March 2026 arXiv papers — page 53

José Luis Romero, Irina Shafkulovska

Folded sampling replaces clipping in analog-to-digital converters by reducing samples modulo a threshold, thereby avoiding saturation artifacts. We study the reconstruction of bandlimited functions from folded samples and show that, for equispaced sampling patterns, the recovery problem is inherently unstable. We then prove that imposing any a priori energy

Bekir Can Lütfüoğlu

We analyze quasinormal modes, grey-body factors, and absorption cross-sections of a massive scalar field in four-dimensional Einstein--Gauss--Bonnet black-hole spacetimes within a stability-constrained coupling window. High-order WKB-Pad\'e spectra show that increasing field mass typically reduces damping and drives the system toward long-lived, quasi-resona

Sagnik Jana, Yulan Qing

Sublinearly Morse directions in proper geodesic spaces are defined by sublinearly Morse stability. In this paper we offer an alternative characterization for sublinearly Morse geodesic lines via middle recurrence. We then study first passage percolation (FPP) on proper geodesic graphs of bounded degree. We associate an i.i.d. collection of random passage tim

Ben Chugg, Aaditya Ramdas, Peter Grünwald

A recurring debate in the philosophy of statistics concerns what, exactly, should count as a measure of evidence for or against a given hypothesis. P-values, likelihood ratios, and Bayes factors all have their defenders. In this paper we add two additional candidates to this list: the e-value and its sequential analogue, the e-process. E-values enjoy several

David Albandea, Simon Kuberski, Fernando P. Panadero

Computing derivatives of observables with respect to parameters of the theory is a powerful tool in lattice QCD, as it allows the study of physical effects not directly accessible in the original Monte Carlo simulation. Prominent examples of this include the impact of the up-down quark mass difference and electromagnetic corrections. In this work, we present

Tao Tan, Rui Xie, Meng Yang, Yue Chen

The rapid deployment of distributed energy resources (DERs) is one of the essential efforts to mitigate global climate change. However, a vast number of small-scale DERs are difficult to manage individually, motivating the introduction of virtual power plants (VPPs). A VPP operator coordinates a group of DERs by setting suitable prices, and aggregates them f

E. Chan-López, A. Martín-Ruiz, Víctor Castellanos

We prove that the critical structure of the prey nullcline governs where oscillatory instabilities can emerge in planar predator--prey systems. For a broad class of Gause--type models, we establish a general geometric localization theorem: the prey coordinate of every Hopf bifurcation point is confined between consecutive critical points of the prey nullclin

Andrey V. Shanin, Valentin D. Kunz, Raphael C. Assier

We propose an extension of the plane-wave representation for wave fields defined on the real sphere $\mathcal{S}^2$. This representation is well-known in the planar setting but has never been developed for curved surfaces. To achieve this, we need to carefully study the geometry of the complexification of $\mathcal{S}^2$ and the properties of the Laplace--Be

Y. Liebsch, U. Javed, L. Skopinski, L. Daniel

Ion irradiation is a versatile tool for nanostructuring surfaces, yet the roles of energy deposition and dissipation at the surface and in ultrathin materials remain poorly understood. In this study, we investigate nanopore formation in monolayer MoS$_2$ on different substrates under irradiation of highly charged ions (HCIs) and swift heavy ions (SHIs): two

Tim Bürchner, Simon Schmid, Ernst Rank, Stefan Kollmannsberger

Accurate modeling of ultrasound wave propagation is essential for high-fidelity simulation and imaging in ultrasonic testing. A primary challenge lies in characterizing the excitation source, particularly for transducers with large apertures relative to the acoustic wavelengths. In such cases, non-uniform excitation and spatial interference significantly aff

Songyang Liu, Chaozhuo Li, Chenxu Wang, Jinyu Hou

OpenClaw has rapidly established itself as a leading open-source autonomous agent runtime, offering powerful capabilities including tool integration, local file access, and shell command execution. However, these broad operational privileges introduce critical security vulnerabilities, transforming model errors into tangible system-level threats such as sens

Xinyang Li, Lumen Eek, Jasper van Wezel, Cristiane Morais Smith

We investigate topological phase transitions for the Haldane and Kane-Mele model in a lattice with $p6$ symmetry, which consists of triangles and hexagons arranged in a two-dimensional geometry. For the Haldane model, which breaks time-reversal symmetry, we calculate the Chern number using a multi-band non-Abelian Wilson loop formalism. By varying the hoppin

