Training deep neural networks by backpropagation consumes significant energy in digital hardware. Boon and Cassola et al. show that homodyne detection can be used to extract gradients directly in a physical device, enabling efficient gradient descent and offering a scalable route to material-based learning.
- Marcus N. Boon
- Lorenzo Cassola
- Wilfred G. van der Wiel
