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Updated: Jul 6, 2025

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Published on: November 11, 2013
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Initial State Encoding via Reverse Quantum Annealing and H-Gain Features
Elijah Pelofske1, Georg Hahn2, Hristo Djidjev1,3
1CCS-3 Information Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545 USA.
Summary
This study explores reverse annealing (RA) and h-gain (HG) features on D-Wave quantum annealers to improve optimization solutions. The h-gain technique offers a viable alternative to reverse annealing for certain problems.
Area of Science:
- Quantum Computing
- Computational Optimization
Background:
- D-Wave quantum annealers offer cloud access to quantum annealing for optimization.
- Improving solution quality in quantum annealing is an active research area.
Purpose of the Study:
- To investigate methods for enhancing quantum annealer solution quality by encoding initial states.
- To compare the effectiveness of reverse annealing (RA) and h-gain (HG) features for initial state encoding.
Main Methods:
- Exploration of D-Wave's reverse annealing (RA) feature for refining solutions.
- Utilizing the h-gain (HG) feature to bias annealing from a specific initial state.
- Development and testing of a hybrid RA-HG method and iterative application of both techniques.
- Evaluation on combinatorial optimization problems like max-cut and max-clique, and on spin glasses using D-Wave hardware.
Main Results:
- The h-gain (HG) feature is demonstrated as a viable alternative to RA for initial state encoding in quantum annealing.
- Iterative application of RA and HG shows potential for monotonically improving solutions.
- Performance of iterative RA and HG is analyzed on various problems and D-Wave hardware architectures (Chimera, Pegasus).
Conclusions:
- Both RA and HG are effective for initial state encoding in quantum annealing.
- Iterative application of these techniques can lead to progressively better solutions.
- HG presents a promising alternative or complement to RA for optimizing problem-solving on quantum annealers.
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