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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Algoritmo de compensación de retroalimentación adaptativa para generadores de números aleatorios cuánticos

Wei Deng1,2,3, Kun Chen1,2,3, Fei Hua1,2,3

  • 1Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, School of Optoelectronic Science and Engineering, South China Normal University, Guangzhou 510006, China.

Entropy (Basel, Switzerland)
|August 28, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio introduce un algoritmo de compensación de retroalimentación adaptativa (AFCA) para mejorar los generadores de números aleatorios cuánticos (QRNG). AFCA mejora la aleatoriedad y la compatibilidad, aumentando significativamente el rendimiento de QRNG para la criptografía cuántica segura.

Palabras clave:
compensación por retroalimentación adaptativaajuste del parámetro dinámicopostprocesamientoGenerador cuántico de números aleatorios

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Área de la Ciencia:

  • Ciencia de la información cuántica
  • Criptografía
  • Física aplicada

Sus antecedentes:

  • Los generadores de números aleatorios cuánticos (QRNG) son cruciales para la criptografía cuántica.
  • Los QRNG existentes se enfrentan a desafíos con la mejora de la aleatoriedad y la compatibilidad posterior al procesamiento.

Objetivo del estudio:

  • Proponer un algoritmo de compensación de retroalimentación adaptativa (AFCA) para los QRNG.
  • Para abordar las limitaciones en la mejora de la aleatoriedad y la compatibilidad del algoritmo.
  • Mejorar la seguridad de los sistemas de comunicación cuántica.

Principales métodos:

  • Desarrolló un algoritmo de compensación de retroalimentación adaptativa (AFCA).
  • Implementación de retroalimentación de parámetros dinámicos y cifrado selectivo.
  • Se utilizó el análisis estadístico de desviación en tiempo real para el ajuste de la transformación no lineal.

Principales resultados:

  • AFCA conserva más del 50% de los bits originales mientras corrige los desequilibrios.
  • El valor p de la prueba Monobit para QRNGs continuos mejoró de 0.1376 a 0.9743.
  • La desviación de distribución 0/1 en los QRNG discretos se redujo del 7,9% al 0,5%.

Conclusiones:

  • AFCA mejora significativamente la aleatoriedad de QRNG y la compatibilidad posterior al procesamiento.
  • El algoritmo reduce las tasas de descarte de datos en más del 55% en comparación con los métodos tradicionales.
  • AFCA ofrece una solución robusta para la comunicación cuántica de alta seguridad y el cifrado de múltiples capas.