November 2024 arXiv papers — page 54

Andrea Marchese, Andrea Merlo

We give a new, elementary proof of the fact that metric 1-currents in the Euclidean space correspond to Federer-Fleming flat chains.

AmirHossein Naghi Razlighi, Tiago Novello, Asen Nachkov, Thomas Probst

In the literature, it has been shown that the evolution of the known explicit 3D surface to the target one can be learned from 2D images using the instantaneous flow field, where the known and target 3D surfaces may largely differ in topology. We are interested in capturing 4D shapes whose topology changes largely over time. We encounter that the straightfor

Victor Valencia Torres

Open heavy flavor and quarkonia have long been identified as ideal probes for understanding the quark-gluon plasma (QGP). Heavy quarks are produced in the early stage of the heavy-ion collisions. Therefore they experience the evolution of the medium produced, providing an important tool to investigate the properties of the QGP. In particular, the magnitude o

Hongsi Liu, Jun Liu, Guangfeng Jiang, Xin Jin

As one of the automotive sensors that have emerged in recent years, 4D millimeter-wave radar has a higher resolution than conventional 3D radar and provides precise elevation measurements. But its point clouds are still sparse and noisy, making it challenging to meet the requirements of autonomous driving. Camera, as another commonly used sensor, can capture

Maximilian Balthasar Mansky, Chonfai Kam, Claudia Linnhoff-Popien

We introduce a novel quantum algorithm for determining graph connectedness using a constant number of measurements. The algorithm can be extended to find connected components with a linear number of measurements. It relies on non-unitary abelian gates taken from ZX calculus. Due to the fusion rule, the two-qubit gates correspond to a large single action on t

Guojun Xiong, Shufan Wang, Daniel Jiang, Jian Li

Federated reinforcement learning (FedRL) enables multiple agents to collaboratively learn a policy without sharing their local trajectories collected during agent-environment interactions. However, in practice, the environments faced by different agents are often heterogeneous, leading to poor performance by the single policy learned by existing FedRL algori

Mohamed Roshdy, Osama R. Bilal

Metamaterials can enable unique mechanical properties based on their geometry rather than their chemical composition. Such properties can go beyond what is possible using conventional materials. Most of the existing literature consider metamaterials in Cartesian coordinates with zero curvature. However, realistic utilization of meta-structures is highly like

Luigi De Masi, Andrea Marchese

We prove a refined version of the celebrated Lusin type theorem for gradients by Alberti, stating that any Borel vector field $f$ coincides with the gradient of a $C^1$ function $g$, outside a set $E$ of arbitrarily small Lebesgue measure. We replace the Lebesgue measure with any Radon measure $\mu$, and we obtain that the estimate on the $L^p$ norm of $Dg$

Andrew Snowden

Let $\mathbb{M}$ be the group of multiplicative characters of a finite field $\mathbb{F}$, and let $\mathbb{J}(\alpha, \beta)$ be the Jacobi sum, for $\alpha, \beta \in \mathbb{M}$. We observe that the function $\mathbb{J} \colon \mathbb{M} \times \mathbb{M} \to \mathbf{C}$ satisfies three elementary properties. We show that these properties (very nearly) ch

Elena Y. Vedmedenko, Mikhail Kostylev

Interfacial Dzyaloshinskii-Moriya interaction (IF-DMI) leads to non-collinear spin configurations within the magnetic layers of multilayer heterostructures, while its interlayer counterpart (IL-DMI) minimizes chiral states between the layers. Here, we demonstrate that the symmetries of these interactions are very different, even though both arise from pairwi

Shaozhen Xu

We investigate $(2+1)-$dimensional oscillatory integral operators characterized by polynomial phase functions. By employing Stein's complex interpolation, we derive sharp $L^2\to L^p$ decay estimates for these operators.

Eugene Eberbach

Evolution by natural selection, which is one of the most compelling themes of modern science, brought forth evolutionary algorithms and evolutionary computation, applying mechanisms of evolution in nature to various problems solved by computers. In this paper we concentrate on evolutionary automata that constitute an analogous model of evolutionary computati

Sneha Sudhir Shetiya, Divya Garikapati, Veeraja Sohoni

Functional safety forms an important aspect in the design of systems. Its emphasis on the automotive industry has evolved significantly over the years. Till date many methods have been developed to get appropriate FTA(Fault Tree analysis) for various scenarios and features pertaining to Autonomous Driving. This paper is an attempt to explore the scope of usi

