high performance computing on graphics processing units: hgpu.org

Supervised learning with a deep convolutional neural network is used to identify the QCD equation of state (EoS) employed in relativistic hydrodynamic simulations of heavy-ion collisions. The final-state particle spectra $rho(p_T,Phi)$ provide directly accessible information from experiments. High-level correlations of $rho(p_T,Phi)$ learned by the neural network act as an "EoS-meter", effective in detecting the nature of the QCD transition. The EoS-meter is model independent and insensitive to other simulation input, especially the initial conditions. Thus it provides a formidable direct-connection of heavy-ion collision observable with the bulk properties of QCD.