December 2025 arXiv papers — page 7

Livia Zhu, R. J. Graham, Dorian S. Abbot

Current understanding suggests that as the Sun brightens in the far future, Earth's carbonate-silicate cycle will offset increasing temperatures by drawing CO$_2$ out of the atmosphere, ultimately leading to the extinction of all terrestrial plant life via either overheating or CO$_2$ starvation. Most previous estimates put the future lifespan of Earth's ter

Jangho Bae, Bomee Lee, Myungshin Im, Hyeonguk Bahk

The recently initiated SPHEREx and 7DS surveys will deliver low-resolution spectra ($R\approx 30-130$) for hundreds of millions of galaxies over the optical to near-infrared range ($0.4-5.0\mu m$), covering a wide sky area without sample selection. These unique datasets will improve redshift estimation and provide a rich redshift catalog for the community. I

Seog-Jin Kim, Xiaopan Lian, Atsuhiro Nakamoto, Kenta Ozeki

The square of a graph $G$, denoted $G^2$, has the same vertex set as $G$ and has an edge between two vertices if the distance between them in $G$ is at most $2$. Thomassen [12] showed that $\chi(G^2) \leq 7$ if $G$ is a subcubic planar graph. A natural question is whether $\chi_{\ell}(G^2) \leq 7$ or not if $G$ is a subcubic planar graph. Recently Kim and Li

Benjamin Morris, Paul P. Martin

The Kadar--Yu algebras are a physically motivated sequence of towers of algebras interpolating between the Brauer algebras and Temperley--Lieb algebras. The complex representation theory of the Brauer and Temperley--Lieb algebras is now fairly well understood, with each connecting in a different way to Kazhdan--Lusztig theory. The semisimple representation t

Xizhe Xie, Wengu Chen, Weiming Li, Peng Song

The Radiative Transfer Equations (RTEs) exhibit high dimensionality and multiscale characteristics, rendering conventional numerical methods computationally intensive. Existing deep learning methods perform well in low-dimensional or linear RTEs, but still face many challenges with high-dimensional or nonlinear RTEs. To overcome these challenges, we propose

Pouria Mortezaagha, Joseph Shaw, Bowen Sun, Arya Rahgozar

Biomedical evidence synthesis relies on accurate extraction of methodological, laboratory, and outcome variables from full-text research articles, yet these variables are embedded in complex scientific PDFs that make manual abstraction time-consuming and difficult to scale. Existing document AI systems remain limited by OCR errors, long-document fragmentatio

Amir Tahmasbi, Sadegh Majidi, Kazem Taram, Aniket Bera

Spatial reasoning in large language models (LLMs) has gained increasing attention due to applications in navigation and planning. Despite strong general language capabilities, LLMs still struggle with spatial transformations and multi-step planning in structured environments. We propose a two-stage approach that decomposes spatial reasoning into atomic build

Dar-jen Chang, Suranjan Gautam

This paper proposes an alternative approach to formally establishing the correctness of the RSA public key cryptosystem. The methodology presented herein deviates slightly from conventional proofs found in existing literature. Specifically, this study explores the conditions under which the choice of the positive integer N, a fundamental component of RSA, ca

Nikolaos Mavrogeorgis, Christos Vasiladiotis, Pei Mu, Amir Khordadi

Heterogeneous-ISA processor designs have attracted considerable research interest. However, unlike their homogeneous-ISA counterparts, explicit software support for bridging ISA heterogeneity is required. The lack of a compilation toolchain ready to support heterogeneous-ISA targets has been a major factor hindering research in this exciting emerging area. F

Ali Fathi Jouzdani, Shahram Taeb, Mehdi Maghsudi, Arman Gorji

Lung cancer remains the leading cause of cancer-related mortality worldwide, with survival strongly dependent on early detection. Standard-dose computed tomography (CT) screening using the Lung Imaging Reporting and Data System (Lung-RADS) standardizes pulmonary nodule assessment but is limited by inter-reader variability and reliance on qualitative descript

Matieyendou Lamboni

This study proposes a unified stochastic framework for approximating and computing the gradient of every smooth function evaluated at non-independent variables, using $\ell_p$-spherical distributions on $\R^d$ with $d, p\geq 1$. The upper-bounds of the bias of the gradient surrogates do not suffer from the curse of dimensionality for any $p\geq 1$. Also, the

