activity
20232026
collaborators

10 papers

quant-ph2026

Normalizing Flow-Based Bayesian Parameter Estimation for Noisy Quantum States

Hsien-Yi Hsieh, Yuan-Ting Liu, Juan Camilo Rodrıguez +5

To extract complete information about experimental noisy quantum states, as well as correlations among different physical parameters, we develop an efficient machine learning-assis…

quant-ph2026

Quantum steering in networks: Measurement-device-independent detection, continuous variables, and practical Gaussian schemes

Shao-Hua Hu, Chung-Yun Hsieh, Huan-Yu Ku +2

We consider quantum steering certification in multipartite networks, with a focus on minimal trust scenarios: all-except-one parties are untrusted and treated device-independently.…

quant-ph2026

Monitoring Beam Splitter Entanglement using Quantumness

Hua-Li Chen, Hsien-Yi Hsieh, Chien-Ming Wu +2

We report on an experiment in which two independent squeezed vacuum states get entangled by mixing them with a balanced beam splitter. We follow standard practice and use an insepa…

quant-ph2026

Wigner's Phase Space Current for Variable Beam Splitters -- Phase Space Rotations and Newtonian Trajectories

Ole Steuernagel, Hsien-Yi Hsieh, Hua-Li Chen +1

Beam splitters allow us to superpose two continuous single mode quantum systems. To study the behaviour of beam splitters' strongly mode mixing dynamics we consider variable beam s…

quant-ph2025

A Sensitive Nonclassicality Certification Functional for Continuous-Variable Systems

Ole Steuernagel, Ray-Kuang Lee

If the phase space-based Glauber-Sudarshan distribution, , has negative values the quantum state, , it describes is nonclassical. Due to 's singular behavi…

quant-ph2025

Machine Learning for Quantum State Tomography: Robust Covariance Matrix Estimation for Squeezed Vacuum States with Thermal Noise

Juan Camilo Rodrıguez, Hsien-Yi Hsieh, Hua-Li Chen +3

We present a supervised machine learning-based method using convolutional neural networks to estimate the covariance matrix of Gaussian quantum states in the presence of thermal no…

quant-ph2025

Machine Learning Enhanced Quantum State Tomography on FPGA

Hsun-Chung Wu, Hsien-Yi Hsieh, Zhi-Kai Xu +7

Machine learning techniques have opened new avenues for real-time quantum state tomography (QST). In this work, we demonstrate the deployment of machine learning-based QST onto edg…

quant-ph2024

Adding or Subtracting a single Photon is the same for Pure Squeezed Vacuum States

Ole Steuernagel, Ray-Kuang Lee

The addition of a single photon to a light field can lead to exactly the same \emph{outcome} as the subtraction of a single photon. We prove that this \cterm is true for pure squee…

quant-ph2024

Neural Network Enhanced Single-Photon Fock State Tomography

Hsien-Yi Hsieh, Yi-Ru Chen, Jingyu Ning +7

Even though heralded single-photon sources have been generated routinely through the spontaneous parametric down conversion, vacuum and multiple photon states are unavoidably invol…

quant-ph2023

A Sensitive Quantumness Measure for One-Dimensional Continuous-Variable Systems

Ole Steuernagel, Hsien-Yi Hsieh, Yi-Ru Chen +1

For one-dimensional continuous-variable quantum systems such as single-mode quantum optical systems, we give a quantification of the quantumness of such a system's state, ρ, by int…