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- 2018 (221) (entfernen)
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- Heavy Ion Experiments (5)
- focused electron beam induced deposition (3)
- BESIII (2)
- Electronic properties and materials (2)
- Magnetic properties and materials (2)
- Phase transitions and critical phenomena (2)
- correlation functions (2)
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Institut
- Physik (221) (entfernen)
A primordial state of matter consisting of free quarks and gluons that existed in the early universe a few microseconds after the Big Bang is also expected to form in high-energy heavy-ion collisions. Determining the equation of state (EoS) of such a primordial matter is the ultimate goal of high-energy heavy-ion experiments. Here we use supervised learning with a deep convolutional neural network to identify the EoS employed in the relativistic hydrodynamic simulations of heavy ion collisions. High-level correlations of particle spectra in transverse momentum and azimuthal angle learned by the network act as an effective EoS-meter in deciphering the nature of the phase transition in quantum chromodynamics. Such EoS-meter is model-independent and insensitive to other simulation inputs including the initial conditions for hydrodynamic simulations.