Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Guglielmo Mazzola"'
Publikováno v:
Physical Review Research, Vol 5, Iss 3, p 033225 (2023)
The variational approach is a cornerstone of computational physics, considering both conventional and quantum computing computational platforms. The variational quantum eigensolver algorithm aims to prepare the ground state of a Hamiltonian exploitin
Externí odkaz:
https://doaj.org/article/f4775779b6af4546849217fe86dfb9ab
Autor:
Julian Schuhmacher, Guglielmo Mazzola, Francesco Tacchino, Olga Dmitriyeva, Tai Bui, Shanshan Huang, Ivano Tavernelli
Publikováno v:
AIP Advances, Vol 12, Iss 11, Pp 115321-115321-16 (2022)
Solving electronic structure problems represents a promising field of applications for quantum computers. Currently, much effort is spent in devising and optimizing quantum algorithms for near-term quantum processors, with the aim of outperforming cl
Externí odkaz:
https://doaj.org/article/aafb1aeb74c649c09bdeda67dff0939e
Publikováno v:
Quantum, Vol 6, p 770 (2022)
We introduce a quantum algorithm to compute the market risk of financial derivatives. Previous work has shown that quantum amplitude estimation can accelerate derivative pricing quadratically in the target error and we extend this to a quadratic erro
Externí odkaz:
https://doaj.org/article/068b4e19145a40ae84be01c3397a5aaa
Publikováno v:
Physical Review Research, Vol 3, Iss 4, p 043209 (2021)
Quantum computation represents an emerging framework to solve lattice gauge theories (LGTs) with arbitrary gauge groups, a general and long-standing problem in computational physics. While quantum computers may encode LGTs using only polynomially inc
Externí odkaz:
https://doaj.org/article/7c5b6ec1887f48b8af5ac08eb2046fde
Autor:
Guillermo García-Pérez, Matteo A.C. Rossi, Boris Sokolov, Francesco Tacchino, Panagiotis Kl. Barkoutsos, Guglielmo Mazzola, Ivano Tavernelli, Sabrina Maniscalco
Publikováno v:
PRX Quantum, Vol 2, Iss 4, p 040342 (2021)
Many prominent quantum computing algorithms with applications in fields such as chemistry and materials science require a large number of measurements, which represents an important roadblock for future real-world use cases. We introduce a novel appr
Externí odkaz:
https://doaj.org/article/5da1496b21fb49308f6dfc6cbb4cd089
Autor:
Shouvanik Chakrabarti, Rajiv Krishnakumar, Guglielmo Mazzola, Nikitas Stamatopoulos, Stefan Woerner, William J. Zeng
Publikováno v:
Quantum, Vol 5, p 463 (2021)
We give an upper bound on the resources required for valuable quantum advantage in pricing derivatives. To do so, we give the first complete resource estimates for useful quantum derivative pricing, using autocallable and Target Accrual Redemption Fo
Externí odkaz:
https://doaj.org/article/dfb092388b6f47b8994a20234f743159
Autor:
Giuseppe Carleo, Kenny Choo, Damian Hofmann, James E.T. Smith, Tom Westerhout, Fabien Alet, Emily J. Davis, Stavros Efthymiou, Ivan Glasser, Sheng-Hsuan Lin, Marta Mauri, Guglielmo Mazzola, Christian B. Mendl, Evert van Nieuwenburg, Ossian O’Reilly, Hugo Théveniaut, Giacomo Torlai, Filippo Vicentini, Alexander Wietek
Publikováno v:
SoftwareX, Vol 10, Iss , Pp - (2019)
We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques. The framework is built around a general and flexible implementation of neural-network quantum states, which are u
Externí odkaz:
https://doaj.org/article/d09a9ec97b6d44d190c7e5f50486a66c
Autor:
Igor O. Sokolov, Panagiotis Kl. Barkoutsos, Lukas Moeller, Philippe Suchsland, Guglielmo Mazzola, Ivano Tavernelli
Publikováno v:
Physical Review Research, Vol 3, Iss 1, p 013125 (2021)
Ab initio molecular dynamics (AIMD) is a powerful tool to predict properties of molecular and condensed matter systems. However, the quality of this procedure relies on the availability of rigorous electronic structure calculations. The development o
Externí odkaz:
https://doaj.org/article/a1d0bbf5aab24ddeaad8c20c04da2563
Publikováno v:
Physical Review Research, Vol 2, Iss 2, p 022060 (2020)
The measurement precision of modern quantum simulators is intrinsically constrained by the limited set of measurements that can be efficiently implemented on hardware. This fundamental limitation is particularly severe for quantum algorithms where co
Externí odkaz:
https://doaj.org/article/4645587fc3b54da2932f2cb2640dd046
Autor:
Ivano Tavernelli, Boris Sokolov, Sabrina Maniscalco, Guillermo García-Pérez, Matteo A. C. Rossi, Francesco Tacchino, Guglielmo Mazzola, Panagiotis Kl. Barkoutsos
Many prominent quantum computing algorithms with applications in fields such as chemistry and materials science require a large number of measurements, which represents an important roadblock for future real-world use cases. We introduce a novel appr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a47b712e3069cb278117d53bb8d28ac
http://hdl.handle.net/10138/337245
http://hdl.handle.net/10138/337245