From the 1 of 11 linked papers with an AI index.
11 papers
Imaging non-hydrodynamic modes with jet wakes
Aleksi Kurkela, Ian Moult, Alexander Soloviev +1
The authors propose that the angular pattern of the energy deposited by a jet (the jet wake) in heavy‑ion collisions can be used to detect non‑hydrodynamic excitations of the quark…
Causality alone bounds the maximum radius difference between different-mass neutron stars
Aleksi Kurkela, Tuhin Malik
We investigate how the assumption of a common causal equation of state (EoS) correlates the radii of neutron stars at different masses and thereby reduces the uncertainties inferre…
As above, so below: assessing extremeness of the neutron-star equation of state based on the unstable branch
Tyler Gorda, Oleg Komoltsev, Aleksi Kurkela +1
Microscopic models of neutron-star matter have been widely used in astrophysical applications. The focus of attention has been on densities up to the maximal densities reached in s…
Constrained Gaussian-process bridge prior for neutron-star equation-of-state inference
Tyler Gorda, Oleg Komoltsev, Aleksi Kurkela +1
We set forth a new method for generating model-agnostic, nonparametric priors for neutron star equation-of-state inference that are stable, causal and thermodynamically consistent…
Solving the QCD effective kinetic theory with neural networks
Sergio Barrera Cabodevila, Aleksi Kurkela, Florian Lindenbauer
Event-by-event QCD kinetic theory simulations are hindered by the large numerical cost of evaluating the high-dimensional collision integral in the Boltzmann equation. In this work…
Machine learning approach to QCD kinetic theory
Sergio Barrera Cabodevila, Aleksi Kurkela, Florian Lindenbauer
The effective kinetic theory (EKT) of QCD provides a possible picture of various non-equilibrium processes in heavy- and light-ion collisions. While there have been substantial adv…