arXiv subjects

Wenlong Yang

Publications and source records attributed to Wenlong Yang.

9 recordsLinked to original sources

arXiv2026

Opening Knowledge Gaps Drives Scientific Progress

Knowledge production is often viewed as an endogenous process in which discovery arises through the recombination of existing theories, findings, and concepts. Yet not all recombinations are equally valuable, and identifying those that may prove most generative remains challenging. We propose that a crucial form of recombination occurs when linking concepts creates knowledge gaps---empty regions in the conceptual landscape that focus scientific attention on unexplored connections. Using computational topology, we develop a method to identify knowledge gaps in science at scale. In this framework, gaps form when new connections complete cycles in evolving networks of scientific concepts. We apply the method to 34,363,623 papers in Microsoft Academic Graph spanning 1900--2020. The main analyses use samples ranging from 8,643,571 to 31,983,201 papers. Compared with papers that introduce novel concept pairs without opening gaps, gap-opening papers have greater long-term citation impact, are more disruptive of prior work, and exhibit greater delayed recognition. Gap-opening papers receive fewer citations within five years of publication but more over twenty years, consistent with scientific communities needing time to recognize and develop newly opened research territories. Evidence for the generative capacity of gap-opening papers---as indicated by high citation impact and disruption---replicates in five additional databases (OpenAlex, the PubMed Knowledge Graph, Dimensions, American Physical Society journals, and United States patents) and across eight concept vocabularies, including several derived directly from text. Together, these results reveal a distinctive generative role for gap opening in scientific discovery.

cs.CY↗

arXiv2026

A chemical avenue to manipulate field-reentrant superconducting rivalries in infinite layer nickelates

Recently, preliminary magnetic field-reentrant superconductivity manifested in high-temperature (Tc) Eu-doped infinite-layer (IL) nickelates, beyond analogous discoveries exclusively in low-Tc systems. This evokes intriguing fundamental issues about potential quantum-phase boundary and criticality between unconventional superconductivity and field-reentrant-one, which are inexplicable owing to formidable challenges in growing IL-nickelates towards later-series rare-earths. Herein, we open up chemical avenues to enable effective growth of (RE1-yRE'y)1-xEuxNiO2 (RE/RE': Pr, Nd, Sm, Gd, Dy), giving rise to discoveries of RE-4f-related quantum competition between high-Tc and reentrant superconductivity. Robust magnetic-field-reentrant superconductivity with uniaxial anisotropy is observed at superconducting-dome boundaries, stemming from Eu2+-4f7 associated competition between magnetic-fluctuation promoted pairing and exchange-field interactions. Their quantum-criticality is further modulable via RE(RE')-magnetism, which either reinforces reentrancy or elevates Tc (40.1 K) with more robust critical-current-density (~266 kA/cm2 at 2 K) beyond Sr-/Ca-doped counterparts. Our synthetic route enables the establishment of an ideal platform via IL-nickelates for studying 4f-related unconventional superconductivity and quantum-criticality.

cond-mat.supr-con↗

arXiv2026

RRNet: Configurable Real-Time Video Enhancement with Arbitrary Local Lighting Variations

With the growing demand for real-time video enhancement in live applications, existing methods often struggle to balance speed and effective exposure control, particularly under uneven lighting. We introduce RRNet (Rendering Relighting Network), a lightweight and configurable framework that achieves a state-of-the-art tradeoff between visual quality and efficiency. By estimating parameters for a minimal set of virtual light sources, RRNet enables localized relighting through a depth-aware rendering module without requiring pixel-aligned training data. This object-aware formulation preserves facial identity and supports real-time, high-resolution performance using a streamlined encoder and lightweight prediction head. To facilitate training, we propose a generative AI-based dataset creation pipeline that synthesizes diverse lighting conditions at low cost. With its interpretable lighting control and efficient architecture, RRNet is well suited for practical applications such as video conferencing, AR-based portrait enhancement, and mobile photography. Experiments show that RRNet consistently achieves the best overall result in low-light enhancement, localized illumination adjustment, and glare removal.

cs.CV↗

arXiv2026

FilterFusion: Prior-Guided Adaptive Filter Fusion for Efficient Video Denoising

Real-world video denoising for communication systems must handle mixed degradations such as sensor noise, compression artifacts, and motion-induced inconsistency while remaining deployable under tight latency budgets. Purely deep models often achieve high accuracy but come with significant computational cost, whereas classical filters are robust and efficient but insufficiently adaptive. We present FilterFusion, a prior-guided multi-frame denoising framework that combines temporally-aware learned features with an interpretable bank of denoising branches. The model predicts a low-cost guidance signal and uses it to adaptively mix a compact set of denoising responses at the original resolution. The lightweight design uses only 109K parameters and explicitly injects temporal variance and spatial variance cues into the low-resolution controller. On CRVD (real sensor noise), it reaches 34.72 dB PSNR and 0.9330 SSIM with only 0.18 GFLOPs (network-only). Because the filter-bank operations are simple and regular (Gaussian blur, median, weighted sum), a straightforward compiled C implementation of the synthesis path achieves 17.9ms per frame (55.9 FPS) on a single CPU thread at 1080p---exceeding real-time and 122--252 times faster than lightweight CNN baselines that require over 2 seconds per frame. The results demonstrate a strong quality-efficiency-speed trade-off and a practical route to real-time denoising through low-resolution control and explicit filter-based synthesis.