Habib Badawi, Mohamed Hani, Taufikin Taufikin

Financial markets often appear chaotic, yet ranges are rarely accidental. They emerge from structured interactions between market context and capital conditions. The four-hour timeframe provides a critical lens for observing this equilibrium zone where institutional positioning, leveraged exposure, and liquidity management converge. Funding mechanisms, espec

Alina Voronina, Oleksandr Romanko, Ruiwen Cao, Roy H. Kwon

This paper investigates how Large Language Models (LLMs) from leading providers (OpenAI, Google, Anthropic, DeepSeek, and xAI) can be applied to quantitative sector-based portfolio construction. We use LLMs to identify investable universes of stocks within S&P 500 sector indices and evaluate how their selections perform when combined with classical portfolio

Fenwick C. Cooper, Shruti Nath, Andrew T. T. McRae, Bobby Antonio

Ensemble forecasting has proven over the years to be a vital tool for predicting extreme or only partially predictable weather events. In particular life-threatening weather events. Many National Meteorological Services in East Africa do not have the computing resources to enable them to run their local area models in full ensemble mode over the full period

Richard H. Bamler, Yi Lai

We resolve the Mean Convex Neighborhood Conjecture for mean curvature flows in all dimensions and for all types of cylindrical singularities. Specifically, we show that if the tangent flow at a singular point is a multiplicity-one cylinder, then in a neighborhood of that point the flow is mean-convex, its time-slices arise as level sets of a continuous funct

Kingsley Yeon, Steven B. Damelin, Michael Werman

We investigate deep composite polynomial approximations of continuous but non-differentiable functions with algebraic cusp singularities. The functions in focus consist of finitely many cusp terms of the form $|x-a_j|^{\alpha_j}$ with rational exponents $\alpha_j\in(0,1)$ on a real-analytic background. We propose a constructive approximation scheme that comb

Fatemeh Hosseinabadi, Mohammad Mojtaba Rohani

Pediatric pneumonia remains a leading cause of morbidity and mortality in children worldwide. Timely and accurate diagnosis is critical but often challenged by limited radiological expertise and the physiological and procedural complexity of pediatric imaging. This study investigates the performance of state-of-the-art convolutional neural network (CNN) arch

Hongwei Huang, Jie Zhou, Weizhou Cai, Weiting Wang

Distributed quantum computing architectures require high-performance quantum interconnects between quantum information processing units, while previous implementations have been fundamentally limited by transmission line losses. Here, we demonstrate a low-loss interconnect between two superconducting modules using an aluminum coaxial cable, achieving a bus m

Baiqiang Liu, Chenxi Wan, Rui Liu, Zhen Gong

Improving hydrogen storage density is essential for reducing the extreme conditions required in applications such as nuclear fusion. However, the recognition of metallic hydrogen as the "Holy Grail" of high-pressure science highlights the difficulty of high-density hydrogen aggregation. Here, we report a solid-state crystal H9@C20 formed by embedding

Torjus L. Steffensen, Arthur G. S. Torvund, Vegar Stubberud, Julia Lövgren

Continuous cardiovascular monitoring is essential for managing circulatory health and disease, yet most wearable sensors are constrained by reliance on electrical transduction and built-in electronics. We present a circuit-free, wholly optical approach using diffraction from a skin-interfaced nanostructured surface to detect minute skin strains from the arte

Michele Arzano, Goffredo Chirco

We argue that Hopf-algebra deformations of symmetries -- as encountered in non-commutative models of quantum spacetime -- carry an intrinsic content of $operator$ $entanglement$ that is enforced by the coproduct-defined notion of composite generators. As a minimal and exactly solvable example, we analyze the $U_q(\mathfrak{su}(2))$ quantum group and a two-qu

Ákos Prucs, Nara Csutora, Mátyás Antal, Márk Marosi

Large Language Models (LLMs) are demonstrating rapid improvements on complex reasoning benchmarks, particularly when allowed to utilize intermediate reasoning steps before converging on a final solution. However, current literature often overlooks the significant computational burden associated with generating long reasoning sequences. For industrial applica

Surat Layek, Mahesh A. Hingankar, Ayshi Mukherjee, Atasi Chakraborty

Two-dimensional materials are a fertile ground for exploring quantum geometric phenomena, with Berry curvature and its first moment, the Berry curvature dipole, playing a central role in their electronic response. These geometric properties influence electronic transport and result in the anomalous and nonlinear Hall effects, and are typically controlled usi

Junyu Fan, Matthew Steinberg, Alexander Jahn, Chunjun Cao

A crucial insight for practical quantum error correction is that different types of errors, such as single-qubit Pauli operators, typically occur with different probabilities. Finding an optimal quantum code under such biased noise is a challenging problem, related to the (generally unknown) maximum capacity of the corresponding noisy channel. A benchmark fo

Kritika Bhandari, Mark Huber

A new algorithm for exactly sampling from the set of proper colorings of a graph is presented. This is the first such algorithm that has an expected running time that is guaranteed to be linear in the size of a graph with maximum degree \( \Delta \) when the number of colors is greater than \( 3.637 \Delta + 1\).

