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Journal Articles

Importance sampling for counting statistics in one-dimensional systems

Ivan N. Burenev, Satya N. Majumdar, Alberto Rosso
Journal: The Journal of Chemical Physics
J. Chem. Phys. 161, 054115 (2024)
https://doi.org/10.1063/5.0221076
Published: August 2024
View article titled, Importance sampling for counting statistics in one-dimensional systems
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Journal Articles

Wigner kernels: Body-ordered equivariant machine learning without a basis

Filippo Bigi, Sergey N. Pozdnyakov, Michele Ceriotti
Journal: The Journal of Chemical Physics
J. Chem. Phys. 161, 044116 (2024)
https://doi.org/10.1063/5.0208746
Published: July 2024
View article titled, Wigner kernels: Body-ordered equivariant machine learning without a basis
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Journal Articles

Multi-armed bandit algorithm for sequential experiments of molecular properties with dynamic feature selection

Md. Menhazul Abedin, Koji Tabata, Yoshihiro Matsumura, Tamiki Komatsuzaki
Journal: The Journal of Chemical Physics
J. Chem. Phys. 161, 014115 (2024)
https://doi.org/10.1063/5.0206042
Published: July 2024
View article titled, Multi-armed bandit algorithm for sequential experiments of molecular properties with dynamic feature selection
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Journal Articles

Multitask methods for predicting molecular properties from heterogeneous data

K. E. Fisher, M. F. Herbst, Y. M. Marzouk
Journal: The Journal of Chemical Physics
J. Chem. Phys. 161, 014114 (2024)
https://doi.org/10.1063/5.0201681
Published: July 2024
View article titled, Multitask methods for predicting molecular properties from heterogeneous data
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Journal Articles

Barrier crossing in a viscoelastic medium under active noise: Predictions of Kramers’ flux-over-population method

Binny J. Cherayil
Journal: The Journal of Chemical Physics
J. Chem. Phys. 161, 014902 (2024)
https://doi.org/10.1063/5.0212289
Published: July 2024
View article titled, Barrier crossing in a viscoelastic medium under active noise: Predictions of Kramers’ flux-over-population method
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Journal Articles

Local number fluctuations in ordered and disordered phases of water across temperatures: Higher-order moments and degrees of tetrahedrality

Michael A. Klatt, Jaeuk Kim, Thomas E. Gartner, III, Salvatore Torquato
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 204502 (2024)
https://doi.org/10.1063/5.0204696
Published: May 2024
View article titled, Local number fluctuations in ordered and disordered phases of water across temperatures: Higher-order moments and degrees of tetrahedrality
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Journal Articles

Multiscale approach to the theory of nonisothermal homogeneous nucleation

D. I. Zhukhovitskii
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 194505 (2024)
https://doi.org/10.1063/5.0198471
Published: May 2024
View article titled, Multiscale approach to the theory of nonisothermal homogeneous nucleation
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Journal Articles

Cascading symmetry constraint during machine learning-enabled structural search for sulfur-induced Cu(111)- ( 43 × 43 ) surface reconstruction

Florian Brix, Mads-Peter Verner Christiansen, Bjørk Hammer
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 174107 (2024)
https://doi.org/10.1063/5.0201421
Published: May 2024
View article titled, Cascading symmetry constraint during machine learning-enabled structural search for sulfur-induced Cu(111)- ( 43 × 43 ) surface reconstruction
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Includes: Supplementary data
Journal Articles

Using machine learning with atomistic surface and local water features to predict heterogeneous ice nucleation

Abhishek Soni, G. N. Patey
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 124501 (2024)
https://doi.org/10.1063/5.0177706
Published: March 2024
View article titled, Using machine learning with atomistic surface and local water features to predict heterogeneous ice nucleation
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Includes: Supplementary data
Journal Articles

Translational eigenstates of He@C60 from four-dimensional ab initio potential energy surfaces interpolated using Gaussian process regression

K. Panchagnula, D. Graf, F. E. A. Albertani, A. J. W. Thom
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 104303 (2024)
https://doi.org/10.1063/5.0197903
Published: March 2024
View article titled, Translational eigenstates of He@C<sub>60</sub> from four-dimensional <em>ab initio</em> potential energy surfaces interpolated using Gaussian process regression
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Includes: Supplementary data
Journal Articles

Finite-temperature vibronic spectra from the split-operator coherence thermofield dynamics

