activity
20182026
most citedNeural network enhanced Bayesian global analysis of relativistic heavy ion collisions

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

hep-ph20261 cited

Neural network enhanced Bayesian global analysis of relativistic heavy ion collisions

Jussi Auvinen, Kari J. Eskola, Henry Hirvonen +1

We introduce a novel deep convolutional neural network (NN) -enhanced Bayesian global analysis of bulk observables in highest-energy heavy-ion collisions, using relativistic 2+1 D…

hep-ph2025

MC-EKRT: Monte Carlo event generator with saturated minijet production for initializing 3+1 D fluid dynamics in high energy nuclear collisions

Harri Niemi, Jussi Auvinen, Kari J. Eskola +3

We present a novel saturation and leading order collinear factorization based Monte-Carlo implementation of the EKRT model for computing QCD matter initial states in high-energy nu…

hep-ph2024

Effects of saturation and fluctuating hotspots for flow observables in ultrarelativistic heavy-ion collisions

Henry Hirvonen, Mikko Kuha, Jussi Auvinen +3

We investigate the effects of saturation dynamics on midrapidity flow observables by adding fluctuating hotspots into the novel Monte Carlo EKRT (MC-EKRT) event generator for high-…

hep-ph2024

MC-EKRT: Monte Carlo event generator with saturated minijet production for initializing 3+1 D fluid dynamics in high energy nuclear collisions

Mikko Kuha, Jussi Auvinen, Kari J. Eskola +3

We present a novel Monte-Carlo implementation of the EKRT model, MC-EKRT, for computing partonic initial states in high-energy nuclear collisions. Our new MC-EKRT event generator i…

nucl-th2018

Latest predictions from the EbyE NLO EKRT model

Harri Niemi, Kari J. Eskola, Risto Paatelainen +1

We present the latest results from the NLO pQCD + saturation + viscous hydrodynamics (EbyE NLO EKRT) model. The parameters in the EKRT saturation model are fixed by the charged had…