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1. Understanding the properties of the fireball with the polarization signature of thermal dileptons

   https://doi.org/10.1051/epjconf/202429607009  

   Seck, Florian; Friman, Bengt; Galatyuk, Tetyana; van_Hees, Hendrik; Speranza, Enrico; Rapp, Ralf; Wambach, Jochen (January 2024, EPJ Web of Conferences)

   Bellwied, R; Geurts, F; Rapp, R; Ratti, C; Timmins, A; Vitev, I (Ed.)

   Multi-differential measurements of dilepton spectra serve as a unique tool to characterize the properties of matter in the interior of the hot and dense fireball created in heavy-ion collisions. An important property of virtual photons is their spin polarization defined in the rest frame of the virtual photon with respect to a chosen quantization axis. Microscopic calculations of in-medium electromagnetic spectral functions have mostly focused on integrated yields which are proportional to the sum of the longitudinal and transverse components of the virtual photon’s self-energy, while photon polarization results from the difference of these components. As the processes that drive the medium effects in the spectral function change with invariant mass and momentum, this becomes a powerful tool for studying the medium composition. We present the polarization observables of thermal virtual photons as a function of mass and momentum and confront the results with existing measurements from HADES and NA60. 

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2. Conservation of longitudinal spin polarization of positrons emitted from a thin Ni(100) foil

   https://doi.org/10.1103/PhysRevA.107.062809  

   Cecchini, G. G.; Greaves, R. G.; Mills, A. P. (June 2023, Physical Review A)

   We have discovered that 5 keV bursts of 5 × 107 positrons with an initial longitudinal spin polarization of (28.8 ± 0.7)%, when implanted into a thin Ni(100) crystal, are emitted with 20% efficiency at thermal energies from its surface with (30.9 ± 0.5)% polarization. We conclude that the positron spin polarization is preserved while interacting with the Ni, despite the 0.61 T average transverse magnetization of the Ni at room temperature. The resulting polarized beam has been focused to a 0.025-mm mean-diameter spot when accelerated to 5 keV and will be uniquely suited for experiments on a neutral spin aligned e+-e − plasma, spin- and angle-resolved positronium emission spectroscopy, and critical for producing a triplet positronium Bose-Einstein condensate. 

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3. Electric conductivity of QCD matter and dilepton spectra in heavy-ion collisions

   https://doi.org/10.1103/PhysRevC.110.054909  

   Rapp, Ralf (November 2024, Physical Review C)

   The electric conductivity, ${\sigma }_{\mathrm{el}}$, is a fundamental transport coefficient of QCD matter that can be related to the zero-energy limit of the electromagnetic (EM) spectral function at vanishing three-momentum in the medium. The EM spectral function is also the central quantity to describe the thermal emission rates and pertinent spectra of photon and dilepton radiation in heavy-ion collisions. Employing a model for dilepton rates that combines hadronic many-body theory with nonperturbative QGP emission constrained by lattice QCD which describes existing dilepton measurements in heavy-ion collisions, I investigate the sensitivity of low-mass dilepton spectra in Pb-Pb collisions at the CERN Large Hadron Collider (LHC) to ${\sigma }_{\mathrm{el}}$. In particular, I separately evaluate the contributions from QGP and hadronic emission, and identify signatures that can help to extract ${\sigma }_{\mathrm{el}}$from high-precision experimental data expected to be attainable with future detector systems at the LHC. Published by the American Physical Society2024 

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4. Extracting the speed of sound in quark–gluon plasma with ultrarelativistic lead–lead collisions at the LHC

   https://doi.org/10.1088/1361-6633/ad4b9b  

   The_CMS_Collaboration (June 2024, Reports on Progress in Physics)

   Abstract Ultrarelativistic nuclear collisions create a strongly interacting state of hot and dense quark–gluon matter that exhibits a remarkable collective flow behavior with minimal viscous dissipation. To gain deeper insights into its intrinsic nature and fundamental degrees of freedom, we determine the speed of sound in an extended volume of quark–gluon plasma using lead–lead (PbPb) collisions at a center-of-mass energy per nucleon pair of 5.02 TeV. The data were recorded by the CMS experiment at the CERN LHC and correspond to an integrated luminosity of 0.607 nb⁻¹. The measurement is performed by studying the multiplicity dependence of the average transverse momentum of charged particles emitted in head-on PbPb collisions. Our findings reveal that the speed of sound in this matter is nearly half the speed of light, with a squared value of $0.241\pm 0.002\left(\text{stat}\right)\pm 0.016\left(\text{syst}\right)$in natural units. The effective medium temperature, estimated using the mean transverse momentum, is $219\pm 8\left(\text{syst}\right)\text{MeV}$. The measured squared speed of sound at this temperature aligns precisely with predictions from lattice quantum chromodynamic (QCD) calculations. This result provides a stringent constraint on the equation of state of the created medium and direct evidence for a deconfined QCD phase being attained in relativistic nuclear collisions. 

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5. Identifying the nature of the QCD transition in relativistic collision of heavy nuclei with deep learning

   https://doi.org/10.1140/epjc/s10052-020-8030-7  

   Du, Yi-Lun; Zhou, Kai; Steinheimer, Jan; Pang, Long-Gang; Motornenko, Anton; Zong, Hong-Shi; Wang, Xin-Nian; Stöcker, Horst (June 2020, The European Physical Journal C)

   null (Ed.)

   Abstract 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 model with a hadronic cascade “after-burner”. Two different types of equations of state (EoS) of the medium are used in the hydrodynamic evolution. The resulting spectra in transverse momentum and azimuthal angle are used as the input data to train the neural network to distinguish different EoS. Different scenarios for the input data are studied and compared in a systematic way. A clear hierarchy is observed in the prediction accuracy when using the event-by-event, cascade-coarse-grained and event-fine-averaged spectra as input for the network, which are about 80%, 90% and 99%, respectively. A comparison with the prediction performance by deep neural network (DNN) with only the normalized pion transverse momentum spectra is also made. High-level features of pion spectra captured by a carefully-trained neural network were found to be able to distinguish the nature of the QCD transition even in a simulation scenario which is close to the experiments. 

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