March 2025 arXiv papers — page 22

Kevin Li, Marco Moraschini, George Raptis

We construct the analogue of the Serre spectral sequence for the bounded cohomology of simplicial sets with seminormed local coefficients. As applications, we obtain a (non-isometric) generalization of Gromov's mapping theorem and some partial results on the simplicial volume of manifold bundles.

Andrew Ustinov, Matey Yordanov, Andrei Kuchma, Mikhail Bychkov

This paper evaluates the Audio Spectrogram Transformer (AST) architecture for synthesized speech detection, with focus on generalization across modern voice generation technologies. Using differentiated augmentation strategies, the model achieves 0.91% EER overall when tested against ElevenLabs, NotebookLM, and Minimax AI voice generators. Notably, after tra

Alif Aqsha, Philippe Bergault, Leandro Sánchez-Betancourt

We find the equilibrium contract that an automated market maker (AMM) offers to their strategic liquidity providers (LPs) in order to maximize the order flow that gets processed by the venue. Our model is formulated as a leader-follower stochastic game, where the venue is the leader and a representative LP is the follower. We derive approximate closed-form e

Viktor Rindert, Alexander Ruder, Steffen Richter, Philipp Kühne

We report a Mueller matrix ellipsometer design using dual continuously rotating anisotropic meta wave plates which determines the full set of Mueller matrix elements in the terahertz spectral range. The instrument operates in the frequency domain and employs a frequency tunable, solid state synthesizer based, continuous wave terahertz source with sub-MHz ban

S. N. Gninenko, N. V. Krasnikov

Mirror matter from the dark hidden sector with the same particle content and gauge interactions as in the standard model is still an interesting candidate for dark matter. Several experiments on search for positronium and neutron oscillations into their mirror partner have been conducted recently. In this work we consider the transitions $K^0-K^0_m$ of a neu

Jing Li, Hao Sun

Neural networks have emerged as a powerful paradigm for tasks in high energy physics, yet their opaque training process renders them as a black box. In contrast, the traditional cut flow method offers simplicity and interpretability but requires extensive manual tuning to identify optimal cut boundaries. To merge the strengths of both approaches, we propose

Ludvig Ericson, José Pedro, Patric Jensfelt

Autonomous exploration in mobile robotics often involves a trade-off between two objectives: maximizing environmental coverage and minimizing the total path length. In the widely used information gain paradigm, exploration is guided by the expected value of observations. While this approach is effective under budget-constrained settings--where only a limited

M. Žerjal, C. Dominguez-Tagle, N. Vitas, N. Sedighi

We present a catalogue of 5306 new ultracool dwarf (UCD) candidates in the three Euclid Deep Fields in the Q1 data release. They range from late M to late T dwarfs, and include 1200 L and T dwarfs. A total of 546 objects have been spectroscopically confirmed, including 329 L dwarfs and 26 T dwarfs. We also provide empirical Euclid colours as a function of sp

Luke Rowe, Roger Girgis, Anthony Gosselin, Liam Paull

We introduce Scenario Dreamer, a fully data-driven generative simulator for autonomous vehicle planning that generates both the initial traffic scene - comprising a lane graph and agent bounding boxes - and closed-loop agent behaviours. Existing methods for generating driving simulation environments encode the initial traffic scene as a rasterized image and,

S. Van Thurenhout

We give an overview of recent developments in the computation of the anomalous dimension matrix of composite operators in non-forward kinematics. The elements of this matrix set the evolution of non-perturbative parton distributions such as the generalized parton distribution functions. The latter provide important information about hadronic structure and ar

Grégoire Béchade, Torbjörn Lundh, Philip Gerlee

Forecasts of hospitalisations of infectious diseases play an important role for allocating healthcare resources during epidemics and pandemics. Large-scale analysis of model forecasts during the COVID-19 pandemic has shown that the model rank distribution with respect to accuracy is heterogeneous and that ensemble forecasts have the highest average accuracy.

