arXiv subjects

Jinhui Chen

Publications and source records attributed to Jinhui Chen.

At least 19 recordsLinked to original sources

arXiv2026

Mean-$p_T$ fluctuations in Au+Au collisions at $\sqrt{s_{\rm NN}}=3.0$--$19.6$ GeV within JAM2

Event-by-event mean-$p_T$ fluctuations probe initial-state fluctuations and their evolution through the dynamics of heavy-ion collisions. We study second-order mean-$p_T$ fluctuations in Au+Au collisions at $\sqrt{s_{\rm NN}}=3.0$--$19.6$ GeV using JAM2 in the RQMDv mean-field mode with the MH2 parameterization. The model qualitatively reproduces the measured identified-particle $p_T$ spectra, providing a single-particle baseline for the fluctuation analysis. The scaled fluctuation $k_2$ decreases with increasing $\langle N_{\rm part}\rangle$ and shows broad agreement with the available measurements at 7.7--19.6 GeV, whereas its calculated centrality dependence is stronger than that in the data at 3.0--4.5 GeV. For the combined proton-plus-antiproton sample, the unnormalized correlator $\langle c_2\rangle$ is positive and larger than that for charged pions. The charged-pion correlator $\langle c_2\rangle$ is negative or consistent with zero over most centrality intervals at 3.0 and 3.5 GeV, becomes weakly positive at 4.5 GeV, and remains positive at higher energies. Its energy evolution resembles the change in the reaction-plane elliptic flow, but this comparison does not establish a common microscopic origin. These calculations provide species-dependent predictions within a transport model without an explicit partonic stage. Isolating the contributions of mean fields, rescattering, and spectator interactions requires controlled variations of the transport dynamics.

nucl-ex↗

arXiv2026

Recovering topological information of light by topological learning

The evolution of modern-day communication networks towards optical solutions with enhanced capacity and robustness is driving interest in topological light waves, exploiting their stability against perturbations through a topological invariant, e.g., the skyrmion number. However, detecting the underlying topology remains a computationally intense process even under ideal conditions, becoming intractable after passing through strongly disordered channels, where the degradation into unrecognisable speckle appears to destroy the topology. Here, we propose and demonstrate a topology-enhanced artificial intelligence (AI) approach to recover and classify such apparently lost topological information by computationally leveraging topological invariants in the data across many length scales. By aligning the topological classification of information with the topology of light, our topology-enhanced learning protocol, termed TOPO$^{2}$, achieves highly efficient recognition of the topological states of light, even from speckle, without the need for any prior learning. Our approach outperforms benchmark tests against standard computational algorithms and has the benefit of requiring just a single intensity pattern as the input, facilitating single-shot operation. To demonstrate this, we leverage the skyrmion number as a robust data carrier of images through a disordered channel, using TOPO$^{2}$ to accurately reconstruct the transmitted images. This work synergises topological photonics and topological AI for unravelling hidden topological signatures in light, opening a pathway towards robust communications even in extreme disordered environments.

physics.optics↗

arXiv2026

Response-Based Frequency Stability Assessment under Multi-Scale Disturbances in High-Renewable Power Systems

In high-renewable power systems, active-power disturbances are becoming larger and exhibit increasingly diverse time scales, which complicates frequency stability assessment under unanticipated events. This paper presents a response-based frequency stability assessment method that uses disturbance power, inferred from generator electrical responses, to provide a unified treatment of multi-scale disturbances. Unanticipated disturbances are first classified into short-term and permanent events; permanent disturbances are further divided into step, second-level slope and minute-level slope disturbances. Based on the measured power responses of generator groups, a unified disturbance-power model is constructed to identify the disturbance type online and to quantify disturbance intensity through the disturbance power and its rate of change. Analytical frequency-response models are then derived for each disturbance class. For step disturbances, the maximum tolerable disturbance power is obtained under steady-state and transient frequency deviation constraints, and a safety-margin index is defined. For slope-type disturbances, an improved system frequency response (SFR) model and the rotor motion equation after exhaustion of primary frequency regulation are used to compute the over-limit time of frequency deviation. The proposed response-based assessment method is validated on the CSEE-FS frequency-stability benchmark system, demonstrating its effectiveness and accuracy for quantitative frequency stability assessment in high-renewable power systems.

eess.SY↗

arXiv2026

Booster-based beam recycling for swap-out injection at the High Energy Photon Source

