arXiv subjects

Jing Wang

Publications and source records attributed to Jing Wang.

At least 37 records · Page 2Linked to original sources

arXiv2026

Fermion-fermion interaction driven phase transitions in rhombohedral trilayer graphene

The effects of short-range fermion-fermion interactions on the low-energy properties of rhombohedral trilayer graphene are comprehensively investigated using the momentum-shell renormalization group method. We take into account all one-loop corrections and establish the energy-dependent coupled evolutions of independent fermionic couplings that carry the physical information stemming from the interplay of various fermion-fermion interactions. With detailed numerical analysis, we observe that the ferocious competition among all fermion-fermion interactions can drive fermionic couplings to four distinct fixed points, dubbed $\textrm{FP}_{1}$, $\textrm{FP}_{2}$, $\textrm{FP}_{3}$, and $\textrm{FP}_{4}$, in the interaction-parameter space. These fixed points primarily dictate the fate of the system in the low-energy regime and are always associated with some instabilities characterized by specific symmetry breakings, leading to certain phase transitions. To determine the favorable states arising from the potential phase transitions, we introduce a number of fermion-bilinear source terms to characterize the underlying candidate states. By comparing their related susceptibilities, we find that the dominant states correspond to spin-singlet superconductivity, spin-triplet pair-density-waves, and spin-triplet superconductivity for fixed points $\textrm{FP}_{1,3}$, $\textrm{FP}_{2}$, and $\textrm{FP}_{4}$, respectively. These provide valuable insights into the low-energy properties of rhombohedral trilayer graphene and analogous materials.

cond-mat.str-el↗

arXiv2026

Codes and designs in multivariate $Q$-polynomial association schemes

We generalize the fundamental bounds of Delsarte thesis (1973) on codes of given degree and designs of given strength in the new setting of Bannai et al. (2025). We assume the scheme is weakly metric in the sense of (Solé, 1989). We give upper bounds on the size of codes of given degree, and also on the size of codes with a given number of pairwise distances. Codes meeting these bounds are characterized by the identification of suitable annihilators with the degree (resp. distance) Wilson polynomial. We give two analogues of the Rao bound on the size of designs with given strength. Designs meeting that bound we call degree tight designs or distance tight design depending on the bound met. In both cases, the existence of a tight design implies a Lloyd-like condition on a suitable analogue of the Wilson polynomial. Applications to the Lee distance, mixed level orthogonal arrays, ordered orthogonal arrays, and more are given. The formal duality between codes and designs, connecting perfect codes and tight designs, is made concrete in self-dual translation schemes.

math.CO↗

arXiv2026

The Population of Type~1 Active Galactic Nuclei in Dark Energy Spectroscopic Instrument. I. Profile-dependent Measurements of the Low-redshift Sample

We present a spectral analysis of a large sample of low-redshift type 1 active galactic nuclei (AGNs) selected from the first data release of the Dark Energy Spectroscopic Instrument (DESI DR1). For objects at $z\le0.9$, we perform spectral fitting and ML-assisted refinement, yielding 114,754 type 1 AGNs. We use two fitting schemes that differ only in the broad-line model: the broad Balmer components are fitted with either a Lorentzian function or a sum of Gaussians. The continuum and [O III] luminosity measurements agree closely between the two schemes, whereas the Gaussians scheme generally yields larger broad-H$β$ full width at half maximum (FWHM) values, larger virial black hole masses, and lower accretion rates. The adopted broad-Balmer profile also changes the decomposition of narrow Balmer emission. Specifically, the anti-correlation between [O III]$\lambda5007$/narrow H$β$ and accretion rate is stronger under the Gaussians scheme with a Spearman rank correlation coefficient $r_{\rm s}=-0.412$, than under the Lorentzian scheme with $r_{\rm s}=-0.206$; the same tendency is observed in the narrow-line Seyfert 1 galaxies (NLS1s) subset ($r_{\rm s}=-0.435$ and $-0.259$ for the Gaussians and Lorentzian schemes, respectively), suggesting that the Gaussians scheme may provide a more self-consistent separation of the broad and narrow H$β$ components. Moreover, the consistent correlations recovered under both profile prescriptions favor a continuous type 1 accretion-state sequence, with NLS1s occupying its high-accretion end rather than constituting a distinct population.

