The Ecosystem consists of projects, tools, utilities, libraries and tutorials from a broad community of developers and researchers. The goal of the Ecosystem is to recognize, support and accelerate development of quantum technologies using Qiskit.
To join the Ecosystem create a submission issue
Main (9)
| Name | Description |
|---|---|
| qiskit-aer | Aer provides high-performance quantum computing simulators with realistic noise models.  |
| qiskit-optimization | Qiskit Optimization is an open-source framework that covers the whole range from high-level modeling of optimization problems, with automatic conversion of problems to different required representations, to a suite of easy-to-use quantum optimization algorithms that are ready to run on classical simulators, as well as on real quantum devices via Qiskit.   |
| qiskit-metal | Qiskit Metal is an open-source framework for engineers and scientists to design superconducting quantum devices with ease.   |
| qiskit-machine-learning | The Machine Learning package contains sample datasets and quantum ML algorithms.  |
| qiskit-nature | Qiskit Nature allows researchers and developers in different areas of natural sciences (including physics, chemistry, material science and biology) to model and solve domain-specific problems using quantum simulations   |
| qiskit-finance | Qiskit Finance is an open-source framework that contains uncertainty components for stock/securities problems, Ising translators for portfolio optimizations and data providers to source real or random data to finance experiments.  |
| qiskit-experiments | Qiskit Experiments is an open-source project for running characterizing, calibrating, and benchmarking experiments in Qiskit. |
| qiskit-dynamics | Qiskit Dynamics is an open-source project for building, transforming, and solving time-dependent quantum systems in Qiskit.  |
| OpenQASM | OpenQASM is an imperative programming language designed for near-term quantum computing algorithms and applications. Quantum programs are described using the measurement-based quantum circuit model with support for classical feed-forward flow control based on measurement outcomes.  |
Community (17)
| Name | Description |
|---|---|
| pyEPR | Qiskit Metal E&M analysis with Ansys and the energy-participation-ratio method is based on pyEPR.  |
| c3 | The C3 package is intended to close the loop between open-loop control optimization, control pulse calibration, and model-matching based on calibration data. |
| qiskit-superstaq | This package is used to access SuperstaQ via a Web API through Qiskit. Qiskit programmers can take advantage of the applications, pulse level optimizations, and write-once-target-all features of SuperstaQ with this package. |
| qtcodes | Qiskit Topological Codes |
| kaleidoscope | Kaleidoscope |
| pytket-qiskit | an extension to Pytket (a python module for interfacing with CQC tket) that allows Pytket circuits to be run on IBM backends and simulators, as well as conversion to and from Qiskit representations. |
| quantuminspire | platform allows to execute quantum algorithms using the cQASM language. |
| mitiq | Mitiq is a Python toolkit for implementing error mitigation techniques on quantum computers  |
| pennylane-qiskit | The PennyLane-Qiskit plugin integrates the Qiskit quantum computing framework with PennyLane's quantum machine learning capabilities |
| quantumcat | quantumcat is a platform-independent, open-source, high-level quantum computing library, which allows the quantum community to focus on developing platform-independent quantum applications without much effort |
| Blueqat | A quantum computing SDK |
| python-open-controls | Q-CTRL Open Controls is an open-source Python package that makes it easy to create and deploy established error-robust quantum control protocols from the open literature |
| qiskit-rigetti | Rigetti Provider for Qiskit  |
| QiskitBot | A discord bot that allows you to execute Quantum Circuits, look up the IBMQ Qiskit's Documentation, and search questions on the Quantum Computing StackExchange  |
| pytorch-quantum | A PyTorch-centric hybrid classical-quantum dynamic neural networks framework. |
| QPong | A quantum version of the classic game Pong built with Qiskit and PyGame  |
| q-kernel-ops | Code base on the paper Kernel Matrix Completion for Offline Quantum-Enhanced Machine Learning 2112.08449.  |
Extensions (9)
| Name | Description |
|---|---|
| qiskit-alt | Python package uses a backend written in Julia to implement high performance features for standard Qiskit.  |
| qiskit-cold-atom | This project builds on this functionality to describe programmable quantum simulators of trapped cold atoms in a gate- and circuit-based framework. |
| Entanglement forging | This module allows a user to simulate chemical and physical systems using a Variational Quantum Eigensolver (VQE) enhanced by Entanglement Forging. Entanglement Forging doubles the size of the system that can be exactly simulated on a fixed set of quantum bits.  |
| Quantum kernel training | The quantum kernel training (QKT) toolkit is designed to enable users to leverage quantum kernels for machine learning tasks; in particular, researchers who are interested in investigating quantum kernel training algorithms in their own research, as well as practitioners looking to explore and apply these algorithms to their machine learning applications. |
| Quantum Random Access Optimization | The Quantum Random Access Optimization (QRAO) module is designed to enable users to leverage a new quantum method for combinatorial optimization problems. |
| qiskit-ibm-runtime | This module provides the interface to access Qiskit Runtime.  |
| qiskit-ionq | Project contains a provider that allows access to IonQ ion trap quantum systems. |
| qiskit-ibm-provider | Project contains a provider that allows accessing the IBM Quantum systems and simulators. |
| mthree | Matrix-free Measurement Mitigation (M3) |
See the contributing document to learn about the source code contribution process developers follow.
See the code of conduct to learn about the social guidelines developers are expected to adhere to.
See the open issues for a list of proposed features (and known issues).