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Updated: May 18, 2026

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

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Published on: September 8, 2023

Controlling complex networks: how much energy is needed?

Gang Yan1, Jie Ren, Ying-Cheng Lai

  • 1Temasek Laboratories, National University of Singapore, Singapore.

Physical Review Letters
|September 26, 2012
PubMed
Summary
This summary is machine-generated.

Researchers derived energy scaling laws for complex network control, offering a practical estimate for the energy costs involved. This work advances the understanding of controllability in networked systems.

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Last Updated: May 18, 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:

  • Complex network theory
  • Systems engineering
  • Dynamical systems analysis

Background:

  • Controlling complex networks is a significant challenge across science and engineering.
  • Understanding the energy requirements for control is crucial for practical applications and technological advancements.

Purpose of the Study:

  • To derive and validate scaling laws for the lower and upper energy bounds in complex network control.
  • To provide a more accurate estimate of the energy cost associated with controlling networked dynamical systems.

Main Methods:

  • Derivation of theoretical scaling laws for energy bounds.
  • Validation of these scaling laws through physical principles and potentially simulations or experimental data (details not provided in abstract).

Main Results:

  • Established scaling laws that define the lower and upper bounds for control energy.
  • These bounds offer a quantitative estimate of the energy cost for achieving control.

Conclusions:

  • The derived energy bounds represent a significant step forward in the study of network controllability.
  • This research provides a foundation for the ultimate control of complex networked dynamical systems by addressing energy efficiency.