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---
title: PotentialBase
description: API reference for qiskit.chemistry.algorithms.pes_samplers.PotentialBase
in_page_toc_min_heading_level: 1
python_api_type: class
python_api_name: qiskit.chemistry.algorithms.pes_samplers.PotentialBase
---
# qiskit.chemistry.algorithms.pes\_samplers.PotentialBase
<Class id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase" isDedicatedPage={true} github="https://github.com/qiskit-community/qiskit-aqua/tree/stable/0.9/qiskit/chemistry/algorithms/pes_samplers/potentials/potential_base.py" signature="PotentialBase(molecule)" modifiers="class">
Class to hold prescribed 1D potentials (e.g. Morse/Harmonic) over a degree of freedom.
### \_\_init\_\_
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.__init__" signature="__init__(molecule)">
Initialize self. See help(type(self)) for accurate signature.
</Function>
## Methods
| | |
| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------- |
| [`__init__`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.__init__ "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.__init__")(molecule) | Initialize self. |
| [`dissociation_energy`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.dissociation_energy "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.dissociation_energy")(\[scaling]) | Returns the dissociation energy (scaled by ‘scaling’) |
| [`eval`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.eval "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.eval")(x) | After fitting the data to the fit function, predict the energy at a point x. |
| [`fit`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.fit "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.fit")(xdata, ydata\[, initial\_vals, bounds\_list]) | Fits surface to data |
| [`get_equilibrium_geometry`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_equilibrium_geometry "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_equilibrium_geometry")(\[scaling]) | Get the equilibrium energy. |
| [`get_maximum_trusted_level`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_maximum_trusted_level "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.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`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_minimal_energy "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_minimal_energy")(\[scaling]) | Get the minimal energy. |
| [`get_num_modes`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_num_modes "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_num_modes")() | This (1D) potential represents a single vibrational mode |
| [`get_trust_region`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_trust_region "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.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`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.update_molecule "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.update_molecule")(molecule) | Wipe state if molecule changes, and check validity of molecule for potential. |
| [`vibrational_energy_level`](#qiskit.chemistry.algorithms.pes_samplers.PotentialBase.vibrational_energy_level "qiskit.chemistry.algorithms.pes_samplers.PotentialBase.vibrational_energy_level")(n) | Returns the n-th vibrational energy level for a given mode. |
### dissociation\_energy
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.dissociation_energy" signature="dissociation_energy(scaling=1.0)" modifiers="abstract">
Returns the dissociation energy (scaled by ‘scaling’)
**Return type**
`float`
</Function>
### eval
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.eval" signature="eval(x)" modifiers="abstract">
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
</Function>
### fit
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.fit" signature="fit(xdata, ydata, initial_vals=None, bounds_list=None)" modifiers="abstract">
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`
</Function>
### get\_equilibrium\_geometry
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_equilibrium_geometry" signature="get_equilibrium_geometry(scaling=1.0)" modifiers="abstract">
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
</Function>
### get\_maximum\_trusted\_level
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_maximum_trusted_level" signature="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
</Function>
### get\_minimal\_energy
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_minimal_energy" signature="get_minimal_energy(scaling=1.0)" modifiers="abstract">
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
</Function>
### get\_num\_modes
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_num_modes" signature="get_num_modes()">
This (1D) potential represents a single vibrational mode
**Return type**
`int`
</Function>
### get\_trust\_region
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.get_trust_region" signature="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`]
</Function>
### update\_molecule
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.update_molecule" signature="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
</Function>
### vibrational\_energy\_level
<Function id="qiskit.chemistry.algorithms.pes_samplers.PotentialBase.vibrational_energy_level" signature="vibrational_energy_level(n)" modifiers="abstract">
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
</Function>
</Class>
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