February 15, 2024
Journal Article

Quantum Machine Learning with SQUID


In this work we present the Scaled QUantum IDentifier (SQUID), an open-source framework for exploring hybrid Quantum-Classical algorithms for classification problems. The classical infrastructure is based on PyTorch and we provide a standardized design to implement a variety of quantum models with the capability of back-propagation for efficient training. We present the structure of our framework and provide examples of using SQUID in a standard binary classification problem from the popular MNIST dataset. In particular, we highlight the implications for scalability for gradient-based optimization of quantum models on the choice of output for variational quantum models.

Published: February 15, 2024


Roggero A., J. Filipek, S. Chang, and N.O. Wiebe. 2022. Quantum Machine Learning with SQUID. Quantum 6. PNNL-SA-179120. doi:10.22331/Q-2022-05-30-727