December 2025 arXiv papers — page 79

Nathan Welch, Chris Marsden

Designing superconducting coils for a tokamak fusion device is a highly coupled, non-linear design problem. The coils have many disparate engineering requirements from structural to power electronics, as well strict limits placed on the system by the high temperature superconducting (HTS) cables. Simultaneously, the coils must be able to contain multiple pla

Brent Motmans, Digvijay Ghogare, Thijs G. I. van Wijk, Joren Van Herck

Copper nanoparticles (Cu NPs) have a broad applicability, yet their synthesis is sensitive to subtle changes in reaction parameters. This sensitivity, combined with the time- and resource-intensive nature of experimental optimization, poses a major challenge in achieving reproducible and size-controlled synthesis. While Machine Learning (ML) shows promise in

Michael M. Kay

In the context of Risk Neutral Pricing theory, we consider the classic problem of calibrating a martingale over $\mathbb{R}^n$ to a finite number of marginals thereof, or more practically, to prices of an arbitrary finite set of (joint) European contingent claims. For $n=1$, one can rely on the work of Dupire, while for $n\geq 2$ an analogous natural unique

Tim Dietrich, Tanja Hinderer, Micaela Oertel, Conrado A. Torres

Understanding dense matter under extreme conditions is one of the most fundamental puzzles in modern physics. Complex interactions give rise to emergent, collective phenomena. While nuclear experiments and Earth - based colliders provide valuable insights, much of the quantum chromodynamics phase diagram at high density and low temperature remains accessible

Mohammad Momani, Thomas Delamotte, Andreas Knopp

The increasing deployment of massive active antenna arrays in low Earth orbit (LEO) satellites necessitates computationally efficient and adaptive precoding techniques to mitigate dynamic channel variations and enhance spectral efficiency. Regularized zero-forcing (RZF) precoding is widely used in multi-user MIMO systems; however, its real-time implementatio

Gissel P. Montaguth, Ana Laura O'Mill, Claudia Mendes de Oliveira, Ciria Lima-Dias

Compact Groups (CGs) of galaxies are dense systems where projected separations are comparable to their optical diameters. A subset - non-isolated CGs - are embedded within major structures. Using multi-band S-PLUS data, we analyse galaxies in 122 non-isolated CGs within more massive systems such as larger groups and clusters. We compare them to galaxies in t

Primoz Kocbek, Gregor Stiglic

This work describes our submission to the CLEF 2025 SimpleText track Task 1, addressing both sentenceand document-level simplification of scientific texts. The methodology centered on using the gpt-4.1, gpt-4.1mini, and gpt-4.1-nano models from OpenAI. Two distinct approaches were compared: a no-context method relying on prompt engineering and a fine-tuned (

Flavio Salizzoni, Luca Sodomaco, Julian Weigert

We study the locus of square matrices having at least one eigenvector on a prescribed algebraic variety $X$. When $X$ is a linear subspace, this data locus is known as the Kalman variety of $X$ and was studied first by Ottaviani and Sturmfels. Motivated by recent applications to quantum chemistry and optimization, in this work, we focus on nonlinear Kalman v

Hengzhun Chen, Yingzhou Li, Bichen Lu, Jianfeng Lu

The variational quantum eigensolver (VQE) is one of the most promising algorithms for low-lying eigenstates calculation on Noisy Intermediate-Scale Quantum (NISQ) computers. Specifically, VQE has achieved great success for ground state calculations of a Hamiltonian. However, excited state calculations arising in quantum chemistry and condensed matter often r

Xiao Li, Yue Li, Hao Wu, Yue Zhang

As large language models (LLMs) are increasingly adopted for code vulnerability detection, their reliability and robustness across diverse vulnerability types have become a pressing concern. In traditional adversarial settings, code obfuscation has long been used as a general strategy to bypass auditing tools, preserving exploitability without tampering with

Hui Liu, Ligong Bian

In this study, we show that, in the background of the primordial magnetic field, the chiral magnetic effect effect can significantly amplify the chiral chemical potential sourced by the CP violation near the bubble walls during the first-order electroweak phase transition. This effect can lift the generated baryon asymmetry by several orders, and make it pos

Stephan Durr, Tolga S. H. Kiel

We consider $\phi^4$ theory with $\phi(x)\in\mathbb{R}$ in two Euclidean dimensions. We determine for a variety of self-couplings $\hat{\lambda}$ the (negative) critical bare mass $\hat{\mu}_{0\mathrm{c}}^2(\hat{\lambda})$ where the lattice-regularized system changes from the symmetric to the broken phase. Based on these data, the transition to infinite volu

