stochastic-physical-neural-networks

name

stochastic-physical-neural-networks

description

Stochastic Physical Neural Networks (PNNs) methodology using single-electron and single-photon stochastic neurons. Training via empirical backward pass with few trials achieves >97% MNIST accuracy. Use when: physical neural networks, stochastic neurons, single-electron tunneling, quantum dot neurons, single-photon neurons, PNN training strategies, MNIST classification, noise-resilient deep learning, arXiv:2604.10861, stochastic physical computing, quantum neurons.

Stochastic Physical Neural Networks

Train physical neural networks where neurons are realized by stochastic activation switches — single-electron tunneling or single-photon processes.

Electronic Stochastic Neuron

• Implementation: Single-electron tunneling through a quantum dot
• Basis: Charge state of the quantum dot
• Stochasticity: Inherent tunneling statistics

Photonic Stochastic Neuron

• Implementation: Single-photon source driving one of two modes via controllable beam-splitter interaction
• Basis: Occupation of the undriven mode
• Stochasticity: Photon detection statistics

Training Strategies

Strategy	Forward Pass	Backward Pass	Key Finding
True probability	Expected values	True gradients	Lower accuracy
Empirical outputs	Sampled values	Empirical gradients	>97% MNIST accuracy

Key Insight

Using empirical outputs in the backward pass (not true probabilities) achieves significantly higher accuracy with fewer trials per layer.

Noise Robustness

• Maintains >97% test accuracy under high noise and model uncertainty
• Works with single-hidden-layer architecture
• Simplicity enables practical implementation

Training Protocol

1. Build single-hidden-layer stochastic PNN with electronic or photonic neurons
2. Vary number of trials per layer to control forward-pass stochasticity
3. Use empirical outputs (sampled values) for gradient estimation in backward pass
4. Train on target task — monitor convergence under noise conditions

Architectural Simplicity

Unlike DNNs requiring backpropagation through time, stochastic PNNs:

• No BPTT needed
• Only simple readout training
• Natural noise resilience
• Compatible with quantum hardware constraints

Activation Keywords

stochastic PNN, physical neural network, single-electron neuron, single-photon neuron, quantum dot neuron, stochastic neuron training, empirical backward pass, MNIST stochastic, Dou Kumara Burns