astro-ph.GA↗

arXiv2026

Spectral-control-assisted Kerr-lens mode-locking in a Tm:Y2O3 ceramic laser

We report a soft-aperture Kerr-lens mode-locked Tm:Y2O3 ceramic laser stabilized by suppressing wavelength competition under high population-inversion conditions. The laser delivers an average output power of 0.5 W with a pulse duration of 112 fs at a repetition rate of 90 MHz and a central wavelength of 2.08 um. Further optimization for shorter pulses yields a pulse duration of 107 fs, through with a reduced output power of 0.22 W. These results demonstrate that spectral-control is an effective approach for achieving stable mode-locking in such laser with strong spectral competition.

physics.optics↗

arXiv2026

Beyond Action Entropy: Quotient-Space Exploration for Genome-Scale Metabolic Model Repair

Repairing scientific models from functional observations differs fundamentally from supervised prediction: feedback may certify a solution without revealing which structural correction is responsible. We study this setting for genome-scale metabolic model (GEM) repair, where multiple reaction edits can explain the same phenotypes and many apparently distinct edits correspond to the same biological mechanism. This many-to-one structure creates a hidden failure mode for conventional exploration: diversity in the output space need not translate into diversity of scientific hypotheses. We introduce QuotientPO, which collapses equivalent repairs into canonical mechanisms and optimizes exploration directly over the resulting quotient space. To make quotient exploration informative under finite rollouts, we derive a kernelized Rényi estimator that resolves graded crowding among distinct repair cores beyond coarse exact-match counts. On 2,212 held-out GEMs, QuotientPO improves Success@32 from 17.93% to 20.10% (+12.1% relative) while consistently increasing distinct successful-core discovery under the same sampling budget. These results establish quotient-space exploration as a principled approach to mechanism-level discovery under verifier-induced equivalence.

cs.LG↗

arXiv2026

Pressure-induced double-dome superconductivity in doped kagome metal Cs(V0.86Ta0.14)3Sb5 without charge density wave

The vanadium-based kagome superconductor CsV$_3$Sb$_5$ exhibits an intricate interplay between charge density wave (CDW) and superconductivity (SC). Substituting Ta for V will suppress the CDW order and enhance superconductivity. Here, we report a high-pressure study up to 48 GPa on Ta-doped Cs(V$_{0.86}$Ta$_{0.14}$)$_3$Sb$_5$ with enhanced $T_\mathrm{c}$ around 5.29 K and without CDW order. At low pressures, unlike the characteristic $``$M-shaped" temperature-pressure phase diagram of the pristine CsV$_3$Sb$_5$, the Ta-doped compound exhibits a distinct non-monotonic evolution. Initially, $T_\mathrm{c}$ drops slightly from 5.29 K at ambient pressure to 4.90 K at 0.33 GPa, before increasing to a maximum of 5.70 K at 0.61 GPa. Upon further compression, $T_\mathrm{c}$ decreases continuously to 0.98 K at 12.3 GPa. At higher pressures, $T_\mathrm{c}$ rises again, reaching 4.46 K at 47.7 GPa. This evolution of $T_\mathrm{c}$ establishes two superconducting domes under pressure, which are similar to those in CsV$_3$Sb$_5$. Our results demonstrate that pressure-induced double-dome superconductivity is intrinsic to these V-based kagome superconductors, even in the absence of long-range CDW order.

cond-mat.supr-con↗

arXiv2026

Interaction-driven quantum criticality in two-dimensional quadratic band crossing semimetals with time-reversal symmetry breaking