Alexander Zimmermann

We study the analogue of the Hopkins-Levitzky Theorem for dg-algebras $(A,d)$. We first consider the Hopkins approach. Here we show that for acyclic dg-algebras with graded-Artinian algebras of cycles $\ker(d)$, we also have that $(A,d)$ is left dg-Noetherian, and we show that acyclic dg-Artinian dg-algebras are dg-Noetherian. Then, studying the Levitzki app

Quentin Blomet, Bruno Da Ré

Recently, arXiv:2312.16035 showed that all logics based on Boolean Normal monotonic three-valued schemes coincide with classical logic when defined using a strict-tolerant standard ($\mathbf{st}$). Conversely, they proved that under a tolerant-strict standard ($\mathbf{ts}$), the resulting logics are all empty. Building on these results, we show that classic

Hidekazu Takahashi, Takefumi Nagumo, Kensei Jo, Aumiller Andreas

Every generation of mobile devices strives to capture video at higher resolution and frame rate than previous ones. This quality increase also requires additional power and computation to capture and encode high-quality media. We propose a method to reduce the overall power consumption for capturing high-quality videos in mobile devices. Using video frame in

Ketai Chen, Jared DeLeo, Owen Henderschedt

In 1985, Golumbic and Scheinerman established an equivalence between comparability graphs and containment graphs, graphs whose vertices represent sets, with edges indicating set containment. A few years earlier, McMorris and Zaslavsky characterized upper bound graphs, those derived from partially ordered sets where two elements share an edge if they have a c

Subhadip Ghosh, Priyadarshi Mukherjee, Sasthi C. Ghosh

These days, unmanned aerial vehicle (UAV)-based millimeter wave (mmWave) communication systems have drawn a lot of attention due to the increasing demand for faster data rates. Given the susceptibility of mmWave signals to obstacles and high propagation loss of mmWaves, ensuring line-of-sight (LoS) connectivity is critical for maintaining robust and efficien

Zakhar Kabluchko, David Albert Steigenberger

Let $X_1,\ldots, X_n$ be independent random points in the unit ball of $\mathbb R^d$ such that $X_i$ follows a beta distribution with the density proportional to $(1-\|x\|^2)^{\beta_i}1_{\{\|x\| <1\}}$. Here, $\beta_1,\ldots, \beta_n> -1$ are parameters. We study random polytopes of the form $[X_1,\ldots,X_n]$, called beta polytopes. We determine explicitly

Sakineh Khodadadi, Tohid Kargar Tasooji, Afshin Shariat-Mohayman, Navid Kalantari

Emergency preparedness reduces the severity and impact of major disasters. In the case of earthquakes, a rapid and efficient emergency response is essential to reduce the number of fatalities. Therefore, the design and planning of an adequate emergency transportation network are crucial in earthquake-prone locations. In the context of emergency transportatio

Yanze Han, Min Li, Xingyu Zhao, Ming-Min Zhao

This work investigates the potential of exploiting movable antennas (MAs) to enhance the performance of a multi-user downlink integrated sensing and communication (ISAC) system. Specifically, we formulate an optimization problem to maximize the transmit beampattern gain for sensing while simultaneously meeting each user's communication requirement by jointly

Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

Residential electricity demand forecasting is critical for efficient energy management and grid stability. Accurate predictions enable utility companies to optimize planning and operations. However, real-world residential electricity demand data often exhibit intricate temporal variability, including multiple seasonalities, periodicities, and abrupt fluctuat

H. Adhikary, P. Adrich, K. K. Allison, N. Amin

This paper presents results on multiplicity fluctuations of positively and negatively charged hadrons as well as net-electric charge fluctuations measured in central Ar+Sc interactions at beam momenta 13A, 19A, 30A, 40A, 75A, and 150A GeV/c. The fluctuation analysis is one of the tools to search for the predicted critical point of strongly interacting matter

Oliver Gueckstock, Tim Amrhein, Beatrice Andres, Pilar Jiménez-Cavero

We study femtosecond spin transport in a Gd|Pt stack induced by a laser pulse. Remarkably, the dynamics of the spin current from Gd to Pt suggests that its dominant driving force is the ultrafast spin Seebeck effect. As the contribution of a transient spin voltage in the metal Gd is minor, Gd acts akin a magnetic insulator here. This view is supported by tim

Réka Somogyfoki, Péter Ván

Since black holes lack a straightforward notion of geometrical volume due to their event horizon structure and coordinate dependence, various approaches have been proposed to introduce a meaningful geometric and thermodynamic volume. In this work we investigate the stability conditions of AdS black holes with and without volume.

Thomas Hansen, Lars Bojer Madsen, Yuta Murakami

Charge creation via quantum tunneling, i.e. dielectric breakdown, is one of the most fundamental and significant phenomena arising from strong light(field)-matter coupling. In this work, we conduct a systematic numerical analysis of quantum tunneling in one-dimensional Mott insulators described by the extended ($U$-$V$) Hubbard model. We discuss the applicab

Wangtao Sun, Xiang Cheng, Xing Yu, Haotian Xu

Reinforcement learning from human feedback (RLHF) is a critical technique for training large language models. However, conventional reward models based on the Bradley-Terry model (BTRM) often suffer from overconfidence when faced with inconsistent labels or out-of-distribution samples, leading to reward hacking, where the policy model blindly optimizes for p

