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Título
Finding eigenvectors with a quantum variational algorithm
Año del Documento
2024
Editorial
Springer
Descripción
Producción Científica
Documento Fuente
Quantum Information Processing, 2024, vol. 23, n. 7
Resumen
This paper presents a hybrid variational quantum algorithm that finds a random eigen-
vector of a unitary matrix with a known quantum circuit. The algorithm is based on the
SWAP test on trial states generated by a parametrized quantum circuit. The eigenvec-
tor is described by a compact set of classical parameters that can be used to reproduce
the found approximation to the eigenstate on demand. This variational eigenvector
finder can be adapted to solve the generalized eigenvalue problem, to find the eigen-
vectors of normal matrices and to perform quantum principal component analysis on
unknown input mixed states. These algorithms can all be run with low-depth quantum
circuits, suitable for an efficient implementation on noisy intermediate-scale quantum
computers and, with some restrictions, on linear optical systems. In full-scale quan-
tum computers, where there might be optimization problems due to barren plateaus
in larger systems, the proposed algorithms can be used as a primitive to boost known
quantum algorithms. Limitations and potential applications are discussed.
Materias (normalizadas)
Computación cuántica
Fotónica
Materias Unesco
2210.23 Teoría Cuántica
1203 Ciencia de Los Ordenadores
2209 Óptica
Palabras Clave
Quantum algorithms
Variational algorithms
Hybrid quantum algorithms
Eigenvectors
Quantum principal component analysis
SWAP test
Revisión por pares
SI
Patrocinador
Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLE
Ministerio de Ciencia e Innovación (MCIN) - (project PID2020-119418GB-I00)
Ministerio de Ciencia e Innovación (MCIN) - (project PID2020-119418GB-I00)
Version del Editor
Propietario de los Derechos
© 2024 The Author(s)
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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