We present a systematic investigation of all sixteen marginally relevant fermion-fermion interactions in two-dimensional time-reversal symmetry-breaking kagomé semimetals hosting a quadratic band crossing point. Employing a momentum-shell renormalization group approach that treats every interaction on equal footing, we derive energy-dependent flow equations that capture the hierarchical evolutions of interaction parameters. Our analysis begins by tracking the energy-dependent flows of fermion-fermion interactions. The interaction couplings go towards divergence at a critical energy scale, signaling quantum critical behavior. Such behavior is characterized by a certain fixed point (FP) whose characteristics depends intimately on structural parameters $d_{0,1,2,3}$ that cluster the microscopic model into rotationally symmetric and asymmetric cases. Then, we identify two stable FPs in the rotationally symmetric and nine additional FPs in asymmetric case dubbed FP$_{1-10}$. Their boundary conditions are approximately demarcated and established by linear and plane fitting techniques in the structural parameter space. Furthermore, we examine distinct interaction-driven instabilities nearby these FPs by incorporating the relevant external source terms and computing their susceptibilities. It indicates that the charge density wave and superconductivity become dominant at FP$_{2,4,5,6,8}$ and FP$_{1,9,10}$, while the $x$-current and bond density prevail at FP$_3$ and FP$_7$, respectively. In addition to these leading states, several underlying subordinate instabilities are presented as well. These results would be helpful to further study the low-energy critical behavior in 2D kagomé QBCP and related materials.

cond-mat.str-el↗

arXiv2026

MambaDSF: Multi-Scale SSM with Dilated Feature Fusion for Sonar Small Target Detection

Sonar imaging is the primary modality for underwater target detection, yet small targets remain difficult to detect due to insufficient pixel coverage, low acoustic contrast, and scale ambiguity across imaging ranges. CNN-based detectors extract local features efficiently but cannot suppress noise-induced false alarms without global acoustic context. Transformer-based methods capture long-range dependencies at quadratic computational cost. Existing Mamba-based vision models offer efficient linear-cost scanning but lack multi-scale semantic alignment across pyramid levels, multi-receptive-field fusion, and small-target-aware training supervision needed for reliable sonar detection. This letter proposes Mamba Dilated-Scale Fusion (MambaDSF), a hybrid framework addressing these limitations through three contributions: a Mamba Enhanced Feature Pyramid (MambaEFP) backbone that jointly captures local echo cues and global acoustic context at linear complexity; a Dilate Fusion Mamba (DFMamba) encoder that enforces multi-scale feature alignment across pyramid levels; and Scale-Adaptive Weighted IoU (SA-WIoU) and Cross-Scale Coherence (CSC) losses that stabilize small-target training. MambaDSF achieves 91.5% mAP50 on the UATD forward-looking sonar benchmark with 28.7 million parameters, surpassing all compared detectors. On a small-target subset the gain reached +2.2 percentage points, and cross-domain evaluation on FLS and MD-FLS confirms the generalization of the proposed architecture. The codes are publicly available at https://github.com/IDontKnowAAA/MambaDSF.

cs.CV↗

arXiv2026

D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation

Dataset distillation (DD) aims to compress large-scale datasets into compact synthetic sets while preserving training efficacy. However, existing studies mainly focus on image classification, leaving dense prediction tasks such as semantic segmentation largely underexplored. In this work, we identify three key challenges for segmentation DD: (i) long-tailed class imbalance, (ii) the need for strict pixel-wise alignment between images and dense labels, and (iii) the high computational cost of optimizing high-resolution data with complex models. To address these challenges, we propose D3S2, a Diffusion-guided Dataset Distillation framework for Semantic Segmentation. Our method adopts a two-stage design. In Class-Balanced Mask Selection, we construct a representative mask set via a greedy strategy that prioritizes underrepresented classes. In Diffusion-Guided Image Synthesis, we employ a pretrained layout-to-image diffusion model to generate images conditioned on the selected masks, naturally ensuring spatial alignment. To further enhance the training utility of synthesized data, we introduce guided diffusion sampling with two complementary objectives: a segmentation-consistency loss for pixel-level alignment, and a class-wise feature matching loss for aligning per-class feature statistics across layers. Extensive experiments demonstrate the superiority of D3S2. Notably, at an extremely compression rate of 1%, our method achieves 24.99% and 35.49% mIoU on ADE20K and COCO-Stuff with Mask2Former (Swin-S), outperforming random selection by 9.34% and 5.70%, respectively. Our code is available at https://github.com/zwj084/D3S2.

