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SUMMARY:Equation of State of Strongly Interacting Matter from Physics-Info
 rmed Neural Networks
DTSTART;VALUE=DATE-TIME:20260923T073000Z
DTEND;VALUE=DATE-TIME:20260923T075000Z
DTSTAMP;VALUE=DATE-TIME:20260914T032353Z
UID:indico-contribution-541@indico.bitp.kiev.ua
DESCRIPTION:Speakers: Musfer Adzhymambetov (Bogolyubov Institute for Theor
 etical Physics)\nUnderstanding the properties of strongly interacting matt
 er is one of the central challenges in high-energy physics. In heavy-ion c
 ollisions\, nuclei are smashed together at relativistic speeds to recreate
  extreme conditions of temperature and density\, briefly producing a state
  of matter known as the quark-gluon plasma. This hot\, dense matter behave
 s as a nearly perfect liquid — flowing with remarkably low viscosity —
  and is best described by relativistic hydrodynamics\, whose key input is 
 the equation of state encoding the system's thermodynamic properties.\n\nT
 he underlying theory\, quantum chromodynamics\, cannot yet be solved from 
 first principles across the full phase diagram. Lattice QCD is reliable on
 ly at low baryon chemical potential\, while the hadron resonance gas model
  holds only at low particle densities. Between them lies a critical gap 
 — one that coincides precisely with the region being probed by next-gene
 ration experiments such as RHIC BES\, FAIR\, and CBM.\n\nIn this talk\, I 
 present a neural-network approach to bridging this gap. The network is tra
 ined to reproduce lattice QCD and hadron resonance gas thermodynamics in t
 heir regimes of validity\, while extrapolating into the uncharted high-bar
 yon-density region in a manner that remains thermodynamically consistent 
 — enforced through convexity-preserving architecture and derivative cons
 traints\, in the spirit of physics-informed neural networks. The result is
  a four-dimensional equation of state\, $P(T\, μ_B\, μ_Q\, μ_S)$\, span
 ning the full phase space relevant to heavy-ion collisions. I will conclud
 e by showing how this equation of state is implemented within a full relat
 ivistic hydrodynamic simulation framework.\n\nThis work was partially supp
 orted by the National Research Foundation of Ukraine (project № 2025.07/
 0050).\n\nhttps://indico.bitp.kiev.ua/event/18/contributions/541/
LOCATION:Bogolyubov Institute for Theoretical Physics Conference Hall
URL:https://indico.bitp.kiev.ua/event/18/contributions/541/
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