Dominant Reaction Pathways by Quantum Computing

TL;DR

This paper proposes a quantum annealing approach to efficiently identify dominant reaction pathways in complex energy landscapes, potentially enabling advanced biophysical simulations on quantum computers.

Contribution

It introduces a novel quantum annealing scheme that maps transition path problems onto a generalized Ising model, avoiding lattice discretization for realistic all-atom models.

Findings

Finite-size scaling suggests efficient solvability by quantum annealing.

Method leverages qubits to describe system transitions without lattice discretization.

Approach applicable to biophysical models with realistic atomic detail.

Abstract

Characterizing thermally activated transitions in high-dimensional rugged energy surfaces is a very challenging task for classical computers. Here, we develop a quantum annealing scheme to solve this problem. First, the task of finding the most probable transition paths in configuration space is reduced to a shortest-path problem defined on a suitable weighted graph. Next, this optimization problem is mapped into finding the ground state of a generalized Ising model. A finite-size scaling analysis suggests this task may be solvable efficiently by a quantum annealing machine. Our approach leverages on the quantized nature of qubits to describe transitions between different system's configurations. Since it does not involve any lattice space discretization, it paves the way towards future biophysical applications of quantum computing based on realistic all-atom models.