# Qiskit Nature PySCF
[](https://opensource.org/licenses/Apache-2.0)
**Qiskit Nature PySCF** is a third-party integration plugin of Qiskit Nature + PySCF.
## Installation
We encourage installing Qiskit Nature PySCF via the pip tool (a python package manager).
```bash
pip install qiskit-nature-pyscf
```
**pip** will handle all dependencies automatically and you will always install the latest
(and well-tested) version. It will also install Qiskit Nature if needed.
If you want to work on the very latest work-in-progress versions, either to try features ahead of
their official release or if you want to contribute to Qiskit Nature PySCF, then you can install from source.
## Usage
This plugin couples the APIs of PySCF and Qiskit Nature, enabling a user of PySCF to leverage
Quantum-based algorithms implemented in Qiskit to be used in-place of their classical counterparts.
### Active Space Calculations
One very common approach is to use a Quantum algorithm to find the ground state in an active space
calculation. To this extent, this plugin provides the `QiskitSolver` class, which you can inject
directly into your `CASCI` or `CASSCF` simulation objects of PySCF.
Below we show a simple example of how to do this.
```python
from pyscf import gto, scf, mcscf
import numpy as np
from qiskit.primitives import Estimator
from qiskit_algorithms import VQE
from qiskit_algorithms.optimizers import SLSQP
from qiskit_nature.second_q.algorithms import GroundStateEigensolver
from qiskit_nature.second_q.circuit.library import HartreeFock, UCCSD
from qiskit_nature.second_q.mappers import ParityMapper
from qiskit_nature_pyscf import QiskitSolver
mol = gto.M(atom="Li 0 0 0; H 0 0 1.6", basis="sto-3g")
h_f = scf.RHF(mol).run()
norb = 2
nalpha, nbeta = 1, 1
nelec = nalpha + nbeta
cas = mcscf.CASCI(h_f, norb, nelec)
mapper = ParityMapper(num_particles=(nalpha, nbeta))
ansatz = UCCSD(
norb,
(nalpha, nbeta),
mapper,
initial_state=HartreeFock(
norb,
(nalpha, nbeta),
mapper,
),
)
vqe = VQE(Estimator(), ansatz, SLSQP())
vqe.initial_point = np.zeros(ansatz.num_parameters)
algorithm = GroundStateEigensolver(mapper, vqe)
cas.fcisolver = QiskitSolver(algorithm)
cas.run()
```
More detailed information for this plugin can be found in its
[Documentation](https://qiskit-community.github.io/qiskit-nature-pyscf/). For further
information and explanations we recommend to check out the documentation of
[PySCF](https://pyscf.org/) and [Qiskit Nature](https://qiskit-community.github.io/qiskit-nature/).
## Citation
If you use this plugin, please cite the following references:
- PySCF, as per [these instructions](https://github.com/pyscf/pyscf#citing-pyscf).
- Qiskit, as per the provided [BibTeX file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib).
- Qiskit Nature, as per https://doi.org/10.5281/zenodo.7828767
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"description": "# Qiskit Nature PySCF\n\n[](https://opensource.org/licenses/Apache-2.0)\n\n**Qiskit Nature PySCF** is a third-party integration plugin of Qiskit Nature + PySCF.\n\n## Installation\n\nWe encourage installing Qiskit Nature PySCF via the pip tool (a python package manager).\n\n```bash\npip install qiskit-nature-pyscf\n```\n\n**pip** will handle all dependencies automatically and you will always install the latest\n(and well-tested) version. It will also install Qiskit Nature if needed.\n\nIf you want to work on the very latest work-in-progress versions, either to try features ahead of\ntheir official release or if you want to contribute to Qiskit Nature PySCF, then you can install from source.\n\n\n## Usage\n\nThis plugin couples the APIs of PySCF and Qiskit Nature, enabling a user of PySCF to leverage\nQuantum-based algorithms implemented in Qiskit to be used in-place of their classical counterparts.\n\n### Active Space Calculations\n\nOne very common approach is to use a Quantum algorithm to find the ground state in an active space\ncalculation. To this extent, this plugin provides the `QiskitSolver` class, which you can inject\ndirectly into your `CASCI` or `CASSCF` simulation objects of PySCF.\n\nBelow we show a simple example of how to do this.\n\n```python\nfrom pyscf import gto, scf, mcscf\n\nimport numpy as np\n\nfrom qiskit.primitives import Estimator\nfrom qiskit_algorithms import VQE\nfrom qiskit_algorithms.optimizers import SLSQP\nfrom qiskit_nature.second_q.algorithms import GroundStateEigensolver\nfrom qiskit_nature.second_q.circuit.library import HartreeFock, UCCSD\nfrom qiskit_nature.second_q.mappers import ParityMapper\n\nfrom qiskit_nature_pyscf import QiskitSolver\n\nmol = gto.M(atom=\"Li 0 0 0; H 0 0 1.6\", basis=\"sto-3g\")\n\nh_f = scf.RHF(mol).run()\n\nnorb = 2\nnalpha, nbeta = 1, 1\nnelec = nalpha + nbeta\n\ncas = mcscf.CASCI(h_f, norb, nelec)\n\nmapper = ParityMapper(num_particles=(nalpha, nbeta))\n\nansatz = UCCSD(\n norb,\n (nalpha, nbeta),\n mapper,\n initial_state=HartreeFock(\n norb,\n (nalpha, nbeta),\n mapper,\n ),\n)\n\nvqe = VQE(Estimator(), ansatz, SLSQP())\nvqe.initial_point = np.zeros(ansatz.num_parameters)\n\nalgorithm = GroundStateEigensolver(mapper, vqe)\n\ncas.fcisolver = QiskitSolver(algorithm)\n\ncas.run()\n```\n\nMore detailed information for this plugin can be found in its\n[Documentation](https://qiskit-community.github.io/qiskit-nature-pyscf/). For further \ninformation and explanations we recommend to check out the documentation of\n[PySCF](https://pyscf.org/) and [Qiskit Nature](https://qiskit-community.github.io/qiskit-nature/).\n\n\n## Citation\n\nIf you use this plugin, please cite the following references:\n\n- PySCF, as per [these instructions](https://github.com/pyscf/pyscf#citing-pyscf).\n- Qiskit, as per the provided [BibTeX file](https://github.com/Qiskit/qiskit/blob/master/Qiskit.bib).\n- Qiskit Nature, as per https://doi.org/10.5281/zenodo.7828767\n",
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