Jinmin Wang

Let $M$ be a closed aspherical manifold. Assume that the rational strong Novikov conjecture holds for $\pi_1(M)$. We show that on any spin surgery of $M$ along a region whose induced homomorphism on the fundamental group is trivial, every complete metric with non-negative scalar curvature is Ricci-flat. In particular, on the connected sum of $M$ with a spin

Emre Okcu, Emre Mesudiyeli, Hâldun Sevinçli, A. Devrim Güçlü

Artificially engineered lattices provide a flexible platform for reproducing and extending the electronic behavior of atomic-scale materials. Artificial graphene systems, in particular, mimic graphene-like linear dispersion with tunable Dirac cones and offer a route to realizing more exotic band structures. Here we examine the emergence of quartic energy dis

Julien Hermant, Jean-François Aujol, Charles Dossal, Lorick Huang

In convex optimization, continuous-time counterparts have been a fruitful tool for analyzing momentum algorithms. Fewer such examples are available when the function to minimize is non-convex. In several cases, discrepancies arise between the existing discrete-time results, namely those obtained for momentum algorithms, and their continuous-time counterparts

Himanshu Gharat, Himanshi Agrawal, Gourab K. Patro

Large Language Models (LLMs) have empowered AI agents with advanced capabilities for understanding, reasoning, and interacting across diverse tasks. The addition of memory further enhances them by enabling continuity across interactions, learning from past experiences, and improving the relevance of actions and responses over time; termed as memory-enhanced

Ander Alvarez, Alessandro Genuardi, Nilotpal Sinha, Antonio Tiene

Deploying local large language models and vision-language models on edge devices requires balancing accuracy with constrained computational and energy budgets. Although graphics processors dominate modern artificial-intelligence deployment, most consumer hardware--including laptops, desktops, industrial controllers, and embedded systems--relies on central pr

Primoz Kocbek, Leon Kopitar, Gregor Stiglic

This study investigated the application of Large Language Models (LLMs) for simplifying biomedical texts to enhance health literacy. Using a public dataset, which included plain language adaptations of biomedical abstracts, we developed and evaluated several approaches, specifically a baseline approach using a prompt template, a two AI agent approach, and a

Julien Gachadoat, Guillaume Lagarde

Generative art systems often involve high-dimensional and complex parameter spaces in which aesthetically compelling outputs occupy only small, fragmented regions. Because of this combinatorial explosion, artists typically rely on extensive manual trial-and-error, leaving many potentially interesting configurations undiscovered. In this work we make two cont

Fredy Yip

We give a short and elementary argument answering a question of Erd\H{o}s and Ingham negatively. Erd\H{o}s and Ingham showed that a Tauberian estimate they considered was equivalent to the non-vanishing of $1+\sum_{k}a_k^{-1-it}$ for any real number $t$ and any sequence $1<a_1<a_2<\cdots$ of positive integers such that $\sum_k a_k^{-1}<\infty$. We disprove t

Christopher T. Hill

In a recent reformulation of top-quark condensation for the Brout-Englert-Higgs boson we introduced an extended internal wave-function, $\phi(r)$. We show how this leads to a manifestly Lorentz invariant formalism, where the absence of ``relative time'' is a gauge invariance of the bilocal field theory. This dictates a novel and nontrivial Lorentz invariant

M. V. Popov, T. V. Smirnova

The observations of B1237+25 at a frequency of 111 MHz were analyzed. For the first time in the normal radiation mode a new component in the central region in the average profile was detected. This component is manifested in all modes of pulsar emission: quiet-normal (QN), flare-normal (FN) and in the abnormal mode (AB). The subpulse drift is observed in the

Panasun Manorost, Peter Bastian

A non-negativity-preserving cut-cell discontinuous Galerkin method for the degenerate parabolic diffusive wave approximation of the shallow water equation is presented. The method can handle continuous and discontinuous bathymmetry as well as general triangular meshes. It is complemented by a finite volume method on Delauney triangulations which is also show

Alcides Buss, Damián Ferraro

We investigate amenability for $W^*$-Fell bundles over a discrete group $G$, with a focus on its characterization via approximation properties and conditional expectations. Building on the notion of $W^*$-amenability, we construct an enlarged $W^*$-Fell bundle analogous to $\ell^\infty(G, M)$ for a group action $G$ on a von Neumann algebra $M$, and relate am

Zhiwei Li, Yitian Pang, Weining Wang, Zhenan Sun

Vision-Language Models (VLMs), such as CLIP, have achieved impressive zero-shot recognition performance but remain highly susceptible to adversarial perturbations, posing significant risks in safety-critical scenarios. Previous training-time defenses rely on adversarial fine-tuning, which requires labeled data and costly retraining, while existing test-time

C. Pinto, S. Caserta, F. Barra, Y. Xu

Winds are an important ingredient in the evolution of X-ray binary (XRB) systems, particularly those at high accretion rates such as ultra-luminous X-ray sources (ULXs), because they may regulate the accretion of matter onto the compact object. We aim at understanding the properties of ULX winds and their link with the source spectral and temporal behavior.

