March 2026 arXiv papers — page 62

Michael Krebsbach, Florentin Reiter, Thomas Wellens, Hagen-Henrik Kowalski

Generative quantum machine learning models are trained to deduce the probability distribution underlying a given dataset, and to produce new, synthetic samples from it. The majority of such models proposed in the literature, like the Quantum Circuit Born Machine (QCBM), fundamentally work on a binary level. Real-world data, however, is often numeric, requiri

Nathan McDonald, Colyn Seeley, Christian Brazeau

Cognitive map learners (CML) have been shown to enable hierarchical, compositional machine learning. That is, interpedently trained CML modules can be arbitrarily composed together to solve more complex problems without task-specific retraining. This work applies this approach to control the movement of a multi-jointed robot arm, whereby each arm segment's a

Hanzhong Zhang, Siyang Song, Jindong Wang

While large language models simulate social behaviors, their capacity for stable stance formation and identity negotiation during complex interventions remains unclear. To overcome the limitations of static evaluations, this paper proposes a novel mixed-methods framework combining computational virtual ethnography with quantitative socio-cognitive profiling.

Jiacheng Hua, Yishu Yin, Yuhang Wu, Tai Wang

Existing Multimodal Large Language Models (MLLMs) struggle with 3D spatial reasoning, as they fail to construct structured abstractions of the 3D environment depicted in video inputs. To bridge this gap, drawing inspiration from cognitive theories of allocentric spatial reasoning, we investigate how to enable MLLMs to model and reason over text-based spatial

Ryosuke Yoshii, Rio Oto

We study the Kondo effect induced by a topological soliton in a one-dimensional Dirac system with the sign-changing mass term. The soliton hosts a localized zero mode whose spatially extended wavefunction leads to a momentum-dependent exchange coupling with itinerant electrons. We show that this structure generates a nontrivial form factor that suppresses hi

Amlan Datta, Bicky S. Moirangthem, Kamal R. Joshi, Anthony P. Mcfadden

Niobium is a practical material platform for superconducting microwave circuits; however, device-level performance can vary significantly depending on film growth and processing conditions. We compare three epitaxial Nb films grown on $c-$plane sapphire substrates under nominally identical conditions, except for the deposition temperature. To correlate inter

Antoine Martinez, Balthazar Donon, Louis Wehenkel, Efthymios Karangelos

Changing the transmission system topology is an efficient and costless lever to reduce congestion or increase exchange capacities. The problem of finding the optimal switch states within substations is called Optimal Substation Reconfiguration (OSR), and may be framed as a Mixed Integer Linear Program (MILP). Current state-of-the-art optimization techniques

Giacomo Trupiano, Giorgio De Simoni, Francesco Giazotto

We introduce a zero-bias superconducting voltage amplifier that harvests energy from a thermal gradient by exploiting negative differential resistance (NDR) in an asymmetric tunnel junction. The device is based on an asymmetric superconductor-insulator-superconductor (SIS) junction with an energy-gap ratio of $\Delta_1/\Delta_2 = 0.5$, connected in series wi

Neil K. Chada, Lu Yu

Constrained sampling is an important and challenging task in computational statistics, concerned with generating samples from a distribution under certain constraints. There are numerous types of algorithm aimed at this task, ranging from general Markov chain Monte Carlo, to unadjusted Langevin methods. In this article we propose a series of new sampling alg

Nicole Looper, Jit Wu Yap

Let $k$ be a field of characteristic $0$ and let $K = k(B)$ be the function field of a geometrically irreducible projective curve $B$ over $k$. Let $A/K$ be a $g$-dimensional abelian variety with $\mathrm{Tr}_{K/k}(A) = 0$. We prove that any $K$-rational torsion point $x$ of $A$ has order uniformly bounded in terms of $g$ and the gonality of $B$. We also pro

Stefan Antusch, Ivo de Medeiros Varzielas, Miguel Levy

Explaining the observed charged fermion mass hierarchies points to flavour symmetries inducing a suppression of the lighter species' masses. When the symmetries are global, it is expected that such symmetries are broken by gravity via Planck scale suppressed effective operators. The potential of the spontaneous symmetry-breaking "flavon" field, if the symmet

Ruifeng Zheng, Zhihan Xu, Veronika Volkova, Pengjie Zhou

In this paper, we study DNA-based molecular communication with microarray-style reception under reversible hybridization, where the bound-state observation exhibits both inter-symbol interference and colored counting noise. To capture these effects in a communication-oriented form, we develop a Markov state-space framework based on a voxelized reaction--diff

