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Updated: Jun 26, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Quantum adiabatic algorithm for factorization and its experimental implementation.

Xinhua Peng1, Zeyang Liao, Nanyang Xu

  • 1Hefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China.

Physical Review Letters
|December 31, 2008
PubMed
Summary
This summary is machine-generated.

We developed a new quantum algorithm for number factorization that uses fewer qubits than Shor's algorithm. This quantum adiabatic algorithm successfully factored 21, showing promise for efficient large-scale computation.

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Last Updated: Jun 26, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

  • Quantum computing
  • Number theory
  • Algorithm development

Background:

  • Shor's algorithm is a prominent quantum algorithm for integer factorization.
  • Current quantum algorithms for factorization face challenges with qubit requirements and scalability.

Purpose of the Study:

  • To propose and experimentally validate a novel adiabatic quantum algorithm for number factorization.
  • To demonstrate a method requiring fewer qubits compared to Shor's algorithm.

Main Methods:

  • Development of an adiabatic quantum algorithm tailored for number factorization.
  • Implementation of the algorithm on a Nuclear Magnetic Resonance (NMR) quantum information processor.
  • Experimental factorization of the integer 21 using the developed algorithm.

Main Results:

  • The adiabatic quantum algorithm successfully factorized the number 21.
  • The algorithm demonstrated effectiveness within the simulation range of classical computers.
  • Evidence suggests a polynomial scaling of the algorithm's running time with problem size.

Conclusions:

  • The proposed adiabatic quantum algorithm is a viable alternative for number factorization.
  • The algorithm's reduced qubit requirement offers potential advantages for quantum hardware development.
  • Experimental validation supports the theoretical efficiency and scalability of this quantum approach.