Andrea Bastianin, Luca Rossini, Lorenzo Tonni

This paper develops a real-time forecasting framework for the monthly real prices of four key industrial metals -- aluminum, copper, nickel, and zinc -- whose demand is rising due to their widespread use in manufacturing and low-carbon technologies. To replicate the information set available to forecasters in real time, we construct a new dataset combining d

Nikolaos Ellinas, Alexandra Vioni, Panos Kakoulidis, Georgios Vamvoukakis

This paper introduces a cepstrum-based pitch modification method that can be applied to any mel-spectrogram representation. As a result, this method is compatible with any mel-based vocoder without requiring any additional training or changes to the model. This is achieved by directly modifying the cepstrum feature space in order to shift the harmonic struct

Xuefu Dong, Liqiang Xu, Lixing He, Zengyi Han

Silent speech interface (SSI) enables hands-free input without audible vocalization, but most SSI systems do not verify speaker identity. We present HEar-ID, which uses consumer active noise-canceling earbuds to capture low-frequency "whisper" audio and high-frequency ultrasonic reflections. Features from both streams pass through a shared encoder, producing

Zebin Zhu, Bolun Huang, Siqi Xu, Jingming Chen

Topological phase transitions, characterized by the closing and reopening of band gaps and a concomitant change in topological invariants, have played a central role in topological physics. However, such transitions have so far been restricted to spatial crystals, relying solely on energy band gaps and spatial interfaces. Here, we transcend this conventional

Pradeep Singh, Mudasani Rushikesh, Bezawada Sri Sai Anurag, Balasubramanian Raman

We develop a unified, dynamical-systems narrative of the universe that traces a continuous chain of structure formation from the Big Bang to contemporary human societies and their artificial learning systems. Rather than treating cosmology, astrophysics, geophysics, biology, cognition, and machine intelligence as disjoint domains, we view each as successive

Diodato Ferraioli, Paolo Penna, Manvir Schneider, Carmine Ventre

A central challenge in blockchain tokenomics is aligning short-term performance incentives with long-term decentralization goals. We propose a framework for algorithmic monetary policies that navigates this tradeoff in repeated participation games. Agents, characterized by type (capability) and stake, choose to participate or abstain at each round; the polic

Tommaso Pistillo

We consider the problem of finding a minimizer $u$ in $ H^1(\mathbb{R}^3)$ for the Hartree energy functional with convolution potential $w$ in $L^\infty(\mathbb{R}^3)+L^{3/2,\infty}(\mathbb{R}^3)$ with $L^\infty$ part vanishing at infinity. This class includes sums of potentials of the kind $-\frac{1}{|x|^\alpha}$, $0<\alpha\le2$, together with the case $w$

Pompougnac Hugo, Guillon Christophe, Noiry Sylvain, Dutilleul Alban

Achieving high efficiency on AI operators demands precise control over computation and data movement. However, existing scheduling languages are locked into specific compiler ecosystems, preventing fair comparison, reuse, and evaluation across frameworks. No unified interface currently decouples scheduling specification from code generation and measurement.

Hossein Javidnia

Accurate intrinsic decomposition of face images under unconstrained lighting is a prerequisite for photorealistic relighting, high-fidelity digital doubles, and augmented-reality effects. This paper introduces MAGINet, a Multi-scale Attention-Guided Intrinsics Network that predicts a $512\times512$ light-normalized diffuse albedo map from a single RGB portra

Christiane Quesne

We show that the radial harmonic oscillator problem in the position-dependent mass background of the type $m(\alpha;r) = (1+\alpha r^2)^{-2}$, $\alpha>0$, can be solved by using a point canonical transformation mapping the corresponding Schr\"odinger equation onto that of the P\"oschl-Teller I potential with constant mass. The radial harmonic oscillator prob

C. Morin, C. Lagoin, T. Gupta, N. Reinic

In condensed-matter physics, long-range correlations introduce quantum states of matter that challenge intuition. For instance, supersolids combine symmetry-breaking crystalline structure, i.e. density order, and frictionless superfluid flow. Envisioned over fifty years ago, supersolids have proven to only exist under very stringent conditions, with experime