Harsh Yadav, Christian Bohn, Tobias Meisen

Current open-loop trajectory models struggle in real-world autonomous driving because minor initial deviations often cascade into compounding errors, pushing the agent into out-of-distribution states. While fully differentiable closed-loop simulators attempt to address this, they suffer from shortcut learning: the loss gradients flow backward through induced

Imad Limame, Ching-Wen Shih, Kartik Gaur, Martin Podhorský

The deterministic realization of quantum light sources operating at telecom wavelengths is essential for long-distance fiber-based quantum communication and distributed quantum computing. In this work, we demonstrate that telecom O-band emission can be achieved from site-controlled InGaAs/GaAs quantum dots (QDs). Our concept utilizes a buried AlAs/Al$_2$O$_3

Ji Eun Song, Jaeyoun You, Joongseek Lee

A user's ownership perception of virtual objects, such as cloud files, is generally uncertain. Is this valid for streaming platforms featuring accounts designed for sharing (DS)? We observe sharing practices within DS accounts of streaming platforms and identify their ownership characteristics and unexpected complications through two mixed-method studies. Ca

Xinyu Liu, Zhen Chen, Wuyang Li, Chenxin Li

Transformers have shown remarkable performance in 3D medical image segmentation, but their high computational requirements and need for large amounts of labeled data limit their applicability. To address these challenges, we consider two crucial aspects: model efficiency and data efficiency. Specifically, we propose Light-UNETR, a lightweight transformer des

Cătălin Paşcu Moca, Doru Sticlet, Tamás Vicsek, Balázs Dóra

Family-Vicsek (FV) scaling provides an understanding for the growth and finite-size saturation of fluctuations in classical systems. Here, we extend the FV roughness to transferred segment magnetization after quantum quenches in a dissipative XXZ spin chain with homogeneous gain and loss, starting from a nonequilibrium steady state with finite magnetization.

Xiaowen Ma, Onur Ayan, Yunpu Ma, Xueli An

Generative AI is envisioned to have a crucial impact on next generation mobile networking, making the sixth generation (6G) system considerably more autonomous, flexible, and adaptive than its predecessors. By leveraging their natural language processing and code generation capabilities, AI agents enable novel interactions and services between networks and v

Giacomo Avanzi, Marco Giordani, Michele Zorzi

Teleoperated driving (TD) is envisioned as a key application of future sixth generation (6G) networks. In this paradigm, connected vehicles transmit sensor-perception data to a remote (software) driver, which returns driving control commands to enhance traffic efficiency and road safety. This scenario imposes to maintain reliable and low-latency communicatio

Chung-Hoo Poon, James Kwok, Calvin Chow, Jang-Hyeon Choi

Anti-money laundering (AML) systems are important for protecting the global economy. However, conventional rule-based methods rely on domain knowledge, leading to suboptimal accuracy and a lack of scalability. Graph neural networks (GNNs) for digraphs (directed graphs) can be applied to transaction graphs and capture suspicious transactions or accounts. Howe

Chuanrui Zhang, Minghan Qin, Yuang Wang, Baifeng Xie

High-quality articulated 3D assets are indispensable for embodied AI and physical simulation, yet 3D generation still focuses on static meshes, leaving a gap in "sim-ready" interactive objects. Most recent articulated object creation methods rely on multi-stage pipelines that accumulate errors across decoupled modules. Alternatively, unified MLLMs offer a si

Josué Ortega, Gabriel Ziegler, R. Pablo Arribillaga, Geng Zhao

We study the distribution of envy in random matching markets under the Deferred Acceptance (DA) algorithm. Using tools from applied probability, we compute the expected number of proposing agents whom nobody envies and those who envy nobody. We obtain an exact finite-market expression for the former, based on a connection with the coupon collector problem, a

Ankur Ghosh, Tamador K. M. Aldowma, Soebur Razzaque

We present a high-energy spectral analysis of GRB 250129A, which was triggered by the Swift-BAT. The burst exhibits a complex, multi-peaked temporal structure characterized by two distinct emission episodes, with the main peak occurring approximately 180 seconds after the BAT trigger. The time-integrated spectral analysis in the 15 - 150 keV energy range ind

Feifan Luo, Hongyang Chen

Shape matching is a fundamental task in computer graphics and vision, with deep functional maps becoming a prominent paradigm. However, existing methods primarily focus on learning informative feature representations by constraining pointwise and functional maps, while neglecting the optimization of the spectral basis-a critical component of the functional m

