All Paths All at Once: A Quantum Monte Carlo and Neural Committor Approach to Reaction Pathway Search
Abstract
Locating competing reaction pathways is difficult when potential-energy gradients are unavailable. Here we present tReax\_expedition, an energy-only approach combining coupled Monte Carlo exploration, stochastic quench labelling and restrained continuation. Exploration identifies connected states, while continuation resolves candidate channels and records sampled chain maxima. Single-search benchmarks on three two-dimensional potentials recovered an intermediate and competing routes without transition-state guesses. For eight of nine gas-phase reactions on GFN2-xTB, sampled chain maxima differed from independently refined saddle energies by less than 0.76~kJ\,mol−1. Alanine dipeptide instead revealed incomplete conformational relaxation, showing that route connectivity can persist despite structural and energetic errors. Neural committor learning and local straddling-pair sampling connect the resulting paths to transition-region sampling, although molecular shooting diagnostics indicate limited committor calibration. These results show how energy-only exploration and continuation recover candidate pathways, while distinguishing route connectivity from geometric localization, barrier resolution and finite-temperature transition statistics.
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BibTeX
@misc{chang2026paths,
title = {{All Paths All at Once: A Quantum Monte Carlo and Neural Committor Approach to Reaction Pathway Search}},
author = {Chien-Chai Chang},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.03699},
eprint = {2611.03699},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.03699},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - All Paths All at Once: A Quantum Monte Carlo and Neural Committor Approach to Reaction Pathway Search
AU - Chien-Chai Chang
PY - 2026
DA - 2026/11/01
PB - arXiv
DO - 10.48550/arxiv.2611.03699
UR - https://arxiv.org/abs/2611.03699
AB - Locating competing reaction pathways is difficult when potential-energy gradients are unavailable. Here we present tReax\_expedition, an energy-only approach combining coupled Monte Carlo exploration, stochastic quench labelling and restrained continuation. Exploration identifies connected states, while continuation resolves candidate channels and records sampled chain maxima. Single-search benchmarks on three two-dimensional potentials recovered an intermediate and competing routes without transition-state guesses. For eight of nine gas-phase reactions on GFN2-xTB, sampled chain maxima differed from independently refined saddle energies by less than 0.76~kJ\,mol^−1. Alanine dipeptide instead revealed incomplete conformational relaxation, showing that route connectivity can persist despite structural and energetic errors. Neural committor learning and local straddling-pair sampling connect the resulting paths to transition-region sampling, although molecular shooting diagnostics indicate limited committor calibration. These results show how energy-only exploration and continuation recover candidate pathways, while distinguishing route connectivity from geometric localization, barrier resolution and finite-temperature transition statistics.
ER -