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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Hardware-optimal quantum algorithms.

Stefanie Muroya1, Krishnendu Chatterjee1, Thomas A Henzinger1

  • 1Institute of Science and Technology Austria (ISTA), Klosterneuburg 3400, Austria.

Proceedings of the National Academy of Sciences of the United States of America
|March 19, 2025
PubMed
Summary
This summary is machine-generated.

Quantum error correction algorithms can be improved by tailoring them to specific hardware. This study presents a computational tool to automatically synthesize hardware-optimal quantum algorithms, enhancing accuracy for tasks like parity correction and state preparation.

Keywords:
program synthesisquantum error correctionquantum hardware

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Area of Science:

  • Quantum computing
  • Quantum information science
  • Computer science

Background:

  • Quantum hardware is susceptible to noise and errors, limiting the accuracy of quantum computations.
  • Traditional quantum error correction methods may not be optimal for all hardware architectures.

Purpose of the Study:

  • To develop a method for automatically synthesizing hardware-optimal quantum error correction algorithms.
  • To improve the accuracy of quantum computations by adapting algorithms to specific hardware constraints.

Main Methods:

  • Utilized stochastic techniques from computer science for algorithm synthesis.
  • Developed a computational tool to compute exact accuracy guarantees.
  • Optimized algorithms for parity correction, qubit resetting, and Greenberger-Horne-Zeilinger (GHZ) state preparation.
  • Computed hardware-optimal qubit mapping for GHZ state preparation.

Main Results:

  • Demonstrated that hardware-specific optimization can significantly improve the accuracy of quantum error correction.
  • Synthesized novel, hardware-optimal algorithms that differ from traditional approaches.
  • Achieved improvements compared to the Qiskit transpiler for GHZ state preparation.

Conclusions:

  • Automatic synthesis of hardware-optimal quantum algorithms is feasible and beneficial.
  • Tailoring quantum error correction to hardware specifications is crucial for maximizing accuracy.
  • The developed computational tool offers a practical approach to enhance quantum computing performance.