Kuantay Boshkayev, Gulnaz Takey, Vladimir Ivashchuk, Algis Malybayev

This research investigates a non-extreme dyonic-like dilatonic charged black hole solution within a four-dimensional gravity model. This model incorporates two scalar (dilaton) fields and two Abelian vector fields, with interactions between the scalar and vector fields mediated by exponential terms involving two dilatonic coupling vectors. The solution is ch

Maximilian Mews, Ansar Aynetdinov, Vivian Schiller, Peter Eisert

While recent advancements in machine learning, such as LLMs, are revolutionizing software development and creative industries, they have had minimal impact on engineers designing mechanical parts, which remains largely a manual process. Existing approaches to generating 3D geometry most commonly use meshes as a 3D representation. While meshes are suitable fo

Xiang Xu, Hao Wang, Wei Guo, Luankang Zhang

Click-through Rate (CTR) prediction is crucial for online personalization platforms. Recent advancements have shown that modeling rich user behaviors can significantly improve the performance of CTR prediction. Current long-term user behavior modeling algorithms predominantly follow two cascading stages. The first stage retrieves subsequence related to the t

M. Maneyro, E. G. S. Luna, M. Peláez

We investigate the high-energy behavior of the elastic scattering amplitude using the eikonal and $U$-matrix unitarization schemes. This work extends the analysis in [1] by exploring the sensitivity of the Pomeron and Odderon parameters to the inclusion of differential cross-section data over an extended range of $|t|$.

Junhong Shen, Atishay Jain, Zedian Xiao, Ishan Amlekar

Large Language Model (LLM) agents are rapidly improving to handle increasingly complex web-based tasks. Most of these agents rely on general-purpose, proprietary models like GPT-4 and focus on designing better prompts to improve their planning abilities. However, general-purpose LLMs are not specifically trained to understand specialized web contexts such as

Yiyang Cai, Zhengkai Jiang, Yulong Liu, Chunyang Jiang

Facial personalization faces challenges to maintain identity fidelity without disrupting the foundation model's prompt consistency. The mainstream personalization models employ identity embedding to integrate identity information within the attention mechanisms. However, our preliminary findings reveal that identity embeddings compromise the effectiveness of

Guozheng Lu, Yunfan Ren, Fangcheng Zhu, Haotian Li

Trajectory generation for fully autonomous flights of tail-sitter unmanned aerial vehicles (UAVs) presents substantial challenges due to their highly nonlinear aerodynamics. In this paper, we introduce, to the best of our knowledge, the world's first fully autonomous tail-sitter UAV capable of high-speed navigation in unknown, cluttered environments. The UAV

Tsogt-Ochir Enkhbayar

This paper advances the computational efficiency of Deep Hedging frameworks through the novel integration of Kronecker-Factored Approximate Curvature (K-FAC) optimization. While recent literature has established Deep Hedging as a data-driven alternative to traditional risk management strategies, the computational burden of training neural networks with first

Gauthier Wissocq, Yongle Liu, Rémi Abgrall

We present a novel positive kinetic scheme built on the efficient collide-and-stream algorithm of the lattice Boltzmann method (LBM) to address hyperbolic conservation laws. We focus on the compressible Euler equations with strong discontinuities. Starting from the work of Jin and Xin [20] and then [4,8], we show how the LBM discretization procedure can yiel

CMS Collaboration

A search is presented for rare decays of the Z and Higgs bosons to a photon and a J/$\psi$ or a $\psi$(2S) meson, with the charmonium state subsequentially decaying to a pair of muons. The data set corresponds to an integrated luminosity of 123 fb$^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV collected with the CMS detector at the L

Catalina Lesmes, Francisco Zuluaga, Henry Laniado, Andres Gomez

Functional data analysis has gained significant attention due to its wide applicability. This research explores the extension of statistical analysis methods for functional data, with a primary focus on supervised classification techniques. It provides a review on the existing depth-based methods used in functional data samples. Building on this foundation,

Roberto Emparan, Mikel Sanchez-Garitaonandia, Marija Tomašević

Thin enough black strings are unstable to growing ripples along their length, eventually pinching and forming a naked singularity on the horizon. We investigate how string theory can resolve this singularity. First, we study the string-scale version of the static non-uniform black strings that branch off at the instability threshold: "string-ball strings", w

Xingyang Yu

In this paper, we discuss a novel top-down perspective on gauging parameters in quantum field theories (QFTs) by promoting them to partially dynamical fields. Through a generalized notion of symmetry theories, we explore the consequences of this promotion, revealing new topological defects, decompositions as well as generalized symmetry structures across var