cs.CV↗

arXiv2026

Superconducting dome and field-enhanced superconductivity of PLD synthesized Nd1-xEuxNiO2 thin films

We report on the synthesis of infinite-layer Nd1-xEuxNiO2 (0<x<0.7) thin films using pulsed laser deposition (PLD) followed by topotactic reduction with CaH2. Resistivity measurements on these films reveal a superconducting dome within the doping range 0.2<x<0.5, which is wider than that achieved by molecular beam epitaxy and comparable to that obtained by chemical synthesis. The x=0.3 PLD film exhibits the optimal superconducting transition temperature Tc~31 K, much higher than those grown by other vacuum epitaxial techniques. This result indicates that PLD is an ideal approach for fabricating high-quality, high-Tc Nd1-xEuxNiO2 superconducting films. Magneto-transport measurements reveal robust field-enhanced and re-entrant superconductivity in both underdoped and overdoped regimes. At low temperatures just above the onset Tc, the Hall resistance exhibits nonlinear behavior, which may originate from magnetic impurity scattering. These results highlight the crucial role of magnetic rare-earth Eu2+ ions in producing the exotic physical properties of the infinite-layer nickelates.

cond-mat.supr-con↗

arXiv2024

A Likelihood Approach to Incorporating Self-Report Data in HIV Recency Classification

Estimating new HIV infections is significant yet challenging due to the difficulty in distinguishing between recent and long-term infections. We demonstrate that HIV recency status (recent v.s. long-term) could be determined from the combination of self-report testing history and biomarkers, which are increasingly available in bio-behavioral surveys. HIV recency status is partially observed, given the self-report testing history. For example, people who tested positive for HIV over one year ago should have a long-term infection. Based on the nationally representative samples collected by the Population-based HIV Impact Assessment (PHIA) Project, we propose a likelihood-based probabilistic model for HIV recency classification. The model incorporates both labeled and unlabeled data and integrates the mechanism of how HIV recency status depends on biomarkers and the mechanism of how HIV recency status, together with the self-report time of the most recent HIV test, impacts the test results, via a set of logistic regression models. We compare our method to logistic regression and the binary classification tree (current practice) on Malawi, Zimbabwe, and Zambia PHIA data, as well as on simulated data. Our model obtains more efficient and less biased parameter estimates and is relatively robust to potential reporting error and model misspecification.

stat.AP↗

arXiv2024

Asymptotic symmetry of solutions for reaction-diffusion equations via elliptic geometry

In this paper, we investigate the asymptotic symmetry and monotonicity of positive solutions to a reaction-diffusion equation in the unit ball, utilizing techniques from elliptic geometry. Firstly, we discuss the properties of solutions in the elliptic space. Then, we establish crucial principles, including the asymptotic narrow region principle.Finally, we employ the method of moving planes to demonstrate the asymptotic symmetry of the solutions.

math.AP↗

arXiv2024

Achieving High Yield of Perpendicular SOT-MTJ Manufactured on 300 mm Wafers

The large-scale fabrication of three-terminal magnetic tunnel junctions (MTJs) with high yield is becoming increasingly crucial, especially with the growing interest in spin-orbit torque (SOT) magnetic random access memory (MRAM) as the next generation of MRAM technology. To achieve high yield and consistent device performance in MTJs with perpendicular magnetic anisotropy, an integration flow has been developed that incorporates special MTJ etching technique and other CMOS-compatible processes on a 300 mm wafer manufacturing platform. Systematic studies have been conducted on device performance and statistical uniformity, encompassing magnetic properties, electrical switching behavior, and reliability. Achievements include a switching current of 680 uA at 2 ns, a TMR as high as 119%, ultra-high endurance (over 1012 cycles), and excellent uniformity in the fabricated SOT-MTJ devices, with a yield of up to 99.6%. The proposed integration process, featuring high yield, is anticipated to streamline the mass production of SOT-MRAM.

physics.app-ph↗

arXiv2019

Current-driven magnetization switching in a van der Waals ferromagnet Fe3GeTe2

The recent discovery of ferromagnetism in two-dimensional (2D) van der Waals (vdW) materials holds promises for novel spintronic devices with exceptional performances. However, in order to utilize 2D vdW magnets for building spintronic nanodevices such as magnetic memories, key challenges remain in terms of effectively switching the magnetization from one state to the other electrically. Here, we devise a bilayer structure of Fe3GeTe2/Pt, in which the magnetization of few-layered Fe3GeTe2 can be effectively switched by the spin-orbit torques (SOTs) originated from the current flowing in the Pt layer. The effective magnetic fields corresponding to the SOTs are further quantitatively characterized using harmonic measurements. Our demonstration of the SOT-driven magnetization switching in a 2D vdW magnet could pave the way for implementing low-dimensional materials in the next-generation spintronic applications.

cond-mat.mes-hall↗