PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.

A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.

A platform-agnostic quantum runtime framework

Sandbox-environment to work with several quantum-computing packages.

A classical-quantum or hybrid neural network with adversarial defense protection

Mitiq is an open source toolkit for implementing error mitigation techniques on most current intermediate-scale quantum computers.

qBraid-SDK QIR transpiler integration

Cirq adapter for IQM's quantum computers

Study resources for learning quantum computing

A collection of Python samples demonstrating how to get started with IonQ using various quantum frameworks

DNA Game - aDaptive Noise Alleviation by Genetic Algorithms to Mitigate Error. Selected project of Unitary Fund challenge for QRISE 2024.

Demonstrates the implementation of various logical gates using quantum circuits. The code utilizes three popular quantum computing libraries: Cirq, PyQuil, and ProjectQ.

A quantum anomaly detection approach using the Cirq and Pennylane libraries, designed to detect adversarial attacks on quantum circuits.

Basic arithmetic on a Quantum Circuit

Quantum image classification using quantum circuits and variational classifiers on a MNIST dataset.

Project inspired by a book titled, "Artificial Intelligence," by Copeland. One of the World's first Quantum Neural Networks ever invented.

Multi-Party Computation transforms data handling by decentralizing trust among multiple participants. This ensures that no single entity demands absolute trust. An advantage for companies in safeguarding data privacy: once data leaves the user's computer, it remains obscured from any single external entity.

Implementations of Quantum Algorithms

Quantum Circuit Simulator implemented in JavaScript

Playground for Cirq in Py for Quantum Circuits 🎲