Volodymyr Yelahin, Mykola Moroz

We investigate a class of locally complicated self-affine functions defined via the $Q_s$-representation of real numbers. In particular, we compute local H\"older exponents at points with given asymptotic frequencies of digits in their $Q_s$-representation. Furthermore, we establish conditions under which these functions possess continuum level sets. Finally

Shahram Chaudhry, Sidahmed Benabderrahmane, Talal Rahwan

Virtual influencers~(VIs) -- digitally constructed social-media personas -- are becoming increasingly visible in online culture, marketing, and identity formation. Yet it remains unclear whether audiences respond to them through the same discourse patterns used for human influencers~(HIs), or whether virtuality produces distinctive modes of reaction. Existin

Karol Urbański

This article provides a gentle, visual introduction to the basic concepts of differential geometry appropriate for students familiar with special relativity. Visual methods are used to explain basics of differential geometry and build intuition for all types of Riemannian and Lorentzian manifolds of constant curvature. A visual derivation of the Thomas prece

Jean Barron, Frédéric Schmidt, François Andrieu, Gaku Nishiyama

Recent laser altimeters are able to not only measure the ranging distance between the spacecraft and the surface but also the full time-of-flight of the photons or pulse shape. This new capabilities allows to measure the intra-footprint properties: surface slope distribution and surface microtexture. Here we simulate and discuss for the first time the effect

Ching-Lam Cheng, Bin Zhu, Shengfeng He

Generating realistic 3D hand motion from natural language is vital for VR, robotics, and human-computer interaction. Existing methods either focus on full-body motion, overlooking detailed hand gestures, or require explicit 3D object meshes, limiting generality. We propose TSHaMo, a model-agnostic teacher-student diffusion framework for text-driven hand moti

Marc Technau

Given a polynomial $\sum_\nu a_\nu X^\nu$ of degree $<d$, bounded by one on the unit disk, how large can $\lvert a_0+a_1+\ldots+a_n \rvert$ ($n<d$) get? This question dates back at least to the 1952 thesis work of H. S. Shapiro. In 1978, D. J. Newman gave an exact answer for $d=2(n+1)$, but there does not seem to have been further progress on the question si

Charles Jones, Emmanuel Noutahi, Jason Hartford, Cian Eastwood

Flow-matching generative models are increasingly used to simulate cell responses to biological perturbations. However, the design space for building such models is large and underexplored. We systematically analyse the design space of flow matching models for cell-microscopy images, finding that many popular techniques are unnecessary and can even hurt perfo

Erik Leffler

Let $\mathbb{K}$ be an algebraically closed field, and $A \subset \mathbb{K}[x_{1}, \ldots, x_n]$ be a subalgebra of finite codimension. It is known that there exists a (not necessarily unique) finite filtration of $\mathbb{K}$-algebras \[ A = A_{0} \subset A_{1} \subset \ldots \subset A_m = \mathbb{K}[x_{1}, \ldots, x_n], \] where each $A_i$ can be written

Yunbo Long

Existing automated research systems operate as stateless, linear pipelines -- generating outputs without maintaining any persistent understanding of the research landscape they navigate. They process papers sequentially, propose ideas without structured gap analysis, and lack mechanisms for agents to verify, challenge, or refine each other's findings. We pre

L. Pescatore

We prove the global well-posedness of the one-dimensional Navier-Stokes-Korteweg equations driven by a stochastic multiplicative noise. The analysis is performed for the general case of capillarity and viscosity coefficients $k(\rho)= \rho^\beta, \, \beta \in \mathbb{R},\, \mu(\rho)=\rho^\alpha, \, \alpha \ge 0,$ which are not coupled through a BD relation.

Jade Nardi, Rodrigo San-José

We provide a comprehensive overview of the fundamental structural properties of weighted projective Reed-Muller codes. We give a recursive construction for these codes, under some conditions for the weights, and we use it to derive bounds on the generalized Hamming weights and to obtain a recursive construction for their subfield subcodes and their dual code

Bjørnar Vassøy, Benjamin Kille, Helge Langseth

One of the many fairness definitions pursued in recent recommender system research targets mitigating demographic information encoded in model representations. Models optimized for this definition are typically evaluated on how well demographic attributes can be classified given model representations, with the (implicit) assumption that this measure accurate

Niels Benedikter

In recent years it has been shown how approximate bosonization can be used to justify the random phase approximation for the correlation energy of interacting fermions in a mean-field scaling limit. At the core is the interpretation of particle-hole excitations close to the Fermi surface at bosons. The main two approaches however differ in emphasizing collec