Yuhui Lin, Jiahao Zhang, Siyuan Li, Jimin Xiao

Event cameras, as an emerging imaging technology, offer distinct advantages over traditional RGB cameras, including reduced energy consumption and higher frame rates. However, the limited quantity of available event data presents a significant challenge, hindering their broader development. To alleviate this issue, we introduce a tailored U-shaped State Spac

Bauyrzhan K. Primkulov, Davis J. Evans, Joel B. Been, John W. M. Bush

Pilot-wave hydrodynamics concerns the dynamics of 'walkers,' droplets walking on a vibrating bath, and has provided the basis for the burgeoning field of hydrodynamic quantum analogs. We here explore a theoretical model of pilot-wave hydrodynamics that relaxes the simplifying assumption of resonance between the droplet and its pilot wave, specifically the as

Jonas Gösgens, Niklas Jansen, Hector Geffner

Learning STRIPS action models from action traces alone is a challenging problem as it involves learning the domain predicates as well. In this work, a novel approach is introduced which, like the well-known LOCM systems, is scalable, but like SAT approaches, is sound and complete. Furthermore, the approach is general and imposes no restrictions on the hidden

Morteza Alimi, Tobias Mömke, Michael Ruderer

We present an approximation algorithm for the Prize-collecting Ordered Traveling Salesman Problem (PCOTSP), which simultaneously generalizes the Prize-collecting TSP and the Ordered TSP. The Prize-collecting TSP is well-studied and has a long history, with the current best approximation factor slightly below $1.6$, shown by Blauth, Klein and N\"agele [IPCO 2

Wiebke Bennecke, Ignacio Gonzalez Oliva, Jan Philipp Bange, Paul Werner

Two-dimensional transition metal dichalcogenides (TMDs) and organic semiconductors (OSCs) have emerged as promising material platforms for next-generation optoelectronic devices. The combination of both is predicted to yield emergent properties while retaining the advantages of their individual components. In OSCs the optoelectronic response is typically dom

Tim Unger, Arash Sal Moslehian, J. D. Peiffer, Johann Ullrich

Marker-based Optical Motion Capture (OMC) paired with biomechanical modeling is currently considered the most precise and accurate method for measuring human movement kinematics. However, combining differentiable biomechanical modeling with Markerless Motion Capture (MMC) offers a promising approach to motion capture in clinical settings, requiring only mini

Joséphine Pazem, Marius Krumm, Alexander Q. Vining, Lukas J. Fiderer

In the last decade, the free energy principle (FEP) and active inference (AIF) have achieved many successes connecting conceptual models of learning and cognition to mathematical models of perception and action. This effort is driven by a multidisciplinary interest in understanding aspects of self-organizing complex adaptive systems, including elements of ag

S. Krishnamoorthy, T. Dalal

J.-P. Serre, in his paper [1], established a sufficient condition on $n$ for the $n$-th coefficient of the series $\eta^{26}$ to vanish. However, the question that whether this is a necessary condition remained unanswered. In this paper, using the theory of Hecke eigenforms explored by Serre, we prove some partial cases for the converse part.

Ross Glew, Tomasz Lukowski

Motivated by a new term-wise factorised formula for the two-loop MHV integrand for scattering amplitudes in $\mathcal{N}=4$ super Yang-Mills (SYM), together with recent results for the five-point negative ladders in loop space, we present the canonical forms for general ladders in loop space for an arbitrary number of particles to all loops. We make use of t

K. De, U. C. De

In the present paper we study $\eta$-Ricci solitons on Kenmotsu 3-manifolds. Moreover, we consider $\eta$-Ricci solitons on Kenmotsu 3-manifolds with Codazzi type of Ricci tensor and cyclic parallel Ricci tensor. Beside these, we study $\phi$-Ricci symmetric $\eta$-Ricci soliton on Kenmotsu 3-manifolds. Also Kenmotsu 3-manifolds satisfying the curvature cond

E. G. S. Luna, M. G. Ryskin, V. A. Khoze

Odderon is the $C$-odd amplitude that does not fall (or decrease very slowly) with energy. The expected amplitude is small and mainly real. Therefore, extracting it from the data on top of a much larger $C$-even contribution is challenging. The only chance is to consider the very low $|t|$ region of Coulomb nuclear interference or the diffractive dip region.