Simone Sartorello, Pierfrancesco Di Cintio, Alessandro Alberto Trani, Mario Pasquato

Violent relaxation (VR) is often regarded as the mechanism leading stellar systems to collisionless meta equilibrium via rapid changes in the collective potential. We investigate the role of chaotic instabilities on single particle orbits in leading to nearly-invariant phase-space distributions, aiming at disentangling it from the chaos induced by collective

Max Hennick, Stijn De Baerdemacker

We show that the behavior of stochastic gradient descent is related to Bayesian statistics by showing that SGD is effectively diffusion on a fractal landscape, where the fractal dimension can be accounted for in a purely Bayesian way. By doing this we show that SGD can be regarded as a modified Bayesian sampler which accounts for accessibility constraints in

Ryo Misawa, Markus Kriener, Rinsuke Yamada, Ryota Nakano

In kagome metals, flat electronic bands induced by frustrated hopping are a platform for strong electron correlations. In particular, a selective coupling of flat band states to certain kagome phonon modes is proposed as a universal origin of superconductivity in this material class. Here, we investigate the superconductivity in the kagome system LaRu$_3$(Si

Wencai Ren, Peter Bøggild, Joan Redwing, Kostya Novoselov

Over the past two decades, 2D materials have rapidly evolved into a diverse and expanding family of material platforms. Many members of this materials class have demonstrated their potential to deliver transformative impact on fundamental research and technological applications across different fields. In this roadmap, we provide an overview of the key aspec

Chenyang Li, Tanmay Sunil Kapure, Prokash Chandra Roy, Zhengtao Gan

Fatigue life characterizes the duration a material can function before failure under specific environmental conditions, and is traditionally assessed using stress-life (S-N) curves. While machine learning and deep learning offer promising results for fatigue life prediction, they face the overfitting challenge because of the small size of fatigue experimenta

Renata Ferrero, Thomas Thiemann

In a recent series of publications we have started to investigate possible points of contact between the canonical (CQG) and the asymptotically safe (ASQG) approach to quantum gravity, despite the fact that the CQG approach is exclusively for Lorentzian signature gravity while the ASQG approach is mostly for Euclidean signature gravity. Expectedly, the simpl

Hanchao Liu, Rongjun Li, Weimin Xiong, Ziyu Zhou

Workflows play a crucial role in enhancing enterprise efficiency by orchestrating complex processes with multiple tools or components. However, hand-crafted workflow construction requires expert knowledge, presenting significant technical barriers. Recent advancements in Large Language Models (LLMs) have improved the generation of workflows from natural lang

Ronan Lahaye, Kosta Oubrerie, Olena Kononenko, Julien Gautier

Laser-plasma accelerators present a promising alternative to conventional accelerators. To fully exploit the extreme amplitudes of the plasma fields and produce high-quality beams, precise control over electron injection into the accelerating structure is required, along with effective laser pulse guiding to extend the acceleration length. Recent studies hav

R. Caravita, A. Cridland Mathad, J. S. Hangst, M. Hori

The CERN AD/ELENA Antimatter program studies the fundamental charge, parity, time (CPT) reversal invariance through high-precision studies of antiprotons, antihydrogen, and antiprotonic atoms. Utilizing the world-unique Antiproton Decelerator (AD) and the Extra Low Energy Antiproton (ELENA) decelerator, the program supports multiple groundbreaking experiment

E. Fernández-García, R. Wojtak, F. Prada, J. L. Cervantes-Cota

We explore transformations of the Friedman-Lema\^itre-Robertson-Walker (FLRW) metric and cosmological parameters that align with observational data, aiming to gain insights into potential extensions of standard cosmological models. We modify the FLRW metric by introducing a scaling factor, $e^{2\Theta(a)}$ (the cosmological scaling function, CSF), which alte

Qian-Qian Shi, Huan-Qiang Zhou, Murray T. Batchelor, Ian P. McCulloch

Spontaneous symmetry breaking with type-B Goldstone modes is investigated in the SO($2s+1$) ferromagnetic model. A set of orthonormal basis states in the ground state subspace are constructed, which admit an exact Schmidt decomposition, exposing self-similarities in real space of an abstract fractal underlying the ground state subspace. Focusing on the SO(5)

Jeanne Tous, Julien Chiquet

High dimensional Gaussian graphical models provide a rigorous framework to describe a network of statistical dependencies between entities, such as genes in genomic regulation studies or species in ecology. Penalized methods, including the standard Graphical-Lasso, are well-known approaches to infer the parameters of these models. As the number of variables

