Reverse Quantum Annealing for Ground-State Energy Calculation in Molecule

We present the results of our reverse quantum annealing computations of the ground-state energies of alkaline-earth monofluoride molecules. By partitioning the Dirac--Coulomb electronic Hamiltonian into sub-QUBOs and refining forward-annealing solutions through optimized reverse-annealing schedules, residual configuration errors are systematically minimized. The electronic ground-state wave functions and energies are obtained using the Quantum Annealing Eigensolver algorithm. This work provides a pathway for achieving sub-milliHartree chemical accuracy and advancing molecular electronic structure calculations in the quantum annealing paradigm.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-29
DOI
https://doi.org/10.48550/arxiv.2610.39129
Primary Topic
Quantum Computing Algorithms and Architecture
Type
preprint
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preprint

Reverse Quantum Annealing for Ground-State Energy Calculation in Molecule

P. Sahoo
arXiv (Cornell University)
Quantum Computing Algorithms and Architecture
preprint

Reverse Quantum Annealing for Ground-State Energy Calculation in Molecule

P. Sahoo
preprint en

Abstract

We present the results of our reverse quantum annealing computations of the ground-state energies of alkaline-earth monofluoride molecules. By partitioning the Dirac--Coulomb electronic Hamiltonian into sub-QUBOs and refining forward-annealing solutions through optimized reverse-annealing schedules, residual configuration errors are systematically minimized. The electronic ground-state wave functions and energies are obtained using the Quantum Annealing Eigensolver algorithm. This work provides a pathway for achieving sub-milliHartree chemical accuracy and advancing molecular electronic structure calculations in the quantum annealing paradigm.

arXiv (Cornell University)
Quantum Computing Algorithms and Architecture
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Reverse Quantum Annealing for Ground-State Energy Calculation in Molecule — P. Sahoo · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS