arXiv:2611.03699v2 physics.chem-ph

All Paths All at Once: A Quantum Monte Carlo and Neural Committor Approach to Reaction Pathway Search

Chien-Chai Chang

제출 2026-11-04

원문 초록

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. 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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  1. arXiv:2611.03699v2제출 시각 미확인
  2. arXiv:2611.03699v1제출 시각 미확인

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