Jiamin Liu, Yinghe Zhao, Kai-Xing Lu, Jin-Ming Bai

In this paper we present a comprehensive study on the properties of the interstellar medium in NGC~1222, a star-forming early-type merging galaxy that forms a triple system, using optical and far-infrared (FIR) spectroscopic, and multiband photometric data. The fit to the spectral energy distribution reveals a high dust content in the galaxy, with a dust-to-

Ki-Young Choi, Erdenebulgan Lkhagvadorj, Satyabrata Mahapatra

We propose a novel cosmological scenario to explain the exceptional KM3-230213A neutrino event reported at an energy scale of $\mathcal{O}(100)$~PeV by the KM3NeT collaboration, along with its associated gravitational wave (GW) signatures. In our framework, ultra high energy neutrinos originate from the decay of a super-heavy sterile neutrino produced via th

Jonas Heimerl, Andrei Rasputnyi, Jonathan Pölloth, Stefan Meier

Attosecond science relies on driving electrons after photoemission with the strong optical field of a laser pulse, representing an intense classical coherent state of light. Bright squeezed vacuum (BSV) is a quantum state of light intense enough to drive strong-field physics. However, its mean optical electric field is zero, suggesting that, in a semiclassic

Weichen Dai, Zijie Dai, Zhijie Huang, Yixuan Pan

While current large language models (LLMs) demonstrate remarkable linguistic capabilities through training on massive unstructured text corpora, they remain inadequate in leveraging structured scientific data (e.g., chemical molecular properties in databases) that encapsulate centuries of accumulated scientific expertise. These structured datasets hold strat

Rolf Bergs, Uwe Neumann

We investigate spatial dependence in Zipf's law for cities among the OECD countries. The aim is to identify an upper tail of the distribution that follows a power law (Pareto) but is perturbed by spatial autocorrelation, as indicated by a coefficient with a significant minor or major deviation from a distribution corresponding to a (non-spatial) Zipf law. Fo

Krispin Wandel, Hesheng Wang

Semantic correspondence made tremendous progress through the recent advancements of large vision models (LVM). While these LVMs have been shown to reliably capture local semantics, the same can currently not be said for capturing global geometric relationships between semantic object regions. This problem leads to unreliable performance for semantic correspo

M. Aoki, A. M. Baldini, R. H. Bernstein, C. Carloganu

Charged-lepton flavor violation (cLFV) is one of the most powerful probes for New Physics (NP). Since lepton flavor conservation is an accidental symmetry in the Standard Model (SM), it is naturally violated in many NP models, with contributions at the level of the current experimental sensitivities. Moreover, the negligible SM contributions would make the o

YongKang Yan, Zeqian Gan, Luying Hu, Xinrui Xu

High-dimensional imaging technology has demonstrated significant research value across diverse fields, including environmental monitoring, agricultural inspection, and biomedical imaging, through integrating spatial (X*Y), spectral, and polarization detection functionalities. Here, we report a High-Dimensional encoding computational imaging technique, utiliz

Victor Lutz, Ludovic de Matteis, Virgile Batto, Nicolas Mansard

Several recently released humanoid robots, inspired by the mechanical design of Cassie, employ actuator configurations in which the motors are displaced from the joints to reduce leg inertia. While studies accounting for the full kinematic complexity have demonstrated the benefits of these designs, the associated loop-closure constraints greatly increase com

Shengyue Guan, Jindong Wang, Jiang Bian, Bin Zhu

This survey examines evaluation methods for large language model (LLM)-based agents in multi-turn conversational settings. Using a PRISMA-inspired framework, we systematically reviewed nearly 250 scholarly sources, capturing the state of the art from various venues of publication, and establishing a solid foundation for our analysis. Our study offers a struc

Eleftherios Kastis, Derek Kitson

We establish several fundamental properties of the Rigid Unit Mode (RUM) spectrum for symmetric frameworks with a discrete abelian symmetry group and arbitrary linear constraints. In particular, we identify a nonempty subset of the RUM spectrum which derives from the joint eigenvalues of generators for the linear part of the symmetry group. These joint eigen

Abdullah Vanlioglu

We introduce Entropy-Guided Sequence Weighting (EGSW), a novel approach that enhances the exploration-exploitation tradeoff by dynamically assigning weights to generated outputs based on their advantage and entropy for Reinforcement Learning-based Large Language Model fine-tuning. EGSW integrates entropy regularization with advantage-based weighting to balan

James Gabbard, Andrea Paris, Wim M. van Rees

This work presents a multigrid preconditioned high order immersed finite difference solver to accurately and efficiently solve the Poisson equation on complex 2D and 3D domains. The solver employs a low order Shortley-Weller multigrid method to precondition a high order matrix-free Krylov subspace solver. The matrix-free approach enables full compatibility w

