General Classification of Entanglement Using Machine Learning

التفاصيل البيبلوغرافية
العنوان: General Classification of Entanglement Using Machine Learning
المؤلفون: Ayachi, F. El, Baz, M. El
سنة النشر: 2022
المجموعة: Quantum Physics
مصطلحات موضوعية: Quantum Physics
الوصف: A classification of multipartite entanglement in qubit systems is introduced for pure and mixed states. The classification is based on the robustness of the said entanglement against partial trace operation. Then we use current machine learning and deep learning techniques to automatically classify a random state of two, three and four qubits without the need to compute the amount of the different types of entanglement in each run; rather this is done only in the learning process. The technique shows high, near perfect, accuracy in the case of pure states. As expected, this accuracy drops, more or less, when dealing with mixed states and when increasing the number of parties involved.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2210.07711
رقم الأكسشن: edsarx.2210.07711
قاعدة البيانات: arXiv