cs.CV↗

arXiv2026

Large time behavior of Lévy processes and their nonlocal Schrödinger semigroups

We study the large time asymptotics of the Feynman-Kac semigroups of the symmetric Lévy process on unbounded open sets. Our main result proves the exact exponential asymptotic decay rate for the survival probability given in terms of the bottom of the spectrum of the associated nonlocal Schrödinger operator. We also prove quantitative upper bounds with an explicit polynomial correction. The proof is probabilistic and is done by decomposing the Lévy process into a finite-range jump process collecting the small jumps and an independent compound Poisson process describing the large jumps. Our approach gives a direct link between the spectral properties of nonlocal Schrödinger operators and pointwise decay of survival probabilities, which was previously unknown for jump processes.

math.PR↗

arXiv2026

SVOM/C-GFT: Instrumentation and Performances on the SVOM Alerts

The Chinese Ground Follow-up Telescope (C-GFT) is an optical facility upgraded to support the Space Variable Objects Monitor mission (\textit{SVOM}). Located at the Jilin Observation Station, it is capable of rapidly identifying and monitoring the optical counterparts of Gamma-Ray Bursts (GRBs). The 1.2-m telescope is equipped with two switchable focal-plane instruments: the prime-focus wide-field LATIOS camera and the Cassegrain-focus three-channel CATCH camera. In this paper, we present a system overview, including the observatory, the telescope, the instrumentation, the automated operational framework managed by the Operations Center, and the data processing pipelines. We also report the performance results obtained during over one year of \textit{SVOM}'s post-launch operations. The results demonstrate that the system meets its design specifications and delivers robust observational and operational performance.

astro-ph.IM↗

arXiv2026

Symmetry-enabled tunable square-lattice Hubbard models in $Γ$-valley moiré bilayers

Square-lattice moiré systems provide a promising route for quantum simulation of Hubbard physics, yet electrically tunable realizations of the hopping ratio $t'/t$ have so far been limited to specific valley configurations. A natural question is whether the same tunability can be extended to the more broadly occurring $Γ$-valley systems. Here we identify a symmetry-controlled route for realizing electrically tunable square-lattice Hubbard models in $Γ$-valley twisted homobilayers. At small twist angles, an emergent layer-exchange symmetry separates the low-energy states into flat bands localized on two nested square sublattices, suppressing inter-sublattice hopping. An interlayer displacement field breaks this symmetry and induces controllable hybridization between the sublattices, enabling continuous tuning of the $t'/t$ ratio over a wide range while preserving an effective single-band description. We further establish a formal correspondence between $Γ$- and M-valley moiré systems, revealing them as different symmetry limits of a unified framework for tunable square-lattice Hubbard models. Our results uncover a general symmetry principle underlying displacement-field tunability and extend electrically controllable square-lattice Hubbard physics to a broad family of $Γ$-valley materials.

cond-mat.mes-hall↗

arXiv2026

TReVS: Integrating Textual Relevance and Visual Saliency for Efficient Vision-Language Model Token Pruning

