Observation of entanglement transition of pseudo-random mixed states
Tong Liu,
Shang Liu,
Hekang Li,
Hao Li,
Kaixuan Huang,
Zhongcheng Xiang,
Xiaohui Song,
Kai Xu (),
Dongning Zheng () and
Heng Fan ()
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Tong Liu: Chinese Academy of Sciences
Shang Liu: University of California
Hekang Li: Chinese Academy of Sciences
Hao Li: Chinese Academy of Sciences
Kaixuan Huang: Chinese Academy of Sciences
Zhongcheng Xiang: Chinese Academy of Sciences
Xiaohui Song: Chinese Academy of Sciences
Kai Xu: Chinese Academy of Sciences
Dongning Zheng: Chinese Academy of Sciences
Heng Fan: Chinese Academy of Sciences
Nature Communications, 2023, vol. 14, issue 1, 1-7
Abstract:
Abstract Random quantum states serve as a powerful tool in various scientific fields, including quantum supremacy and black hole physics. It has been theoretically predicted that entanglement transitions may happen for different partitions of multipartite random quantum states; however, the experimental observation of these transitions is still absent. Here, we experimentally demonstrate the entanglement transitions witnessed by negativity on a fully connected superconducting processor. We apply parallel entangling operations, that significantly decrease the depth of the pseudo-random circuits, to generate pseudo-random pure states of up to 15 qubits. By quantum state tomography of the reduced density matrix of six qubits, we measure the negativity spectra. Then, by changing the sizes of the environment and subsystems, we observe the entanglement transitions that are directly identified by logarithmic entanglement negativities based on the negativity spectra. In addition, we characterize the randomness of our circuits by measuring the distance between the distribution of output bit-string probabilities and the Porter-Thomas distribution. Our results show that superconducting processors with all-to-all connectivity constitute a promising platform for generating random states and understanding the entanglement structure of multipartite quantum systems.
Date: 2023
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DOI: 10.1038/s41467-023-37511-y
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