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Multi-angle quantum approximate optimization algorithm.

Rebekah Herrman1, Phillip C Lotshaw2, James Ostrowski3

  • 1Department of Industrial and Systems Engineering, University of Tennessee at Knoxville, Knoxville, TN, 37996, USA. rherrma2@tennessee.edu.

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A new multi-angle ansatz for the quantum approximate optimization algorithm (QAOA) enhances approximation ratios for combinatorial problems. This approach uses shallower quantum circuits, making it more practical for current quantum hardware.

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Area of Science:

  • Quantum computing
  • Combinatorial optimization
  • Quantum algorithms

Background:

  • The quantum approximate optimization algorithm (QAOA) offers a promising approach to solving complex optimization problems.
  • However, practical implementation is hindered by gate noise and circuit complexity, limiting performance with increasing ansatz depth.

Purpose of the Study:

  • To introduce and evaluate a novel multi-angle ansatz for QAOA.
  • The goal is to improve approximation ratios while reducing circuit depth for enhanced performance on near-term quantum devices.

Main Methods:

  • Investigated a multi-angle ansatz for QAOA, increasing classical parameters to reduce circuit depth.
  • Analyzed performance on MaxCut instances across various graph sizes.
  • Assessed parameter optimization feasibility and gate reduction potential.

Main Results:

  • The multi-angle ansatz demonstrated a 33% increase in approximation ratio for certain MaxCut instances compared to standard QAOA.
  • One layer of the multi-angle ansatz showed performance comparable to three layers of the traditional ansatz on eight-vertex graphs.
  • Optimized parameters frequently resulted in zero values, enabling gate removal and further circuit depth reduction.

Conclusions:

  • The multi-angle QAOA ansatz offers a more efficient alternative to the standard QAOA, requiring shallower circuits.
  • This advancement makes QAOA more viable for solving combinatorial optimization problems on current intermediate-scale quantum hardware.