Transfer Learning Analysis of Variational Quantum Circuits
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866908449264107520 |
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| author | Tseng, Huan-Hsin Lin, Hsin-Yi Chen, Samuel Yen-Chi Yoo, Shinjae |
| author_facet | Tseng, Huan-Hsin Lin, Hsin-Yi Chen, Samuel Yen-Chi Yoo, Shinjae |
| contents | This work analyzes transfer learning of the Variational Quantum Circuit (VQC). Our framework begins with a pretrained VQC configured in one domain and calculates the transition of 1-parameter unitary subgroups required for a new domain. A formalism is established to investigate the adaptability and capability of a VQC under the analysis of loss bounds. Our theory observes knowledge transfer in VQCs and provides a heuristic interpretation for the mechanism. An analytical fine-tuning method is derived to attain the optimal transition for adaptations of similar domains. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_01507 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Transfer Learning Analysis of Variational Quantum Circuits Tseng, Huan-Hsin Lin, Hsin-Yi Chen, Samuel Yen-Chi Yoo, Shinjae Quantum Physics Artificial Intelligence Machine Learning This work analyzes transfer learning of the Variational Quantum Circuit (VQC). Our framework begins with a pretrained VQC configured in one domain and calculates the transition of 1-parameter unitary subgroups required for a new domain. A formalism is established to investigate the adaptability and capability of a VQC under the analysis of loss bounds. Our theory observes knowledge transfer in VQCs and provides a heuristic interpretation for the mechanism. An analytical fine-tuning method is derived to attain the optimal transition for adaptations of similar domains. |
| title | Transfer Learning Analysis of Variational Quantum Circuits |
| topic | Quantum Physics Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2501.01507 |