Browsing Bergen Open Research Archive by Author "Motornenko, Anton"
Now showing items 1-3 of 3
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Identifying the nature of the QCD transition in heavy-ion collisions with deep learning
Du, Yilun; Zhou, Kai; Steinheimer, Jan; Pang, Long-Gang; Motornenko, Anton; Zong, Hong-Shi; Wang, Xin-Nian; Stöcker, Horst (Journal article; Peer reviewed, 2021)In this proceeding, we review our recent work using deep convolutional neural network (CNN) to identify the nature of the QCD transition in a hybrid modeling of heavy-ion collisions. Within this hybrid model, a viscous ... -
Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning
Du, Yilun; Zhou, Kai; Steinheimer, Jan; Pang, Long-Gang; Motornenko, Anton; Zong, Hong-Shi; Wang, Xin-Nian; Stöcker, Horst (Journal article; Peer reviewed, 2020)Using deep convolutional neural network (CNN), the nature of the QCD transition can be identified from the final-state pion spectra from hybrid model simulations of heavy-ion collisions that combines a viscous hydrodynamic ... -
Kinetic model of resonant nanoantennas in polymer for laser induced fusion
Papp, Istvan; Bravina, Larissa; Csete, Mária; Kumari, Archana; Mishustin, Igor N.; Motornenko, Anton; Rácz, Péter; Satarov, Leonid M.; Stöcker, Horst; Strottman, Daniel D:; Szenes, András; Vass, Dávid; Szokol, Ágnes Nagyné; Kámán, Judit; Bonyár, Attila; Biró, Tamás S.; Csernai, László Pál; Kroó, Norbert (Journal article; Peer reviewed, 2023)Studies of resilience of light-resonant nanoantennas in vacuum are extended to consider the case of polymer embedding. This modifies the nanoantenna’s lifetime and resonant laser pulse energy absorption. The effective ...