Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Javier Gonzalez-Conde"'
Publikováno v:
Quantum, Vol 8, p 1297 (2024)
Loading functions into quantum computers represents an essential step in several quantum algorithms, such as quantum partial differential equation solvers. Therefore, the inefficiency of this process leads to a major bottleneck for the application of
Externí odkaz:
https://doaj.org/article/4fd3f41a04884e8da23aa2cf0e64be8b
Publikováno v:
Physical Review Research, Vol 5, Iss 4, p 043220 (2023)
Pricing financial derivatives, in particular European-style options at different time-maturities and strikes, means a relevant problem in finance. The dynamics describing the price of vanilla options when constant volatilities and interest rates are
Externí odkaz:
https://doaj.org/article/52a64efa686743da971c085ff28e2b1d
Publikováno v:
Physical Review Research, Vol 5, Iss 3, p 033114 (2023)
Loading classical data into quantum computers represents an essential stage in many relevant quantum algorithms, especially in the field of quantum machine learning. Therefore, the inefficiency of this loading process means a major bottleneck for the
Externí odkaz:
https://doaj.org/article/ff452e6ad86e4c00924b433f8f2bc783
Autor:
Yongcheng Ding, Javier Gonzalez-Conde, Lucas Lamata, José D. Martín-Guerrero, Enrique Lizaso, Samuel Mugel, Xi Chen, Román Orús, Enrique Solano, Mikel Sanz
Publikováno v:
Entropy, Vol 25, Iss 2, p 323 (2023)
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-
Externí odkaz:
https://doaj.org/article/50924b601ec24730b01882f2c2193d9d