arXiv subjects

Guo-Liang Ma

Publications and source records attributed to Guo-Liang Ma.

At least 19 recordsLinked to original sources

arXiv2026

Sensitivity of anisotropic flow in Pb+Pb collisions to the neutron skin of $^{208}$Pb at energies available at the CERN Large Hadron Collider

We study the sensitivity of anisotropic flow in Pb+Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$~TeV to the neutron skin of $^{208}$Pb using the improved string-melting version of a multiphase transport (AMPT) model. By varying the neutron surface diffuseness, we trace the impact of several neutron-skin scenarios from the initial nuclear density profiles and eccentricities to final-state charged-particle production and flow cumulants. A systematic response is observed in both the initial eccentricities and the anisotropic flow, indicating that the neutron-skin-induced geometric effects can survive the full transport evolution. A model-to-data comparison with ALICE measurements disfavors the most compact and most diffuse density profiles within the tested AMPT setup, while the reference and moderate-skin configurations give comparable descriptions. Their similarity reflects a geometric degeneracy in large Pb+Pb collision systems, where the inclusive anisotropic flow is dominated by the effective collision geometry and nuclear size, making it only weakly sensitive to the detailed structure of the neutron surface. These results clarify both the sensitivity and the limitations of using anisotropic flow in relativistic heavy-ion collisions to probe neutron-skin effects.

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arXiv2026

Bayesian extraction of TMC-free collectivity in proton-proton and proton-nucleus collisions at the LHC

A central challenge in understanding the origin of collective flow-like signatures in small collision systems calls for a reliable method to disentangle collective flow from substantial background correlations, especially those arising from transverse momentum conservation (TMC). A Bayesian inference framework is developed to integrate TMC calculations with the LHC-ATLAS data on long-range multiparticle azimuthal correlation observables, thereby extracting TMC-free collectivity in small systems. Our analysis indicates that while the TMC-free elliptic and triangular flow ($v_{2}$ and $v_{3}$) are similar, the $p$+$p$ and $p$+Pb systems exhibit distinct TMC backgrounds, TMC-flow interplay, and $v_{2}$-$v_{3}$ correlations. We demonstrate that the extracted $v_{2}$ and $v_{3}$ are well described by the measured four-particle $v_2\{4\}$ and two-particle $v_3\{2\}$ in $p$+Pb collisions, whereas these measurements systematically underestimate the TMC-free flow in $p$+$p$ collisions, due to competing contributions from TMC effects. This establishes a robust and data-driven framework, enabling a quantitatively controlled interpretation of collective signals and opening a new avenue for understanding the origin of collectivity in small collision systems.

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arXiv2026

How transverse momentum conservation breaks azimuthal correlation factorization

The breakdown of azimuthal two-particle correlation factorization, quantified by the ratios $r_2$ and $r_3$, serves as a sensitive probe of transverse-momentum-dependent flow fluctuations. While hydrodynamic models predict $r_3 \leq 1$, experimental data from CMS in p-Pb collisions exhibit $r_3 > 1$, presenting a clear puzzle. We show that transverse momentum conservation (TMC) is the key mechanism dictating this factorization breakdown in small systems. We systematically calculate the effect of TMC as a function of the momentum difference between particles across various multiplicity and momentum ranges. Our results are in quantitative agreement with CMS p-Pb data for both $r_2$ and $r_3$. A central finding is a sign rule: under TMC, the deviation $r_n - 1$ follows $\left ( - 1 \right )^{n+1} $, being negative for even and positive for odd harmonic orders $n$. This work quantifies a dominant non-flow contribution to the factorization ratios $r_n$ in small systems, and demonstrates that this kinematic effect must be subtracted or accounted for before $r_n$ can be used as a reliable probe of genuine flow fluctuations.