Víctor Mañosa, Chara Pantazi

We present a simple method to study the dynamics of planar Kahan-Hirota-Kimura (KHK) maps preserving rational fibrations. Using this approach, we show that integrable KHK maps may exhibit complex dynamics, even when obtained from vector fields with trivial behavior. As an application, we study the KHK map associated with a quadratic planar vector field with

Yating Xu, Yunqi Miao, Evangelos Ververas, Jiankang Deng

Motion transfer from the driving to the source portrait remains a key challenge in the portrait animation. Current diffusion-based approaches condition only on the driving motion, which fails to capture source-to-driving correspondences and consequently yields suboptimal motion transfer. Although flow estimation provides an alternative, predicting dense corr

Jean-Christophe Pain

Tangent numbers $T_{2n-1}$, which enumerate alternating permutations of odd length, play a prominent role in the Taylor series expansion of the tangent function $\tan(x)$. In this work, we adopt a combinatorial approach based on the excedance statistic of permutations, which allows us to interpret the coefficients of the tangent series in a structural and en

Quentin Chuet

A proper colouring of a graph $G$ is $\beta$-frugal if every colour appears at most $\beta$ times in the neighbourhood of each vertex. Let $\chi_\beta(G)$ denote the minimum number of colours needed for a $\beta$-frugal colouring of $G$. For a fixed value of $\beta$, Hind et al. showed that $\chi_\beta(G) = \mathcal{O}(\Delta(G)^{1 + 1/\beta})$, and a constr

Helmut Prodinger

Generating functions related to Catalan words and frequencies of digits are obtained using continued fractions. This is fast, elegant, and flexible. It follows the philosophy of Philippe Flajolet from 1980.

Yuzhi Chen, Ronghan Chen, Dongjie Huo, Yandan Yang

Video-based world models offer a powerful paradigm for embodied simulation and planning, yet state-of-the-art models often generate physically implausible manipulations - such as object penetration and anti-gravity motion - due to training on generic visual data and likelihood-based objectives that ignore physical laws. We present ABot-PhysWorld, a 14B Diffu

Samya Acharja, Kanchan Chowdhury

The task of building a natural language interface to a database, known as NLIDB, has recently gained significant attention from both the database and Natural Language Processing (NLP) communities. With the proliferation of geospatial datasets driven by the rapid emergence of location-aware sensors, geospatial databases play a vital role in supporting geospat

Yajie Bao, Chuchen Zhang, Zhaojun Wang, Haojie Ren

Achieving valid conditional coverage in conformal prediction is challenging due to the theoretical difficulty of satisfying pointwise constraints in finite samples. Building upon the characterization of conditional coverage through marginal moment restrictions, we introduce Minimax Optimization Predictive Inference (MOPI), a framework that generalizes prior

Yong Yuan, Minghui Du, Benyang Zhu, Xin-yi Lin

The cosmic distance duality relation (CDDR), expressed as $d_L(z) = (1+z)^2 D_A(z)$, is a fundamental relation in modern cosmology. In this work, we apply a method to test the CDDR using simulated strongly lensed gravitational-wave (SLGW) signals from massive binary black holes (MBBH) as observed by proposed space-based detector networks. Our analysis is con

G. Cantini, G. Arnone, F. Capone, J. A. Gianfrani

Progress in particle physic leads to increasing in detector luminosity and a consequent increasing overheating induced by Joule effect. An effective cooling strategy is the exploitation of CO\textsubscript{2} heat latency in phase-change. An additional challenge, relevant to detectors for High Energy Particles, is the consequent geometrical constrain due to

Weihang Li, Lorenzo Garattoni, Fabien Despinoy, Nassir Navab

Learning model-free object pose estimation for unseen instances remains a fundamental challenge in 3D vision. Existing methods typically fall into two disjoint paradigms: category-level approaches predict absolute poses in a canonical space but rely on predefined taxonomies, while relative pose methods estimate cross-view transformations but cannot recover s

Katsuhisa Koshino

In this paper, we shall establish Banach-Stone type theorems on spaces of uniformly continuous and lipschitz continuous pseudometrics.

