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qml.qchem.vibrational_pes

vibrational_pes(molecule, n_points=9, method='rhf', optimize=True, localize=True, bins=None, cubic=False, dipole_level=1, num_workers=1, backend='serial')[source]

Computes potential energy surfaces along vibrational normal modes.

Parameters:

  • molecule (Molecule) – the molecule object

  • n_points (int) – number of points for computing the potential energy surface. Default value is 9.

  • method (str) – Electronic structure method used to perform geometry optimization. Available options are "rhf" and "uhf" for restricted and unrestricted Hartree-Fock, respectively. Default is "rhf".

  • optimize (bool) – if True perform geometry optimization. Default is True.

  • localize (bool) – if True perform normal mode localization. Default is False.

  • bins (List[float]) – grid of frequencies for grouping normal modes. Default is None which means all frequencies will be grouped in one bin. For instance, bins = [1300, 2600] allows to separately group and localize modes in three groups that have frequencies below \(1300\), between \(1300-2600\) and above \(2600\).

  • cubic (bool)) – if True include three-mode couplings. Default is False.

  • dipole_level (int) – The level up to which dipole moment data are to be calculated. Input values can be 1, 2, or 3 for up to one-mode dipole, two-mode dipole and three-mode dipole, respectively. Default value is 1.

  • num_workers (int) – the number of concurrent units used for the computation. Default value is set to 1.

  • backend (string) – the executor backend from the list of supported backends. Available options are mp_pool, cf_procpool, cf_threadpool, serial, mpi4py_pool, mpi4py_comm. Default value is set to serial. See Usage Details for more information.

Returns:

the VibrationalPES object

Return type:

VibrationalPES

Example

>>> symbols  = ['H', 'F']
>>> geometry = np.array([[0.0, 0.0, -0.40277116], [0.0, 0.0, 1.40277116]])
>>> mol = qml.qchem.Molecule(symbols, geometry)
>>> pes = qml.qchem.vibrational_pes(mol, optimize=False)
>>> print(pes.freqs)
[0.02038828]

The backend options allow to run calculations using multiple threads or multiple processes.

  • serial: This executor wraps Python standard library calls without support for multithreaded or multiprocess execution. Any calls to external libraries that utilize threads, such as BLAS through numpy, can still use multithreaded calls at that layer.

  • mp_pool: This executor wraps Python standard library multiprocessing.Pool interface, and provides support for execution using multiple processes.

  • cf_procpool: This executor wraps Python standard library concurrent.futures.ProcessPoolExecutor interface, and provides support for execution using multiple processes.

  • cf_threadpool: This executor wraps Python standard library concurrent.futures.ThreadPoolExecutor interface, and provides support for execution using multiple threads. The threading executor may not provide execution speed-ups for tasks when using a GIL-enabled Python.

  • mpi4py_pool: This executor wraps the mpi4py.futures.MPIPoolExecutor class, and provides support for execution using multiple processes launched using MPI.

  • mpi4py_comm: This executor wraps the mpi4py.futures.MPICommExecutor class, and provides support for execution using multiple processes launched using MPI.

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