Isotope Effects in 2D correlation infrared Spectra of Water: HEOM Analysis of Molecular Dynamics-Based Machine Learning Models
Fuente:
arXiv
Saved in:
| Main Authors: | Park, Kwanghee, Hoshino, Ryotaro, Tanimura, Yoshitaka |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
HEOM-Based Numerical Framework for Quantum Simulation of Two-Dimensional Vibrational Spectra in Molecular Liquids (HEOM-2DVS)
by: Hoshino, Ryotaro, et al.
Published: (2026)
by: Hoshino, Ryotaro, et al.
Published: (2026)
System-Bath Modeling in Vibrational Spectroscopy via Molecular Dynamics: A Machine Learning Framework for Hierarchical Equations of Motion (HEOM)
by: Park, Kwanghee, et al.
Published: (2025)
by: Park, Kwanghee, et al.
Published: (2025)
A Multimode Classical Hierarchical Fokker-Planck Equations Approach to Molecular Vibrations: Simulating Two-Dimensional Spectra
by: Hoshino, Ryotaro, et al.
Published: (2025)
by: Hoshino, Ryotaro, et al.
Published: (2025)
sbml4md: A computational platform for System-Bath Modeling via Molecular Dynamics powered by Machine Learning
by: Park, Kwanghee, et al.
Published: (2026)
by: Park, Kwanghee, et al.
Published: (2026)
Analysis of intramolecular modes of liquid water in two-dimensional spectroscopy: a classical hierarchical equations of motion approach
by: Hoshino, Ryotaro, et al.
Published: (2025)
by: Hoshino, Ryotaro, et al.
Published: (2025)
MO-HEOM: Extending Hierarchical Equations of Motion to Molecular Orbital Space
by: Zhang, Yankai, et al.
Published: (2025)
by: Zhang, Yankai, et al.
Published: (2025)
Open Quantum Dynamics Theory for Coulomb Potentials: Hierarchical Equations of Motion for Atomic Orbitals (AO-HEOM)
by: Zhang, Yankai, et al.
Published: (2025)
by: Zhang, Yankai, et al.
Published: (2025)
Classical and quantum thermodynamics in a non-equilibrium regime: Application to Stirling engine
by: Koyanagi, Shoki, et al.
Published: (2024)
by: Koyanagi, Shoki, et al.
Published: (2024)
Classical and quantum thermodynamics described as a system-bath model: The dimensionless minimum work principle
by: Koyanagi, Shoki, et al.
Published: (2024)
by: Koyanagi, Shoki, et al.
Published: (2024)
A Bond-Based Machine Learning Model for Molecular Polarizabilities and A Priori Raman Spectra
by: Sowa, Jakub K., et al.
Published: (2024)
by: Sowa, Jakub K., et al.
Published: (2024)
Ionic Liquid Molecular Dynamics Simulation with Machine Learning Force Fields: DPMD and MACE
by: Park, Anseong, et al.
Published: (2025)
by: Park, Anseong, et al.
Published: (2025)
Impact of Cavity on Molecular Ionization Spectra
by: Fábri, Csaba, et al.
Published: (2023)
by: Fábri, Csaba, et al.
Published: (2023)
Latent Diffusion-Based 3D Molecular Recovery from Vibrational Spectra
by: Wu, Wenjin, et al.
Published: (2026)
by: Wu, Wenjin, et al.
Published: (2026)
INN-FF: A Scalable and Efficient Machine Learning Potential for Molecular Dynamics
by: Mehereen, Taskin, et al.
Published: (2025)
by: Mehereen, Taskin, et al.
Published: (2025)
Neural Network Approach for Predicting Infrared Spectra from 3D Molecular Structure
by: Al, Saleh Abdul, et al.
Published: (2024)
by: Al, Saleh Abdul, et al.
Published: (2024)
Cluster Models for Next-Generation, Machine-Learning-Based Energy Functions for Molecular Simulations
by: Wang, JingChun, et al.
Published: (2025)
by: Wang, JingChun, et al.
Published: (2025)
Modeling Interfacial Electron Transfer using Path Integral Molecular Dynamics
by: Park, Yoonjae, et al.
Published: (2025)
by: Park, Yoonjae, et al.
Published: (2025)
A Universal Deep Learning Force Field for Molecular Dynamic Simulation and Vibrational Spectra Prediction
by: Ji, Shengjiao, et al.
Published: (2025)
by: Ji, Shengjiao, et al.
Published: (2025)
Chemical Space-Informed Machine Learning Models for Rapid Predictions of X-ray Photoelectron Spectra of Organic Molecules
by: Tripathy, Susmita, et al.
Published: (2024)
by: Tripathy, Susmita, et al.
Published: (2024)
Routine Molecular Dynamics Simulations Including Nuclear Quantum Effects: from Force Fields to Machine Learning Potentials
by: Plé, Thomas, et al.
Published: (2022)
by: Plé, Thomas, et al.
Published: (2022)
Simulating Molecular Single Vibronic Level Fluorescence Spectra with ab initio Hagedorn Wavepacket Dynamics
by: Zhang, Zhan Tong, et al.
Published: (2024)
by: Zhang, Zhan Tong, et al.
Published: (2024)
Machine Learning Framework for Modeling Exciton-Polaritons in Molecular Materials
by: Li, Xinyang, et al.
Published: (2023)
by: Li, Xinyang, et al.