Ayan Majumdar, Deborah D. Kanubala, Kavya Gupta, Isabel Valera

Fairness studies of algorithmic decision-making systems often simplify complex decision processes, such as bail or loan approvals, into binary classification tasks. However, these approaches overlook that such decisions are not inherently binary (e.g., approve or not approve bail or loan); they also involve non-binary treatment decisions (e.g., bail conditio

Si-Wei Liu, Ju-Jun Xie

We investigate the $K \Lambda$ strong interaction dynamics around the energy region of $N^*(1535)$ resonance through femtoscopic correlation functions within the Koonin-Pratt formalism, where coupled-channel effects of $\pi N$, $K\Lambda$, $K \Sigma$ and $\eta N$ channels are taken into account, by means of which the $N^*(1535)$ resonance can be dynamically

Diego Coello de Portugal Mecke, Haya Alyoussef, Maximilian Stubbemann, Ilia Koloiarov

Recently, Large Language Models (LLMs) have become very widespread and are used to solve a wide variety of tasks. To successfully handle these tasks, LLMs require longer training times and larger model sizes. This makes LLMs ideal candidates for pruning methods that reduce computational demands while maintaining performance. Previous methods require a retrai

Georges Habib, Felipe Leitner

In this paper, we establish a new eigenvalue estimate for the Kohn-Dirac operator on a compact CR manifold. The equality case of this estimate is characterized by the existence of a CR twistor spinor. We then classify CR manifolds carrying such spinors by showing that the Webster Ricci tensor has at most two eigenvalues. In this context, we construct several

Ahmad Biniaz, Jean-Lou De Carufel, Anil Maheshwari, Michiel Smid

A hypergraph $H$ consists of a set $V$ of vertices and a set $E$ of hyperedges that are subsets of $V$. A $t$-tuple of $H$ is a subset of $t$ vertices of $V$. A $t$-tuple $k$-coloring of $H$ is a mapping of its $t$-tuples into $k$ colors. A coloring is called $(t,k,f)$-polychromatic if each hyperedge of $E$ that has at least $f$ vertices contains tuples of a

Graciana Puentes

A comparison between neural network clustering (NNC), hierarchical clustering (HC) and K-means clustering (KMC) is performed to evaluate the computational superiority of these three machine learning (ML) techniques for organizing large datasets into clusters. For NNC, a self-organizing map (SOM) training was applied to a collection of wavefront sensor recons

Philippe Jaming

In this note we present several questions about the phase retrieval problem for the Schr{\"o}dinger equation. Some partial answers are given as well as some of the heuristics behind these questions.

William Guerin, Mathilde Hugbart, Sarah Tolila, Nolan Matthews

Stellar intensity interferometry consists in measuring the correlation of the light intensity fluctuations at two telescopes observing the same star. The amplitude of the correlation is directly related to the luminosity distribution of the star, which would be unresolved by a single telescope. This technique is based on the well-known Hanbury Brown and Twis

Arun Kumar Varanasi

We investigate the Lagrangian properties of homogeneous, stratified turbulence at different Brunt-V\"ais\"al\"a frequencies.We show increasing vertical confinement of trajectories with increasing stratification strength highlighting the predominantly horizontal dynamics of these flows. We characterize the intermittent properties of the fluid motion by comput

Pengsong Zhang, Heng Zhang, Huazhe Xu, Renjun Xu

Scientific discovery is poised for rapid advancement through advanced robotics and artificial intelligence. Current scientific practices face substantial limitations as manual experimentation remains time-consuming and resource-intensive, while multidisciplinary research demands knowledge integration beyond individual researchers' expertise boundaries. Here,

Philippe Jaming, Rolando Perez

The aim of this paper is to get a deeper understanding of the spaces of variable bandwidth introduced by Gr{\"o}chenig and Klotz (What is variable bandwidth? Comm. Pure Appl. Math., 70 (2017), 2039-2083). In particular, we show that when the variation of the bandwidth is modeled by a step function with a finite number of jumps, then, the sign retrieval princ

C. Dominguez-Tagle, M. Žerjal, N. Sedighi, P. Mas-Buitrago

The Near-Infrared Spectrometer and Photometer onboard the Euclid space mission has obtained near-infrared (NIR) slitless spectra of millions of objects, including hundreds of ultracool dwarfs. Euclid observations retrieve images and spectra simultaneously. This observing mode marks a new era in the discovery of new objects, such as L- and T-type dwarfs, whic

