Machine Learning, artificial intelligence and quantum technologies/Science; research, education and exciting possibilities in the future job market
Contents
What is this talk about?
A simple perspective on the interface between ML and Physics
AI/ML and some statements you may have heard (and what do they mean?)
Scientific Machine Learning
Machine Learning software
Lots of room for creativity
Types of machine learning
Examples
And more
Selected references
What are the basic ingredients?
Quantum Monte Carlo and deep learning
Monte Carlo methods and Neural Networks
Deep learning neural networks, "Variational Monte Carlo calculations of \( A\le 4 \) nuclei with an artificial neural-network correlator ansatz by Adams et al.":"https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.127.022502"
The electron gas in three dimensions with \( N=14 \) electrons
Extrapolations and model interpretability
Physics based statistical learning and data analysis
Bayes' Theorem
Folding and unfolding and response functions
Quantified limits of the nuclear landscape
Quantum Technologies
Quantum Engineering
Candidate systems
Electrons (quantum dots) on superfluid helium
Education at undergraduate level and more
QuSTEAM Model
Courses, Prototype
Important Issues to think of
Observations
Future Needs/Problems
The electron gas in three dimensions with \( N=14 \) electrons
Jane Kim, Bryce Fore, Alessandro Lovato and MHJ, in preparation
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