Design Space Exploration of Hybrid Quantum–Classical Neural Networks
<div><p>The unprecedented success of classical neural networks and the recent advances in quantum computing have motivated the research community to explore the interplay between these two technologies, leading to the so-called quantum neural networks. In fact, universal quantum computer...
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2021
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| _version_ | 1864513506121875456 |
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| author | Muhammad Kashif (3923483) |
| author2 | Saif Al-Kuwari (16904610) |
| author2_role | author |
| author_facet | Muhammad Kashif (3923483) Saif Al-Kuwari (16904610) |
| author_role | author |
| dc.creator.none.fl_str_mv | Muhammad Kashif (3923483) Saif Al-Kuwari (16904610) |
| dc.date.none.fl_str_mv | 2021-11-30T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3390/electronics10232980 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Design_Space_Exploration_of_Hybrid_Quantum_Classical_Neural_Networks/26940268 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Machine learning Theory of computation quantum machine learning quantum neural networks hybrid neural networks amplitude encoding angle encoding variational quantum circuits |
| dc.title.none.fl_str_mv | Design Space Exploration of Hybrid Quantum–Classical Neural Networks |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <div><p>The unprecedented success of classical neural networks and the recent advances in quantum computing have motivated the research community to explore the interplay between these two technologies, leading to the so-called quantum neural networks. In fact, universal quantum computers are anticipated to both speed up and improve the accuracy of neural networks. However, whether such quantum neural networks will result in a clear advantage on noisy intermediate-scale quantum (NISQ) devices is still not clear. In this paper, we propose a systematic methodology for designing quantum layer(s) in hybrid quantum–classical neural network (HQCNN) architectures. Following our proposed methodology, we develop different variants of hybrid neural networks and compare them with pure classical architectures of equivalent size. Finally, we empirically evaluate our proposed hybrid variants and show that the addition of quantum layers does provide a noticeable computational advantage.</p><p> </p></div><h2>Other Information</h2> <p> Published in: Electronics<br> License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/electronics10232980" target="_blank">https://dx.doi.org/10.3390/electronics10232980</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_ed1eec66dcb2925f90433b8c9bd68af6 |
| identifier_str_mv | 10.3390/electronics10232980 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/26940268 |
| publishDate | 2021 |
| repository.mail.fl_str_mv | |
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| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Design Space Exploration of Hybrid Quantum–Classical Neural NetworksMuhammad Kashif (3923483)Saif Al-Kuwari (16904610)Information and computing sciencesMachine learningTheory of computationquantum machine learningquantum neural networkshybrid neural networksamplitude encodingangle encodingvariational quantum circuits<div><p>The unprecedented success of classical neural networks and the recent advances in quantum computing have motivated the research community to explore the interplay between these two technologies, leading to the so-called quantum neural networks. In fact, universal quantum computers are anticipated to both speed up and improve the accuracy of neural networks. However, whether such quantum neural networks will result in a clear advantage on noisy intermediate-scale quantum (NISQ) devices is still not clear. In this paper, we propose a systematic methodology for designing quantum layer(s) in hybrid quantum–classical neural network (HQCNN) architectures. Following our proposed methodology, we develop different variants of hybrid neural networks and compare them with pure classical architectures of equivalent size. Finally, we empirically evaluate our proposed hybrid variants and show that the addition of quantum layers does provide a noticeable computational advantage.</p><p> </p></div><h2>Other Information</h2> <p> Published in: Electronics<br> License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/electronics10232980" target="_blank">https://dx.doi.org/10.3390/electronics10232980</a></p>2021-11-30T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/electronics10232980https://figshare.com/articles/journal_contribution/Design_Space_Exploration_of_Hybrid_Quantum_Classical_Neural_Networks/26940268CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/269402682021-11-30T03:00:00Z |
| spellingShingle | Design Space Exploration of Hybrid Quantum–Classical Neural Networks Muhammad Kashif (3923483) Information and computing sciences Machine learning Theory of computation quantum machine learning quantum neural networks hybrid neural networks amplitude encoding angle encoding variational quantum circuits |
| status_str | publishedVersion |
| title | Design Space Exploration of Hybrid Quantum–Classical Neural Networks |
| title_full | Design Space Exploration of Hybrid Quantum–Classical Neural Networks |
| title_fullStr | Design Space Exploration of Hybrid Quantum–Classical Neural Networks |
| title_full_unstemmed | Design Space Exploration of Hybrid Quantum–Classical Neural Networks |
| title_short | Design Space Exploration of Hybrid Quantum–Classical Neural Networks |
| title_sort | Design Space Exploration of Hybrid Quantum–Classical Neural Networks |
| topic | Information and computing sciences Machine learning Theory of computation quantum machine learning quantum neural networks hybrid neural networks amplitude encoding angle encoding variational quantum circuits |