Pattern capacity of a single quantum perceptron
| Autor: | Stefano Mancini, Fabio Benatti, Giovanni Gramegna |
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| Přispěvatelé: | Benatti, Fabio, Gramegna, Giovanni, Mancini, Stefano |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Statistics and Probability
quantum neural networks Quantum Physics FOS: Physical sciences General Physics and Astronomy quantum perceptron Statistical and Nonlinear Physics Disordered Systems and Neural Networks (cond-mat.dis-nn) Condensed Matter - Disordered Systems and Neural Networks perceptron capacity Modeling and Simulation Quantum Physics (quant-ph) Mathematical Physics |
| Popis: | Recent developments in Quantum Machine Learning have seen the introduction of several models to generalize the classical perceptron to the quantum regime. The capabilities of these quantum models need to be determined precisely in order to establish if a quantum advantage is achievable. Here we use a statistical physics approach to compute the pattern capacity of a particular model of quantum perceptron realized by means of a continuous variable quantum system. 18 pages, 3 figures |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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