Optimizing resetting of superconducting qubits

Many quantum algorithms demand a large number of repetitions to obtain reliable statistical results. Thus, at each repetition it is necessary to reset the qubits efficiently and precisely in the shortest possible time, so that quantum computers actually have advantages over classical ones. In this w...

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Detalles Bibliográficos
Autores: Diniz, Ciro Micheletti, de Assis, Rogério Jorge, de Almeida, Norton Gomes, Villas-Bôas, Celso Jorge
Tipo de recurso: conjunto de datos
Estado:Versión publicada
Fecha de publicación:2023
País:Brasil
Institución:Universidade Federal de São Carlos (UFSCAR)
Repositorio:Repositório Institucional da UFSCAR
Idioma:inglés
OAI Identifier:oai:repositorio.ufscar.br:20.500.14289/19326
Acceso en línea:https://repositorio.ufscar.br/handle/20.500.14289/19326
Access Level:acceso abierto
Palabra clave:Reset protocols
Erasure of information
Quantum computation
Protocolos de reset
Apagamento de informação
Computação quântica
CIENCIAS EXATAS E DA TERRA::FISICA::FISICA GERAL::FISICA CLASSICA E FISICA QUANTICA; MECANICA E CAMPOS
CIENCIAS EXATAS E DA TERRA::FISICA::FISICA GERAL::FISICA ESTATISTICA E TERMODINAMICA
Descripción
Sumario:Many quantum algorithms demand a large number of repetitions to obtain reliable statistical results. Thus, at each repetition it is necessary to reset the qubits efficiently and precisely in the shortest possible time, so that quantum computers actually have advantages over classical ones. In this work, we perform a detailed analysis of three different models for information resetting in superconducting qubits. Our experimental setup consists of a main qubit coupled to different auxiliary dissipative systems, which are employed in order to perform the erasure of the information of the main qubit. Our analysis shows that it is not enough to increase the coupling and the dissipation rate associated with the auxiliary systems to decrease the resetting time of the main qubit, a fact that motivates us to find the optimal set of parameters for each studied approach, allowing a significant decrease in the reset time of the three models analyzed.