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Weijia Wang

Publications and source records attributed to Weijia Wang.

At least 19 recordsLinked to original sources
arXiv2026

Large zeta sums and zeros of the Riemann zeta function

For real $t$ and $x\ge 1$, set \[ S(x,t)=\sum_{n\le x} n^{\ii t}. \] We prove an unconditional inverse theorem relating large values of $S(x,t)$, with $|t|$ large, to zeros of the Riemann zeta function near height $t$. More precisely, if $T\le |t|\le 2T$, $\exp(\sqrt{\log T})\le x\le \sqrt T$, and $|S(x,t)|=x/N$ with $N\le (\log x)^{1/100}$, then for every $cN^6\le L\le (\log x)/2$ a disk centered at $1+\iiϕ$, where $|ϕ-t|\ll N$, contains at least $L/360$ zeros of $ζ(s)$. As a consequence, a quantitative restriction on zeros in a short family of arbitrarily thin fixed windows to the left of the line $\Ree s=1$ yields $S(x,t)\ll x/(\log x)^{1/100}$ in polynomial ranges of $x$. The proof adapts the zero-forcing mechanism of Granville and Soundararajan for large character sums. In the zeta setting the spectral height is shifted by $t$, and an additional residue from the pole of $ζ(s)$ appears in the Gaussian transform; in the range considered here that residue is exponentially small.

math.NT↗
arXiv2026

Large values of quadratic character sums

In this paper, we investigate large values of quadratic Dirichlet character sums. We prove new Omega results for both short and long quadratic character sums under the assumption of the Generalized Riemann Hypothesis (GRH), which improve the previous results.

math.NT↗
arXiv2026

Flexible Beamforming Design with Two-layer Rotatable Antenna: Synergizing Array and Antenna Rotations

Reconfigurable antenna technology, such as movable antennas (MAs) and rotatable antennas (RAs), has emerged as a promising solution to enhance wireless communication performance by exploiting new degrees of freedom (DoFs) in antenna reconfiguration. However, existing RA designs mostly consider array-wise or antenna-wise rotation only, limiting their potential in wide-range radiation pattern control. To overcome this, we propose a new two-layer RA architecture for downlink coverage improvement, which combines array-wise rotation for global orientation adjustment with per-antenna rotation for fine-grained radiation refinement. We then formulate an optimization problem to maximize the minimum beamforming gain over a target region by jointly optimizing the two-layer rotations and transmit beamforming. To solve this non-convex problem, an efficient block coordinate descent (BCD) algorithm is proposed, which alternately optimizes one of the three variables in an iterative manner, with the other two being fixed. Numerical results demonstrate that the proposed two-layer RA significantly improves the minimum beamforming gain over fixed antenna arrays and single-layer RAs.

eess.SP↗
arXiv2026

Extreme values of quadratic Dirichlet $L$-functions

In this paper, we investigate extreme values of quadratic Dirichlet $L$-functions at the central point. We provide new extreme values of $L(\frac12,χ_d)$ as $d$ is large, which improves the recent result of Darbar and Maiti.

math.NT↗
arXiv2026

Quaternionic Mahler measure

We introduce the quaternionic Mahler measure for non-commutative polynomials, extending the classical complex Mahler measure. We establish the existence of quaternionic Mahler measure for slice regular polynomials in one and two variables. We study the quaternionic Mahler measure for real and slice regular polynomials, and consider the associated Lehmer problem. Various formulas of quaternionic Mahler measures are proved.

math.NT↗
arXiv2026

MambaH-Fit: Rethinking Hyper-surface Fitting-based Point Cloud Normal Estimation via State Space Modelling

