Article
Multidisciplinary Sciences
Emanuele Marsili, Federica Agostini, Andre Nauts, David Lauvergnat
Summary: The use of well-adapted coordinates is essential for simplifying the numerical solution of the Schrodinger equations associated with atomic and molecular motions. The numerical approach also enables easy definition of reduced-dimensionality or constrained models.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2022)
Article
Chemistry, Physical
F. Bader, D. Lauvergnat, O. Christiansen
Summary: This study evaluates the validity of different Taylor expansion-based approximations of kinetic energy operators in a polyspherical parametrization and finds that several of the proposed schemes accurately reproduce the vibrational ground state and excitation energies, justifying their application in future investigations. The new approximations also open up the possibility of efficiently treating large molecular systems with vibrational coupled cluster schemes in general coordinates.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Falk Richter, P. Carbonniere
Summary: A potential energy surface accurate for the ground state of H2NOH has been generated at the coupled-cluster level, including trans and cis conformers as well as N-H-2 permutational conformers. The study calculated and assigned the fundamentals for both cis and trans conformers, and determined a complete set of eigenfunctions. The research shows small errors in the observed transitions and discovered local cis eigenfunctions and H-2 permutational/inversion barrier height.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Neurosciences
Uzair Hussain, Corey A. Baron, Ali R. Khan
Summary: Coordinate invariance of physical laws is crucial in physics, allowing freedom to express observations in computationally convenient coordinate systems. Transitioning from Cartesian to curvilinear coordinates in medical imaging can simplify visualization and operation. Introducing tools to enhance existing diffusion tractography approaches, testing showed that tracts from curvilinear coordinates generally have improved sensitivity and specificity compared to Cartesian coordinates. As an application, harmonic coordinates can enhance tractography for the hippocampus.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Mathematics, Applied
J. Bory Reyes, M. A. Perez-de la Rosa
Summary: This paper discusses the application of the Moisil-Theodoresco operator in different coordinate systems, introduces the concept of a quaternionic Laplace operator, and explores how to recover scalar and vector Laplacians from it.
COMPUTATIONAL METHODS AND FUNCTION THEORY
(2021)
Article
Chemistry, Physical
Marco Mendolicchio, Julien Bloino, Vincenzo Barone
Summary: This paper presents the implementation and validation of a second-order perturbative approach for anharmonic vibrations based on curvilinear internal coordinates. The results confirm that curvilinear coordinates significantly reduce inter-mode couplings and increase the reliability of low-order perturbative treatments for semi-rigid molecules. The study also paves the way for accurately representing flexible molecules with different levels of theory.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Engineering, Electrical & Electronic
Jingkai Wu, Yafei Wang, Chengliang Yin
Summary: This paper proposes a comprehensive framework for the coordination of connected and automated vehicles through the use of a distributed controller. The framework effectively integrates road information with vehicle motion state control, achieving coordinated platoon formation and merging actions across multiple lanes. Additionally, the framework takes into account intervehicle safety distance keeping and bounded actuations.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Chemistry, Physical
Anupam Anand Ojha, Saumya Thakur, Surl-Hee Ahn, Rommie E. Amaro
Summary: Recent advances in computational power and algorithms have extended the time scales of molecular dynamics (MD) simulations. However, MD simulations still face limitations in observing conformational transitions associated with biomolecular processes. To address this challenge, enhanced sampling techniques such as the weighted ensemble (WE) method have been developed to estimate kinetic rate constants by sampling transitions between metastable states using weighted trajectories. In this study, deep-learned kinetic modeling approaches are introduced to extract statistically relevant information from short MD trajectories and provide a well-sampled initial state distribution for WE simulations. This hybrid approach overcomes statistical bias and produces a refined free energy landscape closer to the steady state, enabling efficient sampling of kinetic properties.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Physical
Farideh Badichi Akher, Yinan Shu, Zoltan Varga, Suman Bhaumik, Donald G. Truhlar
Summary: This article presents a method of adding a new type of activation function to a neural network to enforce low-dimensional constraints. By using this method, the interaction potential can be forced to approach zero when subsystems are too far separated to interact, even without sufficient training data. Additionally, improved potential energy surfaces for the 14 lowest (3)A' states of O-3 are provided, and a more general method called parametrically managed diabatization by deep neural network (PM-DDNN) is introduced to add other low-dimensional or lower-level knowledge to machine-learned potentials.
