December 2024 arXiv papers — page 181

Tommaso Rossi, Paolo Salvatore

Let $\overline{\mathcal{M}}_{0,n+1}$ be the moduli space of genus zero stable curves with $(n+1)$-marked points. The collection $\overline{\mathcal{M}}=\{\overline{\mathcal{M}}_{0,n+1}\}_{n\geq 2}$ forms an operad in the category of complex projective varieties; its homology $Hycom= H_*(\overline{\mathcal{M}})$ is called the Hypercommutative operad. In this

Ziwen Li, Jiaxin Huang, Runnan Chen, Yunlong Che

Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown strong performance, but existing approaches often incorporate manual 3D annotations to improve dynamic object modeling, which is impractical due to high labeling costs. Some methods

Yongkyu Lee, Shivam Kumar Panda, Wei Wang, Mohammad Khalid Jawed

We present Measure Anything, a comprehensive vision-based framework for dimensional measurement of objects with circular cross-sections, leveraging the Segment Anything Model (SAM). Our approach estimates key geometric features -- including diameter, length, and volume -- for rod-like geometries with varying curvature and general objects with constant skelet

Mahalakshmi Sabanayagam, Omar Al-Dabooni, Pascal Esser

Representation learning aims to extract meaningful lower-dimensional embeddings from data, known as representations. Despite its widespread application, there is no established definition of a ``good'' representation. Typically, the representation quality is evaluated based on its performance in downstream tasks such as clustering, de-noising, etc. However,

Elena R. Loubenets, Louis Hanotel

Violation of the CHSH inequality by a bipartite quantum state is now used in many quantum applications. However, the explicit analytical expression for the maximal value of the CHSH expectation under local Alice and Bob spin-$s$ measurements is still known only for $s=1/2$. In the present article, for an arbitrary state of two spin-$s$ qudits, each of dimens

Engin Başakoğlu, Faruk Temur, Barış Yeşiloğlu, Oğuz Yılmaz

We study the scattering for the energy-subcritical stochastic nonlinear Schr\"odinger equation (SNLS) with additive noise. In particular, we examine the long-time behavior of solutions associated with the noise $\phi(x)g(t,\omega)dB(t,\omega)$ formed by a Schwartz function $\phi$, and an adapted process $g(t,\omega)$ satisfying certain decay. Essentially, th

Etan Basser, Rachel Diethorn, Robert Miranda, Mario Stinson-Maas

We prove that second and higher powers of the edge ideals of anticycles admit linear quotient orderings, although the edge ideals themselves do not, thus resolving an open question of Hoefel and Whieldon in the affirmative and providing the first class of gap-free graphs whose edge ideals satisfy this property on their powers. We also construct an explicit a

Neale Ratzlaff, Man Luo, Xin Su, Vasudev Lal

Multimodal models typically combine a powerful large language model (LLM) with a vision encoder and are then trained on multimodal data via instruction tuning. While this process adapts LLMs to multimodal settings, it remains unclear whether this adaptation compromises their original language reasoning capabilities. In this work, we explore the effects of mu

Chaitanya Gupta, Anthony J. Short

We consider introducing the Dirac sea in a quantum cellular automata model of fermions in discrete spacetime which approximates the Dirac equation in the continuum limit. However, if we attempt to fill up the `negative' energy states, we run into a problem. A new boundary is created between positive and negative energy states, at which pair creation seems en

Hridoy Sankar Dutta

This paper introduces two large-scale multilingual comment datasets, YT-30M (and YT-100K) from YouTube. The analysis in this paper is performed on a smaller sample (YT-100K) of YT-30M. Both the datasets: YT-30M (full) and YT-100K (randomly selected 100K sample from YT-30M) are publicly released for further research. YT-30M (YT-100K) contains 32236173 (108694

B. P. Aware, A. N. Bhavale

In 2020 Bhavale and Waphare introduced the concept of a nullity of a poset as nullity of its cover graph. According to Bhavale and Waphare, if a dismantlable lattice of nullity k contains r reducible elements then 2 $\leq$ r $\leq$ 2k. In 2003 Pawar and Waphare counted all non-isomorphic lattices with equal number of elements and edges, which are precisely t

Vladimir Vovk, Ilia Nouretdinov, Alex Gammerman

In this paper we study the validity and efficiency of a conformal version of the CUSUM procedure for change detection both experimentally and theoretically.

Randy Davila, Houston Schuerger, Ben Small

We prove that the \emph{standard zero forcing number} $Z(G)$ and the \emph{positive semidefinite zero forcing number} $Z_+(G)$ are equal for all claw-free graphs $G$. This result resolves a conjecture proposed by the computer program \emph{TxGraffiti} and highlights a connection between these graph invariants in claw-free structures. As a corollary, we show

J. Joe Payne, Daniel A. Hagen, Denis Garagić, Aaron M. Johnson

As bipedal robots become more and more popular in commercial and industrial settings, the ability to control them with a high degree of reliability is critical. To that end, this paper considers how to accurately estimate which feet are currently in contact with the ground so as to avoid improper control actions that could jeopardize the stability of the rob

Vishal Baibhav, Vicky Kalogera

The origin of black hole (BH) spins remains one of the least understood aspects of BHs. Despite many uncertainties, it is commonly assumed that if BHs originated from isolated massive star binaries, their spins should be aligned with the orbital angular momentum of the binary system. This assumption stems from the notion that BHs inherit their spins from the

