Speaker:Evan McKinney

Evan McKinney

Iowa State University

Title: Evaluating Hybrid Quantum-Classical Classification Models

Abstract: Hybrid Quantum-Classical Neural Networks combine layers of classical neurons with quantum layers containing parameterized quantum circuits. These hybrid networks utilize noisy intermediate-scale quantum computing technology by localizing complexity to low-depth quantum circuits which effectively utilize entanglement to improve classification for datasets containing quantum information. We review emerging quantum machine-learning algorithms, articulate an evaluation framework for hybrid classification neural network architectures, and contribute a discussion on implementation considerations for future advancements in quantum neural network development. With research in quantum machine-learning rapidly expanding and advancing, the next stage of our research involves the completion of a hybrid network test-bench followed by experimentation on circuit architectures and interconnections of classical and quantum layers for different datasets.