semvec/pypi-packages huggingface dataset:
vqesimulation 1.0.1
Paquete para construir hamiltonianos y ejecutar el VQE
Requires Python: >=3.9

# Tesis project
Project to get a degree in computer science.

The main idea is implement a few variational quantum algorithms to study condensed matter and chemistry models and give a basic template to study complex phenomena. This project didnt want to be another quantum library. This should be see as a high level implementation to study systems with a fixed route to be executed, so, the user only need to give the parameters and just the minimun programming is needed (in the demo it's possible to see the code structure). 

# Requirements
It's recommended create a virtual enviroment and install all the libraries indicated in the requiremets.txt. 

``` pip3 install -r requirements.txt ```

# Methods
The main two methods are the following.

1. Variational quantum eigensolver
2. Variational quantum deflation

There are more quantities to calculate with the states.
More information in the repository wiki.

MIT License

Copyright (c) 2023 Javier Norambuena

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
e2xgradingtools 0.0.4
A package for creating autograder tests in Jupyter notebooks
Requires Python: >3.7

# E2X Grading Tools

[![PyPi](https://img.shields.io/pypi/v/e2xgradingtools)](https://pypi.org/project/e2xgradingtools)
[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![Documentation Status](https://readthedocs.org/projects/e2x-grading-tools/badge/?version=latest)](https://e2x-grading-tools.readthedocs.io/en/latest/?badge=latest)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

e2xgradingtools provides a structured approach to execute tests using the global namespace of Jupyter notebooks, with the following highlights:

- Convenient variable and function existence checks
- Continued execution of remaining tests even if one test fails
- Hiding of student’s print statements during test execution
- Built-in type checking for robust testing
- Ability to reference implementation for comparison testing
- Customizable to suit specific needs
- Test output can be parsed by e2xgrader for partial point extraction

Please consult the [docs](https://e2x-grading-tools.readthedocs.io/en/latest) and look at the example notebook in this repository.