We present MambaH-Fit, a state space modelling framework tailored for hyper-surface fitting-based point cloud normal estimation. Existing normal estimation methods often fall short in modelling fine-grained geometric structures, thereby limiting the accuracy of the predicted normals. Recently, state space models (SSMs), particularly Mamba, have demonstrated strong modelling capability by capturing long-range dependencies with linear complexity and inspired adaptations to point cloud processing. However, existing Mamba-based approaches primarily focus on understanding global shape structures, leaving the modelling of local, fine-grained geometric details largely under-explored. To address the issues above, we first introduce an Attention-driven Hierarchical Feature Fusion (AHFF) scheme to adaptively fuse multi-scale point cloud patch features, significantly enhancing geometric context learning in local point cloud neighbourhoods. Building upon this, we further propose Patch-wise State Space Model (PSSM) that models point cloud patches as implicit hyper-surfaces via state dynamics, enabling effective fine-grained geometric understanding for normal prediction. Extensive experiments on benchmark datasets show that our method outperforms existing ones in terms of accuracy, robustness, and flexibility. Ablation studies further validate the contribution of the proposed components.

cs.CV↗
arXiv2026

Xuanwu: Evolving General Multimodal Models into an Industrial-Grade Foundation for Content Ecosystems

In recent years, multimodal large models have continued to improve on general benchmarks. However, in real-world content moderation and adversarial settings, mainstream models still suffer from degraded generalization and catastrophic forgetting because of limited fine-grained visual perception and insufficient modeling of long-tail noise. In this paper, we present Xuanwu VL-2B as a case study of how general multimodal models can be developed into an industrial-grade foundation model for content ecosystems. The model adopts a compact InternViT-300M + MLP + Qwen3 1.7B architecture, balancing fine-grained visual perception, language-semantic alignment, and deployment cost within an approximately 2B-parameter budget. To balance business specialization with the retention of general capabilities, we developed a data iteration and curation mechanism and trained the model through a progressive three-stage pipeline: pre-training, mid-training, and post-training. Ablation studies and offline business evaluations show that Xuanwu VL-2B achieves an average score of 67.90 across seven OpenCompass multimodal metrics (vs. 64.27 for InternVL 3.5 2B), an average recall of 94.38% over seven independent business moderation tasks, and a weighted overall recall of 82.82% on policy-violating text in challenging adversarial OCR scenarios, outperforming Gemini-2.5-Pro (76.72%). These results show that, under a limited parameter budget, Xuanwu VL-2B achieves a practical balance among business alignment, visual perception, general capability retention, and deployment cost.

cs.AI↗
arXiv2026

A note on the scatteredness of reflection orders

In this note, we characterize affine and non-affine Coxeter systems among all Coxeter systems in terms of the structure of their reflection orders. For an infinite irreducible system $(W,S)$, we show that affineness can be characterized in three equivalent ways: by the scatteredness of all reflection orders, by the existence of a reflection order of type $ω+ ω^*$, and by a finiteness property of intervals determined by dihedral reflection subgroups. We also show that non-affineness can be characterized by the existence of order types $(ω+ ω^*)[k]$ for arbitrarily large $k$, obtained by restricting any reflection order to a suitable subset. Our proofs exploit the geometry of projective roots, the isotropic cone, and universal reflection subgroups in infinite non-affine Coxeter groups.

math.GR↗
arXiv2026

Two-stage Multi-beam Training for Multiuser Millimeter-Wave Communications

In this letter, we study an efficient multi-beam training method for multiuser millimeter-wave communication systems. Unlike the conventional single-beam training method that relies on exhaustive search, multi-beam training design faces a key challenge in balancing the trade-off between beam training overhead and success beam-identification rate, exacerbated by severe inter-beam interference. To tackle this challenge, we propose a new two-stage multi-beam training method with two distinct multi-beam patterns to enable fast and accurate user angle identification. Specifically, in the first stage, the antenna array is divided into sparse subarrays to generate multiple beams (with high array gains), for identifying candidate user angles. In the second stage, the array is redivided into dense subarrays to generate flexibly steered wide beams, for which a cross-validation method is employed to effectively resolve the remaining angular ambiguity in the first stage. Last, numerical results demonstrate that the proposed method significantly improves the success beam-identification rate compared to existing multi-beam training methods, while retaining or even reducing the required beam training overhead.

