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Quantum Error Correction Fault Tolerance
Quantum Machine Learning
Criteria for reliable entanglement quantification with finite data
arXiv
Authors: Jun O. S. Yin, Steven J. van Enk
Year
2010
Paper ID
10465
Status
Preprint
Abstract Read
~2 min
Abstract Words
42
Citations
N/A
Abstract
We propose one and a half criteria for determining how many measurements are needed to quantify entanglement reliably. We base these criteria on Bayesian analysis of measurement results, and apply our methods to four-qubit entanglement, but generalizations to more qubits are straightforward.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2010 reference point for readers tracking recent quantum research.
- We propose one and a half criteria for determining how many measurements are needed to quantify entanglement reliably.
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