Demonstration of quantum projective simulation on a single-photon-based quantum computer
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916527490465792 |
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| author | Franceschetto, Giacomo Ricou, Arno |
| author_facet | Franceschetto, Giacomo Ricou, Arno |
| contents | Variational quantum algorithms show potential in effectively operating on noisy intermediate-scale quantum devices. A novel variational approach to reinforcement learning has been recently proposed, incorporating linear-optical interferometers and a classical learning model known as projective simulation (PS). PS is a decision-making tool for reinforcement learning and can be classically represented as a random walk on a graph that describes the agent's memory. In its optical quantum version, this approach utilizes quantum walks of single photons on a mesh of tunable beamsplitters and phase shifters to select actions. In this work, we present the implementation of this algorithm on Ascella, a single-photon-based quantum computer from Quandela. The focus is drawn on solving a test bed task to showcase the potential of the quantum agent with respect to the classical agent. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_12729 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Demonstration of quantum projective simulation on a single-photon-based quantum computer Franceschetto, Giacomo Ricou, Arno Quantum Physics Variational quantum algorithms show potential in effectively operating on noisy intermediate-scale quantum devices. A novel variational approach to reinforcement learning has been recently proposed, incorporating linear-optical interferometers and a classical learning model known as projective simulation (PS). PS is a decision-making tool for reinforcement learning and can be classically represented as a random walk on a graph that describes the agent's memory. In its optical quantum version, this approach utilizes quantum walks of single photons on a mesh of tunable beamsplitters and phase shifters to select actions. In this work, we present the implementation of this algorithm on Ascella, a single-photon-based quantum computer from Quandela. The focus is drawn on solving a test bed task to showcase the potential of the quantum agent with respect to the classical agent. |
| title | Demonstration of quantum projective simulation on a single-photon-based quantum computer |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2404.12729 |