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arXiv2026

Exploring the chiral magnetic effect in Au+Au collisions at $\sqrt{s_{NN}}=7.7-200$ GeV through Chiral Anomaly Transport

High-energy heavy-ion collisions have the potential to create local domains of chirality-imbalanced quarks, reflecting the topological characteristics of quantum chromodynamics. This phenomenon can potentially induce local $\mathcal{P}$ and $\mathcal{CP}$ violations in the quark-gluon plasma. The Chiral Magnetic Effect (CME) predicts an electric charge separation along the intense magnetic field generated during these collisions, which is typically investigated through charge-dependent azimuthal correlations ($Δγ$). In this work, we investigate the CME in Au+Au collisions at $\sqrt{s_{NN}} = 7.7 - 200$ GeV using a multiphase transport (AMPT) model equipped with a Chiral Anomaly Transport (CAT) module. we employ two independent methods: direct subtraction of the correlator $\langle N_{part}Δγ\rangle$ between simulations with zero and finite chiral chemical potential $μ_5$, and the event-shape-selection (ESS) approach. Our results reveal a significant CME signal within the energy range of 11.5-27 GeV and the centrality range of $20-50\%$, where the AMPT model aligns well with STAR experimental data. Furthermore, the CME fractions extracted by both methods are consistent within uncertainties across these energies. However, the CME signal disappears at both 7.7 and 200 GeV. These findings underscore that the observability of the CME critically depends on both the dynamic evolution of the magnetic field and the chemical freeze-out time of the partonic phase, which vary significantly with collision energy.

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arXiv2026

Universal imprinting of short-range correlations in relativistic heavy-ion collisions

Protons and neutrons within atomic nuclei undergo intense and fleeting encounters driven by the strong force at short distances. These interactions generate close-proximity pairs, a phenomenon known as short-range correlations (SRCs). While the properties of SRCs have been extensively studied in cold nuclear matter, their behavior under extremely hot and dense conditions remains largely unexplored. Here, we incorporate correlated nucleon configurations into relativistic heavy-ion collisions, using the quark-gluon plasma (QGP), a state of matter present microseconds after the Big Bang, as a sensitive diagnostic tool. We find that these correlations induce substantial modifications to event-by-event geometry, which are quantitatively identified through higher-order moments of the transverse profile. Most importantly, we find a surprising linear relation between QGP geometry fluctuations and the SRC scale factor spanning systems from deuteron to lead, which reflects the universal imprinting of SRCs in relativistic heavy-ion collisions. Our findings reveal the emergence of short-range structural effects across vastly different energy scales from low-energy electron scattering to high-energy nuclear collisions.

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arXiv2026

Schrödinger Generator for High-Dimensional Integration and Sampling on Quantum Many-Body States

Integration and sampling in high dimensions are among central challenges in modern science and technology, underlying applications ranging from quantum many-body physics to Bayesian inference and artificial intelligence. Although conventional Monte Carlo methods are formally scalable, their efficiency deteriorates rapidly in the presence of strong correlations or sharp features in high-dimensional configuration space. Here we introduce a new framework, termed the Schr"odinger Generator, for integration and sampling based on the explicit optimization of coordinate transformations. The method decomposes the total Jacobian into two complementary components, including an adaptive map that minimizes estimator variance by learning the marginal structure in each dimension, and a normalizing-flow-based transformation that captures non-factorizable correlations in the target distribution. A final resampling step guarantees unbiased sampling even when the learned transformation is imperfect. We demonstrate stable and scalable performance for nuclear quantum many-body states in dimensions exceeding 600. Short-range correlations among nucleons in finite nucleus are faithfully reproduced. The framework offers a physically transparent approach to high-dimensional stochastic integration and sampling, opening new possibilities for simulations of complex quantum systems.

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arXiv2026

Investigating forward-backward asymmetry in D-meson production and anisotropic flow in p-Pb collisions at the LHC

We investigate the forward--backward asymmetry in the production and elliptic flow of prompt D0 mesons in proton--lead (p--Pb) collisions at$\sqrt{s_{\mathrm{NN}}}=8.16$ TeV using the heavy-flavor improved string-melting version of the AMPT model. The model calculations provide a simultaneous description of nuclear modification factor $R_{\mathrm{pPb}}$ and $v_2$ in forward and backward rapidities. We find that the observed asymmetry arises from the interplay of initial-state cold nuclear matter effects and final-state partonic interactions, with the competition between coalescence and fragmentation playing a critical role in shaping the transverse momentum and rapidity dependence of both observables. This work suggests that a partonic medium is formed in high-multiplicity p-Pb collisions at LHC energies.

