Bound entangled states fit for robust experimental verification
Autor: | Johannes N. Greiner, Jens Siewert, Jiangwei Shang, Gael Sentís, Matthias Kleinmann |
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Rok vydání: | 2018 |
Předmět: |
Density matrix
FOS: Computer and information sciences Quantum Physics Tomographic reconstruction Physics and Astronomy (miscellaneous) Computer science FOS: Physical sciences State (functional analysis) Quantum entanglement 01 natural sciences Measure (mathematics) Atomic and Molecular Physics and Optics lcsh:QC1-999 010305 fluids & plasmas Methodology (stat.ME) Quantum state 0103 physical sciences State space Statistical physics 010306 general physics Quantum Physics (quant-ph) Statistics - Methodology lcsh:Physics Statistical hypothesis testing |
Zdroj: | Quantum Quantum, Vol 2, p 113 (2018) |
DOI: | 10.48550/arxiv.1804.07562 |
Popis: | Preparing and certifying bound entangled states in the laboratory is an intrinsically hard task, due to both the fact that they typically form narrow regions in the state space, and that a certificate requires a tomographic reconstruction of the density matrix. Indeed, the previous experiments that have reported the preparation of a bound entangled state relied on such tomographic reconstruction techniques. However, the reliability of these results crucially depends on the extra assumption of an unbiased reconstruction. We propose an alternative method for certifying the bound entangled character of a quantum state that leads to a rigorous claim within a desired statistical significance, while bypassing a full reconstruction of the state. The method is comprised by a search for bound entangled states that are robust for experimental verification, and a hypothesis test tailored for the detection of bound entanglement that is naturally equipped with a measure of statistical significance. We apply our method to families of states of $3\times 3$ and $4\times 4$ systems, and find that the experimental certification of bound entangled states is well within reach. Comment: Accepted version in Quantum |
Databáze: | OpenAIRE |
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