Welcome !
Tangelo is an open-source python package developed by Good Chemistry Company, focusing on the development of end-to-end material simulation workflows on quantum computers.
Its modular design and ease-of-use enables users to easily assemble custom workflows, tinker and define their own building blocks, while keeping track of quantum resource requirements, such as number of qubits, gates or measurements. Through problem decomposition techniques, users can scale up beyond toy models and study the impact of quantum computing on more industrially-relevant use cases. Tangelo is backend-agnostic and compatible with many existing open-source frameworks, making the integration of third-party tools such as state-of-the-art simulators, circuit compilers or quantum cloud services straightforward. It is our wish to develop a community around Tangelo, collaborate, and together leverage the best of what the field has to offer.
This package requires a Python 3 environment. We recommend:
- using Python virtual environments in order to set up your environment safely and cleanly
- installing the "dev" version of Python3 if you encounter missing header errors, such as
python.h file not found. - having good C/C++ compilers and BLAS libraries to ensure good overall performance of computation-intensive code.
TODO: once this package is available on pypi, give the command.
This package can be installed by downloading or cloning the contents of this repository, and typing the following command in the root directory:
python -m pip install .
If the installation of a dependency fails and the reason is not obvious, we suggest installing that dependency
separately with pip, before trying again.
Tangelo enables users to target various backends. In particular, it integrates quantum circuit simulators such as
qulacs, qiskit, cirq or qdk. We leave it to you to install the packages of your choice.
Most packages can be installed through pip in a straightforward way:
pip install qulacs pip install qiskit pip install cirq ...
Depending on your OS and environment, some of these packages may be more challenging to install. For installing Microsoft's QDK or any issue regarding the above packages, please check their respective documentation.
Some environment variables can impact performance (ex: using GPU for quantum circuit simulation, or changing the number of CPU threads used) or are used to connect to web services providing access to some compute backends.
See the list of relevant environment variables and their use in env_var.sh. In order for these variables to be set to
the desired values in your environment, you can run this shell script in Linux with the following command line:
source env_var.sh (you may need to set execution permissions with chmod +x set_env_var.sh first), or you can set
them in whatever way your OS supports it, or even inside your python script using the os package.
TODO: insert sentence and link to sphinx documentation when its online.
Please check the examples folder for jupyter notebook tutorials and other examples.
Unit tests can be found in the tests folders, located in the various toolboxes they are related to. To automatically
find and run all tests (assuming you are in the tangelo subfolder that contains the code of the package):
python -m unittest
Please have a look at the contributions file.
If you use Tangelo in your research, please cite
[TODO: this is a placeholder for our Tangelo paper, to be written and put on arxiv in October]
© Good Chemistry Company 2021. This software is released under the Apache Software License version 2.0.