Wed·Jan 29, 2025Wednesday·January 29, 2025

1. 01*

   Hybrid Hadronization -- A Study of In-Medium Hadronization of Jets

   A. Sengupta🇺🇸 · R. J. Fries🇺🇸 · M. Kordell II🇺🇸 · B. Kim🇺🇸 · A. Angerami🇺🇸 · R. Arora🇺🇸 · S. A. Bass🇺🇸 · Y. Chen🇺🇸 · R. Datta🇺🇸 · L. Du🇨🇦 · R. Ehlers🇺🇸 · H. Elfner🇩🇪 and 41 other authors

   QCD jets are considered important probes for quark gluon plasma created in collisions of nuclei at high energies. Their parton showers are significantly altered if they develop inside of a deconfined medium. Hadronization of jets is also thought to be affected by the presence of quarks and gluons. We present a systematic study of the effects of a thermal bath of partons on the hadronization of parton showers. We use the JETSCAPE framework to create parton showers both in vacuum and in a brick of quark gluon plasma. The brick setup allows important parameters, like the size of the plasma as well as the collective flow of partons, to be varied systematically. We hadronize the parton showers using Hybrid Hadronization, which permits shower partons to form strings with thermal partons, or to recombine directly with thermal partons as well as with each other. We find a sizeable amount of interaction of shower partons with thermal partons during hadronization, indicating a natural continuation of the interaction of jet and medium during this stage. The observed effects grow with the size of the medium. Collective flow easily transfers from the thermal partons onto the emerging jet hadrons. We also see a significant change in hadron chemistry as expected in the presence of quark recombination processes.

   ↳ hep-phnucl-exnucl-th8 citations
2. 02*

   Polarized Dissociation and Spin Alignment of Moving Quarkonium in Quark-Gluon Plasma

   Zhishun Chen🇨🇳 · Shu Lin🇨🇳

   Recent experiments have found spin alignment of $J/\psi$ with respect to event plane in heavy ion collisions, suggesting a medium effect that is spin dependent. We propose a possible mechanism with polarized dissociation from the motion of $J/\psi$ with respect to the medium. We calculate polarized dissociation rate for quarkonium spin triplet state from spin chromomagnetic coupling in the potential non-relativistic QCD framework. This is done for the leading order gluo-dissociation process and next to leading order inelastic Coulomb scattering process. The polarized dissociation rate is expressed as a function of relative velocity between quarkonium and QGP and the quantization axis. Applying the polarized dissociation rate to quarkonium evolution with dissociation effect only in a Bjorken flow, we find the spin $0$ state to dissociate less than the other spin states, leading to positive ${\rho }_{00}-1/3$. Regeneration contribution is expected to give a contribution with the opposite sign.

   ↳ hep-phnucl-exnucl-thPRD(2025)·5 citations
3. 03*

   Object Detection with Deep Learning for Rare Event Search in the GADGET II TPC

   Tyler Wheeler🇺🇸 · S. Ravishankar🇺🇸 · C. Wrede🇺🇸 · A. Andalib🇺🇸 · A. Anthony🇺🇸 · Y. Ayyad🇺🇸 · B. Jain🇺🇸 · A. Jaros🇺🇸 · R. Mahajan🇺🇸 · L. Schaedig🇺🇸 · A. Adams🇺🇸 · S. Ahn🇺🇸 and 41 other authors

   In the pursuit of identifying rare two-particle events within the GADGET II Time Projection Chamber (TPC), this paper presents a comprehensive approach for leveraging Convolutional Neural Networks (CNNs) and various data processing methods. To address the inherent complexities of 3D TPC track reconstructions, the data is expressed in 2D projections and 1D quantities. This approach capitalizes on the diverse data modalities of the TPC, allowing for the efficient representation of the distinct features of the 3D events, with no loss in topology uniqueness. Additionally, it leverages the computational efficiency of 2D CNNs and benefits from the extensive availability of pre-trained models. Given the scarcity of real training data for the rare events of interest, simulated events are used to train the models to detect real events. To account for potential distribution shifts when predominantly depending on simulations, significant perturbations are embedded within the simulations. This produces a broad parameter space that works to account for potential physics parameter and detector response variations and uncertainties. These parameter-varied simulations are used to train sensitive 2D CNN object detectors. When combined with 1D histogram peak detection algorithms, this multi-modal detection framework is highly adept at identifying rare, two-particle events in data taken during experiment 21072 at the Facility for Rare Isotope Beams (FRIB), demonstrating a 100% recall for events of interest. We present the methods and outcomes of our investigation and discuss the potential future applications of these techniques.

   ↳ physics.ins-detnucl-exphysics.data-anNucl.Instrum.Meth.A(2025)·2 citations

* Reconstructed cohort: no mailing for this day survives in the archive. Papers are grouped by their submission times and arXiv's announcement cut-off, assuming announcement without delay; positions follow identifier order. Validated at ~91% exact-day agreement against the archived era.