Skidmore Computational Physics & ML Lab A computational physics and machine-learning research group at Skidmore College

Welcome to the Computational Physics and Machine Learning research group in the Physics Department at Skidmore College.

The research directions of the group include developing and applying numerical and machine-learning techniques to problems in quantum mechanics, quantum field theory and string theory.

If you’re interested in working with us, get in touch!

2026

July

The lab took a break from summer research for an ice cream outing to Dairy Haus.

Lab members at Dairy Haus during summer research

Adam Blyberg, Marta Insolia, Lucia Curran-Lane, Michael Gyampo, and Finlay Savoir presented their summer research posters at the Skidmore Faculty Student Summer Research Program. Adam and Marta presented Phases of quantum D(N) theories via neural quantum states, and Lucia, Michael, and Finlay presented Phases of lattice gauge theories via neural networks.

Adam Blyberg and Marta Insolia presenting their summer research poster Marta Insolia presenting the D(N) theories poster Lucia Curran-Lane, Michael Gyampo, and Finlay Savoir presenting their summer research poster Finlay Savoir and Michael Gyampo with the lattice gauge theories poster

June

Rebecca Merber presented her research, Do neural quantum states exhibit double descent?, at the Skidmore end-of-year Academic Festival.

2025

July

Jack Biggins presented his research, Simulating the strong force with neural networks, at the Skidmore Faculty Student Summer Research Program.

Our paper Holomorphic supergravity in ten dimensions and anomaly cancellation has been released on the arXiv as a preprint.

2024

October

Our paper Deep learning lattice gauge theories has been published in Physical Review B and selected as an “Editors’ Suggestion”.