Sergei Merkulov

A dg cyclic operad $BVHgraphs$ of hypergraphs is introduced which comes equipped with an explicit quasi-isomorphism $BV\rightarrow BVHgraphs$ from the { cyclic} operad $BV$ of Batalin-Vilkovisky algebras. A proof that the cohomology of $BVHgraphs$ equals $BV$ occupies most of this paper. We use this model to construct an explicit quasi-isomorphism $Chains(FF

Nina Andrejevic, Ming Du, Hemant Sharma, James P. Horwath

Materials identification and structural understanding from powder X-ray diffraction (PXRD) data is a long-standing challenge in materials science, fundamental to discovering and characterizing novel materials. A prerequisite for full structure solution is the accurate determination of the crystal lattice, including lattice parameters and crystallographic sym

Vladimir Manuilov

We generalize the notion of a continuous field of C*-algebras to that of Hilbert C*-bimodules. Given a partially ordered set $P$ and a monotonically non-decreasing family of ternary rings of operators (TROs) assigned to the points of $P$, we equip $P$ with a certain zero-dimensional Hausdorff topology and use a certain compactification $\gamma P$ to get the

Jesse F. d'Almeida, Tanner Watts, Susheela Sharma Stern, James Ferguson

Reliable estimation of surgical needle 3D position and orientation is essential for autonomous robotic suturing, yet existing methods operate almost exclusively under stereoscopic vision. In monocular endoscopic settings, common in transendoscopic and intraluminal procedures, depth ambiguity and rotational symmetry render needle pose estimation inherently il

Kyrylo Riabov, Serhii Kryvyi

Ring-mapping protocols need a canonical byte-to-residue layer before any algebraic encryption step can begin. This paper isolates that layer and presents the base-m length codec, a canonical map from byte strings of length less than 2^64 to lists of residues modulo m. The encoder builds on and adapts an rANS-based system proposed by Duda. Decoding is exact f

Xiangjun Zhen, Gongxiang Liu, Jing Yu

Let $H$ be a generalized Liu algebra over an algebraically closed field $k$ of characteristic zero. We prove that all simple Yetter-Drinfeld modules over $H$ are finite-dimensional and present an explicit classification of these modules. Moreover, we completely determine which of them admit a finite-dimensional Nichols algebra.

Roberto Menta, Francesco Cioni, Riccardo Aiudi, Marco Polini

We introduce the concept of quantum actuators as mediators for globally controlled quantum computation. Auxiliary quantum systems act as controllable elements that transiently store and release interaction energy, enabling the selective activation of multi-qubit gates within globally driven architectures. During compilation they remain passive and require no

Nobuyuki Ota

Biological AI models increasingly predict complex cellular responses, yet their learned representations remain disconnected from the molecular processes they aim to capture. We present CDT-III, which extends mechanism-oriented AI across the full central dogma: DNA, RNA, and protein. Its two-stage Virtual Cell Embedder architecture mirrors the spatial compart

A. Ghosh, S. Razzaque, J. Barnard, J. C. Joshi

Gamma-Ray Burst (GRB) afterglows arise from the interaction of relativistic ejecta with the circumburst medium and are observed across the electromagnetic spectrum. Afterglow polarisation is expected at early and late phases depending on the presence of reverse shocks (RS) and the observer's viewing geometry relative to the jet. Polarimetric observations of

Eva Guttmann-Flury, Yun-Hsuan Chen, Qiaoyuan Xiang, Hao Zhang

This proof-of-concept study introduces a novel multimodal framework combining synchronized EEG-fNIRS modalities with neuronal avalanche analysis to identify early network dysfunction in Alzheimer's disease. The approach leverages complementary neural signals to examine motor network dynamics during execution and imagery tasks within an interactive task envir

Arbel Yaniv, Kilian Golinski, Christoph Goebel

This study analyzes Graph Neural Networks (GNNs) for distribution system state estimation (DSSE) by employing an interpretable Graph Neural Additive Network (GNAN) and by utilizing an edge-conditioned message-passing mechanism. The architectures are benchmarked against the standard Graph Attention Network (GAT) architecture. Multiple SimBench grids with topo

Max Marriott-Clarke, Lazar Novakovic, Elizabeth Ratzer, Robert J. Bainbridge

We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predicting cluster assignments or object-centric variables, the method learns a latent representation in which points belonging to the same object are embedded nearby while unrelated points are separated. Clusters are then re

Peng-Yuan Wang, Ziniu Li, Tian Xu, Bohan Yang

Improving data utilization efficiency is critical for scaling reinforcement learning (RL) for long-horizon tasks where generating trajectories is expensive. However, the dominant RL methods for LLMs are largely on-policy: they update each batch of data only once, discard it, and then collect fresh samples, resulting in poor sample efficiency. In this work, w

Markus Kleinau

Reading constructed a Cambrian lattice $C_\Gamma$ for each oriented finite type Coxeter diagram $\Gamma$. We show that the derived category of representations of $C_\Gamma$ is fractionally Calabi-Yau for any $\Gamma$, confirming a conjecture of Chapoton. This extends a result of Rognerud for Cambrian lattices of type $A$ with linear orientation, better known