Qian Zhong

Extended $\gamma$-ray emission has been observed around several nearby pulsars and is commonly interpreted as inverse-Compton radiation produced by relativistic electrons and positrons diffusing in the surrounding interstellar medium. In this work, a unified analysis of the halos associated with the Geminga and Monogem pulsars is presented, combining GeV--Te

Bin Yu, Shijie Lian, Xiaopeng Lin, Zhaolong Shen

Vision-Language-Action (VLA) models leverage Multimodal Large Language Models (MLLMs) for robotic control, but recent studies reveal that MLLMs exhibit limited spatial intelligence due to training predominantly on 2D data, resulting in inadequate 3D perception for manipulation tasks. While recent approaches incorporate specialized 3D vision models such as VG

Gengyu Xue, Yi Yu

Privacy and algorithmic fairness have become two central issues in modern machine learning. Although each has separately emerged as a rapidly growing research area, their joint effect remains comparatively under-explored. In this paper, we systematically study the joint impact of differential privacy and fairness on classification in a federated setting, whe

Jeongju Park, Musu Kim, Sekyung Han

As artificial intelligence assumes cognitive labor, no quantitative framework predicts when human capability loss becomes catastrophic. We present a two-variable dynamical systems model coupling capability (H) and delegation (D), grounded in three axioms: learning requires capability, practice, and disuse causes forgetting. Calibrated to four domains (educat

Saswata Goswami, Guilherme S. L. Fabris, Diganta Mondal, Raphael B. de Oliveira

Dopamine levels are linked to neurological illnesses like Parkinson's and Alzheimer's. Thus, reliable and sensitive detection of dopamine is crucial for early diagnosis and surveillance of neurodegenerative diseases. Non-noble-metal-based nanomaterials are ideal for light-mediated sensing of organic molecules. Among these, 2D quasicrystal structures consisti

Xingming Li, Runke Huang, Yanan Bao, Yuye Jin

High-quality teacher-child interaction (TCI) is fundamental to early childhood development, yet traditional expert-based assessment faces a critical scalability challenge. In large systems like China's-serving 36 million children across 250,000+ kindergartens-the cost and time requirements of manual observation make continuous quality monitoring infeasible,

Danila Gorodecky

This technical note presents a algorithmic approach for generating optimal sets of co-prime moduli within specified integer ranges. The proposed method addresses the challenge of balancing moduli bit-lengths while maximizing the dynamic range in Residue Number System (RNS) implementations. Experimental results demonstrate that the generated moduli sets achie

Zhongweiyang Xu, Ashutosh Pandey, Juan Azcarreta, Zhaoheng Ni

Multi-channel speech enhancement aims to recover clean speech from noisy multi-channel recordings. Most deep learning methods employ discriminative training, which can lead to non-linear distortions from regression-based objectives, especially under challenging environmental noise conditions. Inspired by ArrayDPS for unsupervised multi-channel source separat

Kristóf Péter, Ricardo J. G. B. Campello, James Bailey, Michael E. Houle

The theory of Local Intrinsic Dimensionality (LID) has become a valuable tool for characterizing local complexity within and across data manifolds, supporting a range of data mining and machine learning tasks. Accurate LID estimation requires samples drawn from small neighborhoods around each query to avoid biases from nonlocal effects and potential manifold

Songjin Cai, Linjie Zhong, Ling Guo, Changxing Ding

Generating realistic and physically plausible 3D Human-Object Interactions (HOI) remains a key challenge in motion generation. One primary reason is that describing these physical constraints with words alone is difficult. To address this limitation, we propose a new paradigm: extracting rich interaction priors from easily accessible 2D images. Specifically,

Xiangsen Chen, Ruilong Wu, Yanyan Lan, Ting Ma

Despite deep learning's success in chemistry, its impact is hindered by a lack of interpretability and an inability to resolve activity cliffs, where minor structural nuances trigger drastic property shifts. Current representation learning, bound by the similarity principle, often fails to capture these structural-activity discontinuities. To address this, w

Martina Alutto, Lorenzo Zino, Karl H. Johansson, Angela Fontan

Leadership in social groups is often a dynamic characteristic that emerges from interactions and opinion exchange. Empirical evidence suggests that individuals with strong opinions tend to gain influence, at the same time maintaining alignment with the social context is crucial for sustained leadership. Motivated by the social psychology literature that supp

