dc.creator | Ding, Yongcheng | es |
dc.creator | González Conde, Javier | es |
dc.creator | Lamata Manuel, Lucas | es |
dc.creator | Martín Guerrero, José D. | es |
dc.creator | Lizaso, Enrique | es |
dc.creator | Mugel, Samuel | es |
dc.creator | Sanz, Mikel | es |
dc.date.accessioned | 2023-02-13T13:12:37Z | |
dc.date.available | 2023-02-13T13:12:37Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Ding, Y., González Conde, J., Lamata Manuel, L., Martín Guerrero, J.D., Lizaso, E., Mugel, S. y Sanz, M. (2023). Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer. Entropy, 25 (2), 323. https://doi.org/10.48550/arXiv.1904.05808. | |
dc.identifier.issn | 1099-4300 | es |
dc.identifier.uri | https://hdl.handle.net/11441/142667 | |
dc.description.abstract | Prediction of financial crashes in a complex financial network is known to be an NP-hard problem,
which means that no known algorithm can guarantee to find optimal solutions efficiently. We experimentally
explore a novel approach to this problem by using a D-Wave quantum computer, benchmarking its performance for attaining financial equilibrium. To be specific, the equilibrium condition of a nonlinear financial
model is embedded into a higher-order unconstrained binary optimization (HUBO) problem, which is then
transformed to a spin-1/2 Hamiltonian with at most two-qubit interactions. The problem is thus equivalent
to finding the ground state of an interacting spin Hamiltonian, which can be approximated with a quantum
annealer. The size of the simulation is mainly constrained by the necessity of a large quantity of physical
qubits representing a logical qubit with the correct connectivity. Our experiment paves the way to codify
this quantitative macroeconomics problem in quantum computers. | es |
dc.description.sponsorship | Quantum Microwave Communication and Sensing (QMiCS) de EU Flagship on Quantum Technologies-QMiCS 820505 | es |
dc.description.sponsorship | An Open Superconducting Quantum Computer de EU Flagship on Quantum Technologies-OpenSuperQ 820363 | es |
dc.description.sponsorship | EU FET Open-Quromorphic 828826 | es |
dc.description.sponsorship | Ministerio de Innovación, Ciencia y Empresa de España-Ramon y Cajal RYC-2017-22482 | es |
dc.description.sponsorship | Gobierno Vasco-IT986-16 | es |
dc.description.sponsorship | Shanghai Municipal Science and Technology Commission de China-18010500400 y 18ZR1415500 | es |
dc.description.sponsorship | U.S. Department of Energy, Office of Science, Office of Advance Scientific Computing Research (ASCR)-ERKJ335 | es |
dc.format | application/pdf | es |
dc.format.extent | 13 p. | es |
dc.language.iso | eng | es |
dc.publisher | MDPI | es |
dc.relation.ispartof | Entropy, 25 (2), 323. | |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Quantum Information | es |
dc.subject | Physical Systems | es |
dc.subject | Quantum computation | es |
dc.subject | Financial networks | es |
dc.subject | Adiabatic quantum optimization | es |
dc.title | Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Física Atómica, Molecular y Nuclear | es |
dc.relation.projectID | QMiCS 820505 | es |
dc.relation.projectID | OpenSuperQ 820363 | es |
dc.relation.projectID | Quromorphic 828826 | es |
dc.relation.projectID | RYC-2017-22482 | es |
dc.relation.projectID | IT986-16 | es |
dc.relation.projectID | 18010500400 | es |
dc.relation.projectID | 18ZR1415500 | es |
dc.relation.projectID | ASCR ERKJ335 | es |
dc.relation.publisherversion | https://doi.org/10.48550/arXiv.1904.05808 | es |
dc.identifier.doi | 10.48550/arXiv.1904.05808 | es |
dc.journaltitle | Entropy | es |
dc.publication.volumen | 25 | es |
dc.publication.issue | 2 | es |
dc.publication.initialPage | 323 | es |
dc.contributor.funder | EU Flagship on Quantum Technologies | es |
dc.contributor.funder | European Commission (EC) | es |
dc.contributor.funder | Ministerio de Innovación, Ciencia y Empresa. España | es |
dc.contributor.funder | Gobierno Vasco | es |
dc.contributor.funder | Shanghai Municipal Science and Technology Commission. China | es |
dc.contributor.funder | U.S. Department of Energy, Office of Science, Office of Advance Scientific Computing Research (ASCR). U.S. | es |