qiskit.chemistry.algorithms.pes_samplers.PotentialBase
class PotentialBase(molecule)
Class to hold prescribed 1D potentials (e.g. Morse/Harmonic) over a degree of freedom.
__init__
__init__(molecule)
Initialize self. See help(type(self)) for accurate signature.
Methods
__init__(molecule) | Initialize self. |
dissociation_energy([scaling]) | Returns the dissociation energy (scaled by ‘scaling’) |
eval(x) | After fitting the data to the fit function, predict the energy at a point x. |
fit(xdata, ydata[, initial_vals, bounds_list]) | Fits surface to data |
get_equilibrium_geometry([scaling]) | Get the equilibrium energy. |
get_maximum_trusted_level([n]) | Returns the maximum energy level for which the particular implementation still provides a good approximation of reality. |
get_minimal_energy([scaling]) | Get the minimal energy. |
get_num_modes() | This (1D) potential represents a single vibrational mode |
get_trust_region() | The potential will usually be well-defined (even if not useful) for arbitrary x so we return a fairly large interval here. |
update_molecule(molecule) | Wipe state if molecule changes, and check validity of molecule for potential. |
vibrational_energy_level(n) | Returns the n-th vibrational energy level for a given mode. |
dissociation_energy
abstract dissociation_energy(scaling=1.0)
Returns the dissociation energy (scaled by ‘scaling’)
Return type
float
eval
abstract eval(x)
After fitting the data to the fit function, predict the energy at a point x.
Parameters
x (float) – value to evaluate surface in
Return type
float
Returns
value of surface in point x
fit
abstract fit(xdata, ydata, initial_vals=None, bounds_list=None)
Fits surface to data
Parameters
- xdata (
List[float]) – x data to be fitted - ydata (
List[float]) – y data to be fitted - initial_vals (
Optional[List[float]]) – Initial values for fit parameters. None for default. Order of parameters is d_e, alpha, r_0 and m_shift (see fit_function implementation) - bounds_list (
Optional[Tuple[List[float],List[float]]]) – Bounds for the fit parameters. None for default. Order of parameters is d_e, alpha, r_0 and m_shift (see fit_function implementation)
Return type
None
get_equilibrium_geometry
abstract get_equilibrium_geometry(scaling=1.0)
Get the equilibrium energy.
Returns the geometry for the minimal energy (scaled by ‘scaling’) Default units (scaling=1.0) are Angstroms. Scale by 1E-10 to get meters.
Parameters
scaling (float) – scaling factor
Return type
float
Returns
equilibrium geometry
get_maximum_trusted_level
get_maximum_trusted_level(n=0)
Returns the maximum energy level for which the particular implementation still provides a good approximation of reality. Default value of 100. Redefined where needed (see e.g. Morse).
Parameters
n (int) – vibronic mode
Return type
float
Returns
maximum_trusted_level setted
get_minimal_energy
abstract get_minimal_energy(scaling=1.0)
Get the minimal energy.
Returns the value of the minimal energy (scaled by ‘scaling’) Default units (scaling=1.0) are J/mol. Scale appropriately for Hartrees.
Parameters
scaling (float) – scaling factor
Return type
float
Returns
minimum energy
get_num_modes
get_num_modes()
This (1D) potential represents a single vibrational mode
Return type
int
get_trust_region
get_trust_region()
The potential will usually be well-defined (even if not useful) for arbitrary x so we return a fairly large interval here. Redefine in derived classes if needed.
Return type
Tuple[float, float]
update_molecule
update_molecule(molecule)
Wipe state if molecule changes, and check validity of molecule for potential.
Parameters
molecule (Molecule) – chemistry molecule
Return type
Molecule
Returns
molecule used
vibrational_energy_level
abstract vibrational_energy_level(n)
Returns the n-th vibrational energy level for a given mode.
Parameters
n (int) – number of vibrational mode
Return type
float
Returns
n-th vibrational energy level for a given mode