beta-Variational autoencoder as an entanglement classifier
| Autor: | Nahum Sá, Itzhak Roditi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Physics
Quantum Physics business.industry General Physics and Astronomy Pattern recognition Deep learning Quantum entanglement Space (mathematics) Autoencoder Separable space Set (abstract data type) Separable state Quantum state Entanglement witness Artificial intelligence Representation (mathematics) business |
| Zdroj: | Physics Letters A, 417 |
| ISSN: | 0375-9601 0031-9163 1873-2429 |
| Popis: | We focus on using an architecture similar to the beta-Variational Autoencoder (beta-VAE) to discriminate if a quantum state is entangled or separable based on measurements. We split the data into two sets, the set of local and correlated measurements. Using the latent space, which is a low dimensional representation of the data, we show that restricting ourselves to the set of local data it is not possible to distinguish between entangled and separable states. Meanwhile, when considering both correlated and local measurements, an accuracy of over 80% is attained in the structure of the latent space. Physics Letters A, 417 ISSN:0375-9601 ISSN:0031-9163 ISSN:1873-2429 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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