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arXiv2026

Ultra-Peripheral Collisions as a Nuclear-Structure Interferometer with Interpretable Multitask Deep Learning

Precise knowledge of nuclear structure is essential across fundamental physics, yet probing these structures is notoriously difficult. To address this challenge, ultra-peripheral collisions (UPCs) provide a femtoscopic tomography for imaging the atomic nucleus. UPCs offer a pristine electromagnetic pathway: coherent vector-meson photoproduction generates patterns of diffraction and two-source interference that directly encode the nuclear spatial density. Turning these patterns into quantitative constraints is, however, a challenging inverse problem, complicated by correlated sensitivities to deformation and neutron skin, phase smearing, and experimental backgrounds. Here we introduce an interpretable Multitask deep-learning framework that maps transverse momentum distributions to multiple nuclear-structure indicators simultaneously and identifies the kinematic regions driving each inference. We demonstrate the approach with coherent $J/ψ$ photoproduction in $^{96}_{40}\text{Zr} + ^{96}_{40}\text{Zr}$ collisions, showing that the learned features separate diffraction-dominated and interference-dominated information and provide analysis-ready observables for future high-luminosity data.

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arXiv2026

Jet quenching and its substructure dependence due to color decoherence

Motivated by color coherence and decoherence effects in the QCD medium, we propose a theoretical framework that combines vacuum-like emissions and medium-induced radiation to study jet quenching and its dependence on jet cone sizes and substructure. In our approach, a jet produced at a hard scale $Q$ first undergoes vacuum-like evolution, as described by the well-established generating-function method in the double logarithmic approximation. These vacuum-like emissions generate subjets at an infrared momentum scale $Q_0$. Each subjet then experiences medium-induced energy loss as described by the BDMPS-Z formalism. By modeling the QCD bulk medium using OSU (2+1)-dimensional viscous hydrodynamics and treating $Q_0$ together with the jet-quenching parameters at the initial proper time of the hydrodynamic evolution as free parameters, our approach provides a very good description of the inclusive jet modification factor $R_{AA}$ for large-radius jets and its dependence on jet substructure in 0-10% PbPb collisions at $\sqrt{s_{NN}} = 5.02~\rm{TeV}$, as measured by the ATLAS experiment.

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arXiv2026

Multiplicity distributions in QCD jets and jet topics

We evaluate the Koba-Nielsen-Olesen (KNO) scaling functions for quark- and gluon-initiated jets by incorporating energy conservation into the Double Logarithmic Approximation (DLA). The resulting modified DLA (MDLA) expressions differ substantially from the DLA predictions and qualitatively align with the recently proposed QCD-inspired expressions, albeit with some quantitative differences. By fixing the two parameters in the MDLA expressions, we show that the inclusive charged-particle multiplicity distributions of the two leading jets in $pp$ collisions at $\sqrt{s} = 13$ TeV, measured by ATLAS over a wide jet $p_T$ range of $0.1$-$2.5$ TeV, are well described within experimental uncertainties and consistent with PYTHIA simulations. This conclusion is further supported by direct comparisons with quark- and gluon-initiated jet distributions extracted via jet topics, though the propagated uncertainties from experimental data remain sizable.

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arXiv2026

Nuclear cluster structure effect in $^{16}$O+$^{16}$O collisions at the top RHIC energy

Using the improved string-melting version of a Multi-Phase Transport model, we investigated the impact of nuclear geometry of $^{16}$O on anisotropic flows in O+O collisions at $\sqrt{s_{\rm NN}} = 200$ GeV. To evaluate the influence of nuclear structure and potential alpha clustering, we implemented four candidate configurations: Woods-Saxon, tetrahedron, square, and Nuclear Lattice Effective Field Theory. Initial-state geometry is quantified via the eccentricity cumulant ratio $\varepsilon_{2}\{4\}/\varepsilon_{2}\{2\}$, which provides a robust and evolution-independent measure sensitive to configuration differences. The model reproduces $v_{2}(p_{\rm T})$ at low $p_{\rm T}$ and $v_{3}(p_{\rm T})$ across the full $p_{\rm T}$ range, with integrated $v_{2}\{2\}$ and $v_{3}\{2\}$ matching the STAR data, demonstrating that transport dynamics captures the essential collectivity in this intermediate-size system. These findings establish a baseline for extending nuclear-structure studies in O+O collisions to other energies and differential observables within a unified transport model framework.

