Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909621178859520 |
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| author | Sahin, M. Emre Altamura, Edoardo Wallis, Oscar Wood, Stephen P. Dekusar, Anton Millar, Declan A. Imamichi, Takashi Matsuo, Atsushi Mensa, Stefano |
| author_facet | Sahin, M. Emre Altamura, Edoardo Wallis, Oscar Wood, Stephen P. Dekusar, Anton Millar, Declan A. Imamichi, Takashi Matsuo, Atsushi Mensa, Stefano |
| contents | We present Qiskit Machine Learning (ML), a high-level Python library that combines elements of quantum computing with traditional machine learning. The API abstracts Qiskit's primitives to facilitate interactions with classical simulators and quantum hardware. Qiskit ML started as a proof-of-concept code in 2019 and has since been developed to be a modular, intuitive tool for non-specialist users while allowing extensibility and fine-tuning controls for quantum computational scientists and developers. The library is available as a public, open-source tool and is distributed under the Apache version 2.0 license. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_17756 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators Sahin, M. Emre Altamura, Edoardo Wallis, Oscar Wood, Stephen P. Dekusar, Anton Millar, Declan A. Imamichi, Takashi Matsuo, Atsushi Mensa, Stefano Quantum Physics Emerging Technologies Machine Learning Computational Physics We present Qiskit Machine Learning (ML), a high-level Python library that combines elements of quantum computing with traditional machine learning. The API abstracts Qiskit's primitives to facilitate interactions with classical simulators and quantum hardware. Qiskit ML started as a proof-of-concept code in 2019 and has since been developed to be a modular, intuitive tool for non-specialist users while allowing extensibility and fine-tuning controls for quantum computational scientists and developers. The library is available as a public, open-source tool and is distributed under the Apache version 2.0 license. |
| title | Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators |
| topic | Quantum Physics Emerging Technologies Machine Learning Computational Physics |
| url | https://arxiv.org/abs/2505.17756 |