Vision-Language Models (VLMs) excel at visual understanding and reasoning but often incur substantial inference costs due to the large number of visual tokens. Recent visual token pruning methods increasingly follow a two-stage paradigm: they first remove visually redundant tokens after the vision encoder and then discard tokens irrelevant to the textual query within the Large Language Model (LLM). However, since the first stage typically relies solely on vision-encoder saliency, it may prematurely eliminate query-relevant tokens, depriving the subsequent text-guided stage of critical visual evidence. Our empirical analysis shows that incorporating query guidance into first-stage pruning better preserves task-relevant evidence and consistently improves performance over vision-only saliency-based pruning. We further find that high-variance attention heads are more sensitive to the textual query and yield more discriminative text-to-vision attention signals for second-stage pruning. Motivated by these findings, we propose TReVS, a training-free framework that combines textual relevance with vision-encoder saliency for pre-LLM pruning and leverages high-variance attention heads to remove task-irrelevant tokens at shallow-to-intermediate layers of the LLM. On LLaVA-1.5-7B, TReVS retains 92.8% of the unpruned baseline performance while pruning 94.4% of visual tokens, outperforming prior state-of-the-art methods.

cs.CV↗

arXiv2026

Bridging Body and Brain: Gene-Driven Morphology--Control Co-Design

Morphology--control co-design jointly optimizes an agent's body structure and control policy as an integrated embodied system. However, existing methods typically model morphology design and control with separate networks coupled only indirectly through a shared task objective, limiting explicit high-level coordination. Inspired by natural genes that coordinate biological development, we introduce \textbf{Morphogene}, a compact latent blueprint that bridges an agent's body and brain. Through AdaConcat, Morphogene jointly conditions morphology and control generation at the limb level, allowing its variations to induce coordinated changes in both components. Building on this representation, we propose \textbf{GeCode}, which formulates co-design as exploration in the compact Morphogene space. Each Morphogene anchors a local design region in which nearby body--brain designs are explored, while performance-guided updates move these anchors toward promising regions for more efficient exploration of the broader design space. This process combines local refinement with global exploration while preserving body--brain compatibility. Extensive experiments across diverse 2D and 3D co-design tasks demonstrate that GeCode consistently outperforms existing state-of-the-art methods, achieving substantially faster convergence and higher final performance.

cs.LG↗

arXiv2026

HBF-Sim: An Extensible HBF Simulator for Large-scale GPU Memory Systems

High-bandwidth flash (HBF) is introduced to address the memory wall, which can co-package a dense NAND stack with the GPU, targeting the performance gap between near-accelerator bandwidth and flash density. HBF, however, is neither a large HBM nor a fast NVMe SSD. Its usable bandwidth depends on how GPU cache-line requests map onto NAND pages, how concurrency spreads across channel-affine die sets, and how media management interacts with the GPU memory pipeline. To our knowledge, existing GPU, SSD, or HBF simulators cannot faithfully model this behavior. We present HBF-Sim, an extensible, reusable, and faithful HBF simulator integrated with simulated GPUs. It closes the loop between GPU issue limits, device queuing, and NAND behavior in one end-to-end request path. HBF-Sim separates a GPU-HBF interaction controller from page-based parallel stack storage, and it models the full GPU-HBF request path. It provides an MSHR-based address mapping table that merges cache-line requests into page-based operations, as well as a page-based multi-stack flash manager for highly parallel reads and writes. Validation tests and device-level microbenchmarks expose performance bottlenecks caused by limited channel distribution and resource conflicts, offering concrete guidance for next-generation HBF architectures.

cs.AR↗

arXiv2026

Towards Practical Compression of 3D Gaussian Splatting

3D Gaussian Splatting (3DGS) enables high-quality novel-view synthesis but requires substantial storage. Existing compression methods often rely on spatial context modeling over irregular 3D representations, increasing the complexity of training and coding. Meanwhile, floating-point context inference can introduce numerical inconsistencies across platforms, causing entropy-decoding failures. To address these practical challenges, we propose COSA-GS, which constructs context without spatial aggregation through anchor-wise causal factorization. Specifically, we use geometry context derived from each anchor's coordinates to model a compact learnable anchor latent. The anchor latent is then fused with the geometry context to form an anchor context for attribute coding. The resulting context model features a simple architecture composed solely of linear transformations and activations. We train COSA-GS using rate--distortion optimization with adaptive Gaussian pruning. Further, we develop quantization-aware training and integer inference for the context model to achieve bit-exact consistency of entropy-decoded symbols across platforms. Experiments demonstrate that COSA-GS achieves state-of-the-art compression performance while retaining fast and consistent cross-platform decoding, providing a simple yet effective framework for practical 3DGS compression. Code is available at https://github.com/pengpeng-yu/COSA-GS.