Wenrui Kong

We study higher-order curvature estimates along K\"ahler-Ricci flows on compact K\"ahler manifolds of intermediate Kodaira dimension. We prove that away from singular fibers, the Ricci curvature is uniformly bounded in $C^1$, the Laplacian of the Ricci curvature in $C^0$, and the scalar curvature in $C^2$. We identify a geometric obstruction to higher-order

A. Kotsovolou, F. Soofivand, P. Singha, D. Cecca

Hybrid superconductor/semiconductor devices play a crucial role in advancing quantum science and technology by merging the properties of superconductors and semiconductors. To operate these devices at high temperature, Niobium could substitute the widespread aluminum as superconducting element. Niobium devices show the best superconducting properties when sh

Haiyang Zheng, Nan Pu, Yaqi Cai, Teng Long

Generalized Category Discovery (GCD) leverages labeled data to categorize unlabeled samples from known or unknown classes. Most previous methods jointly optimize supervised and unsupervised objectives and achieve promising results. However, inherent optimization interference still limits their ability to improve further. Through quantitative analysis, we ide

Joe H. N. Pattison, John M. Cumner, Dominic J. Anstey, Saurabh Pegwal

The redshifted 21 cm absorption trough from cosmic atomic hydrogen is one of the most promising probes of the early Universe, but its detection is challenged by bright foregrounds and instrumental systematics. In this work we quantify the impact of antenna mismodelling on signal recovery within a fully Bayesian, forward-modelled data analysis pipeline. We sh

Philipp Stammer, Camilo Granados, Javier Rivera-Dean

Symmetries are ubiquitous in physics and play a pivotal role in light-matter interactions, where they determine the selection rules governing allowed atomic transitions and define the associated conserved quantities. For the up-conversion process of high harmonic generation, the symmetries of the driving field determine the allowed frequencies and the polari

Pengyue Jia, Derong Xu, Yingyi Zhang, Xiaopeng Li

Worldwide image geolocalization aims to predict precise GPS coordinates for images captured anywhere on Earth, which is challenging due to the large visual and geographic diversity. Recent methods mainly follow two paradigms: retrieval-based approaches that match queries against a reference database, and generation-based approaches that directly predict coor

Mohammad AL-Smadi

Clinical trials require strict adherence to medication protocols, yet dosing errors remain a persistent challenge affecting patient safety and trial integrity. We present an automated system for detecting dosing errors in unstructured clinical trial narratives using gradient boosting with comprehensive multi-modal feature engineering. Our approach combines 3

Kseniia Petukhova, Ekaterina Kochmar

Evaluating the pedagogical quality of AI tutors remains challenging: standard NLG metrics do not determine whether responses identify mistakes, scaffold reasoning, or avoid revealing the answers. For the task of mistake remediation, we derive a hierarchy of pedagogical aspects from human pairwise preferences on MRBench, and synthesize minimally contrastive r

Bijit Kumar Banerjee, Devabrat Sharma, Mahen Konwar, Simanta Das

Hourly rainfall extremes cause some of the most destructive weather disasters, yet numerical weather prediction models still struggle to forecast them, and a physical basis for their predictability remains unclear. Here, we identify a trivariate clustering of hourly rainfall extremes with surface temperature, phases of the Monsoon Intraseasonal Oscillation (

Cheng Cui, Yubo Zhang, Ting Sun, Xueqing Wang

The advent of "OCR 2.0" and large-scale vision-language models (VLMs) has set new benchmarks in text recognition. However, these unified architectures often come with significant computational demands, challenges in precise text localization within complex layouts, and a propensity for textual hallucinations. Revisiting the prevailing notion that model scale

Arsen Shebzukhov

Autoformalization - automatically translating natural language mathematical texts into formal proof language such as Lean4 - can help accelerate AI-assisted mathematical research, be it via proof verification or proof search. I fine-tune Qwen3.5-2B with LoRA for natural language to Lean4 formalization on FineLeanCorpus and consider three training regimes: su

Baidong Wu, Fiza Khan, Lingya Yu, Zengbo Wang

We present the first systematic comparison of three TiO2 metamaterial solid immersion lens geometries - sub-hemispherical, super-hemispherical, and full-spherical - for label-free super-resolution imaging. Using SEM, we characterised both the cap profiles and the nanoparticle-fluid immersion at the lens-sample interface, revealing that super-hemispherical le

Paul Leask

This paper introduces soliton_solver, an open-source GPU-accelerated software package for the simulation and real-time visualization of topological solitons in two-dimensional non-linear field theories. The software is structured around a theory-agnostic numerical core implemented using Numba CUDA kernels, while individual physical models are introduced thro