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arXiv2026

Investigation of the shape of uranium in relativistic $^{238}$U+$^{238}$U collisions with nuclear densities from covariant density functional theory

Relativistic $^{238}$U+$^{238}$U collisions have recently been used to extract the quadrupole shape of $^{238}$U. In this study, we employ state-of-the-art three-dimensional (3D) lattice covariant density functional theory (CDFT) with pairing correlations to calculate the density of uranium, including its octupole and hexadecaople deformations, as input for hydrodynamic simulations of these collisions. We find that while the CDFT density well describes elliptic flow, a clear mismatch emerges with transverse-momentum-related observables, indicating a tension in the effective quadrupole deformation. Furthermore, constraining the octupole deformation with triangular flow $v_{3}$ proves to be difficult due to significant sensitivity to the uncertain nuclear structure of the gold reference system. Our results underscore the necessity of realistic nuclear densities for both colliding species and highlight the need for further investigation of correlations related to both flow and transverse momentum to fully characterize nuclear deformation.

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arXiv2026

Identifying $α$-cluster configurations in $^{20}$Ne via ultracentral Ne+Ne Collisions

The initial-state geometry in relativistic heavy-ion collisions provides a novel probe to nuclear cluster structure. For $^{20}$Ne, a novel approach is proposed to distinguish between the cluster configurations (5$α$ versus $α+ ^{16}$O) in order to gain insight into nuclear structure transitions governed by many-body quantum correlations. Through analytical calculations with the microscopic Brink model and event-by-event simulations using the hydrodynamic framework, we establish the normalized symmetric cumulant NSC (3, 2) and the Pearson coefficient $ρ_2 (v_{2}^{2},\ δ[p_{\mathrm{T}}])$ as quantitative discriminators to reveal enhanced cluster degrees of freedom in the ground state of $^{20}$Ne. The ultracentral Ne+Ne collisions at the LHC can experimentally identify these two competing configurations via these flow correlation observables, opening a new paradigm for probing clustering in light nuclei.

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arXiv2025

KNO scaling in quark and gluon jets at the LHC

The Koba-Nielsen-Olesen (KNO) scaling of hadron multiplicity distributions, empirically confirmed to hold approximately in $e^+e^-$ collisions and Deep Inelastic Scattering, has been observed to be violated in hadron-hadron collisions. In this work, we show that the universality of KNO scaling can be extended to hadron-hadron collisions when restricted to QCD jets. We present a comprehensive study of KNO scaling in QCD jets produced in proton-proton collisions at the LHC. Using perturbative QCD calculations in the double logarithmic approximation and PYTHIA simulations, we find that KNO scaling approximately holds for both quark and gluon jets across a broad jet $p_T$ range, from $0.1$ TeV to $2.5$ TeV, at both the parton and hadron levels. Especially, we highlight characteristic differences between the KNO scaling functions of quark and gluon jets, with the quark-jet scaling function lying above that of gluon jets at both low and high multiplicities. This distinction is essential for interpreting inclusive jet data at the LHC. Furthermore, we propose direct experimental tests of KNO scaling in QCD jets at the LHC through quark-gluon discrimination using jet substructure techniques, as demonstrated by applying energy correlation functions to PYTHIA-generated data.

hep-ph↗

arXiv2025

Neural Unfolding of the Chiral Magnetic Effect in Heavy-Ion Collisions

The search for the chiral magnetic effect (CME) in relativistic heavy-ion collisions (HICs) is challenged by significant background contamination. We present a novel deep learning approach based on a U-Net architecture to time-reversely unfold the dynamics of CME-related charge separation, enabling the reconstruction of the physics signal across the entire evolution of HICs. Trained on the events simulated by a multi-phase transport model with different cases of CME settings, our model learns to recover the charge separation based on final-state transverse momentum distributions at either the quark-gloun plasma freeze-out or hadronic freeze-out. This devises a methodological tool for the study of CME and underscores the promise of deep learning approaches in retrieving physics signals in HICs.