Hans G. Feichtinger, Christoph Richard, Christoph Schumacher, Nicolae Strungaru

Mathematical diffraction theory has been developed since about 1995. Hof's initial approach relied on tempered distributions in euclidean space. Nowadays often the Fourier theory by Argabright and Gil de Lamadrid is used, which applies to appropriate measures on locally compact abelian groups. We review diffraction theory using Wiener amalgams as test functi

Dominik Bär, Abdurahman Maarouf, Stefan Feuerriegel

Online hate speech poses a serious threat to individual well-being and societal cohesion. A promising solution to curb online hate speech is counterspeech. Counterspeech is aimed at encouraging users to reconsider hateful posts by direct replies. However, current methods lack scalability due to the need for human intervention or fail to adapt to the specific

Vladimir M. Braun, Hua-Yu Jiang, Alexander N. Manashov, Andreas von Manteuffel

Making use of conformal symmetry of large-$n_f$ QCD in $d=4-2\epsilon$ dimensions at the Wilson-Fischer fixed point, we calculate the two-loop coefficient functions in the operator product expansion of two electromagnetic currents in general kinematics with two different photon virtualities. This result is necessary for the description of the double deeply v

Patrik Kenfack, Ulrich Aïvodji, Samira Ebrahimi Kahou

Neural networks can learn spurious correlations in the data, often leading to performance degradation for underrepresented subgroups. Studies have demonstrated that the disparity is amplified when knowledge is distilled from a complex teacher model to a relatively ``simple'' student model. Prior work has shown that ensemble deep learning methods can improve

Sanket Agrawal, Joris Bierkens, Gareth O. Roberts

Piecewise deterministic Markov processes provide scalable methods for sampling from the posterior distributions in big data settings by admitting principled sub-sampling strategies that do not bias the output. An important example is the Zig-Zag process of [Ann. Stats. 47 (2019) 1288 - 1320] where clever sub-sampling has been shown to produce an essentially

Kaichen Zhang, Yifei Shen, Bo Li, Ziwei Liu

Recent advances in Large Multimodal Models (LMMs) lead to significant breakthroughs in both academia and industry. One question that arises is how we, as humans, can understand their internal neural representations. This paper takes an initial step towards addressing this question by presenting a versatile framework to identify and interpret the semantics wi

Jiankang Chen, Tong Zhang, Wei-Shi Zheng, Ruixuan Wang

Out-of-distribution (OOD) detection is crucial in many real-world applications. However, intelligent models are often trained solely on in-distribution (ID) data, leading to overconfidence when misclassifying OOD data as ID classes. In this study, we propose a new learning framework which leverage simple Jigsaw-based fake OOD data and rich semantic embedding

Johann Ostmeyer, Aniket Sen, Carsten Urbach

We investigate the oblique Lanczos method recently put forward in arXiv:2406.20009 for analysing Euclidean correlators in lattice field theories and show that it is analytically equivalent to the well known Prony Generalised Eigenvalue Method (PGEVM). Moreover, we discuss that the signal-to-noise problem is not aleviated by either of these two methods. Still

Jesús Gómez-Vilardebó, Burak Hasırcıoğlu, Deniz Gündüz

Supporting multiple partial computations efficiently at each of the workers is a keystone in distributed coded computing in order to speed up computations and to fully exploit the resources of heterogeneous workers in terms of communication, storage, or computation capabilities. Multivariate polynomial coding schemes have recently been shown to deliver faste

Samuel Mañas-Valero, Toeno van der Sar, Rembert A. Duine, Bart van Wees

Spintronics is concerned with replacing charge current with current of spin, the electron's intrinsic angular momentum. In magnetic insulators, spin currents are carried by magnons, the quanta of spin-wave excitations on top of the magnetically ordered state. Magnon spin currents are especially promising for information technology due to their low intrinsic

Hristijan Kochankovski, Angels Ramos, Laura Tolos, Sebastian Blacker

We discuss the effects induced by the potential presence of hyperons in hot and ultra-dense matter within the context of neutron star mergers. Specifically, we address their effect on the dominant post-merger frequency of the gravitational waves. By performing a simulation campaign with a large sample of hyperonic and nucleonic equations of state, we explici

Anders Melander, Wojciech Laskowski, Spencer J. Sherwin, Allan P. Engsig-Karup

We present a spectral element model for general-purpose simulation of non-overturning nonlinear water waves using the incompressible Navier-Stokes equations (INSE) with a free surface. The numerical implementation of the spectral element method is inspired by the related work by Engsig-Karup et al. (2016) and is based on nodal Lagrange basis functions, mass

Benjamin Leather

We present a novel approach for calculating the gravitational self-force (GSF) in the Lorenz gauge, employing hyperboloidal slicing and spectral methods. Our method builds on the previous work that applied hyperboloidal surfaces and spectral approaches to scalar-field toy model [Phys. Rev. D 105, 104033 (2022)], extending them to handle gravitational perturb