Javier Durán-Micco, Bilge Atasoy

This paper addresses the Service Network Design (SND) problem for a logistics service provider (LSP) operating in a multimodal freight transport network, considering uncertain travel times and limited truck fleet availability. A two-stage optimization approach is proposed, which combines metaheuristics, simulation and machine learning components. This soluti

Soufiane Bentout, Hoang-Hung Vo

We study a nonlocal SIS epidemic model with free boundaries, advection, and spatial heterogeneity, where the dispersal kernels are not assumed to be symmetric. The model describes the evolution of susceptible and infected populations in a bounded infected habitat whose endpoints move according to nonlocal boundary fluxes. Our goal is to determine the sharp t

S. K. Saroj, P. K. Panigrahi

The present study examines evaporative cooling and the resulting deposition patterns of a sessile $Al_2O_3$-based nanofluid droplet on a hydrophobic glass substrate at different temperatures. Evaporation predominantly occurs in the pinned contact line mode for both heated and non-heated cases, with only slight recession observed without heating. The droplet

Yifeng Zhang, Harsh Goel, Peizhuo Li, Mehul Damani

Adaptive traffic signal control (ATSC) is crucial in alleviating congestion, maximizing throughput and promoting sustainable mobility in ever-expanding cities. Multi-Agent Reinforcement Learning (MARL) has recently shown significant potential in addressing complex traffic dynamics, but the intricacies of partial observability and coordination in decentralize

Debadutta Patra, Ayush Bardhan Tripathy, Soumya Ranjan Sahu, Sucheta Panda

Digital twin technology, when combined with physics-informed machine learning with simulation results of Aspen, offers transformative capabilities for industrial process monitoring, control, and optimization. In this work, the proposed model presents a Physics-Informed Neural Network (PINN) digital twin framework for the dynamic, tray-wise modeling of binary

Dewmini Hasara Wickremasinghe, Michelle Gibogwe, Andrew Bell, Esther Puyol-Antón

The performance of deep learning (DL) methods for the analysis of cine cardiovascular magnetic resonance (CMR) is typically assessed in terms of accuracy, overlooking precision. In this work, uncertainty estimation techniques, namely deep ensemble, test-time augmentation, and Monte Carlo dropout, are applied to a state-of-the-art DL pipeline for cardiac func

Ankita Kakoti

Left-Right Symmetric theory has proved to be one of the most successful models in explaining the origin of neutrino mass and mixings, and the phenomenological origin of neutrinoless double beta decay, lepton flavor violation as well as leptogenesis within its regime. In the current work, left-right symmetric model has been extended with a sterile neutrino pe

Lorenzo Piu, Heinz Pitsch, Alessandro Parente

In the field of computational fluid dynamics, direct numerical simulations generate highly detailed data for the analysis of turbulent flows by resolving all relevant physical scales. Yet their large size, complexity, and heterogeneity make systematic post-processing and data reuse increasingly challenging. Despite the growing availability of high-fidelity s

Yifeng Zhang, Peizhuo Li, Tingguang Zhou, Mingfeng Fan

Adaptive Traffic Signal Control (ATSC) aims to optimize traffic flow and minimize delays by adjusting traffic lights in real time. Recent advances in Multi-agent Reinforcement Learning (MARL) have shown promise for ATSC, yet existing approaches still suffer from limited representational capacity, often leading to suboptimal performance and poor generalizatio

Ian Störmer, Julija Zavadlav

Solidification governs the microstructure and, therefore, the mechanical response of metal components, yet the atomistic details of nucleation and defect formation are often difficult to determine experimentally. Molecular dynamics can bridge this gap, but only if the interatomic model is both accurate and computationally efficient. Here, we develop a Machin

Lynn Janzen, Üveys Eroglu, Dorothea Kolossa, Pia Knöferle

LLMs are increasingly embedded in programming workflows, from code generation to automated code review. Yet, how gendered communication styles interact with LLM-assisted programming and code review remains underexplored. We present a mixed-methods pilot study examining whether gender-related linguistic differences in prompts influence code generation outcome

Mohammadreza Jamalifard, Yaxiong Lei, Parasto Azizinezhad, Javier Fumanal-Idocin

We propose a neuro-symbolic architecture that learns four interpretable physiological concepts, oculomotor dynamics, gaze stability, prefrontal hemodynamics, and multimodal, from eye-tracking and neural hemodynamics, functional near-infrared spectroscopy, (fNIRS) windows using attention-based encoders, and combines them with differentiable approximate reason