JOURNAL OF PHYSICAL CHEMISTRY A
(2023)
Article
Chemistry, Physical
Jie Li, Oufan Zhang, Seokyoung Lee, Ashley Namini, Zi Hao Liu, Joao M. C. Teixeira, Julie D. Forman-Kay, Teresa Head-Gordon
Summary: This article addresses the problem of transforming internal coordinates to 3-dimensional Cartesian coordinates of a biomolecule and highlights the importance of predicting chemically subtle correlations among the internal coordinates. A machine learning algorithm, Int2Cart, is developed to predict bond lengths and bond angles based on backbone torsion angles and residue types of a protein, leading to better reconstruction of protein structures compared to fixed bond lengths and bond angles or a static library method. The Int2Cart algorithm can also be used for structure validation and improving modeling of IDP ensembles.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Physical
Chong Teng, Daniel Huang, Junwei Lucas Bao
Summary: We propose a molecular geometry optimization algorithm based on gradient-enhanced universal kriging (GEUK) with ab initio prior mean functions, integrating prior physical knowledge into surrogate-based optimization. Our implementation is both general and flexible, allowing optimizations in both Cartesian and curvilinear coordinates. We show that the GEUK optimizer accelerates geometry optimization in internal coordinates and demonstrate its efficiency in optimizing challenging molecules with high-accuracy electronic structure methods.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Materials Science, Multidisciplinary
Maria Cinefra
Summary: This paper investigates the implementation of 3D finite elements in curvilinear coordinates using the fundamental equations of 3D elasticity and the Principle of Virtual Displacements. The mathematical model of the geometry is reviewed and the formulation of hexahedral finite elements is presented. These finite elements can handle curved geometries and can apply mixed methods to combat locking phenomenon.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2022)
Article
Chemistry, Physical
Yanze Wu, Xuezhi Bian, Jonathan Rawlinson, Robert G. Littlejohn, Joseph E. Subotnik
Summary: This research proposes an optimal semiclassical approach to study nonadiabatic dynamics in electronic systems with spin degrees of freedom. By generalizing Tully's surface hopping dynamics from coordinate space to phase space, the proposed method is valid in the presence of spin-orbit coupling and/or external magnetic fields.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Yanze Wu, Xuezhi Bian, Jonathan I. Rawlinson, Robert G. Littlejohn, Joseph E. Subotnik
Summary: This research explores the effectiveness of utilizing a generalized Tully's surface hopping dynamics approach for nonadiabatic dynamics simulations in electron systems with spin degrees of freedom. By generating relevant phase-space adiabatic surfaces and incorporating all Berry curvature effects, the algorithm is able to effectively simulate nonadiabatic dynamics in the presence of spin-orbit coupling and external magnetic fields.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Computer Science, Artificial Intelligence
Pragyan Dahal, Simone Mentasti, Stefano Arrigoni, Francesco Braghin, Matteo Matteucci, Federico Cheli
Summary: This paper proposes a Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter with an Unscented Kalman Filter (UKF) estimator to provide obstacle state estimates in curvilinear road coordinates. A hybrid sensor fusion architecture between Lidar and Radar sensors is employed to obtain rich measurement point representations for Extended Object Tracking (EOT). The proposed algorithm is validated through Matlab Driving Scenario Designer simulation and experimental data collected at Monza Eni Circuit.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Review
Physics, Multidisciplinary
Sebastian Mizera
Summary: This article discusses the mathematical properties and physical implications of scattering amplitudes, and traces these properties back to physics through simple scattering problems.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2024)
