.png){kind=icon}
返回
Quantum entanglement recognition
.png){kind=icon}
OA
AI
DOI：10.1103/PhysRevResearch.3.033135.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Entanglement constitutes a key characteristic feature of quantum matter. Its detection, however, still faces major challenges. In this paper, we formulate a framework for probing entanglement based on machine learning techniques. The central element is a protocol for the generation of statistical images from quantum many-body states, with which we perform image classification by means of convolutional neural networks. We show that the resulting quantum entanglement recognition task is accurate and can be assigned a well-controlled error across a wide range of quantum states. We discuss the potential use of our scheme to quantify quantum entanglement in experiments. Our developed scheme provides a generally applicable strategy for quantum entanglement recognition in both equilibrium and nonequilibrium quantum matter.
Keyword:
PYTHON FRAMEWORK
DYNAMICS
ENTROPY
QUTIP
期刊
IF:
4.2
论文数:
7.6K
被引数:
2.7W
机构
引用论文
分享收藏Mental Health Need, Awareness, and Use of Counseling Services Among International Graduate Students
PREAI
分享收藏Retreatment of gefitinib in patients with non-small-cell lung cancer who previously controlled to gefitinib: A single-arm, open-label, phase II study吉非替尼在先前控制吉非替尼的非小细胞肺癌患者中的再治疗: 单臂，开放标签，II期研究.png)
Lung Cancer
Lung CancerIF0
PREAI
分享收藏Machine learning quantum phases of matter beyond the fermion sign problemSCIENTIFIC REPORTS
OAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏分享收藏分享收藏
查看更多内容