TensorFlow Quantum: A Software Framework for Quantum Machine Learning

TL;DR

TensorFlow Quantum (TFQ) is an open-source library that enables rapid development and training of hybrid quantum-classical models for various quantum data processing tasks, integrating quantum circuit simulation with TensorFlow.

Contribution

The paper introduces TensorFlow Quantum, a comprehensive framework combining quantum circuit simulation with TensorFlow for designing and training hybrid quantum-classical models, supporting advanced quantum learning tasks.

Findings

Demonstrated quantum classification and control applications

Showcased quantum circuit simulation for noisy systems

Enabled exploration of quantum algorithms like VQE and quantum phase transition classification

Abstract

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high-level abstractions for the design and training of both discriminative and generative quantum models under TensorFlow and supports high-performance quantum circuit simulators. We provide an overview of the software architecture and building blocks through several examples and review the theory of hybrid quantum-classical neural networks. We illustrate TFQ functionalities via several basic applications including supervised learning for quantum classification, quantum control, simulating noisy quantum circuits, and quantum approximate optimization. Moreover, we demonstrate how one can apply TFQ to tackle advanced quantum learning tasks including meta-learning, layerwise learning, Hamiltonian learning, sampling thermal states, variational quantum eigensolvers, classification of quantum phase transitions, generative adversarial networks, and reinforcement learning. We hope this framework provides the necessary tools for the quantum computing and machine learning research communities to explore models of both natural and artificial quantum systems, and ultimately discover new quantum algorithms which could potentially yield a quantum advantage.