Wilhelm Kerle-Malcharek, Giulio Biondi, Karsten Klein, Ulf Hailer

Immersive technologies, such as virtual and augmented reality, are transforming digital heritage by enabling users to explore and interact with culturally significant sites. It is now possible to view and augment digital twins, or digitally reconstructed versions of them, and to enable access to previously unreachable locations for a broader audience. Here,

Roberto Metere, Mario Lilli, Luca Arnaboldi, Elvinia Riccobene

The latest Wi-Fi security standard, IEEE 802.11, includes a secure authentication protocol called SAE, whose use is mandatory for WPA3-Personal networks. The protocol is specified at two separate but linked levels: a traditional cryptographic description of the communication logic between network devices, and a state machine description that realises the for

J. Khatua, Taeyun Kim, G. Senthil Murugan, S. M. Kumawat

Star lattice, which can be visualized as a honeycomb network with each vertex replaced by a triangle, provides a rare platform for realizing exotic quantum states such as quantum spin liquids and disorder-driven random-singlet (RS) states. Herein, we investigate the ground-state properties of the three-dimensional (3D) stuffed hyper-star lattice Li$_2$Cu$_2$

Naoki Sekiya, Yuri Akiba, Kai Kageyama, Hokuto Nagatakiya

Fracture networks are ubiquitous in nature, spanning scales from millimeter-sized cracks in botanical peels to hundred-kilometer-long lineae on planetary satellites. The propagation of a crack is a complex, nonlinear phenomenon governed by the interplay of mechanical properties, rheological behavior, and system geometry. While fracture mechanics has long add

Simone Moretti, Paolo Pellizzoni, Andrea Pietracaprina, Geppino Pucci

The $k$-center problem is a fundamental clustering variant with applications in learning systems and data summarization. In several real-world scenarios, the dataset to be clustered is not static, but evolves over time, as new data points arrive and old ones become stale. To account for dynamicity, the $k$-center problem has been mainly studied under the sli

Weicheng Fu, Zhen Wang, Wei Lin, Dahai He

The Fermi--Pasta--Ulam--Tsingou (FPUT) problem provides a paradigmatic framework for understanding thermalization in weakly nonlinear many-body Hamiltonian systems. This focused review summarizes major developments in near-integrable dynamics, wave resonances, and phonon kinetic theory, emphasizing recent results on thermalization-time scaling in nonlinear l

Long Mai

Real-time spoken dialogue systems face a fundamental tension between latency and response quality. End-to-end speech-to-speech (S2S) models respond immediately and naturally handle turn-taking, backchanneling, and interruption, but produce semantically weaker outputs. Cascaded pipelines (ASR -> LLM) deliver stronger responses at the cost of latency that grow

Yujie Sun, Zhuoqiang Cai, Chaoyue Niu, Jianchuan Chen

We present FHAvatar, a novel framework for reconstructing 3D Gaussian avatars with composable face and hair components from an arbitrary number of views. Unlike previous approaches that couple facial and hair representations within a unified modeling process, we explicitly decouple two components in texture space by representing the face with planar Gaussian

MD Rashidul Islam, Bakary Gibba

Computer-aided segmentation of brain tumors from MRI data is of crucial significance to clinical decision-making in diagnosis, treatment planning, and follow-up disease monitoring. Gliomas, owing to their high malignancy and heterogeneity, represent a very challenging task for accurate and reliable segmentation into intra-tumoral sub-regions. Manual segmenta

Maya Taylor, Carl Pearson, Luc Berger-Vergiat, Giovanni Long

As AI accelerators gain prominence, their potential for traditional scientific computing workloads remains unclear. This paper explores Tenstorrent's Wormhole architecture, a spatial computing platform designed for neural network acceleration, by implementing three numerical kernels and composing them into a conjugate gradient solver. We present architecture

Jannik Hohmann, Dong Wang, Andreas Nüchter

Material awareness can improve robotic navigation and interaction, particularly in conditions where cameras and LiDAR degrade. We present a lightweight mmWave radar material classification pipeline designed for ultra-low-power edge devices (TI IWRL6432), using compact range-bin intensity descriptors and a Multilayer Perceptron (MLP) for real-time inference.

