Digital-analog quantum programming interface
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Updated
Jun 12, 2024 - Python
Digital-analog quantum programming interface
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.
C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows
Variational Quantum Linear Solver without Barren Plateaus
Code for the article "Quantum Machine Learning Tensor Network States"
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
The Swiss Army Knife of Applied Quantum Technology
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
The Classiq Library is the largest collection of quantum algorithms, applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌
The PennyLane-Lightning plugin provides a fast state-vector simulator written in C++ for use with PennyLane
scikit-qulacs is a library for quantum neural network. This library is based on qulacs and named after scikit-learn.
A differentiable bridge between phase space and Fock space
AI_Research_Junction@Aditi_Khare - Research Papers Summaries Capturing Latest advancements in Generative AI, Quantum AI and Computer Vision
Project inspired by a book titled, "Artificial Intelligence," by Copeland. One of the World's first Quantum Neural Networks ever invented.
Malware Detection with the EMBER Dataset
Unsupervised anomaly detection in the latent space of high energy physics events with quantum machine learning.
Quantum Transformers for High Energy Physics Analysis at the Large Hadron Collider
Group invariant QML and Representation theory for Geometric QML project.
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