions $(|N,0\rangle + |0,N\rangle)/\sqrt{2}$ -achieve the Heisenberg limit $1/N$ for single-parameter estimation, as demonstrated experimentally by Afek et al. (2010) using hybrid coherent-plus-squeezed light up to $N=5$. We present an end-to-end differentiable quantum-optical framework-implemented in Strawberry Fields (Killoran et al., 2019) with a TensorFlow backend -that learns optimal circuit parameters by maximising the classical Fisher information (CFI) across all coincidence channels for $N=2,3,4,5$. Starting from proper numerical reproductions of the Afek et al. coincidence fringes, verified by FFT analysis and parity measurements, we apply gradient descent (Adam) to the eight trainable circuit parameters. Raw CFI improvements grow dramatically with photon number: $+153\%$ ($N=2$), $+834\%$ to $+956\%$ ($N=3$), $+829\%$ to $+1598\%$ ($N=4$), and $+1775\%$ ($N=5$), alongside post-selection rate improvements of $+153\%$ to $+3269\%$, and an $8\times$ to $133\times$ improvement in useful measurement events per pulse across $N=2$-$5$. A fundamental inter-channel trade-off is identified at $N=2$ but weakens at higher $N$ where the Afek initialisation is further from optimal. These results provide numerically rigorous benchmarks for adaptive single-parameter quantum sensing and demonstrate that the Afek working point is significantly suboptimal at $N\geq 3$. QFI calculations confirm that the optimised probe reaches $82\%$ of the Heisenberg limit at $N=2$ and improves from $36\%$ to $58\%$ at $N=5$, while useful measurement events per pulse improve by $8\times$ to $133\times$ across all $N$, making quantum-enhanced sensing at $N\geq 3$ experimentally practical.