Michael Menke

We derive a Riemannian metric on three-dimensional color space from the Fisher information of neural population codes in the visual pathway. Photoreceptor adaptation, retinal opponent channels, and cortical population encoding each map onto a geometric construction, producing a metric tensor whose components correspond to measurable neural quantities. The re

Min Zhang

Camouflaged Object Detection (COD) aims to segment objects that are highly integrated with the background in terms of color, texture, and structure, making it a highly challenging task in computer vision. Although existing methods introduce multi-scale fusion and attention mechanisms to alleviate the above issues, they generally lack the guidance of textual

Vladimir Belavin, Juan Ramos Cabezas, Boris Runov

In this work, we continue the investigation of correlation numbers in $\mathcal{N}=1$ super Minimal Liouville Gravity (SMLG), with physical fields in the Ramond sector. Building upon our previous construction of physical operators and the evaluation of three-point correlation functions involving Ramond and Neveu-Schwarz (NS) insertions, we now turn to the an

Thomas Forbriger, Felix Münch, Laura Hillmann, Verónica Rodríguez Tribaldos

A rigid connection between the optical fiber and the rock makes amplitudes of 'fiber strain' measured with Distributed Acoustic Sensing (DAS) equal to 'rock strain'. We demonstrate this by running four interrogator units (IU) on a DAS testbed with single-fiber patch cables being cemented into a groove in the concrete floor of Black Forest Observatory (BFO).

Iury Domingos, Ranilze da Silva, Alexandre de Sousa, Feliciano Vitório

Tashiro and Tachibana proved that there exist no totally umbilical hypersurfaces in complex space forms with nonzero constant holomorphic sectional curvature, and it is also known that the shape operator of such hypersurfaces cannot be parallel. Motivated by these results, we study real hypersurfaces in products of complex space forms. We establish rigidity

Marcelo Righi, Rodrigo Targino

We develop an averaging approach to robust risk measurement under payoff uncertainty. Instead of taking a worst-case value over an uncertainty neighborhood, we weight nearby payoffs more heavily under a chosen metric and average the baseline risk measure. We prove continuity in the neighborhood radius and provide a stable large-radius behavior. In Banach lat

Qi An, Yan Shao, Zhen-hua Zhao

In this paper, we investigate leptogenesis under the neutrino mass anarchy hypothesis in both type-I and type-II seesaw models. We first revisit the corresponding study in the type-I seesaw framework with two improvements: in contrast to Ref.[25], where an approximate $U(1)$ flavor symmetry was imposed to ensure sizable hierarchies among the right-handed neu

Wouter Montfrooij

Our electronic structure theory for crystalline solids is commonly built on the periodic potential assumption $V(\mathbf r)=V(\mathbf r+\mathbf R)$ for every lattice translation $\mathbf R$, enabling Bloch eigenstates, crystal momentum as a good quantum number, and the standard quasiparticle-based description of the behavior of metals. Because the zero-point

Moorad Alexanian

A recently introduced recurrence-relation ansatz applied to the Bose-Hubbard model is here used in the generalized Aubry-Andre model. The resulting modified Aubry-Andre model allows for a simple parametrization of the solutions in terms of three parameters, viz., the system energy when the quasiperiodicity amplitude Delta = 0, the site mu where the particle

Yang He, Zigui Zhang, Zibo Miao

The performance of quantum processors in the noisy intermediate-scale quantum (NISQ) era is severely constrained by environmental noise and other uncertainties. While the recently proposed quantum control robustness landscape (QCRL) offers a powerful framework for generating robust control pulses for parametric gate families, its application has been practic

R. Terra, A. V. Giannini, F. S. Navarra

Going from lower to higher multiplicity events in proton-proton and proton-lead collisions, the data show a stronger than linear growth of the D-meson normalized yields. In this contribution we try to understand this behavior using a Monte Carlo event generator which implements the $k_T$-factorization formalism. We use different spatial distribution of matte

Yupei Li, Shuaijie Shao, Manuel Milling, Björn Schuller

Current audio deepfake detection has achieved remarkable performance using diverse deep learning architectures such as ResNet, and has seen further improvements with the introduction of large models (LMs) like Wav2Vec. The success of large language models (LLMs) further demonstrates the benefits of scaling model parameters, but also highlights one bottleneck

Lech Pasicki

In this note a criterion for Cauchy sequences is proved which refines the one presented in `Cauchy sequences in b-metric spaces', Topology Appl. 373 (2025) 109477.

