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.

中文翻译：

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量子计算的主导反应途径

表征高维崎energy能量表面中的热激活跃迁对于经典计算机而言是一项非常具有挑战性的任务。在这里，我们开发了量子退火方案来解决这个问题。首先，在配置空间中找到最可能的过渡路径的任务被简化为在合适的加权图上定义的最短路径问题。接下来，将此优化问题映射到寻找广义伊辛模型的基态。有限尺寸缩放分析表明，该任务可以通过量子退火机有效地解决。我们的方法利用量子位的量化性质来描述不同系统配置之间的转换。由于它不涉及任何晶格空间离散化，