Yusaku Okuhara, Keiichi Sakai

We obtain Polyak-Viro type formula for the Milnor triple linking number that can be applied to diagrams with triple or more multiple-crossings. The proof is based on the idea of Brooks and Komendarczyk, but is different from theirs in that we explicitly compute the value of configuration space integral associated to the "Y-graph," and is applicable to the or

Abdelhakim Dahmani, Yacine Chitour, Hoai-Minh Nguyen, Christophe Roman

This paper is devoted to the exponential stability for one-dimensional linear wave equations with in-domain localized damping and several types of Wentzell (or dynamic) boundary conditions. In a quite general boundary setting, we establish the exponential decay of solutions towards the corresponding steady states. The results are obtained either by the multi

Pierre R. Bertrand, Jean-Marc Bardet, Michel Dabonneville, A. Mouzat

A recent model to analyze the Center of Pressure trajectories is based on the fractional Brownian motion. By doing so, one note that standing still is describe by different mechanisms following the frequency. Previous studies exhibit the existence of a control mechanism which stabilize the upright position at a large enough time scales (from 0.3 s to 1.2 s d

Xu Wang, Shuai Zhang, Baoru Huang, Danail Stoyanov

Complete reconstruction of surgical scenes is crucial for robot-assisted surgery (RAS). Deep depth estimation is promising but existing works struggle with depth discontinuities, resulting in noisy predictions at object boundaries and do not achieve complete reconstruction omitting occluded surfaces. To address these issues we propose EndoLRMGS, that combine

Fuhao Li, Huan Jin, Bin Gao, Liaoyuan Fan

Multi-view 3D visual grounding is critical for autonomous driving vehicles to interpret natural languages and localize target objects in complex environments. However, existing datasets and methods suffer from coarse-grained language instructions, and inadequate integration of 3D geometric reasoning with linguistic comprehension. To this end, we introduce Nu

Ian Costa-Alves, Nicolas Gourdain, François Gallard, Anne Gazaix

Despite being considered a hard-to-abate sector, aviation's emissions will play an important role in long-term climate mitigation of transportation. The introduction of low-carbon energy carriers and the deployment of new aircraft in the current fleet are modeled as technology-centered decarbonization policies, while supply constraints in targeted market seg

David Vernotte

Gaussian percolation can be seen as the generalization of standard Bernoulli percolation on $\mathbb{Z}^d$. Instead of a random discrete configuration on a lattice, we consider a continuous Gaussian field $f$ and we study the topological and geometric properties of the random excursion set $\mathcal{E}_\ell(f) := \{x\in \mathbb{R}^d\ |\ f(x)\geq -\ell\}$ whe

Klára Beranová, Kevin C. Prince, Mariana Klementová, Marek Vronka

CeO$_x$-based nanoforms are widely used in catalysis, or biomedical applications due to their redox activity and oxygen storage capacity. The key parameters determining their surface chemistry are the Ce$^{3+}$/Ce$^{4+}$ ratio and the ability to transition between Ce$^{4+}$ and Ce$^{3+}$ states. We synthesized Au@CeO$_x$ core@shell nanoparticles with differe

Mohamed Fkirine, Lassi Paunonen

We investigate the stabilization of mathematical models describing the structural dynamics of monopile wind turbine towers. In the fore-aft plane, we show that the system becomes polynomially stable with an energy decay rate of $t^{-1}$ under static output feedback that relies on the velocity and/or angular velocity of the nacelle. Additionally, we prove tha

Chuan-Hung Chen, Cheng-Wei Chiang, Leon M. G. de la Vega

Right-handed neutrinos $\nu_R$ play a crucial role in flavor-changing neutral-current processes with missing energy, such as $b\to s + \slashed{E} $ and $d\to s + \slashed{E} $, where Belle-II reports unexpectedly large branching fraction in $B\to K \nu \bar\nu$ decays. Assuming $\nu_R$ is the partner of the active neutrino $\nu_L$ in the standard model, a D

Sergio Izquierdo, Mohamed Sayed, Michael Firman, Guillermo Garcia-Hernando

Computing accurate depth from multiple views is a fundamental and longstanding challenge in computer vision. However, most existing approaches do not generalize well across different domains and scene types (e.g. indoor vs. outdoor). Training a general-purpose multi-view stereo model is challenging and raises several questions, e.g. how to best make use of t

Lukas Schwenkel, Johannes Köhler, Matthias A. Müller, Carsten W. Scherer

This article presents a novel framework for the robust controller synthesis problem in discrete-time systems using dynamic Integral Quadratic Constraints (IQCs). We present an algorithm to minimize closed-loop performance measures such as the $\mathcal H_\infty$-norm, the energy-to-peak gain, the peak-to-peak gain, or a multi-objective mix thereof. While IQC

