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Ruixiang Chen

Publications and source records attributed to Ruixiang Chen.

8 recordsLinked to original sources

Medium effect on spin alignment of strange and charm vector mesons

Understanding the spin alignment of vector mesons in relativistic heavy-ion collisions requires a nonperturbative description of their spin-dependent in-medium properties. We investigate this problem within a unified four-flavor soft-wall holographic framework that combines an anisotropic Einstein--Maxwell--dilaton background at finite temperature, baryon chemical potential, and angular velocity. Spin alignment is determined from the medium-induced splitting of the spin-resolved vector-current spectral functions through an instantaneous freeze-out prescription. We systematically study the strange and charm vector mesons $K^{*}$, $\phi$, $D^{*}$, $D_s^{*}$, and $J/\psi$ and the dependence of their spin alignment on transverse momentum, rapidity, temperature, baryon chemical potential, and angular velocity. We find that the heavy charm vector mesons $D^{*}$, $D_s^{*}$, and $J/\psi$ mesons exhibit $\rho_{00}>1/3$ at low transverse momentum, whereas the light strange vector mesons $K^{*}$ and $\phi$ exhibit the opposite low-momentum behavior and angular distributions with $\rho_{00}<1/3$. We trace this flavor-dependent separation to the different locations of the vacuum mass shell relative to the thermally shifted longitudinal and transverse spectral peaks. The results qualitatively reproduce several trends observed at low and intermediate transverse momentum. Spin alignment is insensitive to baryon chemical potential and only weakly affected by angular velocity. These results establish an equilibrium holographic baseline for vector-meson spin alignment across flavor sectors and help delineate the regimes in which additional mechanisms, such as nonequilibrium evolution, fluctuations, and hard production, become important.

hep-ph

Robust Spin Logic Enabled by Generalized $\mathrm{SU}(2)$ Symmetry in $p$-Wave Magnets

Unconventional magnets combine the vanishing stray fields of antiferromagnets with the strong spin-splitting of ferromagnets, offering a unique material platform for spintronics. However, a critical challenge in realizing functional spin-logic devices lies in preserving long-range spin coherence against momentum-degrading scattering and gate-induced dephasing. Here, we demonstrate that the intrinsic momentum-dependent exchange field of a three-dimensional $p$-wave magnet can be precisely tuned against gate-induced Rashba spin-orbit coupling to establish a \textit{generalized} $\mathrm{SU}(2)$ spin-rotation symmetry. This emergent conservation law generates a symmetry-protected Persistent Spin Helix (PSH), effectively integrating the high energy scales of 3D bulk magnetic exchange with the macroscopic coherence of symmetry protection. By modeling a synergistic $p$-wave magnetic spin field-effect transistor (spin-FET), we reveal high-visibility Datta-Das conductance oscillations controlled purely by electrical gating. Crucially, our quantum transport simulations confirm that this symmetry-engineered transport regime exhibits exceptional resilience against strong non-magnetic Anderson disorder and geometric variations. These results establish a synergistic paradigm for non-magnetized spintronics, demonstrating how the active integration of spin-orbit coupling and unconventional magnetism can yield disorder-resilient spintronic logic.

cond-mat.mes-hall

Thermal properties of the scalar glueballs from holography

Based on a machine learning holographic QCD model, we construct a systematical framework to investigate the properties of the scalar glueballs continuously from zero temperature to finite temperature. By using both the quasi-normal frequencies and the spectral functions, we extract the pole masses, thermal widths, screening masses and dispersion relation of the scalar glueballs in hot medium. It is shown that the pole masses almost remain the vacuum values at temperatures far below the critical temperature $T_c$ , and then decrease with the increasing of temperature until a temperature lower than $T_c$. This result qualitatively agrees with earlier lattice simulations. While the pole masses increase monotonically above the critical temperature $T_c$, which agrees with recent lattice calculation. Meanwhile, it is shown that the thermal widths increase monotonically with temperature, which also agrees with the near $T_c$ lattice simulations. The screening mass exhibits a similar temperature-dependent behavior to the pole mass, while the dispersion relation increasingly deviates from the relativistic one as the temperature rises. It is interesting to note that we obtain the imaginary corrections in the thermal correlators, which contains both the temperal and spatial information and might be helpful for the four-dimensional calculations. Furthermore, by comparing the quasi-normal modes and the spectral functions, we note that it requires more careful analysis when applying the spectral functions in studying thermal hadrons from holography, since there could be other types of quasi-normal modes which are not related with bound states while they may contribute to the peaks of the spectral functions.

hep-ph

HiM2SAM: Enhancing SAM2 with Hierarchical Motion Estimation and Memory Optimization towards Long-term Tracking