Paweł Moskal, Aleksander Khreptak, Jarosław Choiński, Pete Jones

The development of PET and positronium imaging techniques is strictly related to the availability of suitable radionuclides and robust radiochemistry platforms. Among the emerging candidates, $^{44}$Sc has attracted significant interest due to its favourable physical properties, including a half-life of $\sim$4 hours, a pure $\beta^{+}$ emission profile, and

Ivan Noden

Using a construction of Kanemitsu from [9] and observations by Rampazzo in [19], we find examples of zero divisors in the Grothendieck ring of varieties by taking the zero loci of sections of vector bundles over symplectic and $F_4$ Grassmannians. These zero divisors yield instances of non-trivially L-equivalent Calabi-Yau varieties. This methodology is insp

Vyacheslav Koval

We study Bedford--McMullen type carpets whose selected grid rectangles may be reflected in one or both coordinates. The organizing principle is that the Hausdorff dimension is controlled by the entropy of the weak-coordinate projection. When this weak projection is separated, we obtain an explicit McMullen-type formula. This yields stability under arbitrary

Chin-Yu Hsiao, Ood Shabtai

We study the distribution kernel of a Toeplitz operator associated with a classical pseudodifferential operator on a compact, embeddable, strictly pseudoconvex CR manifold. The main result consists of a formula for the values at the diagonal of the second coefficient in the expansion of the symbol of the kernel. We also establish asymptotic expansions for To

Xianpeng Hu, Yuanzhi Tu, Changyou Wang, Huanyao Wen

We prove that for sufficiently small $H^3$-perturbations of an affine solution, the Cauchy problem for the compressible nonlinear elastodynamics in $\mathbb{R}^d$, for $d=2,3$, admits a unique global strong solution. Moreover, we establish the asymptotic behavior of the solution.

Qiushuo Cheng, Jingjing Liu, Catherine Morgan, Alan Whone

The self-supervised pretraining paradigm has achieved great success in learning 3D action representations for skeleton-based action recognition using contrastive learning. However, learning effective representations for skeleton-based temporal action localization remains challenging and underexplored. Unlike video-level {action} recognition, detecting action

Elías Guisado Villalgordo, Pat Lank, Kabeer Manali Rahul, Nebojsa Pavic

We study the behavior of integral transforms under base change. In particular, we establish a yoga of local algebra and fibers to test for derived equivalences or fully faithfulness via integral transforms. This generalizes a result of Orlov to singular varieties and strengthens several results in the literature by allowing arbitrary base fields. Additionall

Vishnu A Pai, Titus K Mathew

We derive an extended expression for the relaxation time of a barotropic Israel-Stewart (IS) fluid using the non-linear causality constraint, and propose a new formulation for modeling causal viscous dissipation in barotropic fluids. With this generalized relaxation time, the non-linear IS equation simplifies to a first-order non-linear expression connecting

Beitong Zhou, Zhexiao Huang, Yuan Guo, Zhangxuan Gu

GUI grounding is a critical component in building capable GUI agents. However, existing grounding benchmarks suffer from significant limitations: they either provide insufficient data volume and narrow domain coverage, or focus excessively on a single platform and require highly specialized domain knowledge. In this work, we present VenusBench-GD, a comprehe

S. S. Podkorytov

Given pointed cellular spaces $X$ and $Y$, $X$ compact, and an integer $r\ge0$, we define a relation $\overset r\approx$ on $[X,Y]$ and argue for the conjecture that it always coincides with the $r$-similarity $\overset r\sim$.

Dimitrios Giataganas

We study holographic c-theorems based on timelike entanglement entropy and show that a timelike c-function captures irreversible renormalization group (RG) flow. We demonstrate that timelike c-functions are applicable to both relativistic and non-relativistic quantum matter in nematic phases with broken rotational symmetry, and that they remain monotonic eve

David Cheban, Andrei Sultan

The aim of this paper is studying the problem of almost periodicity of almost periodic lattice dynamical systems of the form $u_{i}'=\nu (u_{i-1}-2u_i+u_{i+1})-\lambda u_{i}+F(u_i)+f_{i}(t)\ (i\in \mathbb Z,\ \lambda >0)$. We prove the existence a unique almost periodic solution of this system if the nonlinearity $F$ is monotone.

