Foundation Model for Unified Characterization of Optical Quantum States

TL;DR

This paper introduces a foundation model that can universally characterize a wide range of optical quantum states, including complex non-Gaussian and multimode states, with limited data and minimal fine-tuning.

Contribution

A novel foundation model for optical quantum state characterization that generalizes across complexity levels and adapts to various tasks with limited fine-tuning.

Findings

Model pretrained on simple states effectively characterizes complex states.

Limited fine-tuning enables accurate prediction of fidelity and negativity.

Applicable to high-dimensional, highly non-Gaussian, and highly squeezed states.

Abstract

Machine learning methods have been used to infer specific properties of limited families of optical quantum states, but a unified model that predicts a broad range of properties for practically relevant-especially multimode non-Gaussian-states without full tomography is still lacking. Here we introduce the first foundation model for the characterization of optical quantum states across a wide range of complexity, defined by three key factors: non-Gaussianity, number of modes, and degree of squeezing. We show that a single model pretrained on low-complexity states can be directly applied to characterize states of higher complexity. With limited fine-tuning, the model adapts to downstream tasks such as predicting quantum fidelity and Wigner negativity over a broad class of experimentally relevant states, including strongly non-Gaussian Schr\"odinger cat states, multimode systems with up to ten modes, and highly squeezed states with squeezing levels up to 10.4dB. Our results establish a unified framework for characterizing optical quantum states from limited measurement data, enabling efficient certification of quantum states relevant to optical quantum information computation, communication and metrology.