Entanglement detection with classical deep neural networks

Understand

In this study, we introduce an autonomous method for addressing the detection and classification of quantum entanglement, a core element of quantum mechanics that has yet to be fully understood.

• We employ a multi-layer perceptron to effectively identify entanglement in both two- and three-qubit systems.
• Our technique yields impressive detection results, achieving nearly perfect accuracy for two-qubit systems and over $90\%$ accuracy for three-qubit systems.
• Additionally, our approach successfully categorizes three-qubit entangled states into distinct groups with a success rate of up to $77\%$.