Denis Kopylov, Manfred Hammer

The guided modes supported by dielectric channel waveguides act as individual carriers of momentum. We show this by proving that the modes satisfy an orthogonality condition which relates to the momentum of the optical electromagnetic field, with a link to the more familiar power (energy) orthogonality. This result forms the basis for a rigorous, self-consis

Mengyuan Liu, Jiajie Liu, Jinyan Zhang, Wenhao Li

The lifting-based methods have dominated monocular 3D human pose estimation by leveraging detected 2D poses as intermediate representations. The 2D component of the final 3D human pose benefits from the detected 2D poses, whereas its depth counterpart must be estimated from scratch. The lifting-based methods encode the detected 2D pose and unknown depth in a

Huma Hafeez, Matthew Garratt, Jo Plested, Sankaran Iyer

The processing of omnidirectional 360-degree images poses significant challenges for object detection due to inherent spatial distortions, wide fields of view, and ultra-high-resolution inputs. Conventional detectors such as YOLO are optimised for standard image sizes (for example, 640x640 pixels) and often struggle with the computational demands of 4K or hi

Theresa Eimer, Lennart Schäpermeier, André Biedenkapp, Alexander Tornede

Empirical research on meta-algorithmics, such as algorithm selection, configuration, and scheduling, often relies on extensive and thus computationally expensive experiments. With the large degree of freedom we have over our experimental setup and design comes a plethora of possible error sources that threaten the scalability and validity of our scientific i

Ali Zafari, Saeid Alikhani

In this paper we first obtain the spectrum of the folded hypercube in a new approach. Then we introduce a new family of graphs called the extended Hamming graph, denoted by $EH(n,2^n)$, which is constructed from the well-known Hamming graph $H(n,2^n)$. The graph $EH(n,2^n)$ shares the same vertex set as $H(n,2^n)$ but includes additional edges, called comple

Seyda Betul Aydin, Holger Brandt

Generalizing causal knowledge across diverse environments is challenging, especially when estimates from large-scale datasets must be applied to smaller or systematically different contexts, where external validity is critical. Model-based estimators of individual treatment effects (ITE) from machine learning require large sample sizes, limiting their applic

Matthias Riegraf, Marc Riedel, Soren Hojgaard Jensen, Srikanth Santhanam

High-temperature solid oxide electrolysis cells (SOECs) are a potential core power-to-X (P2X) technology due to their unparalleled system efficiencies, that can exceed 85 % when excess heat from exothermic downstream processes is available. Recent advancements in materials, cell and stack design have enabled the deployment of megawatt (MW) scale demonstratio

Philipp Plamper, Hanna Köpcke, Anika Groß

Many complex real-world systems exhibit inherently intertwined temporal and spatial characteristics. Spatio-temporal knowledge graphs (STKGs) have therefore emerged as a powerful representation paradigm, as they integrate entities, relationships, time and space within a unified graph structure. They are increasingly applied across diverse domains, including

Kamer Ali Yuksel

Large Language Model (LLM) agents are increasingly deployed in complex, multi-step workflows involving planning, tool use, reflection, and interaction with external knowledge systems. These workflows generate rapidly expanding contexts that must be curated, transformed, and compressed to maintain fidelity, avoid attention dilution, and reduce inference cost.

Vincent Beffara, Corentin Faipeur, Tejas Oke

We consider the random cluster model with parameter $q<1$, for which the FKG inequalities are not valid. On the square lattice, stochastic comparison with Bernoulli percolation implies that the model is subcritical (respectively supercritical) when $p \leq q/(1+q)$ (resp. $p \geq 1/2$); in this paper, we extend these two regions, by improving the classical s

Erik Mårtensson, Paul Stankovski Wagner, Joshua Stapleton

In 1969 Strassen showed surprisingly that it is possible to multiply two 2 x 2 matrices using seven multiplications and 18 additions, instead of the naive eight multiplications and four additions. The number of additions was later reduced to 15. Karstadt and Schwartz further reduced the number of additions to 12 using a change-of-basis method. Both the numbe

Kejun Liu, Yuanyuan Liu, Lin Wei, Chang Tang

Emotion Recognition (ER) is the process of analyzing and identifying human emotions from sensing data. Currently, the field heavily relies on facial expression recognition (FER) because visual channel conveys rich emotional cues. However, facial expressions are often used as social tools rather than manifestations of genuine inner emotions. To understand and

Yuan Li, Yahan Yu, Youyuan Lin, Yong-Hao Yang

Humans assess image quality through a perception-reasoning cascade, integrating sensory cues with implicit reasoning to form self-consistent judgments. In this work, we investigate how a model can acquire both human-like and self-consistent reasoning capability for blind image quality assessment (BIQA). We first collect human evaluation data that capture sev

