tensorcircuit
Tensor network based quantum software framework for the NISQ era
tensorcircuit-ng
The next-gen tensor network based quantum software framework: superseding the original TensorCircuit
pennylane-lightning
The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.
pennylane
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Built by researchers, for research.
https://github.com/agnostiqhq/covalent
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
cuda-quantum
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
https://github.com/agnostiqhq/covalent-braket-plugin
Executor plugin interfacing Covalent with Amazon Braket Hybrid Jobs
https://github.com/agnostiqhq/covalent-slurm-plugin
Executor plugin interfacing Covalent with Slurm
quantum-molecular-encodings
Data and codes used in Boy et al. (2025) - Quantum molecular structure encoding
https://github.com/agnostiqhq/quantum-variational-rewinding
Covalent demonstration of the QVR algorithm using a cryptocurrency time series use case
https://github.com/agnostiqhq/tutorials_covalent_ieee_2022
Tutorials for 2022 IEEE Quantum Week Workshop on Covalent
https://github.com/albertnieto/quantum_convolutional_nn_benchmark
Benchmarking quanvolutional neural networks with QCML and Pennylane.
qcml
A benchmarking library for quantum and classical machine learning, with specialized support for evaluating kernel methods.
https://github.com/agnostiqhq/covalent_tutorials_ieee_2023
Tutorial notebooks for QCE at IEEE 2023 in Bellevue, Washington
classiq-library
The Classiq Library is the largest collection of quantum algorithms and applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌
qandle
QANDLE is a fast and simple quantum state-vector simulator for hybrid machine learning using the PyTorch library.
qdna-lib
Qdna-lib aim to pioneer advancements that not only push the boundaries of quantum computing but also provide benefits to the field of data science and artificial intelligence.
https://github.com/cern-it-innovation/latent-ad-qml
Unsupervised anomaly detection in the latent space of high energy physics events with quantum machine learning.
mind-the-qapp
An Application for Visualizing the Crux in Quantum Machine Learning
classical-shadow-vqe
Qiskit implementation of classical shadow formalism with VQE for calculating ground state energies of molecules
https://github.com/cqcl/quixer
Code repository for the preprint "Quixer: A Quantum Transformer Model"
learning-complexity-gradually
Repository of the paper "Learning complexity gradually in quantum machine learning models"
vmbqc
Designing Variational Measurement-Based Quantum Computing algorithm for generative learning tasks
https://github.com/cern-it-innovation/gqc
Guided Quantum Compression (GQC) network for simultaneous dimensionality reduction and classification of high-dimensional data.
https://github.com/darkstarstrix/qsolvers
The Swiss Army Knife of Applied Quantum Technology
quantum-transfer-learning-metastases
Quantum Transfer Learning for Lymph Node Metastases Detection
qml-essentials
Python package with commonly used Ansaetze, tools and data-reuploading model in quantum machine learning.
https://github.com/albertnieto/quantum-perceptron
Quantum perceptron using Grover, implemented with Pennylane.
classical-quantum-mnist
Single pixel imaging with classical and quantum neutral network