دورية أكاديمية

Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer

التفاصيل البيبلوغرافية
العنوان: Toward Prediction of Financial Crashes with a D-Wave Quantum Annealer
المؤلفون: Yongcheng Ding, Javier Gonzalez-Conde, Lucas Lamata, José D. Martín-Guerrero, Enrique Lizaso, Samuel Mugel, Xi Chen, Román Orús, Enrique Solano, Mikel Sanz
المصدر: Entropy, Vol 25, Iss 2, p 323 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Science
LCC:Astrophysics
LCC:Physics
مصطلحات موضوعية: quantum computation, financial networks, adiabatic quantum optimization, Science, Astrophysics, QB460-466, Physics, QC1-999
الوصف: The prediction of financial crashes in a complex financial network is known to be an NP-hard problem, which means that no known algorithm can efficiently find optimal solutions. We experimentally explore a novel approach to this problem by using a D-Wave quantum annealer, benchmarking its performance for attaining a 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 into 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 number of physical qubits representing a logical qubit with the correct connectivity. Our experiment paves the way for the codification of this quantitative macroeconomics problem in quantum annealers.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 25020323
1099-4300
Relation: https://www.mdpi.com/1099-4300/25/2/323; https://doaj.org/toc/1099-4300
DOI: 10.3390/e25020323
URL الوصول: https://doaj.org/article/50924b601ec24730b01882f2c2193d9d
رقم الأكسشن: edsdoj.50924b601ec24730b01882f2c2193d9d
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:25020323
10994300
DOI:10.3390/e25020323