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arXiv2025

Effect of transverse momentum conservation and flow on symmetric cumulants $sc_{2,3} \left \{ 4 \right \}$ and $sc_{2,3,4} \left \{ 6 \right \}$

Symmetric cumulants can improve our understanding of the joint probability distribution function $ P\left ( v_{m},v_{n},v_{k}, \dots,Ψ_{m},Ψ_{n},Ψ_{k},\dots \right )$, potentially offering new insights into the nature of the fluctuations of the quark-gluon plasma produced in relativistic heavy-ion collisions. In this work, the four-particle symmetric cumulants $sc_{2,3} \left \{ 4 \right \}$, six-particle symmetric cumulants $sc_{2,3,4} \left \{ 6 \right \}$, and the normalized cumulants $nsc_{2,3} \left \{ 4 \right \}$ and $nsc_{2,3,4} \left \{ 6 \right \}$ originating from transverse momentum conservation, collective flow, and the interplay between the two effects are calculated. Our results on $sc_{2,3} \left \{ 4 \right \}$ are consistent with the ATLAS data using the subevent cumulant method, facilitating a more profound understanding of the origins of the symmetric cumulant in small systems. Our results on $sc_{2,3,4} \left \{ 6 \right \}$ serve as theoretical predictions for future experimental measurements in small systems.

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arXiv2025

Latent Representation Learning in Heavy-Ion Collisions with MaskPoint Transformer

A central challenge in high-energy nuclear physics is to extract informative features from the high-dimensional final-state data of heavy-ion collisions (HIC) in order to enable reliable downstream analyses. Traditional approaches often rely on selected observables, which may miss subtle but physically relevant structures in the data. To address this, we introduce a Transformer-based autoencoder trained with a two-stage paradigm: self-supervised pre-training followed by supervised fine-tuning. The pretrained encoder learns latent representations directly from unlabeled HIC data, providing a compact and information-rich feature space that can be adapted to diverse physics tasks. As a case study, we apply the method to distinguish between large and small collision systems, where it achieves significantly higher classification accuracy than PointNet. Principal component analysis and SHAP interpretation further demonstrate that the autoencoder captures complex nonlinear correlations beyond individual observables, yielding features with strong discriminative and explanatory power. These results establish our two-stage framework as a general and robust foundation for feature learning in HIC, opening the door to more powerful analyses of quark--gluon plasma properties and other emergent phenomena. The implementation is publicly available at https://github.com/Giovanni-Sforza/MaskPoint-AMPT.

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arXiv2025

Probing jet-medium interactions via jet substructure observables in relativistic heavy-ion collisions

We present a comprehensive study of jet substructure observables in $pp$ and PbPb collisions at $\sqrt{s_{NN}} = 5.02$~TeV using a multi-phase transport model. To suppress background contamination, the constituent subtraction method is employed for both PbPb and smeared $pp$ events. The jet splitting momentum fraction ($z_g$) and the groomed jet mass to the ungroomed jet transverse momentum ($M_g / p_{T,\text{jet}}$) are reconstructed using the Soft Drop algorithm with two grooming parameter settings. With $z_\text{cut} = 0.1$ and $β= 0.0$, a slight modification in the $z_g$ distribution is observed in central PbPb collisions, whereas a pronounced enhancement in the high $M_g / p_{T,\text{jet}}$ region is found, particularly at low $p_{T,\text{jet}}$ and in more central events. A detailed analysis of the dynamical evolution stages reveals that this enhancement primarily originates from jet-medium interactions, whereas the contributions from hadronization and hadronic rescatterings are largely mitigated by the grooming procedure. In contrast, under a stronger grooming condition ($z_\text{cut} = 0.5$, $β= 1.5$), no significant changes in $M_g / p_{T,\text{jet}}$ are observed, indicating that the medium-induced modifications are predominantly associated with large-angle scattering.

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