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Jet <https://quantum-jet.readthedocs.io>_ is a cross-platform C++ and Python library for simulating quantum circuits using tensor network contractions.

Features

• Runs on a variety of systems, from single-board machines to massively parallel supercomputers.

• Accelerates tensor contractions using a novel task-based parallelism approach.

• Models quantum systems with an arbitrary number of basis states.

To get started with Jet, read one of our tutorial walkthroughs <https://quantum-jet.readthedocs.io/en/stable/use/introduction.html>__ or browse the full API documentation <https://quantum-jet.readthedocs.io/en/stable/api/library_root.html>__.

Installation

C++ ^^^

The Jet C++ library requires Taskflow <https://github.com/taskflow/taskflow>_, a BLAS library with a CBLAS interface, and a C++ compiler with C++17 support. To use Jet, add #include <Jet.hpp> to the top of your header file and link your program with the CBLAS library.

For example, assuming that the Taskflow headers can be found in your g++ include path and OpenBLAS is installed on your system, you can compile the hellojet.cpp program below

.. code-block:: cpp

#include <array>
#include <complex>
#include <iostream>

#include <Jet.hpp>

int main(){
    using Tensor = Jet::Tensor<std::complex<float>>;

    Tensor lhs({"i", "j", "k"}, {2, 2, 2});
    Tensor rhs({"j", "k", "l"}, {2, 2, 2});

    lhs.FillRandom();
    rhs.FillRandom();

    Tensor res = Tensor::ContractTensors(lhs, rhs);

    for (const auto &datum : res.GetData()) {
        std::cout << datum << std::endl;
    }

    std::cout << "You have successfully used Jet version " << Jet::Version() << std::endl;

    return 0;
}

by running

.. code-block:: bash

git clone https://github.com/XanaduAI/jet
g++ --std=c++17 -O3 -Ijet/include hellojet.cpp -lopenblas

The output of this program should resemble

.. code-block:: text

$ ./hellojet
(-0.936549,0.0678852)
(-0.0786964,-0.771624)
(2.98721,-0.657124)
(-1.90032,1.58051)
You have successfully used Jet version 0.2.1

For more detailed instructions, see the development guide <https://quantum-jet.readthedocs.io/en/stable/dev/guide.html>_.

Python ^^^^^^

The Jet Python package requires Python version 3.7 and above. Installation of Jet, as well as all dependencies, can be done using pip:

.. code-block:: bash

pip install quantum-jet

To build the Jet Python distribution locally, a BLAS library with a CBLAS interface and a C++ compiler with C++17 support is required. Simply run

.. code-block:: bash

make dist
pip install dist/*.whl

To verify that Jet is installed, you can run the hellojet.py program below

.. code-block:: python

import jet

lhs = jet.Tensor(["i", "j", "k"], [2, 2, 2])
rhs = jet.Tensor(["j", "k", "l"], [2, 2, 2])

lhs.fill_random()
rhs.fill_random()
res = jet.contract_tensors(lhs, rhs)

for datum in res.data:
    print(f"{datum:.5f}")

print("You have successfully used Jet version", jet.version())

The output of this program should resemble

.. code-block:: text

$ python hellojet.py
1.96289+0.25257j
-0.16588-1.44652j
-1.43005+0.49516j
1.66881-1.67099j
You have successfully used Jet version 0.2.1

Contributing to Jet

We welcome new contributions - simply fork the Jet repository and make a pull request <https://help.github.com/articles/about-pull-requests/>_ containing your contribution. All contributers to Jet will be listed as authors on the releases. See our changelog <https://github.com/XanaduAI/jet/blob/main/.github/CHANGELOG.md>_ for more details.

We also encourage bug reports, suggestions for new features and enhancements, and even links to cool projects or applications built using Jet. Visit the contributions page <https://github.com/XanaduAI/jet/blob/main/.github/CONTRIBUTING.md>_ to learn more about sharing your ideas with the Jet team.

Support

• Source Code: https://github.com/XanaduAI/jet
• Issue Tracker: https://github.com/XanaduAI/jet/issues

If you are having issues, please let us know by posting the issue on our GitHub issue tracker.

Authors

Jet is the work of many contributors <https://github.com/XanaduAI/jet/graphs/contributors>_.

If you are doing research using Jet, please cite our paper:

Trevor Vincent, Lee J. O'Riordan, Mikhail Andrenkov, Jack Brown, Nathan Killoran, Haoyu Qi, and Ish Dhand. *Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction.* 2022. `Published in Quantum <https://doi.org/10.22331/q-2022-05-09-709>`_.

License

Jet is free and open source, released under the Apache License, Version 2.0 <https://www.apache.org/licenses/LICENSE-2.0>_.

Jet contains a copy of JSON for Modern C++ <https://github.com/nlohmann/json>_ from Niels Lohmann which is licenced under the MIT License <https://opensource.org/licenses/MIT>_.