Ron Kohavi, Jakub Linowski, Lukas Vermeer, Fabrice Boisseranc

Underpowered studies (below 50% power) suffer from the winner's curse: A statistically significant positive estimate must exaggerate the true treatment effect to meet the significance threshold. A study by Dipayan Biswas, Annika Abell, and Roger Chacko published in the Journal of Consumer Research (2023) reported that in an A/B test, simply rounding the corn

Simon F. Lang

How should nations price carbon? This paper examines how the treatment of global inequality, captured by regional welfare weights, affects optimal carbon prices. I develop theory to identify the conditions under which accounting for differences in marginal utilities of consumption across countries leads to more stringent global climate policy in the absence

Khalil Al Handawi, Fabian Bastin

The air transportation market is highly competitive and dynamic. Airlines often form alliances to expand their network reach, improve operational efficiency, and enhance customer experience. However, the impact of these alliances on market competition and operational efficiency is not fully understood. In this paper, we propose a novel approach to analyze ai

Ruben Neyroud, Sam Corley

While most LLMs are autoregressive, diffusion-based LLMs have recently emerged as an alternative method for generation. Greedy Coordinate Gradient (GCG) attacks have proven effective against autoregressive models, but their applicability to diffusion language models remains largely unexplored. In this work, we present an exploratory study of GCG-style advers

Trishna Niraula, Jonathan Stubblefield

Artificial intelligence (AI) has transformed medical imaging, with computer vision (CV) systems achieving state-of-the-art performance in classification and detection tasks. However, these systems typically output structured predictions, leaving radiologists responsible for translating results into full narrative reports. Recent advances in large language mo

Thomas Andrews, Mark Law, Sara Ahmadi-Abhari, Alessandra Russo

We introduce LearnAD, a neuro-symbolic method for predicting Alzheimer's disease from brain magnetic resonance imaging data, learning fully interpretable rules. LearnAD applies statistical models, Decision Trees, Random Forests, or GNNs to identify relevant brain connections, and then employs FastLAS to learn global rules. Our best instance outperforms Decis

Fabian Retkowski, Alexander Waibel

Automatic speech transcripts are often delivered as unstructured word streams that impede readability and repurposing. We recast paragraph segmentation as the missing structuring step and fill three gaps at the intersection of speech processing and text segmentation. First, we establish TEDPara (human-annotated TED talks) and YTSegPara (YouTube videos with s

Yizhi Sun, Shoufei Gao, Xiangqi Wang, Xianhao Qi

Delivering a well defined state of polarization over hollow core fibres (HCFs) is pivotal for next generation ultra stable photonic systems. Yet in all existing HCFs, whether birefringent or not, their polarization extinction ratio (PER) rapidly deteriorates during propagation or under mechanical disturbance, leaving no practical high and stable PER solution

Jiani Wei, Xiaocheng Shang

Stochastic gradient Langevin dynamics and its variants approximate the likelihood of an entire dataset, via random (and typically much smaller) subsets, in the setting of Bayesian sampling. Due to the (often substantial) improvement of the computational efficiency, they have been widely used in large-scale machine learning applications. It has been demonstra

Oleg N Vassiliev, Radhe Mohan

The claim that Monte Carlo is the most accurate method is a case of misattributed credit. This claim is based on experience with advanced systems MCNPX, Geant4 and EGS. These systems achieve remarkable performance because they use most accurate physics, not because they use random numbers. The latter simplifies algorithms, but contaminates the solution with

Zhiwei Wei, Mengzi Zhang, Boyan Lu, Zhitao Deng

Understanding urban perception from street view imagery has become a central topic in urban analytics and human centered urban design. However, most existing studies treat urban scenes as static and largely ignore the role of dynamic elements such as pedestrians and vehicles, raising concerns about potential bias in perception based urban analysis. To addres

