117251 20240319080959.0 doi 10.1103/PhysRevA.105.042432 sideral 128753 ART-2022-128753 eng Sancho-Lorente, T. Quantum kernels to learn the phases of quantum matter 2022 Access copy available to the general public Unrestricted Classical machine learning has succeeded in the prediction of both classical and quantum phases of matter. Notably, kernel methods stand out for their ability to provide interpretable results, relating the learning process with the physical order parameter explicitly. Here we exploit quantum kernels instead. They are naturally related to the fidelity, and thus it is possible to interpret the learning process with the help of quantum information tools. In particular, we use a support vector machine (with a quantum kernel) to predict and characterize second-order quantum phase transitions. We explain and understand the process of learning when the fidelity per site (rather than the fidelity) is used. The general theory is tested in the Ising chain in transverse field. We show that for small-sized systems, the algorithm gives accurate results, even when trained away from criticality. Besides, for larger sizes we confirm the success of the technique by extracting the correct critical exponent ¿. Finally, we present two algorithms, one based on fidelity and one based on the fidelity per site, to classify the phases of matter in a quantum processor. info:eu-repo/grantAgreement/ES/CSIC/PTI-001 info:eu-repo/grantAgreement/ES/DGA/E09-17R-Q-MAD info:eu-repo/grantAgreement/EC/H2020/862893/EU/Molecular spin qudits offering new hope for quantum computing/FATMOLS This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 862893-FATMOLS info:eu-repo/grantAgreement/ES/MICINN/PID2020-115221GBC41/AEI/10.13039/501100011033 info:eu-repo/grantAgreement/EUR/MOLSPIN-COST/CA15128 info:eu-repo/grantAgreement/EUR/QUANTERA/SUMO info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 2.9 2022 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL 12 / 35 = 0.343 2022 Q2 T2 OPTICS 44 / 99 = 0.444 2022 Q2 T2 1.11 2022 Atomic and Molecular Physics, and Optics 2022 Q1 5.4 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Roman Roche, J. (orcid)0000-0003-2995-6615 Zueco, D. (orcid)0000-0003-4478-1948 105, 4 (2022), 042432 [9 pp.] Phys. rev., A Physical Review A 2469-9926 673949 http://zaguan.unizar.es/record/117251/files/texto_completo.pdf Versión publicada 2874389 http://zaguan.unizar.es/record/117251/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:117251 articulos driver 2024-03-18-13:59:27 ARTICLE