36 citations · 36 across the 1 of their papers we have counts for
5 papers
Deep learning jet modifications in heavy-ion collisions
Yi-Lun Du, Daniel Pablos, Konrad Tywoniuk
Jet interactions in a hot QCD medium created in heavy-ion collisions are conventionally assessed by measuring the modification of the distributions of jet observables with respect…
Identifying the nature of the QCD transition in heavy-ion collisions with deep learning
Yi-Lun Du, Kai Zhou, Jan Steinheimer +5
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 collision…
Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning
Yi-Lun Du, Kai Zhou, Jan Steinheimer +5
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 colli…
Revisiting heavy quark radiative energy loss in nuclei within the high-twist approach
Yi-Lun Du, Yayun He, Xin-Nian Wang +2
We revisit the calculation of multiple parton scattering of a heavy quark in nuclei within the framework of recently improved high-twist factorization formalism, in which gauge inv…
Fermion Self-energy and Pseudovector Condensate in NJL Model with External Magnetic Field
Song Shi, Yi-Lun Du, Yi Tang +3
In this paper, we aim to study the complete self-energy in the fermion propagator within two-flavor NJL model in the case of finite temperature, chemical potential and external mag…