This paper presents enhancements to the SAM2 framework for video object tracking task, addressing challenges such as occlusions, background clutter, and target reappearance. We introduce a hierarchical motion estimation strategy, combining lightweight linear prediction with selective non-linear refinement to improve tracking accuracy without requiring additional training. In addition, we optimize the memory bank by distinguishing long-term and short-term memory frames, enabling more reliable tracking under long-term occlusions and appearance changes. Experimental results show consistent improvements across different model scales. Our method achieves state-of-the-art performance on LaSOT and LaSOText with the large model, achieving 9.6% and 7.2% relative improvements in AUC over the original SAM2, and demonstrates even larger relative gains on smaller models, highlighting the effectiveness of our trainless, low-overhead improvements for boosting long-term tracking performance. The code is available at https://github.com/LouisFinner/HiM2SAM.

cs.CV

Fast inverse lithography based on a model-driven block stacking convolutional neural network

In the realm of lithography, Optical Proximity Correction (OPC) is a crucial resolution enhancement technique that optimizes the transmission function of photomasks on a pixel-based to effectively counter Optical Proximity Effects (OPE). However, conventional pixel-based OPC methods often generate patterns that pose manufacturing challenges, thereby leading to the increased cost in practical scenarios. This paper presents a novel inverse lithographic approach to OPC, employing a model-driven, block stacking deep learning framework that expedites the generation of masks conducive to manufacturing. This method is founded on vector lithography modelling and streamlines the training process by eliminating the requirement for extensive labeled datasets. Furthermore, diversity of mask patterns is enhanced by employing a wave function collapse algorithm, which facilitates the random generation of a multitude of target patterns, therefore significantly expanding the range of mask paradigm. Numerical experiments have substantiated the efficacy of the proposed end-to-end approach, highlighting its superior capability to manage mask complexity within the context of advanced OPC lithography. This advancement is anticipated to enhance the feasibility and economic viability of OPC technology within actual manufacturing environments.

physics.optics

DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Rendering

Realistic human-centric rendering plays a key role in both computer vision and computer graphics. Rapid progress has been made in the algorithm aspect over the years, yet existing human-centric rendering datasets and benchmarks are rather impoverished in terms of diversity, which are crucial for rendering effect. Researchers are usually constrained to explore and evaluate a small set of rendering problems on current datasets, while real-world applications require methods to be robust across different scenarios. In this work, we present DNA-Rendering, a large-scale, high-fidelity repository of human performance data for neural actor rendering. DNA-Rendering presents several alluring attributes. First, our dataset contains over 1500 human subjects, 5000 motion sequences, and 67.5M frames' data volume. Second, we provide rich assets for each subject -- 2D/3D human body keypoints, foreground masks, SMPLX models, cloth/accessory materials, multi-view images, and videos. These assets boost the current method's accuracy on downstream rendering tasks. Third, we construct a professional multi-view system to capture data, which contains 60 synchronous cameras with max 4096 x 3000 resolution, 15 fps speed, and stern camera calibration steps, ensuring high-quality resources for task training and evaluation. Along with the dataset, we provide a large-scale and quantitative benchmark in full-scale, with multiple tasks to evaluate the existing progress of novel view synthesis, novel pose animation synthesis, and novel identity rendering methods. In this manuscript, we describe our DNA-Rendering effort as a revealing of new observations, challenges, and future directions to human-centric rendering. The dataset, code, and benchmarks will be publicly available at https://dna-rendering.github.io/

cs.CV

The hadron spectra and pion form factor in dynamical holographic QCD model with anomalous 5D mass of scalar field

The simplest version of the dynamical holographic QCD model is described by adding the KKSS model action on a dilaton-graviton coupled background, in which the AdS$_5$ metric is deformed by the gluon condensation and further deformed by the chiral condensation. In this framework, both the chiral symmetry breaking and linear confinement can be realized, the light-flavor hadron spectra and the pion form factor were investigated but it was difficult to reconcile the light-flavor hadron spectra and pion form factor. By considering the anomalous 5-dimension mass correction of the scalar field from QCD running coupling, it is found that the light flavor hadron spectra and pion form factor can be described well simultaneously, especially the ground state and lower excitation states of scalar, pseudo scalar and axial vector meson spectra are improved, but the vector meson spectra is not sensitive to the anomalous 5-dimension mass correction of the scalar field.

hep-ph

SNR-adaptive OCT angiography enabled by statistical characterization of intensity and decorrelation with multi-variate time series model

In OCT angiography (OCTA), decorrelation computation has been widely used as a local motion index to identify dynamic flow from static tissues, but its dependence on SNR severely degrades the vascular visibility, particularly in low- SNR regions. To mathematically characterize the decorrelation-SNR dependence of OCT signals, we developed a multi-variate time series (MVTS) model. Based on the model, we derived a universal asymptotic linear relation of decorrelation to inverse SNR (iSNR), with the variance in static and noise regions determined by the average kernel size. Accordingly, with the population distribution of static and noise voxels being explicitly calculated in the iSNR and decorrelation (ID) space, a linear classifier is developed by removing static and noise voxels at all SNR, to generate a SNR-adaptive OCTA, termed as ID-OCTA. Then, flow phantom and human skin experiments were performed to validate the proposed ID-OCTA. Both qualitative and quantitative assessments demonstrated that ID-OCTA offers a superior visibility of blood vessels, particularly in the deep layer. Finally, implications of this work on both system design and hemodynamic quantification are further discussed.

physics.med-ph