Oisin Campion, Fernando Hernando, Gary McGuire

In this work, we define Generalized Monomial Cartesian Codes (GMCC), which constitute a natural extension of generalized Reed-Solomon codes. We describe how two different generalized Reed-Solomon codes can be combined to construct one GMCC. We further establish sufficient conditions ensuring that the GMCC are Hermitian self-orthogonal, thus leading to new co

Nora M. Villanueva, Marta Sestelo, Luis Meira-Machado

Survival analysis encompasses a broad range of methods for analyzing time-to-event data, with one key objective being the comparison of survival curves across groups. Traditional approaches for identifying clusters of survival curves often rely on computationally intensive bootstrap techniques to approximate the null hypothesis distribution. While effective,

David A. Lowe, Larus Thorlacius

Semiclassical black hole emission in four spacetime dimensions is studied using a non-local effective action. The field equations that determine the time-dependent renormalized stress tensor are solved numerically for a black hole formed by an ingoing null shock wave, and otherwise smooth initial data. We find that Hawking radiation is generated dynamically

Philipp M. Wolf, Eduardo Pitthan, Zhen Zhang, Tuan T. Tran

Titanium silicide is a key contact material in advanced three-dimensional semiconductor device architectures. Here, we examine the formation of ultrathin Ti-silicide on Si(100) using a combination of non-destructive in-situ and ex-situ ion scattering techniques capable of resolving composition and structure at the nanoscale. In-situ Time-of-Flight Low-Energy

Boris Leistedt, Matthew R. Becker, Humna Awan, Eric Gawiser

The Legacy Survey of Space and Time (LSST) that will be carried out by the NSF-DOE Vera C. Rubin Observatory promises to be the defining survey of the next decade, supplying unprecedented access to the night sky to static science- and time-domain science-focused researchers alike. Maximizing the output of the broad remit of Rubin Observatory science requires

Nikolay Kozyrev

In this article we consider the construction of the superconformal mechanics that realize $SU(1,1|n)$ and $OSp(6|2)$ symmetries and involve interactions with non-Abelian bosonic currents. If is shown that for $N>4$ supersymmetries the currents involved have to satisfy the algebraic equations. General considerations on methods of solving these equations are g

Pengfei Sun, Wenyu Jiang, Piew Yoong Chee, Paul Devos

Quantised neural networks (QNNs) shrink models and reduce inference energy through low-bit arithmetic, yet most still depend on a running statistics batch normalisation (BN) layer, preventing true integer-only deployment. Prior attempts remove BN by parameter folding or tailored initialisation; while helpful, they rarely recover BN's stability and accuracy a

Clément Cren

We show that the C*-algebra of a regular 2-step nilpotent lie group can be recovered using continuous fields of Toeplitz algebras and a crossed product. We generalize this result to polycontact manifolds in the sense of van Erp which are endowed with fields of such groups. We also investigate those manifolds with a more rigid structure, namely those modeled

Thijs Beurskens, Tim Ophelders, Bettina Speckmann, Kevin Verbeek

Temporal sequences of terrains arise in various application areas. To analyze them efficiently, one generally needs a suitable abstraction of the data as well as a method to compare and match them over time. In this paper we consider merge trees as a topological descriptor for terrains and the interleaving distance as a method to match and compare them. An i

En-Ming Huang, Li-Shang Lin, Chun-Yi Lee

Large Language Models (LLMs) have achieved impressive results across various tasks, yet their high computational demands pose deployment challenges, especially on consumer-grade hardware. Mixture of Experts (MoE) models provide an efficient solution through selective activation of parameter subsets, which reduces computation requirements. Despite this effici

Wanghan Xu, Yuhao Zhou, Yifan Zhou, Qinglong Cao

Despite advances in scientific AI, a coherent framework for Scientific General Intelligence (SGI)-the ability to autonomously conceive, investigate, and reason across scientific domains-remains lacking. We present an operational SGI definition grounded in the Practical Inquiry Model (PIM: Deliberation, Conception, Action, Perception) and operationalize it vi

Omar Namnakani, Yasmeen Abdrabou, John H. Williamson, Mohamed Khamis

The potential of using gaze as an input modality in the mobile context is growing. While users often encumber themselves by carrying objects and using mobile devices while walking, the impact of encumbrance on gaze input performance remains unexplored. To investigate this, we conducted a user study (N=24) to evaluate the effect of encumbrance on the performa

M. Zahirul Alam, Robert Fickler, Yiyu Zhou, Enno Giese

We re-examine real-time holography for all-optical structuring of light and optical computation using a contemporary material: a subwavelength-thick, spatially unstructured film of indium tin oxide (ITO). When excited by spatially structured light at epsilon-near-zero frequencies, the film acts as an efficient and reconfigurable diffractive optical platform