C. W. Cheng, J. Smith, K. Mashooq, P. Solomon

A device and process strategy for achieving reliable indium gallium zinc oxide and indium oxide transistors compatible with a 400oC BEOL thermal budget and without performance degradation is demonstrated by fully exploiting intrinsic oxide material properties. An indium oxide transistor with a novel amorphous In2O3 mixed with SiO2 capping layer exhibits a po

Ansgar Lowack, Rafael Anton, Bingchen Xue, Kristian Nikolowski

Ceramic solid-state batteries with sodium (Na) metal electrodes promise enhanced safety and energy density compared to contemporary secondary batteries. However, the critical delamination of the Na metal electrode during discharge - when vacancies accumulate at the Na/ceramic interface - remains to be understood and avoided. The study investigates the underl

Arseniy Kuznetsov, Benoit Neichel, Sylvain Oberti, Thierry Fusco

Precise knowledge of the point spread function (PSF) underpins many data analysis steps in astronomy, from photometry and astrometry to source de-blending and deconvolution. In adaptive optics (AO) observations, however, the PSF is highly variable with wavelength, field position, and observing conditions, making it difficult to model. Traditional PSF reconst

Yuji Okitani

We show that the large affine Hecke category defines an oriented, fully extended topological field theory. More generally, we establish conditions under which ind-coherent convolution categories define such theories, analogously to known results for finite Hecke categories and $D$-modules.

J. F. Chen, Haokun Fu, Christina Gao, Jing Shu

Ultralight bosonic dark matter with masses in the meV range, corresponding to terahertz (THz) Compton frequencies, remains largely unexplored due to the difficulty of achieving both efficient signal conversion and single-photon-sensitive detection at THz frequencies. We propose a hybrid detection architecture that integrates a dielectric haloscope, Rydberg-a

Ralph Furmaniak

Bohr's last problem (1952) asks whether every ordinary Dirichlet series with nonzero Lindel\"of order function $\mu$ has $\mu'(\omega_\mu{-}0)\le-1$; a negative answer would imply Lindel\"of for $\zeta$. Kahane (1989) refuted this with half-plane counterexamples. We study the refinement for series with entire continuation of order $\le 1$: the Analytic Linde

C. Cuddy, D. M. Long, M. Nedal, S. Bhunia

Extreme ultraviolet (EUV) waves are global waves in the solar corona which can accelerate particles. The efficiency of the acceleration depends on local plasma characteristics e.g. Alfv\'en speed and the geometry of the magnetic field. This shock-driven particle acceleration can produce radio signatures such as Type II radio bursts and herringbone emission.

Dante Bonolis, Lillian B. Pierce, Katharine Woo

In the 1980's Serre asked how many points of bounded height can lie in a thin set. This has motivated significant research ever since, culminating in a series of recent breakthroughs. It is a good time to take stock of the central questions that have been resolved, and also to highlight remaining open questions. First, we survey recent progress on counting p

Niloufar Amiri, Farrokh Janabi-Sharifi

Tendon-driven aerial continuum manipulators (TD-ACMs) combine the maneuverability of uncrewed aerial vehicles (UAVs) with the compliance of lightweight continuum robots (CRs). Existing coupled dynamic modeling approaches for TD-ACMs incur high computational costs and do not explicitly account for aerial platform underactuation. To address these limitations,

J. Frenkel, S. Martins-Filho

We analyse the gauge-dependence of the effective action in an interacting quantum theory of gravitational and matter fields. An explicit off-shell result is obtained in a general background gauge at one-loop order, which reduces in a particular gauge to the effective action found by 't Hooft-Veltman. We confirm the validity of DeWitt-Kallosh theorem, which i

Masaaki Nakamura, Po-Yu Tsai, Shiun-Jr Yang, King-Chuen Lin

Molecular orientation techniques are becoming available in the study of elementary chemical processes, in order to highlight those structural and dynamical properties that would be concealed by random rotational motions. Recently successful orientation was achieved for asymmetric-top and chiral molecules of much larger complexity than hitherto. In this work,

Maya Taylor, Kavitha Chandrasekar, Laxmikant V. Kale

Parallel applications with irregular and time-varying workloads often suffer from load imbalance. Dynamic load balancing techniques address this challenge by redistributing work during execution. We present a new type of distributed diffusion-based load balancing targeted at communication-intensive applications with persistently communicating objects. Levera

Nikolay Ulyanov

A $3$-dimensional nowhere-zero flow on a graph $G$ is a flow where each edge is assigned a $3$-dimensional vector with unit norm (which corresponds to the points of a $2$-dimensional unit sphere $S^2$). K. Jain posed two conjectures related to this idea. First one suggests that such a flow exists for all bridgeless graphs. The second conjecture states that w

Dani R. Lipman, Cara Battersby, Daniel Walker, Maïca Clavel

The 3D structure of The Milky Way's Central Molecular Zone (CMZ) informs our understanding of star formation cycles, black hole accretion, and the evolution of galactic nuclei. However, a comprehensive 3D model has remained elusive, as no singular dataset nor theory contains the requisite information to describe the orbital motion of the gas. We implement a