C. Lehr, T. Aumann, M. Duer, A. T. Saito

The weak binding and spatially extended neutron densities characteristic of drip-line nuclei give rise to a distinctive low-energy dipole response. The drip-line nucleus $^8$He is the most neutron-rich bound nucleus with a mass-to-charge ratio of $A/Z=4$. We measure the dipole response of $^8$He, including for the first time the four-neutron decay channel. A

I. Boradjiev, A. Adamczak, D. Bakalov, M. Baruzzo

In the present study we determine from the available experimental data the cross section of muon transfer to molecular oxygen at low energies with account of the oxygen molecule structure. Building on an earlier work, the results highlight the role of the molecular structure effects and signifcantly improve the agreement with theoretical calculations of the

Jan Tiemann, Matthew McGinity, Ulrik Günther

In contemporary biology and medicine, 3D microscopy is one of the most widely-used techniques for imaging and manipulation of various kinds of samples. Navigating such a micrometer-sized, 3-dimensional sample under the microscope -- e.g. to find relevant imaging regions -- can pose a tedious challenge for the experimenter. In this paper, we examine whether 2

Anne Driemel, Jan Höckendorff, Ioannis Psarros, Christian Sohler

Given a finite metric space $(X\cup Y, \mathbf{d})$ the $k$-median problem is to find a set of $k$ centers $C\subseteq Y$ that minimizes $\sum_{p\in X} \min_{c\in C} \mathbf{d}(p,c)$. In general metrics, the best polynomial time algorithm computes a $(2+\epsilon)$-approximation for arbitrary $\epsilon>0$ (Cohen-Addad et al. STOC 2025). However, if the metric

Raphael Morisco

The knowledge gap hypothesis suggests that the diffusion of information tends to increase rather than reduce social inequalities. Subsequent research on the digital divide has extended this perspective by focusing on unequal access to and use of digital technologies. The emergence of generative artificial intelligence raises the question of whether these fra

Yanwei Xiong, Martin Centurion

Anisotropic two-dimensional diffraction signals encode additional structural information, including atom-pair angular distributions, beyond conventional isotropic scattering. However, experimental constraints such as beam stops result in missing low-angle scattering data, which limits accurate real-space reconstruction. We develop an iterative algorithm to r

Leihao Chen

Recently, Forr\'e (arXiv:2104.11547, 2021) introduced transitional conditional independence, a notion of conditional independence that provides a unified framework for both random and non-stochastic variables. The original paper establishes a strong global Markov property connecting transitional conditional independencies with suitable graphical separation c

M. Galinier, C. Avdellidou, M. Delbo, L. Galluccio

Erg Chech 002 is an andesitic meteorite that formed early in the Solar System's history, and that is thought to have been formed in the primitive crust of an early accreted and differentiated planetesimal. It shows unique spectral features, and no known asteroid spectral type was initially found to match with its compositional type. In the literature, astero

Ashvin Swaminathan

We determine the squarefree part of the scalar factor that arises when the quartic invariant of the generic binary form $F$ of odd degree $2n+1$ is expressed as the discriminant of the unique quadratic covariant $(F,F)_{2n}$. This squarefree part is exactly $p$ when $n+2$ is a power of an odd prime $p$, and $1$ otherwise. Equivalently, for each prime $p$: $v

Yunzhe Wang, Runhui Xu, Kexin Zheng, Tianyi Zhang

Multimodal LLMs are increasingly deployed as perceptual backbones for autonomous agents in 3D environments, from robotics to virtual worlds. These applications require agents to perceive rapid state changes, attribute actions to the correct entities, and reason about concurrent multi-agent behaviors from a first-person perspective, capabilities that existing

Ping Zhang, Rui Meng, Xiaodong Xu, Yaheng Wang

The International Telecommunication Union (ITU) identifies "Artificial Intelligence (AI) and Communication" as one of six key usage scenarios for 6G. Agentic AI, characterized by its ca-pabilities in multi-modal environmental sensing, complex task coordination, and continuous self-optimization, is anticipated to drive the evolution toward agent-based communi

Ciem Cornelissen, Sam Leroux, Pieter Simoens

Self-supervised learning has emerged as a powerful paradigm for learning visual representations without manual annotations, yet most methods still operate on a single modality and therefore miss the complementary structure available from heterogeneous sensors. We present Le MuMo JEPA, a self-supervised framework that learns unified representations from RGB i

Cheng Cui, Ting Sun, Suyin Liang, Tingquan Gao

Document parsing is a fine-grained task where image resolution significantly impacts performance. While advanced research leveraging vision-language models benefits from high-resolution input to boost model performance, this often leads to a quadratic increase in the number of vision tokens and significantly raises computational costs. We attribute this inef

