Programme

O.24 -- Oral, VCTP-51

Date: Tuesday, 4 August 2026

Time: 15:00- 15:20

Construction of a Machine-Learned Soft-Coulomb Potential Along the HCN–HNC Isomerization Pathway

Duong D. Hoang-Trong (1,2), Minh-Nhut Tran (3), Doan-An Trieu (4,5), Van-Hoang Le (3), and Ngoc-Loan Phan (3)

1) Simulation in Materials Science Research Group, Science and Technology Advanced Institute, Van Lang University, Ho Chi Minh City, Vietnam; (2) Faculty of Applied Technology, Van Lang School of Technology, Van Lang University, Ho Chi Minh City, Vietnam; (3) Ho Chi Minh City University of Education, 280 An Duong Vuong Street, Ward 4, District 5, Ho Chi Minh City 72711, Vietnam; (4) Institute of Fundamental and Applied Sciences, Duy Tan University, Ho Chi Minh City 700000, Vietnam; (5) Faculty of Natural Sciences, Duy Tan University, Da Nang City 550000, Vietnam;

High-order harmonic generation (HHG) has become a powerful tool for probing molecular structure and ultrafast electron dynamics with attosecond temporal resolution [1–4]. Within the strong-field regime, theoretical investigations are commonly performed by solving the time-dependent Schrödinger equation (TDSE) under the single-active-electron approximation which is a low-cost method is a common way for investigating these phenomena theorically [5, 6]. Although HHG is often dominated by the highest occupied molecular orbital (HOMO) [4], recent studies on HCN have shown that lower-lying molecular orbitals and multielectron interactions can also leave observable signatures in harmonic spectra at equilibrium geometries [7, 8]. However, how these orbital contributions evolve during the HCN–HNC isomerization process, where both nuclear and electronic structures undergo substantial changes, remains largely unexplored. In this work, we develop a machine-learning-based soft Coulomb effective potential model for the HCN–HNC isomerization pathway. The proposed model is trained to accurately describe the energies, dipoles and symmetries of deeper occupied molecular orbitals, along the entire reaction coordinate connecting HCN, HNC, and intermediate configurations. The model is constructed from electronic-structure data for representative geometries and is designed to preserve the essential multiorbital characteristics required for strong-field simulations. References [1] J. L. Krause, K. J. Schafer and K. C. Kulander, Phys. Rev. Lett., 1992, 68, 3535. [2] P. B. Corkum, Phys. Rev. Lett., 1993, 71, 1994. [3] M. Lewenstein, P. Balcou, M. Y. Ivanov, A. L’Huillier and P. B. Corkum, Phys. Rev. A, 1994, 49, 2117. [4] J. Itatani, J. Levesque, D. Zeidler, H. Niikura, H. Pépin, J.-C. Kieffer, P. B. Corkum and D. M. Villeneuve, Nature, 2004, 432, 867. V.-H. Le, A.-T. Le, R.-H. Xie and C. D. Lin, Phys. Rev. A, 2007, 76, 013414. [5] M. Abu-Samha, L. B. Madsen, N. I Shvetsov-Shilovski, arXiv (preprint) https://arxiv.org/abs/2404.14254. [6] H. T. Nguyen, K.-N. H. Nguyen, N.-L. Phan, C.-T. Le, D. D. Vu, L.-P. Tran, and V.-H. Le, Phys. Rev. A, 2022, 105, 023106. [7] X. Chu, Phys. Rev. A, 2023, 108, 013116. [8] X. Chu, Phys. Rev. A, 2024, 109, 053103

Presenter: Hoang-Trong D. Duong