Fourth-generation synchrotron light sources employ ultralow-emittance storage rings with stringent injection requirements. On-axis swap-out injection alleviates the dependence on storage-ring dynamic aperture, but high-charge operation requires an efficient injector architecture capable of producing high-charge replacement bunches. This paper presents the accelerator physics design and performance analysis of a booster-based beam-recycling swap-out injection scheme implemented at the High Energy Photon Source (HEPS). In this approach, the full-energy booster serves as both an injector and a high-energy accumulator. An extracted storage-ring bunch is returned to the booster, merged with a low-charge bunch previously injected from the linac and accelerated to full energy. Following high-energy damping, the merged bunch is reinjected into the original storage-ring bucket. The scheme avoids the need for a dedicated accumulator ring while enabling high-charge bunch replacement. The recycling scheme was commissioned through staged machine studies. Full recycling-chain simulations, commissioning studies, and measured performance analysis are presented. The measured results characterize the recycling operation and quantify the transmission efficiency and performance limitations of the complete recycling loop. These results demonstrate the feasibility of the booster-based beam-recycling architecture and establish its operational basis for high-charge swap-out injection in future fourth-generation synchrotron light sources.

physics.acc-ph↗

arXiv2026

Proton-proton Femtoscopy as a Probe of Short-range Structure in High-Energy O+O Collisions

Short-range nucleon-nucleon correlations are a defining feature of the nuclear many-body wave function, yet they are invisible in the one-body density and therefore inaccessible to observables that measure a nuclear size. We show that proton-proton femtoscopy supplies the missing sub-femtometer sensitivity. In $^{16}$O+$^{16}$O collisions at $\rm \sqrt{s_{NN}}=$ 200 GeV, we compare three nuclear-structure inputs spanning mean-field, low-resolution cluster, and short-range-correlated descriptions. The $p$-$p$ correlation function separates all three, most sharply in peripheral collisions, where the \textit{ab initio} input suppresses the extracted source radius by $\sim5\%$ relative to the mean-field baseline. Under identical conditions $π^{+}$-$π^{+}$ correlations respond an order of magnitude more weakly, and the $C_{pp}/C_{π^{+}π^{+}}$ double ratio retains the full effect, pointing to the short-distance weighting of the $^{1}S_{0}$ pair rather than to an overall rescaling of the source. The signal survives the leading theoretical systematic, the choice of strong-interaction potential, which we quantify explicitly. These results identify $p$-$p$ femtoscopy as a short-distance-resolved probe of light-nucleus structure, complementary to flow observables that constrain only the low-order moments of the initial geometry.

nucl-th↗

arXiv2026

MemTools: A Unified Research Framework for Interoperable Agent Memory

While memory systems are essential for agent architectures, pervasive architectural fragmentation restricts systematic research. Existing implementations typically couple different stages of the memory lifecycle, entangle evaluation logic with specific datasets, and provide limited support for the management of heterogeneous memory types. We introduce MemTools, an interoperability research framework that decouples memory system components from their underlying deployment environments. MemTools standardizes the memory lifecycle through declarative data contracts, enabling the interchangeable assembly of components across different systems. It orthogonally separates benchmark datasets from execution protocols to facilitate controlled assessments. Furthermore, MemTools provides a unified computational interface for coordinating symbolic, neural, and multimodal memory representations within a shared runtime. Empirical evaluations on cross-system component integration, evaluation protocol reconfiguration, and heterogeneous memory coordination demonstrate that MemTools enables systematic isolation and analysis of memory design variables. These findings suggest that MemTools provides a practical and extensible infrastructure for advancing principled research on agent memory.

cs.CL↗

arXiv2026

High-order fluctuations of temperature in hot QCD matter

A new thermodynamic state function is introduced to describe the thermodynamics relevant for the mean transverse momentum fluctuations of charged particles in heavy-ion collisions, which allows us to compute the temperature fluctuations of different orders in hot quantum chromodynamics (QCD) matter for the first time. Consequently, it is found that the temperature fluctuations are suppressed remarkably as the system transitions from the hadron resonance gas (HRG) to the quark-gluon plasma (QGP) with increasing temperature or baryon chemical potential, alongside a negative skewness. This is attributed to the general fact that the heat capacity of QCD matter increases significantly in QGP in comparison to that in HRG. These predictions provide a candidate observable to discover the thermodynamic temperature fluctuations in upcoming heavy-ion collision experiments, which also paves a novel way to study QCD thermodynamics and QCD phase diagram through measurements of the mean transverse momentum fluctuations of charged particles.

