Joint optimization of weighted Dicke states and symmetric lossless compression maps increases average multipartite entanglement under average rate constraints for uncertain partitions.
Efficient representation of quantum many-body states with deep neural networks,
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Quantum Compression for Distributed Entanglement
Joint optimization of weighted Dicke states and symmetric lossless compression maps increases average multipartite entanglement under average rate constraints for uncertain partitions.