Nuclear Theory·nucl-th

Monday·April 28, 2025

8 papers—4 primary·4 cross-listed

05
Charm-hadron reconstruction through three body decay in hadronic collisions using Machine Learning
Neelkamal Mallick🇫🇮 · Hadi Hassan🇫🇮 · D.J. Kim🇫🇮
Studies of heavy-quark (charm and beauty) production in hadronic and nuclear collisions provide excellent testing grounds for the theory of strong interaction, quantum chromodynamics. Heavy-quarks are produced predominantly in the initial hard partonic interactions, allowing them to witness the entire evolution process. The charm hadrons are produced in two ways. Firstly, the prompt charm hadrons which are formed from the charm quark hadronization which are produced directly from the initial hard-scatterings or the decay of other excited charm states. Secondly, the nonprompt charm hadrons which are produced from the decay of beauty hadrons. The produced charm hadrons then usually decay to light-flavor hadrons or leptons via two or three body decay. The reconstruction of charm hadrons is challenging due to the large combinatorial background as well as the difficulty of distinguishing between prompt and non-prompt charm hadrons. In this work, we use machine learning models--XGboost and Deep Neural Network--to reconstruct $Λ_{c}^{+} (u d c)$ hadrons via its three body final state decay channel, $Λ_{c}^{+} \to p K_{s}^{0}$ and $K_{s}^{0} \to π^{+} π^{-}$ . Using several experimentally available features of the decay daughters, these models can separate signal from background and identify prompt and nonprompt candidates with nearly 99\% accuracy. This method performs an unbinned track-level reconstruction since the $Λ_{c}$ candidates are tagged directly from their decay daughters. The necessary data for this study are simulated in pp collisions at $s = 13.6$ ~TeV using PYTHIA8 (Monash) model.
↳ hep-phhep-exnucl-th3 citations
06
Machine learning-based b-jet tagging in $pp$ collisions at $s = 13$ TeV
Hadi Hassan🇫🇮 · Neelkamal Mallick🇫🇮 · D.J. Kim🇫🇮
Studying heavy-flavor jets in $pp$ collision is important since they can test pQCD calculations and be used as a reference for heavy-ion collisions. Jets in this analysis are reconstructed from charged particles using the anti- $k_{T}$ algorithm with a resolution parameter $R =$ 0.4 and with pseudorapidity $∣ η ∣ <$ 0.5. Beauty jets are tagged using a machine learning model that uses a convolutional neural network trained on information extracted from the jet, tracks, and secondary vertices. The results show that this model is superior compared to other traditional tagging methods.
↳ hep-phhep-exnucl-thPRD(2026)·3 citations
07
Probing Quantum Phenomena through Photoproduction in Relativistic Heavy-Ion Collisions
James Daniel Brandenburg🇺🇸 · Spencer R. Klein🇺🇸 · Zhangbu Xu🇺🇸 · Shuai Yang🇨🇳 · Wangmei Zha🇨🇳 · Jian Zhou🇨🇳
Photoproduction in ultra-peripheral relativistic heavy-ion collisions displays many unique features, often involving quantum mechanical coherence and two-source interference between photon emission from the two ions. We review the recent experimental results from RHIC and the LHC and theoretical studies of coherent vector meson photoproduction, emphasizing the quantum mechanical aspects of the interactions and the entanglement between the final state particles. These studies enrich our understanding of non-local realism, underscore the critical role of the polarization of the photon source, quantum interference and nuclear effect on the gluon distribution. It paves a way for quantitatively probing the quantum nature of these high-energy nuclear collisions.
↳ nucl-exnucl-thquant-phPPNP(2025)·9 citations
08
Virial theorem for rigidly rotating matter
Sourav Dey🇮🇳
The scaling property of the thermodynamic free energy ( $Φ$ ) of a system at global equilibrium has been examined using a real-time method known as the virial theorem. We demonstrate these scaling properties through a derived relation based on the general structure of equal-time commutators among Poincare charges and their densities. This relation is applicable to any renormalizable fields with spin $\leq 1$ , excluding gauge fields. In this particular study, we investigate a rigidly rotating solution ( $Ω = const$ ) at global equilibrium for massless fermionic matter. It has been shown that the applicability of a hydrodynamic description requires a hierarchy $Ω R ≫ Ω β_{0}$ , where $R$ is the radius of the cylindrical-shaped rotating matter and $β_{0} = 1/ T_{0}$ is the inverse temperature on the rotation axis. Consequently, the thermodynamic free energy $Φ$ depends on the angular velocity through the product $Ω R$ , a dependency that extends to other thermodynamic variables as well. These findings are consistent with recent lattice QCD simulation results. Furthermore, we compute the moment of inertia for massless fermions and estimate the light quark contribution to the total moment of inertia of the Quark-Gluon Plasma (QGP) produced in heavy-ion collisions.
↳ hep-thhep-phnucl-th3 citations

Affiliations

first authorsco-authorsvia INSPIRE

Charm-hadron reconstruction through three body decay in hadronic collisions using Machine Learning

Machine learning-based b-jet tagging in pp collisions at s​=13 TeV

Probing Quantum Phenomena through Photoproduction in Relativistic Heavy-Ion Collisions

Virial theorem for rigidly rotating matter

Affiliations

Machine learning-based b-jet tagging in $pp$ collisions at $s = 13$ TeV