Manon Dausort, Tiffanie Godelaine, Maxime Zanella, Karim El Khoury

Cytology slides are essential tools in diagnosing and staging cancer, but their analysis is time-consuming and costly. Foundation models have shown great potential to assist in these tasks. In this paper, we explore how existing foundation models can be applied to cytological classification. More particularly, we focus on low-rank adaptation, a parameter-eff

Jan Held, Renaud Vandeghen, Abdullah Hamdi, Adrien Deliege

Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes with compositions of Gaussian primitives. However, 3D Gaussians present several limitations for scene reconstruction. Accurately capturing hard edges is challenging without significa

Nihar Gargava, Maryna Viazovska

We investigate the average number of lattice points within a ball for the $n$th cyclotomic number field, where the lattice is chosen at random from the set of unit determinant ideal lattices of the field. We show that this average is nearly identical to the average number of lattice points in a ball among all unit determinant random lattices of the same dime

Alec Wright, Alistair Carson, Lauri Juvela

This paper introduces Open-Amp, a synthetic data framework for generating large-scale and diverse audio effects data. Audio effects are relevant to many musical audio processing and Music Information Retrieval (MIR) tasks, such as modelling of analog audio effects, automatic mixing, tone matching and transcription. Existing audio effects datasets are limited

Colin Diggs, Michael Doyle, Amit Madan, Siggy Scott

Legacy software systems, written in outdated languages like MUMPS and mainframe assembly, pose challenges in efficiency, maintenance, staffing, and security. While LLMs offer promise for modernizing these systems, their ability to understand legacy languages is largely unknown. This paper investigates the utilization of LLMs to generate documentation for leg

Rongchen Li, Yang Bai, Marek Skowronski

A finite element model consisting of a conducting filament with or without a gap was used to reproduce behavior of TaO$_x$-based resistive switching devices. The specific goal was to explore the range of possible filament parameters such a filament diameter, composition, gap width, and composition to reproduce the conductance and shape of I-V while keeping t

Juan Giral Martínez, Silvia de Monte, Matthieu Barbier

A central feature of complex systems is the relevance and entanglement of different levels of description. For instance, the dynamics of ecosystems can be alternatively described in terms of large ecological processes and classes of organisms, or of individual species and their relations. Low-dimensional heuristic 'macroscopic' models that are widely used to

Paolo Ciaccia, Davide Martinenghi

Skyline queries are one of the most widely adopted tools for Multi-Criteria Analysis, with applications covering diverse domains, including, e.g., Database Systems, Data Mining, and Decision Making. Skylines indeed offer a useful overview of the most suitable alternatives in a dataset, while discarding all the options that are dominated by (i.e., worse than)

Lukas Fischer, Yingqiang Gao, Alexa Lintner, Sarah Ebling

Audio description (AD) is a crucial accessibility service provided to blind persons and persons with visual impairment, designed to convey visual information in acoustic form. Despite recent advancements in multilingual machine translation research, the lack of well-crafted and time-synchronized AD data impedes the development of audio description translatio

N. La Palombara, L. Sidoli, S. Mereghetti, G. L. Israel

The persistent BeXRBs are a class of High-Mass X-ray Binaries (HMXRBs), which are characterized by persistent low X-ray luminosities ($L_{\rm X} \sim 10^{34}$ erg s$^{-1}$) and wide ($P_{\rm orb} >$ 30 d), almost circular orbits. In these sources the NS is slowly rotating (with $P_{\rm spin}$ well above 100 s) and accretes matter directly from the wind of th

Joachim Kerner, Olaf Post, Mostafa Sabri, Matthias Täufer

This paper is devoted to the investigation of the spectral theory and dynamical properties of periodic graphs which are not locally finite but carry non-negative, symmetric and summable edge weights. These graphs are shown to exhibit rather intriguing behaviour: for example, we construct a periodic graph whose Laplacian has purely singular continuous spectru

Julio Arrechea, Giulio Neri, Stefano Liberati

In quantum field theory applied to black hole spacetimes, substantial evidence suggests that the Unruh and Hartle-Hawking vacuum states become singular at Cauchy horizons. This raises essential questions regarding the impact of quantum field backreaction on the stability of Cauchy horizons in static scenarios and inner horizons in evolving spacetimes. To app