Srikumar Warrier, Anubhab Roy, Pijush Patra

Collisional growth of tiny particles is a fundamental process governing the growth of cloud droplets and the aggregation of ash particles in volcanic plumes, with direct implications for precipitation formation, cloud lifetime, and ash plume dynamics. The particles in these scenarios often carry electric charges. In this study, we investigate the collision d

Mikaila J. Gossman, Avinash Maurya, Bogdan Nicolae, Jon C. Calhoun

As LLMs and foundation models scale, checkpoint/restore has become a critical pattern for training and inference. With 3D parallelism (tensor, pipeline, data), checkpointing involves many processes, each managing numerous tensors of varying shapes and sizes, that must be persisted frequently to stable storage (e.g., parallel file systems). This turns checkpo

Sarka Necasova, Arnab Roy, Ana Leonor Silvestre

We investigate the steady self-propelled motion of a rigid body immersed in a three-dimensional incompressible viscous fluid governed by the Navier-Stokes equations. The analysis is performed in a body-fixed reference frame, so that the fluid occupies an exterior domain and the propulsion mechanism is modeled through nonhomogeneous Navier-slip boundary condi

Wilder Schaaf, Stephen R. Sharpe

We describe in detail the implementation of the relativistic three-neutron finite-volume quantization condition derived in Ref. [1]. In particular, we show how the complications due to Wigner rotations acting on spins are included, and present concrete formulas for the case when the angular momenta within pairs is restricted to be less than 2. We describe th

Samuel Granovsky, Alexander G. Kosovichev, Irina N. Kitiashvili, Alan A. Wray

While solar flares are primarily associated with enhanced ultraviolet and X-ray emission, a subset of flares exhibit significant continuum brightening in visible light and are classified as white-light flares (WLFs). Despite extensive observational and modeling efforts, the physical mechanisms responsible for the compact, short-lived photospheric brightening

Beren Millidge

Recurrent networks are typically trained with backpropagation through time (BPTT). However, BPTT requires storing the history of all states in the network and then replaying them sequentially backwards in time. This computation appears extremely implausible for the brain to implement. Real Time Recurrent Learning (RTRL) proposes an mathematically equivalent

Samuel Golladay, Majid Bani-Yaghoub

Understanding the limitations of Large Language Models, or LLMs, in mathematical reasoning has been the focus of several recent studies. However, the majority of these studies use the same datasets for benchmarking, which limits the generalizability of their findings and may not fully capture the diverse challenges present in mathematical tasks. The purpose

Zhiwei Wei, Yuxing Liu, Hua Liao, Wenjia Xu

Map environments provide a fundamental medium for representing spatial structure. Understanding how foundation model (FM) agents understand and act in such environments is therefore critical for enabling reliable map-based reasoning and applications. However, most existing evaluations of spatial ability in FMs rely on static map inputs or text-based queries,

Jiachen T. Wang, Tong Wu, Kaifeng Lyu, James Zou

Data teams at frontier AI companies routinely train small proxy models to make critical decisions about pretraining data recipes for full-scale training runs. However, the community has a limited understanding of whether and when conclusions drawn from small-scale experiments reliably transfer to full-scale model training. In this work, we uncover a subtle y

I. A. Belkovich, A. A. Radkevich

A model of microscopic interaction between a superconductor and a one-dimensional topological insulator, an SSH chain, is considered. Using the functional integration method, the effective action of the interaction between a superconductor and a topological insulator is obtained. We obtain corrections to the quasiparticle excitation spectrum of the SSH chain

Tanvirul Abedien, Tianli Feng

Nanoscale hot spots forming tens of nanometers beneath the gate in advanced FinFET and HEMT devices drive heat transport into a non-Fourier regime, challenging conventional (Fourier-based) finite-element (FEM) analyses and complicating future thermal-aware chip design. Molecular dynamics (MD) naturally captures ballistic transport and phonon nonequilibrium,

Vladimir Frants, Sos Agaian

The rapid expansion of generative AI has normalized large-scale synthetic media creation, enabling new forms of covert communication. Recent generative steganography methods, particularly those based on diffusion models, can embed high-capacity payloads without fine-tuning or auxiliary decoders, creating significant challenges for detection and remediation.

