Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor
Symmetry-protected topological phases have fundamentally changed our understanding of quantum matter. An archetypal example of such a quantum phase of matter is the Haldane phase, containing the spin-1 Heisenberg chain. The intrinsic quantum nature of such phases, however, often makes it challenging...
| Autores: | , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:dnet:digitalcsic_::99886fb1d29b18e655abb1995330b7aa |
| Acceso en línea: | http://hdl.handle.net/10261/429354 https://www.scopus.com/pages/publications/105008117312?origin=resultslist |
| Access Level: | acceso abierto |
| Palabra clave: | Quantum optics Qubits Topology Deterministics Haldane Heisenberg chains Quantum matter Quantum nature Quantum phase Quantum processors Qutrits Topological phase Trapped ion Chains |
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Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor |
| title |
Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor |
| spellingShingle |
Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor Edmunds, C.L. Quantum optics Qubits Topology Deterministics Haldane Heisenberg chains Quantum matter Quantum nature Quantum phase Quantum processors Qutrits Topological phase Trapped ion Chains |
| title_short |
Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor |
| title_full |
Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor |
| title_fullStr |
Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor |
| title_full_unstemmed |
Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor |
| title_sort |
Symmetry-Protected Topological Haldane Phase on a Qudit Quantum Processor |
| dc.creator.none.fl_str_mv |
Edmunds, C.L. Rico, E. Arrazola, I. Brennen, G.K. Meth, M. Blatt, R. Ringbauer, M. |
| author |
Edmunds, C.L. |
| author_facet |
Edmunds, C.L. Rico, E. Arrazola, I. Brennen, G.K. Meth, M. Blatt, R. Ringbauer, M. |
| author_role |
author |
| author2 |
Rico, E. Arrazola, I. Brennen, G.K. Meth, M. Blatt, R. Ringbauer, M. |
| author2_role |
author author author author author author |
| dc.contributor.none.fl_str_mv |
Ministerio de Ciencia e Innovación (España) Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72] |
| dc.subject.none.fl_str_mv |
Quantum optics Qubits Topology Deterministics Haldane Heisenberg chains Quantum matter Quantum nature Quantum phase Quantum processors Qutrits Topological phase Trapped ion Chains |
| topic |
Quantum optics Qubits Topology Deterministics Haldane Heisenberg chains Quantum matter Quantum nature Quantum phase Quantum processors Qutrits Topological phase Trapped ion Chains |
| description |
Symmetry-protected topological phases have fundamentally changed our understanding of quantum matter. An archetypal example of such a quantum phase of matter is the Haldane phase, containing the spin-1 Heisenberg chain. The intrinsic quantum nature of such phases, however, often makes it challenging to study them using classical means. Here, we use trapped-ion qutrits to natively engineer spin-1 chains within the Haldane phase. Using a scalable deterministic procedure to prepare the Affleck-Kennedy-Lieb-Tasaki (AKLT) state within the Haldane phase, we study the topological features of this system on a qudit quantum processor. Notably, we verify the long-range string order of the state, despite its short-range correlations, and observe spin fractionalization of the physical spin-1 particles into effective qubits at the chain edges, a defining feature of this system. The native realization of Haldane physics on a qudit quantum processor and the scalable preparation procedures open the door to the efficient exploration of a wide range of systems beyond spin-1/2. © 2025 authors. |
| publishDate |
2025 |
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2025 2026 2026 |
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info:eu-repo/semantics/article http://purl.org/coar/resource_type/c_6501 Publisher's version info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
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http://hdl.handle.net/10261/429354 https://www.scopus.com/pages/publications/105008117312?origin=resultslist |
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http://hdl.handle.net/10261/429354 https://www.scopus.com/pages/publications/105008117312?origin=resultslist |
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Inglés |
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Inglés |
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PRX Quantum https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.6.020349 Sí |
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info:eu-repo/semantics/openAccess |
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openAccess |
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American Physical Society |
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American Physical Society |
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reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC instname:Consejo Superior de Investigaciones Científicas (CSIC) |
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1869405103238152192 |
