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Tutorials_Libra

Tutorials showcasing various capabilities of Libra

TOC

  1. Rigid body
  1. Integrators
  1. Linear algebra
  1. Optimization
  1. Electronic structure calculations in Libra
  1. Dynamics with Libra
  1. Special functions
  1. Model Hamiltonians
  1. Machine learning
  1. Auxiliary functions and data types
  1. Program-specific methods
  1. Molecular builders
  1. Force fields and classical MD (outside the dynamics module)
  1. Molecular integrals

Use cases

  1. Create a chemical system
  1. EHT calculations with Libra
  1. INDO calculations with Libra
  1. Compute .cube files from orbitals computed with Libra
  1. Visualize the MOs from .cube files
  1. Compute pDOS
  1. Plot pDOS
  1. Visualize MD trajectory with py3Dmol:
  1. Construct the vibronic Hamiltonian from the QE MD calculations
  1. Read the vibronic Hamiltonian data files to obtain its properties
  1. Compute the time-averaged nonadiabatic couplings of the vibronic Hamiltonian
  1. Manually construct a Slater Determinant basis
  1. Auto-generate a Slater Determinant basis
  1. Compute the energies and nonadiabatic couplings in the SD basis
  1. Calculate population and coherence dynamics of a quantum system embedded in a bath
  1. Calculate absorbance spectral lineshapes of a quantum system embedded in a bath
  1. Construct and plot the Heller's wavepackets
  1. Compute the matrix elements of various operators with Heller's wavepackets
  1. Define diabatic abstract model Hamiltonian
  1. Define adiabatic abstract model Hamiltonian
  1. Define adiabatic file-based model Hamiltonian
  1. Plot 1D PES
  1. Plot diabatic-to-adiabatic transformaitons vs. coordinate in 1D
  1. Plot 1D PES vs. time
  1. Define Libra/Psi4 intraface Hamiltonian
  1. Define Libra/DFTB+ intraface Hamiltonian
  1. Plot the PES of LiH at the EOM-CCSD/sto-3G level computed via interface of Libra with Psi4
  1. Plot the 1D PES of HFCO at the TD-DFTB level compute with interface of Libra with DFTB+
  1. Generate XYZ trajectory from a list of matrices
  1. Perform a ground state adiabatic MD with Libra
  1. Perform an excited state adiabatic MD with Libra
  1. Compute MD with DFTB+ via Libra
  1. Generate XYZ trajectory from HDF5 files
  1. Compute trajectory-averaged dephasing times
  1. Compute trajectory-averaged energy gaps
  1. Plot trajectory-averaged dephasing times
  1. Fit the probability density of randomly distributed point with Gaussian density kernel functions
  1. Read the HDF5 files to setup Hamiltonians
  1. Read the HDF5 files to plot results of dynamical calculations
  1. Compute nonadiabatic dynamics for atomistic systems with NBRA using Kohn-Sham states
  1. Plot the PES profiles with multidimensional model Hamiltonians
  1. MD and NAMD in the NVT ensemble
  1. Partitioning quantum and classical DOFs
  1. Coupling classical DOFs to thermostat
  1. Constraining DOFs in dynamics
  1. Numerically exact TD-SE
  1. DVR calculations
  1. Making animated gifs
  1. Integrating quantum Liouville's equation of motion
  1. Machine learning with MLP
  1. Artificial neural networks (ANN) and error Back Propagation algorithm
  1. Derivatives of ANNs
  1. Convert Libra and Python data types
  1. Manipulate vectors (lists of data)
  1. Setup default values of Python dictionary
  1. Interfacing ErgoSCF and Libra
  1. Sampling random numbers from common distributions
  1. Sampling random numbers from arbitrary distributions
  1. Computing data probability densities and cumulative distribution functions
  1. Generating (deterministic) quasi-random numbers
  1. Dynamical regimes and chaotic systems
  1. Wigner sampling
  1. Canonical and microcanonical enesemble sampling
  1. Analyzing MD trajectories
  1. Normal modes
  1. Constructing quantum dots
  1. Constructing periodic structures
  1. Automatically determining connectivity in complex structures
  1. Computing NACs using ErgoSCF/Libra
  1. Computing NACs using DFTB+/Libra
  1. Computing NACs using CP2K/Libra
  1. Computing single-particle (KS-DFT, HF, semiempirical) NACs
  1. Computing many-body (TD-DFT, TD-DFTB, CI) NACs
  1. Saving ANNs to files and creating ANNs from XML files
  1. Rprop algorithm for ANN training
  1. Momentum algorithm in the ANN training
  1. Weight decay in the ANN training
  1. Rotating and translating molecular fragments
  1. Creating classical force fields
  1. Molecular mechanics calculations (Hamiltonian_Atomistic)
  1. Mixing force fields
  1. NVE ensemble MD with force fields
  1. Simulated annealing
  1. Molecular mechanics molecular structure optimization
  1. Conduct quantum trajectories calculations (QTAG)
  1. Mapping multidimensional vectors of ints to an integer and vice versa
  1. Working with multidimensional grids
  1. Computing hyperplanes of multidimensional grids
  1. Compute ACF of data series
  1. Compute spectra
  1. Processing the MOPAC calculations results
  1. Computing CI wavefunction time-overlaps with MOPAC
  1. Define Libra/MOPAC interface Hamiltonian

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