Iman Poernomo

We introduce Open Horn Type Theory (OHTT), an extension of dependent type theory with two primitive judgment forms: coherence and gap, subject to a mutual exclusion law. Unlike classical or intuitionistic negation, gap is not defined via implication but is a primitive witness of non-coherence. Judgments may also be open -- neither coherent nor gapped -- yiel

A. V. Flegel, Liang-Wen Pi, M. V. Frolov

An analytic description of high harmonic generation (HHG) in solids induced by intense low-frequency pulses is presented within an adiabatic approach, which treats laser-matter interactions nonperturbatively. We derive the analytical expression for the laser-dressed state of an electron in an arbitrary spatially periodic potential, taking into account multib

Zamina Guliyeva, Yagub Aliyev

The cevians passing through a point in a simplex create a cevian simplex, which is divided by these cevians into smaller simplices. We consider the problem about the maximum of the ratio of the sum of the volumes of some of these smaller simplices by the volume of the reference simplex. The special case of tetrahedron is given as an example.

Foster Thompson, Daniel K. J. Boneß, Mark Dykman, Alex Kamenev

Parametrically driven oscillators can emerge as a basis for the next generation of qubits. Classically, these systems exhibit two stable oscillatory states with opposite phases. Upon quantization, these states turn into a pair of closely spaced Floquet states, which can serve as the logical basis for a qubit. However, interaction with the environment induces

Xiuqing Huang

Recently, the nickel-based superconductor $T_c$ record was updated to $96\ \text{K}$ in bilayer $\mathrm{La_{3-x}Sm_{x}Ni_{2}O_{7-\delta}}$ (LSNO) under pressure, raising a critical question: Can its $T_c$ exceed the 164 K benchmark of copper-based superconductors? We find that both monoclinic and tetragonal LSNO have an octahedral quantum well structure (de

Bai-Ling Wang

The year 2025 marked the passing of two towering figures of twentieth-century mathematical physics, Rodney Baxter and Chen-Ning Yang. Yang reshaped modern physics through the introduction of non-abelian gauge theory and, independently, through the consistency conditions underlying what is now called the Yang-Baxter equation. Baxter transformed those conditio

Chi Ho Leung, Philip E. Paré

Control barrier functions for port-Hamiltonian systems inherit model uncertainty when the Hamiltonian is learned from data. We show how to propagate this uncertainty into a safety filter with independently tunable credibility budgets. To propagate this uncertainty, we employ a two-stage Bayesian approach. First, posterior prediction over the Hamiltonian yiel

Youssef Megahed, Aylin Erman, Robin Ducharme, Mark C. Walker

Congenital heart disease remains the most common congenital anomaly and a leading cause of neonatal morbidity and mortality. Although first-trimester fetal echocardiography offers an opportunity for earlier detection, automated analysis at this stage is challenging due to small cardiac structures, low signal-to-noise ratio, and substantial inter-operator var

Graeme Baker, Ankita Chatterjee

We consider a reflected process in the positive orthant driven by an exogenous jump process. For a given input process, we show that there exists a unique minimal strong solution to the given particle system up until a certain maximal stopping time, which is stated explicitly in terms of the dual formulation of a linear programming problem associated with th

Abdelkader Hamdouni, Imed Basdouri, Mariem Jendoubi, Ahmed Zahari Abdou Damdji

Hom-quadri dendriform algebras and Hom-six-dendriform agebras are introduced and studied which is a splitting of a Hom-diassociative and Hom-triassociative algebras, respectively. Moreover we explore the connections be tween these categories of Hom-algebras. Finally We elaborate a classification of Hom-quadri-dendriform algebra in low dimensional.

Veronika E. Hubeny, Massimiliano Rota

We prove that the ``chordality condition'', which was established in arXiv:2412.18018 as a necessary condition for an entropy vector to be realizable by a holographic simple tree graph model, is also sufficient. The proof is constructive, demonstrating that the algorithm introduced in arXiv:2512.18702 for constructing a simple tree graph model realization of

Mikolaj Krysa, Mikolaj Rogalski, Piotr Arcab, Pawel Goclowski

Fourier ptychographic microscopy (FPM) is a promising quantitative phase imaging technique that enables high-resolution, label-free imaging over a large field-of-view. Here, we present the first application of FPM for the quantitative analysis of human brain organoid slices, providing a powerful, cost-effective, and label-free enhancement to the current gold

Erik Lentz, Emily Ellwein, Bill Kay, Audun Myers

This paper presents novel interpretations to the field of classical signal processing of the Wigner-Ville transform as an information measurement tool. The transform's utility in detecting and localizing information-laden signals amidst noisy and cluttered backgrounds, and further providing measure of their information volumes, are detailed herein using Tsal