A. Bazrafshan, M. Ghanaatian, P. Mirsalari, Gh. Forozani

In this paper, we derive exact black hole solutions within the framework of fourth-order quasitopological gravity (4QTG) coupled to power-law Maxwell electrodynamics in five-dimensional spacetimes. We explore the thermodynamic properties of these solutions, including entropy, temperature, and electric potential, and verify the validity of the first law of th

Abhinav Pathak, Rajkumar Muthusamy

Efficient and safe retrieval of stacked objects in warehouse environments is a significant challenge due to complex spatial dependencies and structural inter-dependencies. Traditional vision-based methods excel at object localization but often lack the physical reasoning required to predict the consequences of extraction, leading to unintended collisions and

Yuto Nishida, Makoto Morishita, Hiroyuki Deguchi, Hidetaka Kamigaito

The $k$-nearest-neighbor language model ($k$NN-LM), one of the retrieval-augmented language models, improves the perplexity for given text by directly accessing a large datastore built from any text data during inference. A widely held hypothesis for the success of $k$NN-LM is that its explicit memory, i.e., the datastore, enhances predictions for long-tail

Azat F. Aminov, Alexey A. Sokolik

Surface plasmons or phonons propagating on a two-dimensional (2D) material can exhibit coupling with resonant excitations in its substrate, and the resulting coupled modes were extensively studied. Similar coupling of edge modes propagating along a boundary of 2D material with the substrate excitations remains unexplored. This paper aims to bridge this gap b

Mathieu Suter, Jens P. Metzger, Andreas Port, Christoph R. Müller

Granular materials such as gravel, cereals, or pellets, are ubiquitous in nature, daily life, and industry. While sharing some characteristics with gases, liquids, and solids, granular matter exhibits a wealth of phenomena that defy these analogies and are yet to be fully understood. Advancing granular physics requires experimental observation at the level o

Zhonghao Jiang, Xiaoxue Ren, Meng Yan, Wei Jiang

Issue solving aims to generate patches to fix reported issues in real-world code repositories according to issue descriptions. Issue localization forms the basis for accurate issue solving. Recently, LLM-based issue localization methods have demonstrated state-of-the-art performance. However, these methods either search from files mentioned in issue descript

Sai Karthikey Pentapati, Gregoire Phillips, Alan C. Bovik

Implicit neural representations (INRs) have been successfully used to compress a variety of 3D surface representations such as Signed Distance Functions (SDFs), voxel grids, and also other forms of structured data such as images, videos, and audio. However, these methods have been limited in their application to unstructured data such as 3D meshes and point

Esteban Gómez-López, Dominik Ritter, Jisoo Kim, Harald Kübler

Quantum memories are essential for photonic quantum technologies, enabling long-distance quantum communication and serving as delay units in quantum computing. Hot atomic vapors using electromagnetically induced transparency provide a simple platform with second-long photon storage capabilities. Light-guiding structures enhance performance, but current hollo

Niklas Eiermann, Orkun Furat, Jan Nicklas, Urs A. Peuker

The agglomeration of small poorly wetted alumina particles in a stirred tank is investigated. For different experimental conditions, two bivariate probability densities for the area-equivalent diameter and aspect ratio of primary particles and agglomerates, respectively, are determined, using 2D image data from an inline camera system. Throughout each experi

Hayk Karapetyan

The polynomials $x^n + (1-x)^n + a^n$ arise naturally from FLT (Fermat's Last Theorem). We formulate a conjecture about them which is a generalization of FLT. We investigate the complex roots of these polynomials, and our main result is that in the cases $|a|\leq \frac12$ and $a=-1$, they lie on an explicitly given curve while 'filling in' that curve. We hyp

Jiangyong Huang, Baoxiong Jia, Yan Wang, Ziyu Zhu

Existing 3D vision-language (3D-VL) benchmarks fall short in evaluating 3D-VL models, creating a "mist" that obscures rigorous insights into model capabilities and 3D-VL tasks. This mist persists due to three key limitations. First, flawed test data, like ambiguous referential text in the grounding task, can yield incorrect and unreliable test results. Secon

Katharina T. Huber, Darren Overman

Horizontal gene transfer (HGT) is an important process in bacterial evolution. Current phylogeny-based approaches to capture it cannot however appropriately account for the fact that HGT can occur between bacteria living in different ecological niches. Due to the fact that arboreal networks are a type of multiple-rooted phylogenetic network that can be thoug

