I am a theoretical physicist working in the field of elementary particle physics. My main research interests revolve around (super)string theory, gravity and quantum field theory. I am especially interested in the non-perturbative structure of quantum field theory and a variety of bootstrap ideas that can bring together tools from very different directions (analytic and numeric, perturbative and non-perturbative). More recently, in this context, I have been thinking about Artificial Intelligence and how Machine Learning algorithms can be employed to address fundamental questions in formal quantum field theory.

Research topics

• Non-perturbative dynamics and duality in Quantum Field Theory

• Supersymmetry and supersymmetry breaking

• Machine learning applications to Quantum Field Theory

• Holographic dualities

• String theory

• Black Holes

BootSTOP: a STochastic OPtimizer for Conformal Bootstrap studies  - GitHub link and a dedicated website link
[Release 2 includes the modifications of the improved truncation methods with tail approximation, more pre-generated conformal blocks and access to all the PyGMO algorithms.]

FeynTune: Large Language Models for High Energy Theory
[The code used to curate the datasets, fine-tune and evaluate the models can be found at https://github.com/Paul-Richmond/FeynTune.
The fine-tuned models are available as LoRA adapters at https://huggingface.co/LLMsForHepth/models.]