McMahon Lab

Physics-Aware-Training

Instructional implementation of Physics-Aware Training (PAT) with demonstrations on simulated experiments.

Image-sensing-with-multilayer-nonlinear-optical-neural-networks

Implementation of image sensing using a 2-layer optical neural network with optical-to-optical nonlinear activations

cim-optimizer

Reference implementation of a simulator of multiple variants of the Coherent Ising Machine (CIM).

ONN-QAT-SQL

Scripts for training neural networks resistant to photon shot noise with quantization-aware training, together with the code for simulating neural network performance under shot noise.

ONN-device-control

Device control modules for an optical matrix-vector multiplier with a low photon count.

error_mitigation_vqe

Tools for optimizing quantum circuits and for performing rescaling-based error mitigation.

Fourier-Series-Loader

Single-Photon-Detection-Neural-Networks

Physics-aware stochastic training for single-photon-detection neural networks (SPDNNs)

MultimodeNonlinearOptics

2D-programmable-waveguide

sweeps

Run parameter sweeps easily, in parallel, with JSON parameters, logs, diverse language support, and parameter data frames.

Hamiltonian-Reconstruction-Metric

mcmahon-lab.github.io

The-Benefits-of-Self-Supervised-Learning-for-Training-Physical-Neural-Networks

Repository that contains the code to reproduce the results presented in the paper.