eess.SP↗
arXiv2026

Anomalous Collision of Exceptional Points on Nonorientable Manifolds

Band degeneracies, ranging from Hermitian Dirac points to non-Hermitian exceptional points (EPs), play a central role in topological phase transitions. Beyond the topology of individual degeneracies, their mutual interactions yield richer phenomena. A representative example is the anomalous non-annihilating collision of pairwise-created degeneracies, previously believed to occur only in non-Abelian multiband systems. Here, we theoretically reveal and experimentally demonstrate that such an anomalous collision can emerge even in a simple two-band system without non-Abelian nature. In a two-dimensional non-Hermitian lattice whose Brillouin zone forms a nonorientable Klein bottle, two EPs with opposite topological charges, pairwise created from a hybrid point, merge into a new vortex point upon re-encounter, instead of annihilating. Remarkably, the hybrid point is a defective degeneracy featuring no eigenenergy braiding, whereas the vortex point is a non-defective degeneracy yet exhibits nontrivial eigenenergy braiding. This process manifests a non-Hermitian phase transition from a gapped phase to a gapless phase, a scenario that we directly observe in a hybrid-dimensional acoustic lattice via momentum-resolved band braid and Berry phase measurements. Our findings identify nonorientability as a new arena for engineering band degeneracies and topological phases, and pave the way for experimentally exploring the interplay between exceptional and nonorientable topology.

cond-mat.mes-hall↗
arXiv2025

Large character sums with multiplicative coefficients

In this paper, we investigate large values of Dirichlet character sums with multiplicative coefficients $\sum_{n\le N}f(n)χ(n)$. We prove a new Omega result in the region $\exp((\log q)^{\frac12+δ})\le N\le\sqrt q$, where $q$ is the prime modulus.

math.NT↗
arXiv2025

Large values of Dirichlet polynomials with multiplicative coefficients

In this paper, we investigate large values of Dirichlet polynomials with multiplicative coefficients $\sum_{n\le N}f(n)n^{it}$, where $1\ll t\le T$ for large $T$. We prove an improved Omega result in the region $\exp((\log T)^{\frac12+\varepsilon})\le N\le\sqrt T$, where $T$ is large. We also show an Omega result when $\log N$ is around $\sqrt{\log T\log_2T}$.

math.NT↗
arXiv2025

The Diophantine Frobenius Problem revisited

Let $k\ge 2$ and $a_1, a_2, \cdots, a_k$ be positive integers with \[ \gcd(a_1, a_2, \cdots, a_k)=1. \] It is proved that there exists a positive integer $G_{a_1, a_2, \cdots, a_k}$ such that every integer $n$ strictly greater than it can be represented as the form \[ n=a_1x_1+a_2x_2+\cdots+a_kx_k, \quad (x_1, x_2, \cdots, x_k\in\mathbb{Z}_{\ge 0},~\gcd(x_1, x_2, \cdots, x_k)=1). \] We then investigate the size of $G_{a_1, a_2}$ explicitly. Our result strengthens the primality requirement of $x$'s in the classical Diophantine Frobenius Problem.

math.NT↗
arXiv2025

Solving generic parametric linear matrix inequalities

We consider linear matrix inequalities (LMIs) $A = A_0 + x_1 A_1 + ... + x_n A_n \succeq 0$ with the $A_i$'s being $m \times m$ symmetric matrices, with entries in a ring $\mathcal{R}$. When $\mathcal{R} = \mathbb{R}$, the feasibility problem consists in deciding whether the $x_i$'s can be instantiated to obtain a positive semidefinite matrix. When $\mathcal{R} = \mathbb{Q}[y_1, ... , y_t]$, the problem asks for a formula on the parameters $y_1, ..., y_t$, which describes the values of the parameters for which the specialized LMI is feasible. This problem can be solved using general quantifier elimination algorithms, with a complexity that is exponential in n. In this work, we leverage the LMI structure of the problem to design an algorithm that computes a formula $Φ$ describing a dense subset of the feasible region of parameters, under genericity assumptions. The complexity of this algorithm is exponential in n, m and t but becomes polynomial in $n$ when $m$ and $t$ are fixed. We apply the algorithm to a parametric sum-of-squares problem and to the convergence analyses of certain first-order optimization methods, which are both known to be equivalent to the feasibility of certain parametric LMIs, hence demonstrating its practical interest.

cs.SC↗