Mara Pompili

We determine the class group of those generalized cluster algebras that are Krull domains. In particular, this provides a criterion for determining whether or not a generalized cluster algebra is a UFD. In fact, any finitely generated abelian group can be realized as the class group of a generalized cluster algebra. Additionally, we show that generalized clu

Liangrui Pan, Qingchun Liang, Wenwu Zeng, Yijun Peng

Spread through air spaces (STAS) is a distinct invasion pattern in lung cancer, crucial for prognosis assessment and guiding surgical decisions. Histopathology is the gold standard for STAS detection, yet traditional methods are subjective, time-consuming, and prone to misdiagnosis, limiting large-scale applications. We present VERN, an image analysis model

Hitesh Laxmichand Patel, Amit Agarwal, Bhargava Kumar, Karan Gupta

Accurate barcode detection and decoding in Identity documents is crucial for applications like security, healthcare, and education, where reliable data extraction and verification are essential. However, building robust detection models is challenging due to the lack of diverse, realistic datasets an issue often tied to privacy concerns and the wide variety

Jieming Bian, Lei Wang, Letian Zhang, Jie Xu

Foundation models (FMs) achieve strong performance across diverse tasks with task-specific fine-tuning, yet full parameter fine-tuning is often computationally prohibitive for large models. Parameter-efficient fine-tuning (PEFT) methods like Low-Rank Adaptation (LoRA) reduce this cost by introducing low-rank matrices for tuning fewer parameters. While LoRA a

Alexandra Shlapentokh, Caleb Springer

In this paper, we study questions of definability and decidability for infinite algebraic extensions ${\bf K}$ of $\mathbb{F}_p(t)$ and their subrings of $\mathcal{S}$-integral functions. We focus on fields ${\bf K}$ satisfying a local property which we call $q$-boundedness. This can be considered a function field analogue of prior work of the first author w

Sahil Goyal, Abhinav Mahajan, Swasti Mishra, Prateksha Udhayanan

Graphic designs are an effective medium for visual communication. They range from greeting cards to corporate flyers and beyond. Off-late, machine learning techniques are able to generate such designs, which accelerates the rate of content production. An automated way of evaluating their quality becomes critical. Towards this end, we introduce Design-o-meter

Ben Knudsen, Shmuel Weinberger

We show that the analog category of a finite group is essentially proportional to the size of its largest Sylow subgroup. We conclude that the universal upper bound given by the order of the group is very far from optimal.

Aniket Bhattacharyya, Anurag Tripathi

Invoices and receipts submitted by employees are visually rich documents (VRDs) with textual, visual and layout information. To protect against the risk of fraud and abuse, it is crucial for organizations to efficiently extract desired information from submitted receipts. This helps in the assessment of key factors such as appropriateness of the expense clai

Hana Krasna, Christopher S. Jacobs, Matthias Schartner, Patrick Charlot

Aims: We computed a celestial reference frame (CRF) from Very Long Baseline Interferometry (VLBI) Global Observing System (VGOS) data after five years of regular observations (155 multi-baseline 24-hour VGOS sessions until 2024.0). In this paper we document the source selection and scheduling strategies for the individual sessions, and investigate the effect

Koichi Yamagata

In the estimation for a parametric family of quantum state on a Hilbert space $\mathcal{H}$, the Gill and Massar bound is known as a lower bound of weighted traces of covariances of unbiased estimators. The Gill and Massar bound is derived by considering the convexity of the set of classical Fisher information matrices, and the bound is locally achievable by

D. Chaver, S. Harris, L. Pinuel, O. Kindgren

The RVfpga course offers a solid introduction to computer architecture using the RISC-V instruction set and FPGA technology. It focuses on providing hands-on experience with real-world RISC-V cores, the VeeR EH1 and the VeeR EL2, developed by Western Digital a few years ago and currently hosted by ChipsAlliance. This course is particularly aimed at educators

Miriam Alber, Christoph Hönes, Patrick Baier

One of the most promising use-cases for machine learning in industrial manufacturing is the early detection of defective products using a quality control system. Such a system can save costs and reduces human errors due to the monotonous nature of visual inspections. Today, a rich body of research exists which employs machine learning methods to identify rar

Dietrich Burde, Friedrich Wagemann

We study the adjoint cohomology of perfect Lie algebras over the complex numbers. For the family of perfect Lie algebras $\mathfrak{g}=\mathfrak{sl}_2(\Bbb C)\ltimes V_m$ we obtain some explicit results for $H^k(\mathfrak{g},\mathfrak{g})$ with $k\ge 0$. Here $V_m$ is the irreducible representation of $\mathfrak{sl}_2(\Bbb C)$ of dimension $m+1$. For the com