Published: (2023)
High-Accuracy Molecular Simulations with Machine-Learning Potentials and Semiclassical Approximations to Quantum Dynamics
by: Andreichev, Valerii, et al.
Published: (2026)
by: Andreichev, Valerii, et al.
Published: (2026)
Thermodynamic Descriptors from Molecular Dynamics as Machine Learning Features for Extrapolable Property Prediction
by: Espejo, Nuria H., et al.
Published: (2026)
by: Espejo, Nuria H., et al.
Published: (2026)
Molecular Insights into Yb(III) Speciation in Sulfate-Bearing Hydrothermal Fluids from X-ray Absorption Spectra Informed by ab initio Molecular Dynamics
by: Zhao, Xiaodong, et al.
Published: (2025)
by: Zhao, Xiaodong, et al.
Published: (2025)
Probing the Temporal Response of Liquid Water to a THz Pump Pulse Using Machine Learning-Accelerated Non-Equilibrium Molecular Dynamics
by: Joll, Kit, et al.
Published: (2025)
by: Joll, Kit, et al.
Published: (2025)
Molecular Fingerprints of Ice Surfaces in Sum Frequency Generation Spectra: a First Principles Machine Learning Study
by: Berrens, Margaret L., et al.
Published: (2024)
by: Berrens, Margaret L., et al.
Published: (2024)
Electrochemical Interfaces at Constant Potential: Data-Efficient Transfer Learning for Machine-Learning-Based Molecular Dynamics
by: Bianchi, Michele Giovanni, et al.
Published: (2025)
by: Bianchi, Michele Giovanni, et al.
Published: (2025)
NepoIP/MM: Towards Accurate Biomolecular Simulation with a Machine Learning/Molecular Mechanics Model Incorporating Polarization Effects
by: Song, Ge, et al.
Published: (2025)
by: Song, Ge, et al.
Published: (2025)
Dynamic Training Enhances Machine Learning Potentials for Long-Lasting Molecular Dynamics
by: Žugec, Ivan, et al.
Published: (2025)
by: Žugec, Ivan, et al.
Published: (2025)
Computing Anharmonic Infrared Spectra of Polycyclic Aromatic Hydrocarbons Using Machine-Learning Molecular Dynamics
by: Mai, Xinghong, et al.
Published: (2025)
by: Mai, Xinghong, et al.
Published: (2025)
Vibrational Spectra of Materials and Molecules from Partially-Adiabatic Elevated-Temperature Centroid Molecular Dynamics
by: Castro, Jorge, et al.
Published: (2025)
by: Castro, Jorge, et al.
Published: (2025)
Tree Tensor Networks Methods for Efficient Calculation of Molecular Vibrational Spectra
by: Sun, Shuo, et al.
Published: (2025)
by: Sun, Shuo, et al.
Published: (2025)
Impact and Interplay of Quantum Coherence and Dissipative Dynamics for Isotope Effects in Excited-State Intramolecular Proton Transfer
by: Dé, Brieuc Le, et al.
Published: (2025)
by: Dé, Brieuc Le, et al.
Published: (2025)
Isotope Effects and the Negative Thermal Expansion Phenomena in Ice and Water
by: Min, B. I., et al.
Published: (2025)
by: Min, B. I., et al.
Published: (2025)
Investigating Anharmonicities in Polarization-Orientation Raman Spectra of Acene Crystals with Machine Learning
by: Lazzaroni, Paolo, et al.
Published: (2025)
by: Lazzaroni, Paolo, et al.
Published: (2025)
Mathematical crystal chemistry II: Random search for ionic crystals and analysis on oxide crystals registered in ICSD
by: Koshoji, Ryotaro
Published: (2025)
by: Koshoji, Ryotaro
Published: (2025)
Explicit, Machine-Learned Two-Body Potentials for Molecular Simulations
by: Chaton, Kham Lek, et al.
Published: (2026)
by: Chaton, Kham Lek, et al.
Published: (2026)
Predicting Solvation Free Energies of Molecules and Ions via First-Principles and Machine-Learning Molecular Dynamics
by: Yu, Junting, et al.
Published: (2026)
by: Yu, Junting, et al.
Published: (2026)
Revolutionising Antibacterial Warfare: Machine Learning and Molecular Dynamics Unveiling Potential Gram-Negative Bacteria Inhibitors
by: Joshi, Pritish, et al.
Published: (2025)
by: Joshi, Pritish, et al.
Published: (2025)
Similar Items
-
HEOM-Based Numerical Framework for Quantum Simulation of Two-Dimensional Vibrational Spectra in Molecular Liquids (HEOM-2DVS)
by: Hoshino, Ryotaro, et al.
Published: (2026) -
System-Bath Modeling in Vibrational Spectroscopy via Molecular Dynamics: A Machine Learning Framework for Hierarchical Equations of Motion (HEOM)
by: Park, Kwanghee, et al.
Published: (2025) -
A Multimode Classical Hierarchical Fokker-Planck Equations Approach to Molecular Vibrations: Simulating Two-Dimensional Spectra
by: Hoshino, Ryotaro, et al.
Published: (2025) -
sbml4md: A computational platform for System-Bath Modeling via Molecular Dynamics powered by Machine Learning
by: Park, Kwanghee, et al.
Published: (2026) -
Analysis of intramolecular modes of liquid water in two-dimensional spectroscopy: a classical hierarchical equations of motion approach
by: Hoshino, Ryotaro, et al.
Published: (2025)