Yunfeng Wu, Hongying Cheng, Zihao He, Songhua Liu

Transformer-based video diffusion models rely on 3D attention over spatial and temporal tokens, which incurs quadratic time and memory complexity and makes end-to-end training for ultra-high-resolution videos prohibitively expensive. To overcome this bottleneck, we propose a pure image adaptation framework that upgrades a video Diffusion Transformer pre-trai

Shigeaki Yokota

The observable distance $d_{\mathrm{conc}}$ based on measure concentration and the box distance $\Box$ based on collapsing theory are extended to geometric data sets introduced by Hanika--Schneider--Stumme. On the set $\mathcal{D}$ of isomorphism classes of geometric data sets, $d_{\mathrm{conc}}$ is non-separable and $\Box$ is complete and non-separable. We

Chuanqing Zhuang, Xin Lu, Zehui Deng, Zhengda Lu

Omnidirectional 3D Gaussian Splatting with panoramas is a key technique for 3D scene representation, and existing methods typically rely on slow SfM to provide camera poses and sparse points priors. In this work, we propose a pose-free omnidirectional 3DGS method, named PFGS360, that reconstructs 3D Gaussians from unposed omnidirectional videos. To achieve a

Federico Giarrè, Holger Karl

Multi-access Edge Computings (MECs) enables low-latency services by executing applications at the network edge. To fulfill low-latency requirements of mobile users, providers have to keep multiple edge servers running at multiple locations, even when, in low-load phases, their capacity is not needed. This significantly increases energy consumption. Multi-sta

Hanjing Wang, S. Mostafa Mousavi, Patrick Robertson, Richard M. Allen

Android's Earthquake Alert (AEA) system provided timely early warnings to millions during the Mw 6.2 Marmara Ereglisi, T\"urkiye earthquake on April 23, 2025. This event, the largest in the region in 25 years, served as a critical real-world test for smartphone-based Earthquake Early Warning (EEW) systems. The AEA system successfully delivered alerts to user

Akane Kanno

Let $G$ be a graph and $I(G)$ its edge ideal. In this paper, we give a complete characterization of the graphs $G$ for which $\reg(R/I(G)) = 3$.

Nicola Pellicciotta, Luca Angelani, Roberto Di Leonardo

Proliferation is a defining feature of life. Through growth, division, and death, living systems consume energy and inject mass, breaking conservation laws and driving collective phenomena from biofilm formation to embryonic development. Yet, while active matter physics has advanced our understanding of self-propelled agents, quantitative frameworks for prol

Duy Dao Do, Anaïs Halftermeyer, Thi-Bich-Hanh Dao

Temporal Relation Extraction (TRE) requires identifying how two events or temporal expressions are related in time. Existing attention-based models often highlight globally salient tokens but overlook the pair-specific cues that actually determine the temporal relation. We propose WISTERIA (Weak Implicit Signal-based Temporal Relation Extraction with Attenti

Marc Van den Bossche, Oliver Gressel

Class II protoplanetary discs feature numerous non-axisymmetric substructures like spirals and the underlying mechanisms for their formation are still highly debated. Coincidentally, early stage, massive discs are subject to the gravitational instability that causes them to collapse into denser substructures. However, like for most instabilities, real system

Shigeaki Yokota

Hanika, Schneider, and Stumme introduced geometric data set as a generalization of metric measure space for the computation of the observable diameter, and extended the observable distance between metric measure spaces to that between geometric data sets. In this paper, we begin by proving the non-separability of the observable distance between geometric dat

Benjamin Lange

When providers update AI companions, users report grief, betrayal, and loss. A growing literature asks whether the norms governing personal relationships extend to these interactions. So what, if anything, is morally significant about them? I argue that this debate has missed a prior structural question: who controls the relationship, and from where? Human-A

Angelo Valli, Laura Fanfarillo

Superconductivity and nematicity coexist in the phase diagram of many correlated systems, including iron-based superconductors. We investigate how Hund-driven correlations reshape boson-mediated superconductivity in a multiorbital nematic metal. We find that dynamical correlation effects beyond a quasiparticle-only description are essential to capture the ro

De-Chao Song, Ying Li, Qiao Li, Xiaofeng Liu

The hydrogen \lya\ line and the white-light (WL) continuum are two key diagnostics of energy transport in the lower atmosphere during solar flares, yet their relationship remains poorly understood. Here we present a statistical analysis of 69 white-light flares (WLFs) to investigate the relationships among the \lya, soft X-ray (SXR), and WL continuum emissio