Lutz Terfloth, Heike M. Buhl, Vivien Lohmer, Michael Schaffer

Purpose: Understanding a technical artifact requires grasping both its internal structure (Architecture) and its purpose and significance (Relevance), as formalized by Dual Nature Theory. This controlled experimental study investigates whether how explainers address these perspectives affects explainees' understanding. Methods: In a between-subjects experime

Fatemeh Fazel Hesar, Mojtaba Raouf, Amirmohammad Chegeni, Peyman Soltani

We present an innovative, cost-effective framework integrating laboratory Hyperspectral Imaging (HSI) of the Bechar010 Lunar meteorite with ground-based lunar HSI and supervised Machine Learning(ML) to generate high-fidelity mineralogical maps. A 3mm thin section of Bechar010 was imaged under a microscope with a 30mm focal length lens at 150mm working distan

Shiqin Wang, Haoyang Chen, Huaizhou Huang, Yinkan He

The learning order of semantic classes significantly impacts unsupervised domain adaptation for semantic segmentation, especially under adverse weather conditions. Most existing curricula rely on handcrafted heuristics (e.g., fixed uncertainty metrics) and follow a static schedule, which fails to adapt to a model's evolving, high-dimensional training dynamic

Shoeb Joarder, Mohamed Amine Chatti, Louis Born

Self-Service Learning Analytics (SSLA) tools aim to support educational stakeholders in creating learning analytics indicators without requiring technical expertise. While such tools promise user control and trans- parency, their effectiveness and adoption depend critically on usability aspects. This paper presents a compre- hensive usability evaluation and

Igor S. Sergeev

This article provides a survey of circuit complexity bounds for basic boolean transforms exploited in digital circuit design and efficient methods for synthesizing such circuits. The exposition covers structurally simple functions and operators, such as counters, adders, encoders, and multiplexors, and excludes more complex algebraic operations with numbers,

Davood Soleymanzadeh, Ivan Lopez-Sanchez, Hao Su, Yunzhu Li

State-of-the-art generalist manipulation policies have enabled the deployment of robotic manipulators in unstructured human environments. However, these frameworks struggle in cluttered environments primarily because they utilize auxiliary modules for low-level motion planning and control. Motion planning remains challenging due to the high dimensionality of

Pablo Blanco, Doron Zeilberger

We first fully implement, in Maple, the ingenious method of Robert Stoyan and Volker Strehl from 1995 to automatically derive generating functions for the number of Hamiltonian cycles in an m by n grid graph ,for a fixed width m, but general length n, and actually compute these generating functions for all m up to ten. We also show how to generate a uniforml

Fengxiang Zhao, Yaqing Yang, Yibing Chen, Kun Xu

This study presents a high-order finite volume scheme capable of large time-step integration for three-temperature radiation diffusion (3TRD) equations, where conservation is naturally achieved through energy update. To handle local large gradients and discontinuities in temperature, a central generalized ENO (GENO) reconstruction is developed for diffusion

Igor V. Nikolaev

We introduce a zeta function counting imaginary quadratic number fields by their class numbers. It is proved that such a function is rational depending only on the eight roots of unity of degrees $1$ and $2$. As a corollary, one gets a lower bound $2p$ for the number of imaginary quadratic fields of the prime class number $p$. Our method is based on the stud

Zhihong Yao, Yi Yu, Yunxia Wu, Hao Li

The time-space (TS) traffic diagram serves as a crucial tool for characterizing the dynamic evolution of traffic flow, with its resolution directly influencing the effectiveness of traffic theory research and engineering applications. However, constrained by monitoring precision and sampling frequency, existing TS traffic diagrams commonly suffer from low re

Kumar Ghosh

Quantum magnets in the $M\mathrm{Nb_2O_6}$ and BaCo$_2$V$_2$O$_8$ families realise frustrated transverse-field Ising models whose competing ferromagnetic and antiferromagnetic couplings generate a sign problem provably intractable for quantum Monte Carlo at any system size, leaving their quantum phase boundaries numerically Inaccessible. Using a D-Wave Advan

Sergi Burniol Clotet, Françoise Dal'Bo

We exhibit orbits of the geodesic flow on a hyperbolic surface with at least one cusp such that every tubular neighborhood contains uncountably many distinct geodesic flow orbits. The proof relies on new phenomena, namely the existence of strong stable sets in the dynamical sense that do not coincide with the stable horocycles. When the surface has finite vo