6 papers · 1 filter
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…
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…
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…
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…
Generation of heralded optical `Schroedinger cat' states by photon-addition
Yi-Ru Chen, Hsien-Yi Hsieh, Jingyu Ning +7
Optical "Schrödinger cat" states, the non-classical superposition of two quasi-classical coherent states, serve as a basis for gedanken experiments testing quantum physics on mesos…
Direct parameter estimations from machine-learning enhanced quantum state tomography
Hsien-Yi Hsieh, Jingyu Ning, Yi-Ru Chen +4
With the capability to find the best fit to arbitrarily complicated data patterns, machine-learning (ML) enhanced quantum state tomography (QST) has demonstrated its advantages in…