hep-ph↗

arXiv2026

Scaling approach to rigid and soft nuclear deformation through flow fluctuations in high-energy nuclear collisions

The nature of octupole deformation, whether static or vibrational, remains an open question in nuclear physics. Here, we propose a scaling approach to probe this ambiguity by triangular flow fluctuations using multi-particle cumulants, $c_{3,\varepsilon}\{4\}$, in relativistic $^{238}$U+$^{238}$U collisions. We demonstrate that both $|c_{3,\varepsilon}\{4\}|$ and the ratio $|c_{3,\varepsilon}\{4\}/c^2_{3,\varepsilon}\{2\}|$ scale linearly with the fourth-order moment of octupole deformation, $\langle β^4_{3,\mathrm{U}} \rangle$. Combined with the known linear relation of $c_{3,\varepsilon}\{2\}$ to $\langle β^2_{3,\mathrm{U}} \rangle$, this new relation provides a direct extraction of both the mean and variance of the octupole deformation fluctuations, finally discriminating between static and dynamic origins. This work establishes a new tool to probe the static and dynamic collective modes in high-energy nuclear collisions, advancing a significant step toward refining the initial conditions of quark-gluon plasma.

nucl-th↗

arXiv2026

Imprints of octupole collectivity in uranium-238 on relativistic heavy-ion flow observables

Some atomic nuclei exhibit enhanced octupole collectivity, reflected in finite reflection-asymmetric multipole correlations rather than necessarily in a rigid static pear-shaped ground state. Low-energy studies indicate finite octupole strength in uranium-238, commonly interpreted as soft or vibrational in nature, in addition to its large prolate quadrupole collectivity~\cite{MCGOWAN1994569,KIBEDI:2002wxc}, in addition to its large prolate quadrupole collectivity. Here we investigate how such octupole correlations can be encoded in the initial geometry of relativistic heavy-ion collisions and mapped to final-state flow observables. Using state-of-the-art hydrodynamic calculations, we demonstrate quantitative sensitivity to octupole-induced features encoded in the initial-state geometry and suggest a modest octupole collectivity in uranium-238, confirmed by the latest high-energy experimental measurements~\cite{STAR:2025elk}. These findings provide as a complementary probe of odd-order nuclear collectivity and help constrain quark-gluon plasma initial conditions.

nucl-th↗

arXiv2026

Nonflow Subtraction Beyond Two-Particle Correlations

Establishing collective flow in small collision systems is crucial for pinning down the minimum conditions for quark-gluon plasma (QGP) formation. In two-particle correlations, nonflow has been subtracted with good control, pushing the reach of flow measurements down to very small particle multiplicities $N$. However, the multi-particle nature of collectivity has not been established in the same $N$ regime, because the residual nonflow surviving the subevent procedure in multi-particle cumulants has never been quantified. We develop a general nonflow subtraction framework for $m$-particle cumulants, built around the approximate $1/N^{m-1}$ scaling of nonflow in the independent-source picture. Correlators containing $v_1$ serve as clean nonflow estimators, since the $p_{\rm T}$-integrated dipolar flow nearly vanishes. Using \HIJING{} as a controlled nonflow-only environment, we test the subtraction for three target observables ($\langle v_2^2\rangle$, $\langle v_2^2δp_{\rm T}\rangle$, and $c_2\{4\}$) in O+O and $d$+Au at $\sqrt{s_{\rm NN}} = 5.36$ TeV and 200 GeV. Most of the nonflow is removed, with residual fractions typically within 20--30% when converted to the two-particle level, though the best estimator differs across the three targets. We identify a multiplicity-reweighting correction, previously overlooked in two-particle correlations, that explains the long-standing undersubtraction of the naive $1/N$-scaling method; its impact grows as a power of the correlator order. The framework gives a systematic route to nonflow subtraction beyond two-particle correlations, broadening the class of multi-particle observables accessible to the small-system flow program.

nucl-th↗

arXiv2026

Global Cross-Modal Geo-Localization: A Million-Scale Dataset and a Physical Consistency Learning Framework

