On the distance between A and B in molecular configuration space

ABSTRACT

In this brief review, we discuss the question of calculating the distance between different molecular configurations. We focus on the theoretical basis of different existing methods for this problem, including ones which are more physics-driven and ones which are more data-driven. We explain the key ideas behind these methods, and conclude with what we see as the central challenges. We hope this review will be helpful to someone aiming to understand these methods, many of which are new and have not been compared and reviewed together. We also hope it will help develop new methods that address the challenges we identify and others.

KEYWORDS:

• Kinetics
• reaction coordinate
• molecular dynamics
• sampling
• machine learning

Acknowledgments

Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research (PRF 60512-DNI6). We thank Zachary Smith for proofreading this manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research (PRF 60512-DNI6).