Longfei Zhao, Jingbo Tan, Jintao Wang, Ian F Akyildiz

Underwater acoustic (UWA) communications are essential for high-speed marine data transmission but remain severely constrained by limited bandwidth, significant propagation loss, and sparse multipath structures. Conventional underwater acoustic multiple-input multiple-output (MIMO) systems primarily utilize spatial diversity but suffer from limited array res

Jiayu Zhang, Kaixing Zhao, Tianhao Shao, Bin Guo

Mobile visual crowdsensing enables large-scale, fine-grained environmental monitoring through the collection of images from distributed mobile devices. However, the resulting data is often redundant and heterogeneous due to overlapping acquisition perspectives, varying resolutions, and diverse user behaviors. To address these challenges, this paper proposes

Danial Safaei, Siddartha Khastgir, Mohsen Alirezaei, Jeroen Ploeg

Virtual testing using synthetic data has become a cornerstone of autonomous vehicle (AV) safety assurance. Despite progress in improving visual realism through advanced simulators and generative AI, recent studies reveal that pixel-level fidelity alone does not ensure reliable transfer from simulation to the real world. What truly matters is whether the syst

George Sarantoglou, Georgios Aias Karydis, Adonis Bogris, Charis Mesaritakis

An alternative extreme learning machine -ELM- paradigm is presented exploiting random non-linearities -RN, named RN-ELM, instead of a conventional fixed node non-linearity. This method is implemented on a hybrid neural engine, with the physical layer realized by an integrated silicon photonic mesh and the digital layer by a simple regression algorithm. Non-l

Pietro Baratella, Joan Elias Miro

The formalism of Dashen, Ma and Bernstein (DMB) expresses the thermal partition function of a system in terms of the S-matrix operator, roughly $Z(\beta) \propto \int dE\, e^{-\beta E}\,\text{Tr}\,\ln S(E),$ where $S$ denotes the full scattering operator on the asymptotic Fock space -- i.e. including all multi-particle sectors -- defined via the Lippmann-Sch

Jinwu Chen, Qidie Wu, Bin Li, Lin Ma

Optimizing CUDA kernels is a challenging and labor-intensive task, given the need for hardware-software co-design expertise and the proprietary nature of high-performance kernel libraries. While recent large language models (LLMs) combined with evolutionary algorithms show promise in automatic kernel optimization, existing approaches often fall short in perf

Peter Thalmeier

The influence of hyperfine coupling to nuclear spins and of their quadrupolar splitting on the induced moment order in singlet ground state magnets is investigated. The latter are found among non-Kramers f electron compounds. Without coupling to the nuclear spins these magnets have a quantum critical point (QCP) separating paramagnetic and induced moment reg

Rebecca Farina, Francois Mercier, Christian Wohlfart, Serge Masson

Hospital readmission among patients with chronic heart failure (HF) is a major clinical and economic burden. Dynamic prediction models that leverage longitudinal biomarkers may improve risk stratification over traditional static models. This study aims to develop and validate a joint model using longitudinal N-terminal pro-B-type natriuretic peptide (NT-proB

Li Cai, Taiwang Deng

Let $\mathcal{O}$ be the ring of integers for some number field $F$. Let $\chi(x)\in \mathcal{O}[x]$ be a regular monic polynomial of degree $n$. We study the asymptotic count of integral $n\times n$ matrices over $\mathcal{O}$ with the characteristic polynomial $\chi$ and bounded archimedean norm. Previous works establish such an asymptotic with a positive

Tin Stribor Sohn, Maximilian Dillitzer, Jason J. Corso, Eric Sax

Autonomous robotic systems require spatio-temporal understanding of dynamic environments to ensure reliable navigation and interaction. While Vision-Language Models (VLMs) provide open-world semantic priors, they lack grounding in 3D geometry and temporal dynamics. Conversely, geometric perception captures structure and motion but remains semantically sparse

Damian Contant, Maria Hellgren

We extend the capabilities of correlation energy functionals based on the adiabatic-connection fluctuation-dissipation theorem by implementing the analytical atomic forces within the random phase approximation (RPA), in the context of plane waves and pseudopotentials. Forces are calculated at self-consistency through the optimized effective potential method

Ying-Xing Ding, Wen-Tong Li, Li-Min Zhang, Yu-Biao Wu

Fractional Chern insulators arise in topologically nontrivial flat bands, characterized by an integer Chern number C that corresponds to the number of dissipationless edge states in the non-interacting regime. Higher Chern numbers can replicate the physics of higher Landau levels and often confer enhanced topological robustness. However, realizing correlated