Lecheng Zheng, Jian Ni, Chris Zobel, John R Birge

Financial institutions face escalating challenges in identifying high-risk customer behaviors within massive transaction networks, where fraudulent activities exploit market fragmentation and institutional boundaries. We address three fundamental problems in customer risk analytics: data silos preventing holistic relationship assessment, extreme behavioral c

Shahar Nahum, Adi Y. Elkabetz, Matan Elbaz, Liav Daraf

As small particles skim our airways during breathing, or our intestines during digestion, the surface epithelium is subjected to local exogenous shear that deforms hundreds to thousands of tightly interacting cells. Unlike shear deformations applied at the macro-tissue scale or the micro-cell scale, the effects of such perturbations at the meso-scale remain

M. Aissaoui, C. Kahloun, O. U. Salman, S. Queyreau

Strain rate sensitivity is a key feature of material deformation, whose importance is growing both because miniaturized components experience higher effective rates and because small scale simulations increasingly probe such conditions. As a dynamical characteristic, strain rate dependence is shown to be intimately connected to dislocation avalanches, which

Sunjeev Venkateswaran, Costas Kravaris

A systematic method for the design of linear residual generators for combined fault detection and estimation in nonlinear systems is developed. The proposed residual generator is a linear functional observer built for an extended system that incorporates the fault dynamics from a linear exo-system, and in addition possesses disturbance-decoupling properties.

Liyuan Liang, Yilong Song, Kun Yuan

Decentralized optimization over directed graphs is essential for applications such as robotic swarms, sensor networks, and distributed learning. In many practical scenarios, the underlying network takes the form of a Time-Varying Broadcast Network (TVBN), where only row-stochastic mixing matrices can be constructed due to the unavailability of out-degree inf

Xavier Lemay, Fabian Bastin

We investigate the factors contributing to departure and arrival delays at a major international airport and develop predictive models to estimate both the likelihood and duration of delays. Using logistic regression, random forest, and gradient boosting methods, we identify key predictors of flight punctuality, including historical delay rates of flight num

Mendrit Latifi

We study the dynamics of a charged scalar field in the near-horizon region of an extremal charged BTZ black hole. The near-horizon geometry contains an AdS2 throat with a constant electric field, which lowers the effective mass of the scalar and can trigger a violation of the AdS2 Breitenlohner-Freedman bound. We show that this instability is resolved by the

C. Pallis

I present some memories of my Ph.D supervisor and, later, collaborator but always encouraging supporter Prof. G. Lazarides. Some of his contributions to our common and related scientific activities on the phenomenology of MSSM and inflation are also summarized.

Jorge Gamboa, Natalia A. Tapia Arellano

We reformulate the strong $CP$ problem from an infrared viewpoint in which the vacuum angle $\theta$ is not treated as a local coupling but as a global Berry-type holonomy of the infrared-dressed state space over $\mathcal{A}/\mathcal{G}$. Infrared dressing is described as adiabatic parallel transport of physical states in configuration space, generated by a

Malcolm K. Druett, Graham S. Kerr, Joel C. Allred, Philippa K. Browning

Solar flares are the largest energy-release events in the Solar System, allowing us to study fundamental physical phenomena under extreme conditions. Those include magnetic reconnection, particle acceleration, radiation transport, and various plasma physics processes, all of which occur throughout the heliosphere and rest of the Universe. Flares and eruptive

Hyunjun Kim

Causal discovery from observational data remains fundamentally limited by identifiability constraints. Recent work has explored leveraging Large Language Models (LLMs) as sources of prior causal knowledge, but existing approaches rely on heuristic integration that lacks theoretical grounding. We introduce HOLOGRAPH, a framework that formalizes LLM-guided cau

Wei Li, Junshan Lin, Jiayu Qiu, Hai Zhang

In this work, we develop a mathematical theory for the photonic Hall effect and prove the existence of guided electromagnetic waves at the interface of two honeycomb photonic crystals. The guided wave resembles the edge states in electronic systems: it is induced by the topological Hall effect, and the wave propagates along the interface but not in the bulk

Vitali Vougalter, Vitaly Volpert

In the first part of the article we establish the existence in the sense of sequences of solutions in $H^{2}(R)$ for some nonhomogeneous linear differential equation in which one of the terms has the argument translated by a constant. It is shown that under the reasonable technical conditions the convergence in $L^{2}(R)$ of the source terms implies the exis

