How to Prove Einstein Wrong and Put Elon Musk Out of a Job

Einstein’s Theory of General Relativity comprises one of the two pillars of modern physics and informs us of the dynamics of the largest objects in the observable universe. However, with neither GR or the Standard Model of Particle Physics able to give us insight into the nature of dark matter and dark energy new theories of physics have been proposed which predict a violation of GR’s ‘Achille’s Heel’, Einstein’s Equivalence Principle (EEP). In the first half of this talk I will discuss the recent progress made in the Gravity and Earth Exploration (GEE) Lab towards upgrading a long-period torsion pendulum instrument capable of detecting violations of the EEP. In the latter half I will present the results of a novel machine learning algorithm I developed during the initial pandemic lockdown based on the standard Multi-layer Perceptron (MLP) neural network model. Using an intuitive connectivity architecture between neurons in the network, this algorithm significantly improves the results of deep networks on a regression task to predict the critical temperature of superconducting materials.