Zhan Tong Zhang, Jiří J. L. Vaníček
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 084103 (2024)
https://doi.org/10.1063/5.0187823
Published: February 2024
View article titled, Finite-temperature vibronic spectra from the split-operator coherence thermofield dynamics
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Journal Articles

Balanced implicit Patankar–Euler methods for positive solutions of stochastic differential equations of biological regulatory systems

Aimin Chen, Quanwei Ren, Tianshou Zhou, Pamela Burrage, Tianhai Tian, Kevin Burrage
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 064117 (2024)
https://doi.org/10.1063/5.0187202
Published: February 2024
View article titled, Balanced implicit Patankar–Euler methods for positive solutions of stochastic differential equations of biological regulatory systems
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Journal Articles

Inferring energy–composition relationships with Bayesian optimization enhances exploration of inorganic materials

Andrij Vasylenko, Benjamin M. Asher, Christopher M. Collins, Michael W. Gaultois, George R. Darling, Matthew S. Dyer, Matthew J. Rosseinsky
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 054110 (2024)
https://doi.org/10.1063/5.0180818
Published: February 2024
View article titled, Inferring energy–composition relationships with Bayesian optimization enhances exploration of inorganic materials
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Includes: Supplementary data
Journal Articles

Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimension

Sergei Manzhos, Manabu Ihara
Journal: The Journal of Chemical Physics
J. Chem. Phys. 160, 021101 (2024)
https://doi.org/10.1063/5.0187867
Published: January 2024
View article titled, Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimension
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Journal Articles

Machine learning of kinetic energy densities with target and feature smoothing: Better results with fewer training data

Sergei Manzhos, Johann Lüder, Manabu Ihara
Journal: The Journal of Chemical Physics
J. Chem. Phys. 159, 234115 (2023)
https://doi.org/10.1063/5.0175689
Published: December 2023
View article titled, Machine learning of kinetic energy densities with target and feature smoothing: Better results with fewer training data
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Includes: Supplementary data
Journal Articles

Gaussian approximation potentials: Theory, software implementation and application examples

Sascha Klawohn, James P. Darby, James R. Kermode, Gábor Csányi, Miguel A. Caro, Albert P. Bartók
Journal: The Journal of Chemical Physics
J. Chem. Phys. 159, 174108 (2023)
https://doi.org/10.1063/5.0160898
Published: November 2023
View article titled, Gaussian approximation potentials: Theory, software implementation and application examples
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Includes: Supplementary data
Journal Articles

Different glassy characteristics are related to either caging or dynamical heterogeneity

Puneet Pareek, Monoj Adhikari, Chandan Dasgupta, Saroj Kumar Nandi
Journal: The Journal of Chemical Physics
J. Chem. Phys. 159, 174503 (2023)
https://doi.org/10.1063/5.0166404
Published: November 2023
View article titled, Different glassy characteristics are related to either caging or dynamical heterogeneity
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Journal Articles

Molecular dynamics-driven global potential energy surfaces: Application to the AlF dimer

Xiangyue Liu, Weiqi Wang, Jesús Pérez-Ríos
Journal: The Journal of Chemical Physics
J. Chem. Phys. 159, 144103 (2023)
https://doi.org/10.1063/5.0169080
Published: October 2023
View article titled, Molecular dynamics-driven global potential energy surfaces: Application to the AlF dimer
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Journal Articles

Nuclear induction lineshape modeling via hybrid SDE and MD approach

Mohamad Niknam, Louis-S. Bouchard
Journal: The Journal of Chemical Physics
J. Chem. Phys. 159, 124201 (2023)
https://doi.org/10.1063/5.0163782
Published: September 2023
View article titled, Nuclear induction lineshape modeling via hybrid SDE and MD approach
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Journal Articles

Bridging semiempirical and ab initio QM/MM potentials by Gaussian process regression and its sparse variants for free energy simulation

Ryan Snyder, Bryant Kim, Xiaoliang Pan, Yihan Shao, Jingzhi Pu
Journal: The Journal of Chemical Physics
J. Chem. Phys. 159, 054107 (2023)
https://doi.org/10.1063/5.0156327
Published: August 2023
View article titled, Bridging semiempirical and <em>ab initio</em> QM/MM potentials by Gaussian process regression and its sparse variants for free energy simulation
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Includes: Supplementary data