Akanksha Dagore, Prajwel Joseph, S. N. Tandon, Annapurni Subramaniam

The Ultra-Violet Imaging Telescope (UVIT) is one of the five payloads onboard the first Indian multiwavelength astronomical observatory, AstroSat, launched by the Indian Space Research Organisation on 28 September 2015. UVIT, designed for simultaneous imaging in the far-ultraviolet (FUV; 1300-1800 {\AA}) and near-ultraviolet (NUV; 2000-3000 {\AA}) channels,

Mehmet Asim Gumus, Simon Metayer, Piotr Tourkine

We study massive $2 \to 2$ scattering of identical scalar particles in spacetime dimensions 3 to 11 using non-perturbative S-matrix bootstrap techniques. Treating $d$ as a continuous parameter, we compute two-sided numerical bounds on low-energy observables and find smooth branches of extremal amplitudes separated by sharp kinks at $d=5$ and $d=7$, coincidin

Devendra K. Jangid, Ripon K. Saha, Dilshan Godaliyadda, Jing Li

With the advent of Generative AI, Single Image Super-Resolution (SISR) quality has seen substantial improvement, as the strong priors learned by Text-2-Image Diffusion (T2IDiff) Foundation Models (FM) can bridge the gap between High-Resolution (HR) and Low-Resolution (LR) images. However, flagship smartphone cameras have been slow to adopt generative models

Chon-Fai Kam

Spin squeezing in collective atomic ensembles enables quantum-enhanced metrology by reducing noise below the standard quantum limit through nonlinear interactions. Extending the one-axis and two-axis twisting paradigms of Kitagawa and Ueda, we introduce a general class of three-axis spin squeezed states within the anisotropic Lipkin-Meshkov-Glick model. The

CMS Collaboration

A search is presented for charged Higgs bosons (H$^\pm$) in proton-proton (pp) collision events via the pp $\to$ (b)H$^\pm$ processes, with H$^\pm$ decaying into top (t) and bottom (b) quarks. The search targets final states with one lepton, missing transverse momentum, and two or more b jets. The analysis is based on data collected at a center-of-mass energ

Gregory L. Eyink, Nigel Goldenfeld

In this perspective, we consider the development of statistical hydrodynamics, focusing on the way in which the intrinsic stochasticity of turbulent phenomena was identified and is being explored. A major purpose of our discussion is to bring out the role of anomalies in turbulent phenomena, in ways that are not usually done, and to emphasize how the descrip

Augustin Cosse

We study deterministic constructions of graphs for which the unique completion of low rank matrices is generically possible regardless of the values of the entries. We relate the completability to the presence of some patterns (particular unions of self-avoiding walks) in the subgraph of the lattice graph generated from the support of the bi-adjacency matrix

Ulle Endriss

Given the stated preferences of several people over a number of proposals regarding public policy initiatives, some of those proposals might be judged to be more ``divisive'' than others. When designing online participatory platforms to support digital democracy initiatives enabling citizens to deliberate over such proposals, we might wish to equip those pla

Mustafa Bakr

Boundary conditions in confined geometries and measurement interactions in quantum mechanics share a common structural role: both select a preferred basis by determining which states are compatible with the imposed constraint. This paper develops this perspective for circuit QED dispersive readout through a first-principles derivation starting from the circu

Ava Polzin, Katherine E. Whitaker, C. Megan Urry, Henna Abunemeh

Women are consistently underrepresented in astrophysics yet are simultaneously subject to disproportionate attrition at every career stage. This disparity between demonstrated efficacy in job performance and ultimate career outcome was the primary motivation for the Picture an Astronomer series, which included both targeted public outreach to increase repres

Zichang Wang

To a quiver with involution, we show that there is an algebra homomorphism from the corresponding shifted twisted Yangian to the quantized Coulomb branch algebra of the 3d $\mathcal{N}=4$ involution-fixed part of the quiver gauge theory in the second symmetric power case.

Wolfgang Wagner

Thirty years after the first observation of on-shell top quarks the investigation of the heaviest elementary particle remains a thriving field of basic research, as was illustrated by the 18th edition of the annual Workshop on Top-Quark Physics hosted by Hanyang University in Seoul, Korea. Observing new scattering processses involving top quarks, precision m

Yoonha Cha, Victoria Jackson, Lauren Shu, Stacy Branham

The software development workplace poses numerous technical and collaborative accessibility challenges for blind and low vision software professionals (BLVSPs). Though Generative AI (GenAI) is increasingly adopted within the software development industry and has been a rapidly growing topic of interest in research, to date, the unique perspectives of BLVSPs

