Quantum computation of molecular geometry via many-body nuclear spin echoes

TL;DR

This paper demonstrates how nuclear magnetic resonance experiments measuring out-of-time-ordered correlators can be used to determine molecular structures, augmented by quantum computing techniques to improve accuracy and efficiency.

Contribution

It introduces a novel protocol combining NMR measurements and quantum computing to accurately infer molecular geometries from many-body nuclear spin echoes.

Findings

OTOC measurements estimate molecular distances and angles with spectroscopic accuracy.

Quantum circuits and zero-noise extrapolation improve data interpretation.

The approach offers a low-resource quantum computational method for structural learning.

Abstract

Quantum-information-inspired experiments in nuclear magnetic resonance spectroscopy may yield a pathway towards determining molecular structure and properties that are otherwise challenging to learn. We measure out-of-time-ordered correlators (OTOCs) [1-4] on two organic molecules suspended in a nematic liquid crystal, and investigate the utility of this data in performing structural learning tasks. We use OTOC measurements to augment molecular dynamics models, and to correct for known approximations in the underlying force fields. We demonstrate the utility of OTOCs in these models by estimating the mean ortho-meta H-H distance of toluene and the mean dihedral angle of 3',5'-dimethylbiphenyl, achieving similar accuracy and precision to independent spectroscopic measurements of both quantities. To ameliorate the apparent exponential classical cost of interpreting the above OTOC data, we simulate the molecular OTOCs on a Willow superconducting quantum processor, using AlphaEvolve-optimized [5] quantum circuits and arbitrary-angle fermionic simulation gates. We implement novel zero-noise extrapolation techniques based on the Pauli pathing model of operator dynamics [6], to repeat the learning experiments with root-mean-square error $0.05$ over all circuits used. Our work highlights a computational protocol to interpret many-body echoes from nuclear magnetic systems using low resource quantum computation.