Josef Hanke, Sebastian Pujalte Ojeda, Shengyu Zhang, Werngard Czechtizky

The accurate prediction of protein-RNA binding affinity remains an unsolved problem in structural biology, limiting opportunities in understanding gene regulation and designing RNA-targeting therapeutics. A central obstacle is the structural flexibility of RNA, as, unlike proteins, RNA molecules exist as dynamic conformational ensembles. Thus, committing to

Hernan Haimovich, Jose L. Mancilla-Aguilar

Time-invariant finite-dimensional systems, under reasonable continuity assumptions, exhibit the property that if solutions exist for all future times, the set of vectors reachable from a bounded set of initial conditions over bounded time intervals is also bounded. This property can be summarized as follows: forward completeness implies bounded reachability

Chuong Huynh, Hossein Souri, Abhinav Kumar, Vitali Petsiuk

Large-scale Vision-Language Models (VLMs) such as CLIP learn powerful semantic representations but operate in Euclidean space, which fails to capture the inherent hierarchical structure of visual and linguistic concepts. Hyperbolic geometry, with its exponential volume growth, offers a principled alternative for embedding such hierarchies with low distortion

Longkun Li, Evangelos Pournaras

Autonomous vehicles generate large volumes of data for applications such as fleet monitoring, model retraining, and high-definition map updates. Existing studies often rely on generic traffic traces, which do not capture the characteristics of autonomous driving workloads. This paper proposes a system-level workload modeling framework for vehicle-to-cloud da

Mengran Li, Daniela Castro-Camilo

Extreme quantile treatment effects (eQTEs) measure the causal impact of a treatment on the tails of an outcome distribution and are central for studying rare, high-impact events. Standard QTE methods often fail in extreme regimes due to data sparsity, while existing eQTE methods rely on restrictive tail assumptions or on interior-quantile theory. We propose

V. K. Cody Bumgardner, Mitchell A. Klusty, Mahmut S. Gokmen, Evan W. Damron

Automated radiology report generation from 3D computed tomography (CT) volumes is challenging due to extreme sequence lengths, severe class imbalance, and the tendency of large language models (LLMs) to ignore visual tokens in favor of linguistic priors. We present Ker-VLJEPA-3B, a four-phase curriculum learning framework for free-text report generation from

Wenjie Liu, Ching Hua Lee, Zhoutao Lei

Topological pumping is conventionally governed by single-particle band topology. Here we show that promoting tunneling to a dynamical, occupation-conditioned variable fundamentally reshapes this paradigm, leading to occupation-selective topological pumping. In a periodically driven one-dimensional superlattice with density-dependent hopping, two-body bound s

David Alfaya, Luis Ángel Calvo, Pedro-José Cazorla, Javier Rodrigo

We study infinite paths of Markoff $m$-triples, that is, solutions to the generalised Markoff equation \[ x^2+y^2+z^2=3xyz+m, \] with $m>0$, with at least two $k$-Fibonacci components. First, we obtain a complete classification of Markoff $m$-triples whose last two entries are $k$-Fibonacci numbers and that are not roots of any Markoff trees. We then prove t

Mohammad Hassan Ahmad Yarandi, Luca Ganassali

We investigate contextual graph matching in the Gaussian setting, where both edge weights and node features are correlated across two networks. We derive precise information-theoretic thresholds for exact recovery, and identify conditions under which almost exact recovery is possible or impossible, in terms of graph and feature correlation strengths, the num

Emir Karaosman, Advije Rizvani, Irdin Pekaric

Financial institutions face increasing cyber risk while operating under strict regulatory oversight. To manage this risk, they rely heavily on Cyber Threat Intelligence (CTI) to inform detection, response, and strategic security decisions. Artificial intelligence (AI) is widely suggested as a means to strengthen CTI. However, evidence of trustworthy producti

Prabakaran Rajamanickam

A simplified phenomenological model is proposed to couple the long-wave Darrieus--Landau (DL) instability and the short-wave diffusive-thermal (DT) instability in premixed flames. By identifying a cubic coupling term in the linear dispersion relation, representing the leading-order interaction between hydrodynamic expansion and diffusive transport, this fram

Benoît Bonnet-Weill, Giovanni Colombo, Denis Shishmintsev, Emmanuel Trélat

In this article, we establish exponential turnpike theorems for a class of nonlinear deterministic meanfield optimal control problems. We carry out our analysis simultaneously in the so-called Lagrangian and Eulerian frameworks. In the Lagrangian setting, the problem is lifted to a Hilbert space of random variables, and we prove an exponential turnpike theor