cs.CV↗

arXiv2026

Galaxy evolution in the post-merger regime. V - Atomic gas evolution traced by ALFALFA stacks

(Abridged) In this work, we investigate the role of atomic hydrogen (HI) gas in the galaxy merger lifecycle. In order to both identify galaxies in mergers, as well as to predict their time since coalescence, we present an extension of the MUlti Model Merger Identifier (MUMMI) machine vision pipeline applied to Dark Energy Camera Legacy Survey (DECaLS) imaging. The new MUMMI-DECaLS catalog contains 19,951 post-mergers, of which 14,638 have robust time post-merger (T_PM) predictions. The MUMMI-DECaLS post-merger galaxy catalog is cross-matched with the Arecibo Legacy Fast ALFA (ALFALFA) survey. For the 752 post-mergers thus identified, as well as a matched control sample, we produce median spectral stacks of 21~cm emission, finding that the post-mergers are HI deficient by 0.11 dex compared with non-interacting galaxies. When divided into T_PM bins we find that the HI deficit (or excess) is strongly dependent on both the time since coalescence and whether the galaxies are star-forming or quenched. Star-forming post-mergers in particular show a strong HI evolution with T_PM, exhibiting a 0.1 dex MHI excess immediately after coalescence, a 0.3 dex MHI deficit at 0.16 < T_PM < 0.96 Gyr and normal gas masses by ~ 1.5 Gyr after coalescence. On the other hand, despite being matched in star formation rate, stellar mass and redshift, quenched post-mergers are HI deficient at both short and long post-coalescence times. Nonetheless, a significant mass of HI (>10^9 M_sun) remains even in these late-time quenched post-mergers, representing a resource which could potentially re-fuel star formation in the future. Our results demonstrate the complexity of quantifying the HI behaviour in mergers, which depends not only on timing, but also star-forming status, which can complicate comparisons between different studies and samples.

astro-ph.GA↗

arXiv2026

Mrk 382: A Narrow-line Seyfert 1 Galaxy with Recurrent X-ray State Transitions

We report recurrent X-ray state transitions in the nearby narrow-line Seyfert~1 galaxy Mrk~382 using multi-epoch observations from \textit{Swift}, \textit{Chandra}, \textit{XMM-Newton}, and eROSITA, together with archival ultraviolet, optical, and infrared data. The 0.3--2 keV flux varies by nearly an order of magnitude over the past $\sim15$ yr, with multiple transitions between bright and faint states. The source brightened by a factor of $\sim10$ between the 2010 \textit{Chandra} observation and the 2011 \textit{XMM-Newton} high state, then declined by $\sim6$--7 to a low state in 2019, followed by renewed brightening in recent \textit{Swift} monitoring. The X-ray spectrum shows strong state-dependent evolution, changing from a steep high-state continuum ($Γ=2.32\pm0.04$) to a much harder low-state spectrum ($Γ=1.39\pm0.06$). The low-state spectrum also exhibits a narrow Fe K$α$ line with an equivalent width of $\sim330$ eV. Reflection modeling indicates that the low-flux state is strongly reflection dominated, with the reflection fraction increasing from $R_{\rm refl}\sim4$ to $\sim34$, consistent with a compact corona subject to strong light-bending effects. The ultraviolet emission broadly follows the long-term X-ray variability but with smaller amplitude, while the optical and mid-infrared bands vary more mildly. Despite the dramatic X-ray variability, Mrk~382 does not enter an extreme X-ray-weak state, and we did not detect clear optical spectral-type changes based on the currently available observations. Mrk~382 is therefore a rare nearby Seyfert galaxy undergoing recurrent X-ray state transitions, providing a valuable laboratory for studying changing coronal geometry and multiwavelength AGN variability.

astro-ph.HE↗