Machine-learning certification of multipartite entanglement for noisy quantum hardware
Entanglement is a fundamental aspect of quantum physics, both conceptually and for its many applications. Classifying an arbitrary multipartite state as entangled or separable—a task referred to as the separability problem—poses a significant challenge, since a state can be entangled with respect to...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | New Journal of Physics |
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| Online Access: | https://doi.org/10.1088/1367-2630/adde80 |
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| _version_ | 1850108043101995008 |
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| author | Andreas J C Fuchs Eric Brunner Jiheon Seong Hyeokjea Kwon Seungchan Seo Joonwoo Bae Andreas Buchleitner Edoardo G Carnio |
| author_facet | Andreas J C Fuchs Eric Brunner Jiheon Seong Hyeokjea Kwon Seungchan Seo Joonwoo Bae Andreas Buchleitner Edoardo G Carnio |
| author_sort | Andreas J C Fuchs |
| collection | DOAJ |
| description | Entanglement is a fundamental aspect of quantum physics, both conceptually and for its many applications. Classifying an arbitrary multipartite state as entangled or separable—a task referred to as the separability problem—poses a significant challenge, since a state can be entangled with respect to many different of its partitions. We develop a certification pipeline that feeds the statistics of random local measurements into a non-linear dimensionality reduction algorithm, to determine with respect to which partitions a given quantum state is entangled. After training a model on randomly generated quantum states, entangled in different partitions and of varying purity, we verify the accuracy of its predictions on simulated test data, and finally apply it to states prepared on IBM quantum computing hardware. |
| format | Article |
| id | doaj-art-e0bad8b3701a46eab453a6f30b67f10f |
| institution | OA Journals |
| issn | 1367-2630 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj-art-e0bad8b3701a46eab453a6f30b67f10f2025-08-20T02:38:28ZengIOP PublishingNew Journal of Physics1367-26302025-01-0127707450110.1088/1367-2630/adde80Machine-learning certification of multipartite entanglement for noisy quantum hardwareAndreas J C Fuchs0Eric Brunner1https://orcid.org/0000-0001-7631-6528Jiheon Seong2Hyeokjea Kwon3https://orcid.org/0000-0003-1709-8481Seungchan Seo4https://orcid.org/0000-0002-2256-8989Joonwoo Bae5https://orcid.org/0000-0002-2345-1619Andreas Buchleitner6Edoardo G Carnio7https://orcid.org/0000-0002-1270-7607Physikalisches Institut, Albert-Ludwigs-Universität Freiburg , Hermann-Herder-Straße 3, D-79104 Freiburg, GermanyQuantinuum, Partnership House , Carlisle Place, London SW1P 1BX, United KingdomSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology , Daejeon, Republic of KoreaSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology , Daejeon, Republic of KoreaSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology , Daejeon, Republic of KoreaSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology , Daejeon, Republic of KoreaPhysikalisches Institut, Albert-Ludwigs-Universität Freiburg , Hermann-Herder-Straße 3, D-79104 Freiburg, Germany; EUCOR center for Quantum Science and Quantum Computing, Albert-Ludwigs-Universität Freiburg , Hermann-Herder-Straße 3, D-79104 Freiburg, GermanyPhysikalisches Institut, Albert-Ludwigs-Universität Freiburg , Hermann-Herder-Straße 3, D-79104 Freiburg, Germany; EUCOR center for Quantum Science and Quantum Computing, Albert-Ludwigs-Universität Freiburg , Hermann-Herder-Straße 3, D-79104 Freiburg, GermanyEntanglement is a fundamental aspect of quantum physics, both conceptually and for its many applications. Classifying an arbitrary multipartite state as entangled or separable—a task referred to as the separability problem—poses a significant challenge, since a state can be entangled with respect to many different of its partitions. We develop a certification pipeline that feeds the statistics of random local measurements into a non-linear dimensionality reduction algorithm, to determine with respect to which partitions a given quantum state is entangled. After training a model on randomly generated quantum states, entangled in different partitions and of varying purity, we verify the accuracy of its predictions on simulated test data, and finally apply it to states prepared on IBM quantum computing hardware.https://doi.org/10.1088/1367-2630/adde80machine learningmultipartite entanglementnonlinear dimensionality reductionentanglement certificationrandomized correlatorsquantum computing |
| spellingShingle | Andreas J C Fuchs Eric Brunner Jiheon Seong Hyeokjea Kwon Seungchan Seo Joonwoo Bae Andreas Buchleitner Edoardo G Carnio Machine-learning certification of multipartite entanglement for noisy quantum hardware New Journal of Physics machine learning multipartite entanglement nonlinear dimensionality reduction entanglement certification randomized correlators quantum computing |
| title | Machine-learning certification of multipartite entanglement for noisy quantum hardware |
| title_full | Machine-learning certification of multipartite entanglement for noisy quantum hardware |
| title_fullStr | Machine-learning certification of multipartite entanglement for noisy quantum hardware |
| title_full_unstemmed | Machine-learning certification of multipartite entanglement for noisy quantum hardware |
| title_short | Machine-learning certification of multipartite entanglement for noisy quantum hardware |
| title_sort | machine learning certification of multipartite entanglement for noisy quantum hardware |
| topic | machine learning multipartite entanglement nonlinear dimensionality reduction entanglement certification randomized correlators quantum computing |
| url | https://doi.org/10.1088/1367-2630/adde80 |
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