Dominant Reaction Pathways by Quantum Computing.

Area of Science:

• Computational Chemistry
• Quantum Computing
• Biophysics

Background:

• Classical computers struggle with characterizing thermally activated transitions in high-dimensional energy landscapes.
• Efficiently finding transition paths is crucial for understanding molecular dynamics and chemical reactions.

Purpose of the Study:

• To develop a quantum annealing scheme for solving the challenging problem of characterizing thermally activated transitions.
• To enable efficient computation of transition paths on rugged energy surfaces.

Main Methods:

• Reduced the problem of finding transition paths to a shortest-path problem on a weighted graph.
• Mapped this optimization problem to finding the ground state of a generalized Ising model.
• Utilized quantum annealing by leveraging the quantized nature of qubits.

Main Results:

• A finite-size scaling analysis suggests efficient solvability by a quantum annealing machine.
• The quantum approach describes transitions between system configurations without lattice space discretization.
• Demonstrated a novel quantum annealing scheme for complex energy surface analysis.

Conclusions:

• The developed quantum annealing scheme offers a promising computational tool for analyzing complex energy landscapes.
• This method paves the way for future biophysical applications of quantum computing using realistic all-atom models.
• Quantum annealing provides an efficient alternative for characterizing thermally activated transitions.