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Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra. Schrödinger...
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Updated: Jun 11, 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 analogue computing.

Vivien M Kendon1, Kae Nemoto, William J Munro

  • 1School of Physics and Astronomy, University of Leeds, Leeds LS2 9JT, UK. v.kendon@leeds.ac.uk

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|July 7, 2010
PubMed
Summary
This summary is machine-generated.

Quantum simulation uses quantum computers to model quantum systems, differing from classical computation by directly mapping data. This approach has implications for precision and error correction in quantum computing.

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Last Updated: Jun 11, 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
  • Quantum Simulation

Background:

  • Quantum computers offer potential for simulating complex quantum systems.
  • Building quantum computers is challenging due to their complexity.

Purpose of the Study:

  • To review the principles of quantum computers and their applications, focusing on quantum simulation.
  • To explore the unique data encoding methods in quantum simulation.

Main Methods:

  • Quantum simulation maps the Hilbert space of a target system directly onto the Hilbert space of qubits.
  • This direct mapping contrasts with the binary encoding in classical digital computation.

Main Results:

  • Increasing precision in quantum simulation is exponentially costly.
  • Quantum simulation necessitates specific precision and error-correction strategies.
  • Continuous-variable quantum computers are identified as an efficient architecture for quantum simulation.

Conclusions:

  • Quantum simulation's direct data encoding presents unique challenges and opportunities.
  • Lessons from classical analogue computers can inform the development of future quantum simulators.
  • The practicality of quantum simulation requires further investigation into precision and error correction.