Quantum Machine Learning Python Packages

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 an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.

covalent

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

cudaq

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

cuda-quantum-cu13

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

cudaq-logical

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

pennylane-lightning-kokkos

The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.

cuda-quantum-cu12

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

classiq

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 🙌

pennylane-lightning-gpu

The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.

tfq-nightly

An open-source Python framework for hybrid quantum-classical machine learning.

pyqtorch

PyTorch-based state vector and density matrix simulator

cuda-quantum

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

tensorcircuit-ng

Next-gen AI-native tensor-network-based quantum software framework

tensorflow-quantum

An open-source Python framework for hybrid quantum-classical machine learning.

qml-essentials

Python package with commonly used Ansaetze, tools and data-reuploading model in quantum machine learning.

qmlkit

A backend-agnostic quantum machine learning library for SpinQit, Qiskit, Cirq and PyTorch. Exact gradients, composable ansatze, quantum kernels. Cross-validated against PennyLane.

quoptuna

Fairness-aware, explainable AutoML for quantum + classical ML — 21 models, one Optuna search, SHAP & AI reports. uvx quoptuna

tensorcircuit

Tensor network based quantum software framework for the NISQ era

qhbmlib

Quantum Hamiltonian-Based Models built on TensorFlow Quantum

cova

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

cqlib-qml

A quantum machine learning toolkit built on Cqlib, featuring quantum data encoders, parameterized quantum circuits, quantum and hybrid quantum-classical neural networks, quantum kernel methods, and end-to-end training components.

flagquantum

Sharded, differentiable quantum simulation and training in PyTorch, reaching domestic accelerators through FlagOS.

quonic

Quantum programming framework — 3 lines of code, 12+ backends, 77 algorithm templates. Write quantum programs as simple as Python.