How to experimentally evaluate the adiabatic condition for quantum annealing
Yuichiro Mori1, Shiro Kawabata2,3, Yuichiro Matsuzaki4,5
1Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1, Umezono, Tsukuba, Ibaraki, 305-8568, Japan. mori-yuichiro.9302@aist.go.jp.
We present a new experimental method to assess the adiabatic condition in quantum annealing (QA). This technique measures the transition matrix element and energy gap, crucial for solving real-world problems with QA.
Area of Science:
- Quantum Computing
- Quantum Annealing
- Experimental Physics
Background:
- Quantum annealing (QA) is a promising approach for solving complex optimization problems.
- Evaluating the adiabatic condition is critical for ensuring the success of QA.
- Current methods for assessing the adiabatic condition can be computationally intensive or indirect.
Purpose of the Study:
- To propose a novel experimental method for evaluating the adiabatic condition during quantum annealing.
- To provide a direct and efficient way to measure key components of the adiabatic condition.
- To establish a robust experimental basis for analyzing QA performance.
Main Methods:
- An experimental technique is proposed to evaluate the adiabatic condition without diagonalizing the Hamiltonian.
- The method involves applying an oscillating field during the quantum annealing process.
- The power spectrum of the resulting time-domain signal is measured.
Main Results:
- The proposed method simultaneously provides information on the transition matrix element and the energy gap.
- Estimates of the transition matrix element and energy gap are derived from the measured power spectrum.
- The technique offers a practical approach for experimental verification of the adiabatic condition.
Conclusions:
- The developed experimental method offers a powerful tool for analyzing quantum annealing performance.
- This approach facilitates the practical application of quantum annealing by providing essential performance metrics.
- The findings pave the way for more reliable and efficient quantum annealing implementations.
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