Seohui Bae, Jeonghye Kim, Youngchul Sung, Woohyung Lim

In this paper, we propose a test-time adaptive agent that performs exploratory inference through posterior-guided belief refinement without relying on gradient-based updates or additional training for LLM agent operating under partial observability. Our agent maintains an external structured belief over the environment state, iteratively updates it via actio

Titas Ramancauskas, Kotryna Ramancauske

This paper presents the design, development, and evaluation of a proposed revision platform assisting candidates for the International English Language Testing System (IELTS) writing exam. Traditional IELTS preparation methods lack personalised feedback, catered to the IELTS writing rubric. To address these shortcomings, the platform features an attractive u

Michael E. Rose, Nils A. Herrmann, Sebastian Erhardt

Scientific abstracts are often used as proxies for the content and thematic focus of research publications. However, a significant share of published abstracts contains extraneous information-such as publisher copyright statements, section headings, author notes, registrations, and bibliometric or bibliographic metadata-that can distort downstream analyses,

Ya Deng

This survey presents recent developments concerning the Shafarevich conjecture, non-abelian Hodge theories, hyperbolicity, and the topology of complex algebraic varieties, as well as the interplay among these areas. More precisely, we present the main ideas and techniques involved in the linear versions of the following conjectures: the Shafarevich conjectur

Adel Daoud, Richard Johansson, Connor T. Jerzak

Text-based causal inference increasingly employs textual data as proxies for unobserved confounders, yet this approach introduces a previously undertheorized source of bias: treatment leakage. Treatment leakage occurs when text intended to capture confounding information also contains signals predictive of treatment status, thereby inducing post-treatment bi

Henrique Lin, Tiago Dias, Miguel Correia

The real estate sector remains highly dependent on manual document handling and verification, making processes inefficient and prone to fraud. This work presents a system that integrates optical character recognition (OCR), natural language processing (NLP), and verifiable credentials (VCs) to automate document extraction, verification, and management. The a

Gentian Zavalani

In this paper, we extend the classical quadrilateral based hierarchical Poincar\'e-Steklov (HPS) framework to triangulated geometries. Traditionally, the HPS method takes as input an unstructured, high-order quadrilateral mesh and relies on tensor-product spectral discretizations on each element. To overcome this restriction, we introduce two complementary h

Sanjay Nayak, Venkata Raveendra Nallagatla, Ravindra Singh Bisht, Dmytro Solonenko

Large-area deposition of Aluminium-Scandium-Nitride (Al1-xScxN) thin films with higher Sc content (x) remains challenging due to issues such as abnormal orientation growth, stress control, and the undesired crystal phase. These anomalies across the wafer hinder the development of high scandium-content AlScN films, which are critical for microelectromechanica

E. K. Berinyuy, P. Djorwé, J. -X. Peng, A. Sohail

In this work, we investigate the dynamics of quantum synchronization in a four-mode optomechanical system, focusing on the influence of the Coulomb interaction between two mechanical resonators. We analyze the effect of the Coulomb coupling on three distinct synchronization regimes, i.e., complete quantum synchronization, $\phi$-synchronization, and quantum

William Paul Heath, Sayar Das, Joaquin Carrasco

Dynamic multipliers can be used to guarantee the stability of Lurye systems with slope-restricted nonlinearities, but give no guarantee that the closed-loop system has finite incremental gain. We show that multipliers guarantee the closed-loop power gain to be bounded and quantifiable. Power may be measured about an appropriate steady state bias term, provid

Yalin E. Sagduyu, Tugba Erpek, Aylin Yener, Sennur Ulukus

Semantic communications conveys task-relevant meaning rather than focusing solely on message reconstruction, improving bandwidth efficiency and robustness for next-generation wireless systems. However, learned semantic representations can still leak sensitive information to unintended receivers (eavesdroppers). This paper presents a deep learning-based seman

Zuoxian Wang, Yuhao Zhang, Gaopu Hou, Zihua Liang

Conventional practice of spatially resolved detection in diffusion-coupled thermal atomic vapors implicitly treat localized responses as mutually independent. However, in this study, it is shown that observable correlations are governed by the intrinsic spatiotemporal covariance of a global spin-fluctuation field, such that spatial separation specifies only

The Tien Mai

Reduced rank regression (RRR) is a fundamental tool for modeling multiple responses through low-dimensional latent structures, offering both interpretability and strong predictive performance in high-dimensional settings. Classical RRR methods, however, typically rely on squared loss and Gaussian noise assumptions, rendering them sensitive to heavy-tailed er