Kinga Nagy

The dimension of random simplicial complexes (defined as the maximal dimension among all faces) is a natural extreme value associated with the complex, and is closely related to other functionals defined by a maximum, such as the clique number of geometric graphs or scan statistics. We extend existing results in the binomial point process case to the Poisson

Francisco Ríos, Fernanda Muñoz, Valeria Bravo, Gonzalo Castillo

The relationship between socioeconomic background, academic performance, and post-secondary educational outcomes remains a significant concern for policymakers and researchers globally. While the literature often relies on self-reported or aggregate data, its ability to trace individual pathways limits these studies. Here, we analyze administrative records f

Masashi Hatano, Saptarshi Sinha, Jacob Chalk, Wei-Hong Li

Human motion generation is a challenging task that aims to create realistic motion imitating natural human behaviour. We focus on the well-studied behaviour of priming an object/location for pick up or put down - that is, the spotting of an object/location from a distance, known as gaze priming, followed by the motion of approaching and reaching the target l

Tianhao Shao, Kaixing Zhao, Feng Liu, Lixin Yang

As unmanned systems such as Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) become increasingly important to applications like urban sensing and emergency response, efficiently recruiting these autonomous devices to perform time-sensitive tasks has become a critical challenge. This paper presents MPBS (Mobility-aware Prediction and Behavi

Ali Hassanzadeh, Morteza Davari, Dries Goossens

The National Basketball Association (NBA) is actively considering the addition of two expansion teams, raising the question of how to restructure its conferences and divisions to balance travel efficiency, fairness, and revenue opportunities. This study fills a gap at the intersection of sports operations and strategic league design by providing a quantitati

Jiayang Yang, Martin Guay, Zhixing Cao, Chunhui Zhao

Large language models (LLMs) offer promising capabilities for interpreting multivariate time-series data, yet their application to real-world battery energy storage system (BESS) operation and maintenance remains largely unexplored. Here, we present TimeSeries2Report (TS2R), a semantic translation framework that converts raw lithium-ion battery operational t

A. Talha Yalta, A. Yasemin Yalta

Contemporary AI regulation, including the EU Artificial Intelligence Act and related governance frameworks, increasingly requires institutions to justify the training data used in automated decision-making. Yet existing governance regimes provide limited operational methods for selecting, weighting, and explaining data inputs. We introduce the Smart Data Por

Zhi-Han Liu, Shigeki Matsumoto, Jie Sheng, Chuan-Yang Xing

The sub-keV mass range has long posed a challenge for the direct detection of dark matter via elastic scattering. In this Letter, we propose a new mechanism in which dark matter, assumed to be quadratically coupled to SM particles, scatters from random heterogeneous materials with intrinsic density fluctuations, yielding an enhanced coherent response. This e

Abhishek Kashyap, Yuxuan Yang, Henrik Andreasson, Todor Stoyanov

In vision-based robot manipulation, a single camera view can only capture one side of objects of interest, with additional occlusions in cluttered scenes further restricting visibility. As a result, the observed geometry is incomplete, and grasp estimation algorithms perform suboptimally. To address this limitation, we leverage diffusion models to perform ca

Shabnam Bagheri Marzijarani, Mohammad Zolfaghari, Hedieh Sajedi

The Internet of Things (IoT) is a concept by which objects find identity and can communicate with each other in a network. One of the applications of the IoT is in the field of medicine, which is called the Internet of Medical Things (IoMT). Acute Lymphocytic Leukemia (ALL) is a type of cancer categorized as a hematic disease. It usually begins in the bone m

Sören Auer, Allard Oelen, Mohamad Yaser Jaradeh, Mutahira Khalid

The rapid advancements in Generative AI and Large Language Models promise to transform the way research is conducted, potentially offering unprecedented opportunities to augment scholarly workflows. However, effectively integrating AI into research remains a challenge due to varying domain requirements, limited AI literacy, the complexity of coordinating too

Enis Yalcin, Joshua O'Hara, Maria Stamatopoulou, Chengxu Zhou

Vision-language models (VLMs) show promise in automating reward design in humanoid locomotion, which could eliminate the need for tedious manual engineering. However, current VLM-based methods are essentially "blind", as they lack the environmental perception required to navigate complex terrain. We present E-SDS (Environment-aware See it, Do it, Sorted), a

Sreerag Puravankara, Vipin P. Veetil

A tight alignment between the degree vector and the leading eigenvector arises naturally in networks with neutral degree mixing and the absence of local structures. Many real-world networks, however, violate both conditions. We derive bounds on the divergence between the degree vector and the eigenvector in networks with degree assortativity and local mesosc