From the 1 of 6 linked papers with an AI index.
7 papers
Inclusive P-wave Quarkonium Decay Widths from Lattice QCD and pNRQCD
Nora Brambilla, Viljami Leino, Julian Mayer-Steudte +4
The paper develops a method that combines lattice QCD with potential nonrelativistic QCD to calculate inclusive decay widths of P‑wave heavy quarkonium states, determining a key no…
Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions
Panayiotis Panayiotou, Ãzgür ÅimÅek
Causal discovery is challenging in general dynamical systems because, without strong structural assumptions, the underlying causal graph may not be identifiable even from intervent…
CausalProfiler: Generating Synthetic Benchmarks for Rigorous and Transparent Evaluation of Causal Machine Learning
Panayiotis Panayiotou, Audrey Poinsot, Alessandro Leite +4
Causal machine learning (Causal ML) aims to answer "what if" questions using machine learning algorithms, making it a promising tool for high-stakes decision-making. Yet, empirical…
Perturbative study of NLO chromoelectric correlators in Euclidean space
Panayiotis Panayiotou
We report on the perturbative study, at next-to-leading order (NLO), of correlation functions at finite temperature of two chromoelectric fields connected by an adjoint Wilson line…
Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite +3
Causal machine learning has the potential to revolutionize decision-making by combining the predictive power of machine learning algorithms with the theory of causal inference. How…
The chromoelectric adjoint correlators in Euclidean space at next-to-leading order
Nora Brambilla, Panayiotis Panayiotou, Saga Säppi +1
The physics of quarkonium created in heavy-ion collisions is intrinsically connected to the correlation functions of adjoint chromoelectric fields in quantum chromodynamics. We stu…