FIELD NOTES TOPIC
machine learning in physics
2 notes, newest first.
Learning to Trace Seiberg Dualities
In this paper, the authors use machine learning methods to develop a practical tool for establishing Seiberg dualities in supersymmetric quiver gauge theories. They find that network architectures consisting of…
Grounded autonomous research: a fault-tolerant LLM pipeline from corpus to manuscript in frontier computational physics
The paper presents a pipeline for an autonomous research agent that can generate publication-grade manuscripts in the field of condensed matter physics. The agent is able to autonomously conceive a research direction…
