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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.23373 |
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| _version_ | 1866909526443163648 |
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| author | de Borba, Jhordan Silveira Maziero, Jonas |
| author_facet | de Borba, Jhordan Silveira Maziero, Jonas |
| contents | The first artificial quantum neuron models followed a similar path to classic models, as they work only with discrete values. Here we introduce an algorithm that generalizes the binary model manipulating the phase of complex numbers. We propose, test, and implement a neuron model that works with continuous values in a quantum computer. Through simulations, we demonstrate that our model may work in a hybrid training scheme utilizing gradient descent as a learning algorithm. This work represents another step in the direction of evaluation of the use of artificial neural networks efficiently implemented on near-term quantum devices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_23373 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Non-binary artificial neuron with phase variation implemented on a quantum computer de Borba, Jhordan Silveira Maziero, Jonas Quantum Physics Artificial Intelligence Machine Learning Neural and Evolutionary Computing The first artificial quantum neuron models followed a similar path to classic models, as they work only with discrete values. Here we introduce an algorithm that generalizes the binary model manipulating the phase of complex numbers. We propose, test, and implement a neuron model that works with continuous values in a quantum computer. Through simulations, we demonstrate that our model may work in a hybrid training scheme utilizing gradient descent as a learning algorithm. This work represents another step in the direction of evaluation of the use of artificial neural networks efficiently implemented on near-term quantum devices. |
| title | Non-binary artificial neuron with phase variation implemented on a quantum computer |
| topic | Quantum Physics Artificial Intelligence Machine Learning Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2410.23373 |