Self-calibrating Tomography for Angular Schmidt Modes in Spontaneous Parametric Down-Conversion
Stanislav Straupe, Denis Ivanov, Alexander Kalinkin, Ivan Bobrov,, Sergey P. Kulik, D.Mogilevtsev
TL;DR
This paper introduces a self-calibrating tomography method for high-dimensional quantum entanglement characterization using Schmidt decomposition, enabling accurate inference of eigenvalues and detection efficiencies.
Contribution
It presents a novel self-tomography approach based on maximal likelihood estimation for entanglement analysis in high-dimensional quantum systems.
Findings
Successfully characterized Schmidt eigenvalues and detection efficiencies.
Demonstrated the effectiveness of self-calibration in quantum tomography.
Enhanced accuracy in entanglement measurement in experimental setups.
Abstract
We report an experimental self-calibrating tomography scheme for entanglement characterization in high-dimensional quantum systems using Schmidt decomposition techniques. The self-tomography technique based on maximal likelihood estimation was developed for characterizing non-ideal measurements in Schmidt basis allowing us to infer both Schmidt eigenvalues and detecting efficiencies.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.