Cross-modal Geo-localization (CMGL) matches ground-level text descriptions with geo-tagged aerial imagery, which is crucial for pedestrian navigation and emergency response. However, existing studies are constrained by narrow geographic coverage and simplistic scene diversity, failing to reflect the immense spatial heterogeneity of global architectural styles and topographic features. To bridge this gap and facilitate universal positioning, we introduce CORE, the first million-scale dataset dedicated to global CMGL. CORE comprises 1,034,786 cross-view images sampled from 225 distinct geographic regions across six continents, offering an unprecedented variety of perspectives in varying environmental conditions and urban layouts. We leverage the zero-shot reasoning of Large Vision-Language Models (LVLMs) to synthesize high-quality scene descriptions rich in discriminative cues. Furthermore, we propose a physical-law-aware network (PLANET) for cross-modal geo-localization. PLANET introduces a novel contrastive learning paradigm to guide textual representations in capturing the intrinsic physical signatures of satellite imagery. Extensive experiments across varied geographic regions demonstrate that PLANET significantly outperforms state-of-the-art methods, establishing a new benchmark for robust, global-scale geo-localization. The dataset and source code will be released at https://github.com/YtH0823/CORE.

cs.CV↗

arXiv2026

Hyperon-Nucleon Spectrometer

Chirality lies at the heart of low-energy QCD, governing the symmetry structure that shapes hadron masses and strong interaction dynamics. Among the most compelling open questions tied to chiral dynamics and spontaneous chiral symmetry breaking is the longstanding $Λ$ polarization puzzle, in which $Λ$ hyperons produced in unpolarized hadronic collisions exhibit a surprisingly large transverse polarization that remains theoretically unexplained. This whitepaper presents the proposal for the Hyperon-Nucleon Spectrometer (H-NS) at the High-Intensity heavy-ion Accelerator Facility (HIAF). Leveraging the high energy and high intensity of HIAF's proton and heavy-ion beams, the H-NS experiment will perform systematic studies of hyperon polarization phenomena and their underlying mechanisms in proton-proton ($pp$), proton-nucleus ($pA$), and nucleus-nucleus ($AA$) collisions in the fixed target mode. A wide-range beam energy scan, including proton beams from 3 GeV up to 9.3 GeV (HIAF) and up to 32 GeV (upgraded HIAF), will be conducted to examine the dependence of polarization on collision energy. The spectrometer is designed with specialized detectors capable of high-precision reconstruction of final-state baryon polarizations. Among its many interesting and important measurements, H-NS will simultaneously measure hyperon and proton spin observables to explore the polarization mechanism in hadronic interactions and the spin structure of baryons. Furthermore, the use of $pA$ and $AA$ collisions will enable detailed investigations of cold and hot nuclear matter effects on spin polarization. Its physics program and detector development will significantly benefit the future Electron-ion Collider in China.

physics.ins-det↗

arXiv2026

Probing the neutron-skin thickness through $J/ψ$ photoproduction in ultra-peripheral collisions

We study the impact of neutron-skin thickness on $J/ψ$ photoproduction in ultra-peripheral $^{208}\mathrm{Pb}+{}^{208}\mathrm{Pb}$ collisions. Within the Color Glass Condensate framework, we calculate coherent and incoherent cross sections and examine their dependence on the momentum transfer $|t|$ for different neutron-skin thicknesses. We find a clear imprint of the neutron skin on the $|t|$ spectra: a larger neutron skin leads to a smoother and more extended color-density profile, suppressing the coherent cross section at large $|t|$ while enhancing the incoherent cross section through increased event-by-event configurational fluctuations in the nuclear periphery. We further show that the ratio of incoherent to coherent integrated cross sections provides a particularly sensitive and robust observable, with reduced theoretical uncertainties. These results establish diffractive vector-meson photoproduction in ultra-peripheral collisions as a powerful tomographic tool to constrain the neutron-skin thickness and the transverse gluon distribution at the LHC and future Electron-Ion Colliders.

nucl-th↗

arXiv2026

Isolation of photon-nuclear interaction backgrounds in the search for the chiral magnetic effect in relativistic heavy-ion collisions

The chiral magnetic effect (CME) in relativistic heavy-ion collisions originates from a chirality imbalance among quarks within metastable QCD vacuum domains and may be linked to $CP$ violation, which is believed to play a crucial role in the matter-antimatter asymmetry of the universe. Over the past two decades, extensive experimental efforts at RHIC and the LHC have been devoted to the search for evidence of the CME. Recent advances have greatly improved our understanding of background contributions that can mimic CME-like signals. In particular, analyses utilizing techniques designed to suppress flow-related backgrounds indicate that the CME signal at RHIC, if present, is small. To further investigate potential background sources, particularly those associated with strong electromagnetic fields, we estimate the contribution from coherent photon-nuclear interactions. These interactions are driven by intense electromagnetic fields produced in ultrarelativistic heavy-ion collisions, with cross sections that scale with the field strength. Notably, the polarization of the incident photons is aligned with the electric field, which is oriented along the impact parameter direction and perpendicular to the magnetic field. Consequently, such processes can generate charge-dependent correlations that mimic key features of the CME signal, yet originate from different physics mechanisms and are distinct from flow-induced backgrounds. In this study, we quantitatively assess the influence of these coherent photon-nuclear interactions on the precision measurement of the CME, aiming to improve the separation of the genuine CME signal from these background contributions.

