qexlibs

This is a meta repository that contains links to externally hosted libraries.

List of libraries

No.	Name	URL	Documentation
1.	QSE	https://github.com/ICHEC/qse	https://ichec.github.io/qse
2.	QUEX	https://github.com/ICHEC/quex	https://ichec.github.io/quex
3.	QCAP	https://github.com/QCT-UEA-management/QCAP	https://munich-quantum-software-stack.github.io/MQSS-Interfaces/
4.	qc2	https://github.com/qc2nl/qc2	https://qc2.readthedocs.io/en/latest/
5.	QQuantLib	https://github.com/NEASQC/FinancialApplications	https://neasqc.github.io/FinancialApplications/dl.html
6.	wntr_quantum	https://github.com/Quantum4WaterDistribution/wntr-quantum	https://quantum4waterdistribution.github.io/wntr-quantum/
7.	qsvm4eo	https://github.com.mcas.ms/ICHEC/qsvm4eo	https://github.com.mcas.ms/ICHEC/qsvm4eo/tree/main/notebooks

QSE

Quantum Simulation Environment (QSE) is developed at ICHEC, to explore analog quantum computing.

Installation

QSE is available via pip, so one can install it by following commands in a python environment of one's choice -

pip install qse                   # basic installation
pip install "qse[pulser]"         # pulser backend
pip install "qse[myqlm]"          # myqlm backend
pip install "qse[myqlm,pulser]"   # both backends

QUEX

Quantum Executor, provides classical simulated circuit runs, in a hardware agnostic way. It targets acceleration via cupy and jax and works on CPU, Nvidia GPUs and AMD GPUs.

pip install quex                # basic installation, Numpy
pip install "quex[nvidia]"       # nvidia backend, Cupy and Jax
pip install "quex[amd]"          # amd backend, Cupy and Jax
pip install "quex[metal]"        # apple-metal backend

QCAP

QCAP contains a catalog of foundational quantum computational chemistry algorithms running on simulators and real quantum hardware. It is not a framework as it introduces no abstraction layers, no base classes, and no hidden dependencies, but just readable, runnable code implemented in popular quantum SDKs.

Environment setup

Dependencies are managed from the root pyproject.toml using uv. Install base dependencies plus your chosen SDK:

uv sync --extra qiskit
# or
uv sync --extra pennylane
# or both
uv sync --extra cudaq

Run any entry:

uv run python algorithms/vqe/h2_uccsd_qiskit/run_aer.py

qc2

qc2 is a modular software designed to seamlessly integrate traditional computational chemistry codes and quantum computing frameworks. It is specifically crafted for hybrid quantum-classical workflows such as the variational quantum eigensolver (VQE) algorithm.

Installation

To install qc2 from GitHub repository, do:

git clone git@github.com:qc2nl/qc2.git
cd qc2
python3 -m pip install -e .

In this current version, qc2 can perform hybrid quantum-classical calculations using both Qiskit Nature and PennyLane. However, the latter is an optional dependency. To install Pennylane and perform automatic testing with it, follow these steps:

git clone git@github.com:qc2nl/qc2.git
cd qc2
python3 -m pip install -e .[pennylane] # (use ".[pennylane]" if you have zsh shell)

QQuantLib

Quantum Quantitative Finance Library (QQuantLib) encompasses various state-of-the-art quantum algorithms and techniques tailored for the financial industry. It was programmed using the quantum software stack myQLM developed by EVIDEN.

Installation

The mandatory Python libraries and packages for using the QQuantLib can be found into the environment.yml file.

wntr_quantum

wntr_quantum builds on the python package WNTR to leverage quantum computing for the simulation and optimization of water networks.

Installation

To install wntr_quantum from GitHub repository, do:

git clone git@github.com:QuantumApplicationLab/wntr-quantum.git
cd wntr-quantum
python -m pip install .

WNTR Quantum can use a dedicated EPANET solver that allows to offload calculation to quantum linear solvers. This custom EPANET code can be found at : https://github.com/QuantumApplicationLab/EPANET. To install this sover follow the instructions below:

# clone EPANET
git clone https://github.com/QuantumApplicationLab/EPANET

# build EPANET
cd EPANET
mkdir build
cd build 
cmake .. 
cmake --build . --config Release

# copy the shared lib
cp lib/libepanet2.so <path to wntr-quantum>/wntr-quantum/wntr_quantum/epanet/Linux/libepanet22_amd64.so

# export environment variable
export EPANET_TMP=<path to tmp dir>/.epanet_quantum 
export EPANET_QUANTUM = <path to EPANET_QUANTUM>

qsvm4eo

qsvm4eo is a package for running Support Vector Machines (SVMs) computed with a quantum kernel for Earth Observation data.

Installation

Clone the repo and (making sure you’re in the directory where the pyproject.toml file is situated) install the package and its dependencies using pip (to install in editbale mode use the -e flag)

pip install .

Exporting environment

The pyproject.toml file can be used via uv package manager to maintain a cumulative dependencies of the libraries that we add.

If one needs a more traditional requirements.txt file to install the necessary libraries, one can export on using -

uv export --format requirements.txt --no-hashes --output-file=requirements.txt