5 citations · 5 across the 5 of their papers we have counts for
5 papers
Deep-learning classification of physically admissible nuclear-matter equations of state
Ahmed Abuali, Micheal Kahangirwe, Francesco Di Clemente +3
Thermodynamic stability and causality impose fundamental constraints on the equation of state (EoS) of nuclear matter. Verifying these constraints conventionally requires calculati…
Studying the QCD Matter produced in Heavy-Ion Collisions using the MUSES Calculation Engine
Johannes Jahan, Kevin P. Pala, Yumu Yang +42
The equation of state of hot and dense matter is essential for describing heavy-ion collisions at all collision energies. Here, we explore the capabilities of the latest version of…
Detecting the 3D Ising model phase transition with a ground-state-trained autoencoder
Ahmed Abuali, David A. Clarke, Morten Hjorth-Jensen +3
We develop a one-class, deep-learning framework to detect the phase transition and recover critical behavior of the 3D Ising model. A 3D convolutional neural network autoencoder (C…
A new 4D lattice QCD equation of state: extended density coverage from a generalized -expansion
Ahmed Abuali, Szabolcs Borsányi, Zoltán Fodor +7
We present a new equation of state for QCD in which the temperature and the three chemical potentials for baryon number , electric charge and strangeness can b…
Deep learning of phase transitions with minimal examples
Ahmed Abuali, David A. Clarke, Morten Hjorth-Jensen +3
Over the past several years, there have been many studies demonstrating the ability of deep neural networks to identify phase transitions in many physical systems, notably in class…