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Symmetry-Protected Topological Haldane Phase on a Qudit Quantum ProcessorEdmunds, C.L.Rico, E.Arrazola, I.Brennen, G.K.Meth, M.Blatt, R.Ringbauer, M.Quantum opticsQubitsTopologyDeterministicsHaldaneHeisenberg chainsQuantum matterQuantum natureQuantum phaseQuantum processorsQutritsTopological phaseTrapped ionChainsSymmetry-protected topological phases have fundamentally changed our understanding of quantum matter. An archetypal example of such a quantum phase of matter is the Haldane phase, containing the spin-1 Heisenberg chain. The intrinsic quantum nature of such phases, however, often makes it challenging to study them using classical means. Here, we use trapped-ion qutrits to natively engineer spin-1 chains within the Haldane phase. Using a scalable deterministic procedure to prepare the Affleck-Kennedy-Lieb-Tasaki (AKLT) state within the Haldane phase, we study the topological features of this system on a qudit quantum processor. Notably, we verify the long-range string order of the state, despite its short-range correlations, and observe spin fractionalization of the physical spin-1 particles into effective qubits at the chain edges, a defining feature of this system. The native realization of Haldane physics on a qudit quantum processor and the scalable preparation procedures open the door to the efficient exploration of a wide range of systems beyond spin-1/2. © 2025 authors.This research was funded by the European Union (EU) under the Horizon Europe program—Grant Agreement No. 101080086—NeQST and by the European Research Council (ERC), QUDITS, Grant No. 101039522. The views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. This research was funded in part by the Austrian Science Fund (FWF) [10.55776/F71]. For open access purposes, the authors have applied a CC BY public copyright license to any author accepted manuscript version arising from this submission and the EU-QuantERA project “Tensor Networks in Simulation of Quantum matter” (T-NiSQ) (N-6001), and by IQI GmbH. This project has received funding from the EU Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 801110 and the Austrian Federal Ministry of Education, Science, and Research (BMBWF). It reflects only the authors’ views; the EU Agency is not responsible for any use that may be made of the information it contains. G.K.B. acknowledges support from the Australian Research Council Centre of Excellence for Engineered Quantum Systems (Grant No. CE 170100009). E.R. acknowledges support from the Basque Quantum (BasQ) strategy of the Department of Science, Universities, and Innovation of the Basque Government. E.R. is supported by Grant No. PID2021-126273NB-I00, funded by MCIN/AEI/10.13039/501100011033 and by the “European Regional Development Fund (ERDF) “A Way of Making Europe” and the Basque Government through Grant No. IT1470-22. This work was supported by the EU via QuantERA project T-NiSQ Grant No. PCI2022-132984, funded by MCIN/AEI/10.13039/501100011033 and by the EU “NextGenerationEU”/PRTR. This work has been financially supported by the Ministry of Economic Affairs and Digital Transformation of the Spanish Government through the QUANTUM ENIA project called the “Quantum Spain” project, as part of the National Strategy for Artificial Intelligence (ENIA), and by the EU through the Recovery, Transformation, and Resilience Plan–NextGenerationEU within the framework of the Digital Spain 2026 Agenda. I.A. acknowledges support from the EU Horizon Europe research and innovation program under Grant Agreement No. 101114305 (EU Project “MILLENION-SGA1”).This research was funded by the European Union (EU) under the Horizon Europe program—Grant Agreement No. 101080086—NeQST and by the European Research Council (ERC), QUDITS, Grant No. 101039522. The views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. This research was funded in part by the Austrian Science Fund (FWF) [10.55776/F71]. For open access purposes, the authors have applied a CC BY public copyright license to any author accepted manuscript version arising from this submission and the EU-QuantERA project “Tensor Networks in Simulation of Quantum matter” (T-NiSQ) (N-6001), and by IQI GmbH. This project has received funding from the EU Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 801110 and the Austrian Federal Ministry of Education, Science, and Research (BMBWF). It reflects only the authors’ views; the EU Agency is not responsible for any use that may be made of the information it contains. G.K.B. acknowledges support from the Australian Research Council Centre of Excellence for Engineered Quantum Systems (Grant No. CE 170100009). E.R. acknowledges support from the Basque Quantum (BasQ) strategy of the Department of Science, Universities, and Innovation of the Basque Government. E.R. is supported by Grant No. PID2021-126273NB-I00, funded by MCIN/AEI/10.13039/501100011033 and by the “European Regional Development Fund (ERDF) “A Way of Making Europe” and the Basque Government through Grant No. IT1470-22. This work was supported by the EU via QuantERA project T-NiSQ Grant No. PCI2022-132984, funded by MCIN/AEI/10.13039/501100011033 and by the EU “NextGenerationEU”/PRTR. This work has been financially supported by the Ministry of Economic Affairs and Digital Transformation of the Spanish Government through the QUANTUM ENIA project called the “Quantum Spain” project, as part of the National Strategy for Artificial Intelligence (ENIA), and by the EU through the Recovery, Transformation, and Resilience Plan–NextGenerationEU within the framework of the Digital Spain 2026 Agenda. I.A. acknowledges support from the EU Horizon Europe research and innovation program under Grant Agreement No. 101114305 (EU Project “MILLENION-SGA1”).Peer reviewedAmerican Physical SocietyMinisterio de Ciencia e Innovación (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202620262025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/429354https://www.scopus.com/pages/publications/105008117312?origin=resultslistreponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésPRX Quantumhttps://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.6.020349Síinfo:eu-repo/semantics/openAccessoai:dnet:digitalcsic_::99886fb1d29b18e655abb1995330b7aa2026-05-22T06:33:51Z |
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15,81155 |