hep-ph↗

arXiv2026

The High Level Trigger and Express Data Production at STAR

To meet the demands of the Beam Energy Scan phase-II (BES-II) program, the STAR experiment at RHIC developed a dual real-time framework consisting of a High Level Trigger (HLT) and an Express Data Production system (xProduction). The HLT operates online within the Data Acquisition (DAQ) chain on a multicore CPU cluster, with optional acceleration using Xeon Phi coprocessors. It employs parallelized algorithms, such as the Cellular Automaton track finder, for fast tracking, vertexing, and event filtering, enabling real-time event selection and detector monitoring. In parallel, xProduction runs independently of the DAQ loop and performs near offline-quality calibration and reconstruction within hours. Using the express data stream, enhanced by HLT selections, and the STAR calibration framework, it enables early physics analysis and provides collaboration-wide access to analysis-ready datasets. Together, HLT and xProduction form a complementary system combining real-time selection with rapid high-quality reconstruction. This framework has enabled prompt reconstruction of the ${}^5_Λ\mathrm{He}$ hypernucleus and efficient processing of large datasets, demonstrating scalability for future high-luminosity experiments.

physics.ins-det↗

arXiv2026

Disentangling nuclear structure through multiparticle azimuthal correlations in high-energy isobar collisions

Event-by-event fluctuations in the amplitudes of flow harmonics offer a novel approach to probing the initial-state characteristics in heavy-ion collisions. In this study, we conduct a systematic investigation of correlations among various flow harmonics utilizing multiparticle cumulants in $^{96}$Ru+$^{96}$Ru and $^{96}$Zr+$^{96}$Zr collisions at $\sqrtsnn =$ 200 GeV within the framework of a multiphase transport model. Correlated nuclear density distributions specific to the isobar systems are incorporated to evaluate the sensitivity of selected observables to variations in nuclear deformation and neutron skin thickness. The analysis reveals that multiparticle azimuthal correlations are responsive to these nuclear structure features, predominantly in the most central collision events. Furthermore, the examined correlations exhibit shallow dependence on the assumed shear viscosity values. These findings provide a quantitative evaluation of the extent to which multiparticle flow observables can discern nuclear structure effects in isobar collisions and offer valuable guidance for future detailed dynamical investigations and experimental measurements.

nucl-th↗

arXiv2026

Selected highlights from STAR experiment

In this paper, we review recent highlights in heavy-ion collisions and proton-proton collisions at top energies from STAR experiment at the Relativistic Heavy Ion Collider (RHIC) with key contributions from Chinese groups, including the Quark-Gluon Plasma (QGP) bulk properties, electromagnetic probes, heavy flavor and jets, antimatter hyper-nucleus, nuclear structure, global polarization, and nucleon spin structure. These data serve as important ingredients in the physics of Quantum Chromodynamics (QCD).

nucl-ex↗

arXiv2025

DeepGESI: A Non-Intrusive Objective Evaluation Model for Predicting Speech Intelligibility in Hearing-Impaired Listeners

Speech intelligibility assessment is essential for many speech-related applications. However, most objective intelligibility metrics are intrusive, as they require clean reference speech in addition to the degraded or processed signal for evaluation. Furthermore, existing metrics such as STOI are primarily designed for normal hearing listeners, and their predictive accuracy for hearing impaired speech intelligibility remains limited. On the other hand, the GESI (Gammachirp Envelope Similarity Index) can be used to estimate intelligibility for hearing-impaired listeners, but it is also intrusive, as it depends on reference signals. This requirement limits its applicability in real-world scenarios. To overcome this limitation, this study proposes DeepGESI, a non-intrusive deep learning-based model capable of accurately and efficiently predicting the speech intelligibility of hearing-impaired listeners without requiring any clean reference speech. Experimental results demonstrate that, under the test conditions of the 2nd Clarity Prediction Challenge(CPC2) dataset, the GESI scores predicted by DeepGESI exhibit a strong correlation with the actual GESI scores. In addition, the proposed model achieves a substantially faster prediction speed compared to conventional methods.

cs.SD↗