Luca Glawion, Julius Polz, Harald Kunstmann, Benjamin Fersch

The spatial and temporal distribution of precipitation has a significant impact on human lives by determining freshwater resources and agricultural yield, but also rainfall-driven hazards like flooding or landslides. While the ERA5 reanalysis dataset provides consistent long-term global precipitation information that allows investigations of these impacts, i

Zhuo Li, Mingshuang Luo, Ruibing Hou, Xin Zhao

Human motion generation has been widely studied due to its crucial role in areas such as digital humans and humanoid robot control. However, many current motion generation approaches disregard physics constraints, frequently resulting in physically implausible motions with pronounced artifacts such as floating and foot sliding. Meanwhile, training an effecti

Ogulcan Isitman, Gokhan Alcan, Ville Kyrki

Robotic magnetic manipulation offers a minimally invasive approach to gastrointestinal examinations through capsule endoscopy. However, controlling such systems using external permanent magnets (EPM) is challenging due to nonlinear magnetic interactions, especially when there are complex navigation requirements such as avoidance of sensitive tissues. In this

Aloïs Castellano, J. P. Alvarinhas Batista, Olle Hellman, Matthieu J. Verstraete

The temperature-dependent phonons are a generalization of interatomic force constants varying in T, which as found widespread use in computing the thermal transport of materials. A formal justification for using this combination to access thermal conductivity in anharmonic crystals, beyond the harmonic approximation and perturbation theory, is still lacking.

Simeon Minic, Luka Velickovic, Burkhard Annighöfer, Aurélien Thureau

The red macroalgae Porphyra, commonly known as Nori, is widely used as food around the world due to its high nutrient content, including the significant abundance of coloured phycobiliproteins (PBPs). Among these, R-phycocyanin (R-PC) stands out for its vibrant purple colour and numerous bioactive properties, making it a valuable protein for the food industr

Mike Shengbo Wang, Florian Beutler, J. Aguilar, S. Ahlen

In galaxy survey analysis, the observed clustering statistics do not directly match theoretical predictions but rather have been processed by a window function that arises from the survey geometry including the sky footprint, redshift-dependent background number density and systematic weights. While window convolution of the power spectrum is well studied, f

Lars Nieradzik, Henrike Stephani, Janis Keuper

In this paper, we present an approach for evaluating attribution maps, which play a central role in interpreting the predictions of convolutional neural networks (CNNs). We show that the widely used insertion/deletion metrics are susceptible to distribution shifts that affect the reliability of the ranking. Our method proposes to replace pixel modifications

Dorit Assaf, Giorgia Adorni, Elia Lutz, Lucio Negrini

This paper addresses the incorporation of problem decomposition skills as an important component of computational thinking (CT) in K-12 computer science (CS) education. Despite the growing integration of CS in schools, there is a lack of consensus on the precise definition of CT in general and decomposition in particular. While decomposition is commonly refe

Jungeng Zhou, Jiahao Huang, Jinye Wei, Chengyin Han

Entanglement-enhanced quantum sensors encounter a fundamental trade-off: while entanglement improves precision to the Heisenberg limit, it restricts dynamic range. To address this trade-off, we present a credible-interval-based adaptive Bayesian quantum frequency estimation protocol for Greenberger-Horne-Zeilinger (GHZ)-state-based atomic clocks. Our method

Geoffrey M. Diederich, Mai Nguyen, John Cenker, Jordan Fonseca

Collective excitations presenting nonlinear dynamics are fundamental phenomena with broad applications. A prime example is nonlinear optics, where diverse frequency mixing processes are central to communication, sensing, wavelength conversion, and attosecond physics. Leveraging recent progress in van der Waals magnetic semiconductors, we demonstrate nonlinea

Koji Hashimoto, Koshiro Matsuo, Masaki Murata, Gakuto Ogiwara

Topological solitons, which are stable, localized solutions of nonlinear differential equations, are crucial in various fields of physics and mathematics, including particle physics and cosmology. However, solving these solitons presents significant challenges due to the complexity of the underlying equations and the computational resources required for accu

F. Erman, O. T. Turgut

There are few exactly solvable potentials in quantum mechanics for which the completeness relation of the energy eigenstates can be explicitly verified. In this article, we give an elementary proof that the set of bound (discrete) states together with the scattering (continuum) states of the reflectionless potential form a complete set. We also review a dire