Adrián Detavernier, Jasper De Bock

Based on existing ideas in the field of imprecise probabilities, we present a new approach for assessing the reliability of the individual predictions of a generative probabilistic classifier. We call this approach robustness quantification, compare it to uncertainty quantification, and demonstrate that it continues to work well even for classifiers that are

David Fischinger, Martin Boyer

The deliberate manipulation of public opinion, especially through altered images, which are frequently disseminated through online social networks, poses a significant danger to society. To fight this issue on a technical level we support the research community by releasing the Digital Forensics 2023 (DF2023) training and validation dataset, comprising one m

Simon Bienewald, Diego Marcel Fieguth, James R. Anglin

Thought experiments like Maxwell's Demon or the Feynman-Smoluchowski Ratchet can help in pursuing the microscopic origin of the Second Law of Thermodynamics. Here we present a more sophisticated physical system than a ratchet, consisting of a Hamiltonian active particle which can harvest energy from an environment which may be in thermal equilibrium at a sin

Pingzhi Yuan, Xuan Pang, Danyao Wu

It is well known that there exists a significant equivalence between the vector space $\mathbb{F}_{q}^n$ and the finite fields $\mathbb{F}_{q^n}$, and many scholars often view them as the same in most contexts. However, the precise connections between them still remain mysterious. In this paper, we first show their connections from an algebraic perspective,

Shankar Dutt, Joydipto Bhattacharya, Kailash Kumar, Rajashri Urkude

Structural phase transitions in the organic inorganic metal halide perovskites are driven via rearrangement of methylammonium cation and distortion in the PbX6 octahedra. Compositional tuning is usually incorporated for suppression of the structural phase transition in these systems with cation or anion tuning. Along with the compositional tuning, behaviour

Zonghao Huang, Neil Zhenqiang Gong, Michael K. Reiter

The growing trend of legal disputes over the unauthorized use of data in machine learning (ML) systems highlights the urgent need for reliable data-use auditing mechanisms to ensure accountability and transparency in ML. We present the first proactive, instance-level, data-use auditing method designed to enable data owners to audit the use of their individua

Philippe Brax, Pierre Brun

We study the effects of the oscillating axion field present in our environment on the Casimir pressure between two metallic plates. We take into account the finite conductivity of the boundary plates and model the interactions between matter and photons in the Schwinger-Keldysh formalism. This allows us to take into account dissipation in the quantum field d

Petter Törnberg, Juliana Chueri

Toxic and uncivil politics is widely seen as a growing threat to democratic values and governance, yet our understanding of the drivers and evolution of political incivility remains limited. Leveraging a novel dataset of nearly 18 million Twitter messages from parliamentarians in 17 countries over five years, this paper systematically investigates whether po

Kunpeng Zhang, Lei Xu, Xinlei Yi, Ming Cao

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal-dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an $\mathcal{O}( {{T^{\m

Sebastián Espinel-Ríos, José L. Avalos, Ehecatl Antonio del Rio Chanona, Dongda Zhang

Efficient and robust bioprocess control is essential for maximizing performance and adaptability in advanced biotechnological systems. In this work, we present a reinforcement-learning framework for multi-setpoint and multi-trajectory tracking. Tracking multiple setpoints and time-varying trajectories in reinforcement learning is challenging due to the compl

Xiaolei Bian, Changfu Zou, Björn Fridholm, Christian Sundvall

Accurate state-of-charge (SOC) estimation is essential for optimizing battery performance, ensuring safety, and maximizing economic value. Conventional current and voltage measurements, however, have inherent limitations in fully inferring the multiphysics-resolved dynamics inside battery cells. This creates an accuracy barrier that constrains battery usage

V. K. Dobrev

In the present paper we continue the project of systematic construction of invariant differential operators on the example of the non-compact exceptional Lie algebra $F'_4=F_{4(4)}$ which is split real form of the exceptional Lie algebra $F_4$. We consider induction from a maximal parabolic algebra. We classify the reducible Verma modules over $F_4$ which ar

Jackson Welch

Typosquatting is a long-standing cyber threat that exploits human error in typing URLs to deceive users, distribute malware, and conduct phishing attacks. With the proliferation of domain names and new Top-Level Domains (TLDs), typosquatting techniques have grown more sophisticated, posing significant risks to individuals, businesses, and national cybersecur

Wei-Jin Huang, Yuan-Ming Li, Zhi-Wei Xia, Yu-Ming Tang

Error detection in procedural activities is essential for consistent and correct outcomes in AR-assisted and robotic systems. Existing methods often focus on temporal ordering errors or rely on static prototypes to represent normal actions. However, these approaches typically overlook the common scenario where multiple, distinct actions are valid following a