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This study demonstrates a modular superconducting quantum processor for implementing the toric code model, enabling efficient simulation of anyonic statistics crucial for topological quantum computing.

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Area of Science:

  • Quantum Computing
  • Condensed Matter Physics
  • Quantum Information Science

Background:

  • Anyons, quasiparticles with non-trivial exchange statistics, are key to topological quantum computing.
  • The toric code model is a leading proposal for realizing anyonic fractional statistics.
  • Scaling quantum simulations of the toric code is challenging due to its complex entangled ground state.

Purpose of the Study:

  • To demonstrate a hardware-efficient implementation of the toric code model using a modular superconducting quantum processor.
  • To enable scalable simulation of topological phases and anyonic braiding statistics.
  • To benchmark the performance and verify path independence of anyonic braiding.

Main Methods:

  • Utilizing a modular superconducting quantum processor with in-parallel control across separate modules.
  • Generating a 10-qubit toric code ground state in four operational steps.
  • Performing correlation measurements to verify path independence of anyonic braiding statistics.

Main Results:

  • Successful hardware-pragmatic implementation of the toric code model.
  • Generation of a 10-qubit toric code ground state.
  • Realization and benchmarking of six distinct anyonic braiding paths, confirming path independence.
  • Efficient and scalable verification of anyonic statistics.

Conclusions:

  • A modular quantum processor provides a practical approach for implementing the toric code model.
  • This method offers a promising pathway for scalable quantum simulation of topological phases.
  • The distributed quantum simulation approach facilitates advancements in topological quantum computing.