Madalina N. Tudorache, M. J. Jarvis, A. A. Ponomareva, I. Heywood

The interplay between atomic gas, the star-formation history of a galaxy and its environment are intrinsically linked, and we need to decouple these dependencies to understand their role in galaxy formation and evolution. In this paper, we analyse the star formation histories (SFHs) of 187 galaxies from the MIGHTEE-HI Survey Early Science Release data, focus

Joseph Farrington, Samah Alimam, Martin Utley, Kezhi Li

Efforts to reduce platelet wastage in hospital blood banks have focused on ordering policies, but the predominant practice of issuing the oldest unit first may not be optimal when some units are returned unused. We propose a novel, machine learning (ML)-guided issuing policy to increase the likelihood of returned units being reissued before expiration. Our M

Wen-Li Yuan, Chun Huang, Chen Zhang, Enping Zhou

The observations of compact star inspirals from LIGO/Virgo combined with mass and radius measurements from NICER provide a valuable tool to study the highly uncertain equation of state (EOS) of dense matter at the densities characteristic of compact stars. In this work, we constrain the solid states of strange-cluster matter, called strangeon matter, as the

Junjie Shan, Ziqi Zhao, Jialin Lu, Rui Zhang

Foundation models that bridge vision and language have made significant progress. While they have inspired many life-enriching applications, their potential for abuse in creating new threats remains largely unexplored. In this paper, we reveal that vision-language models (VLMs) can be weaponized to enhance gradient inversion attacks (GIAs) in federated learn

Lorenzo Dello Schiavo

We develop a unifying theory for four different objects: (1) infinite systems of interacting massive particles; (2) solutions to the Dean-Kawasaki equation with singular drift and space-time white noise; (3) Wasserstein diffusions with a.s. purely atomic reversible random measures; (4) metric measure Brownian motions induced by Cheeger energies on $L^2$-Wass

Shihang Shen, Serdar Elhatisari, Dean Lee, Ulf-G. Meißner

We present a systematic ab initio study of the low-lying states in beryllium isotopes from 7Be to 12Be using nuclear lattice effective field theory with the N3LO interaction. Our calculations achieve good agreement with experimental data for energies, radii, and electromagnetic properties. We introduce a novel, model-independent method to quantify nuclear sh

Heikki Mäntysaari, Pragya Singh

We quantify the effect of high-energy JIMWLK evolution on the deformed structure or heavy (Uranium) and intermediate (Ruthenium) nuclei. The soft gluon emissions in the high-energy evolution are found to drive the initially deformed nuclei towards a more spherical shape, although the evolution is slow ,especially for the longest distance-scale quadrupole def

Stefano De Marchi, Giacomo Cappellazzo

Polynomial reproduction plays a relevant role in deriving error estimates for various approximation schemes. Local reproduction in a quasi-uniform setting is a significant factor in the estimation of error and the assessment of stability but for some computationally relevant schemes, such as Rescaled Localized Radial Basis Functions (RL-RBF), it becomes a li

Bojan Kuzma, Sushil Singla

We classify real or complex finite-dimensional $C^*$-algebras and their underlying fields from the properties of Birkhoff-James orthogonality. Application to strong Birkhoff-James orthogonality preservers is also given.

G. R. Boroun

The dipole cross-section behavior for protons and nuclei is analyzed with and without considering the heavy quark masses in the Bjorken variable $x$ using the Kharzeev-Levin-Nardi (KLN) model of low $x$ gluon distributions. The Color Glass Condensate (CGC) effects in the color dipole model are influenced by the heavy quark masses in the Bjorken variable $x$

Sergio Bengoechea, Paul Over, Dieter Jaksch, Thomas Rung

This article proposes a Variational Quantum Algorithm to solve linear and nonlinear thermofluid dynamic transport equations. The hybrid classical-quantum framework is applied to problems governed by the heat, wave, and Burgers' equation in combination with different engineering boundary conditions. Topics covered include the encoding of band matrices, as in

Selina Kunkel, Stephan Wystub, Jürgen Schaffner-Bielich

The minimal masses and radii of proto-neutron stars during different stages of their evolution are investigated. In our work we focus on two stages, directly after the supernova shock wave moves outwards, where neutrinos are still captured in the core and the lepton per baryon ratio is fixed to $Y_L = 0.4$, and a few seconds afterwards, when all neutrinos ha

Antonio Barbalau

In subpopulation shift scenarios, a Curriculum Learning (CL) approach would only serve to imprint the model weights, early on, with the easily learnable spurious correlations featured. To the best of our knowledge, none of the current state-of-the-art subpopulation shift approaches employ any kind of curriculum. To overcome this, we design a CL approach aime