Herzallah Alharazin

most citedReconstruction of Gravitational Form Factors using Generative Machine Learning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

nucl-th2026

Generative artificial intelligence for reconstructing neutron-star matter

Julia Yu. Panteleeva, Herzallah Alharazin, Evgeny Epelbaum

Neutron-star cores hold the only known matter in the universe that is simultaneously cold and strongly interacting, compressed beyond nuclear density into a state of unknown compos…

hep-ph2026★ 1 cited

Reconstruction of Gravitational Form Factors using Generative Machine Learning

Herzallah Alharazin, Julia Yu. Panteleeva

We develop a generative framework based on denoising diffusion for the model-independent reconstruction of hadronic form factors from sparse and noisy data. The generative prior is…

hep-lat2026

Three-body study of the $T_{cc} (3875)^{+}$ from lattice QCD

We discuss an ongoing first lattice study of the doubly-charmed tetraquark $T_{cc}^{+}$ (3875) via a three-body approach. We investigate the $D D I ¨ $ system in the $I = 0$ , $C = 2$ sector,…

Generative artificial intelligence for reconstructing neutron-star matter

Reconstruction of Gravitational Form Factors using Generative Machine Learning

Three-body study of the Tcc​(3875)+ from lattice QCD

Three-body study of the $T_{cc} (3875)^{+}$ from lattice QCD