Matteo Genoni, Hans Dekker, Stefano Covino, Roberto Cirami

In the era of Extremely Large Telescopes, the current generation of 8-10m facilities are likely to remain competitive at ground-UV wavelengths for the foreseeable future. The Cassegrain U-Band Efficient Spectrograph (CUBES) has been designed to provide high instrumental efficiency ( $>$ 37\%) observations in the near UV (305-400 nm requirement, 300-420 nm go

Aiden Ross, Mohamed S. M. M. Ali, Akash Saha, Rui Zu

Ferroelectric materials underlie key optical technologies in optical communications, integrated optics and quantum computing. Yet, there is a lack of a consistent thermodynamic framework to predict the optical properties of ferroelectrics and the mutual connections among ferroelectric polarization, optical properties, and optical dispersion. For example, the

Raffaella Fiamma Cabini, Horacio Tettamanti, Mattia Zanella

In this article we extend a recently introduced kinetic model for consensus-based segmentation of images. In particular, we will interpret the set of pixels of a 2D image as an interacting particle system which evolves in time in view of a consensus-type process obtained by interactions between pixels and external noise. Thanks to a kinetic formulation of th

Serhii Abakumov, Andriy Gusak

Formation of the intermediate phase patterns in the thin-film co-deposition process is simulated using the Stochastic Kinetic Mean-Field method and Monte Carlo. Three basic morphologies of the 2D sections are distinguished: (1) spots (rod-like in 3D), (2) layered structures-lamellae, zigzags, and labyrinths (plate-like in 3D), and (3) net-like structures (in

Azhar Hussian, Mathias Zinnen, Thi My Hang Tran, Andreas Maier

Recognizing gestures in artworks can add a valuable dimension to art understanding and help to acknowledge the role of the sense of smell in cultural heritage. We propose a method to recognize smell gestures in historical artworks. We show that combining local features with global image context improves classification performance notably on different backbon

Bingcheng Jin, Luis C. Ho, Wen Sun

We study the rest-frame ultraviolet-optical color gradients of 441 galaxies at $4<z<8$ by characterizing the wavelength dependence of their structural parameters derived from simultaneously fitting the seven-band NIRCam images acquired with the James Webb Space Telescope. Distinct from trends observed at lower redshifts, where most galaxies exhibit negative

Qian Hu, Jessica Irwin, Qi Sun, Christopher Messenger

Gravitational waves (GWs) from binary neutron stars (BNSs) offer valuable understanding of the nature of compact objects and hadronic matter, and the science potential will be greatly enhanced by the third-generation (3G) GW detectors, which are expected to detect BNS signals with order-of-magnitude improvements in duration, detection rates, and signal stren

Dario Serez, Marco Cristani, Alessio Del Bue, Vittorio Murino

Attackers can deliberately perturb classifiers' input with subtle noise, altering final predictions. Among proposed countermeasures, adversarial purification employs generative networks to preprocess input images, filtering out adversarial noise. In this study, we propose specific generators, defined Multiple Latent Variable Generative Models (MLVGMs), for a

Shir Bar, Or Hirschorn, Roi Holzman, Shai Avidan

In the study of animal behavior, researchers often record long continuous videos, accumulating into large-scale datasets. However, the behaviors of interest are often rare compared to routine behaviors. This incurs a heavy cost on manual annotation, forcing users to sift through many samples before finding their needles. We propose a pipeline to efficiently

Bin Tan, Rui Yu, Yujun Shen, Nan Xue

This paper presents PlanarSplatting, an ultra-fast and accurate surface reconstruction approach for multiview indoor images. We take the 3D planes as the main objective due to their compactness and structural expressiveness in indoor scenes, and develop an explicit optimization framework that learns to fit the expected surface of indoor scenes by splatting t

Oksana Braganets, Alexander Iksanov

We investigate a nested balls-in-boxes scheme in a random environment. The boxes follow a nested hierarchy, with infinitely many boxes in each level, and the hitting probabilities of boxes are random and obtained by iterated fragmentation of a unit mass. The hitting probabilities of the first-level boxes are given by a stick-breaking model $P_k = W_1 W_2\cdo

Marilena Barnabei, Niccolò Castronuovo, Matteo Silimbani

Hertzsprung patterns, recently introduced by Anders Claesson, are subsequences of a permutation contiguous in both positions and values, and can be seen as a subclass of bivincular patterns. This paper investigates Hertzsprung patterns within involutions, where additional structural constraints introduce new challenges. We present a general formula for enume

Dilipkumar N. Asthagiri, Arjun Valiya Parambathu, Thomas L. Beck

Earlier we showed that in the molecular dynamics simulation of a rigid model of water it is necessary to use an integration time-step $\delta t \leq 0.5$ fs to ensure equipartition between translational and rotational modes. Here we extend that study in the $NVT$ ensemble to $NpT$ conditions and to an aqueous protein. We study neat liquid water with the rigi

N. Benjamin Murphy, Daniel Hallman, Elena Cherkaev, Kenneth M. Golden

We previously demonstrated that the bulk transport coefficients of uniaxial polycrystalline materials, including electrical and thermal conductivity, diffusivity, complex permittivity, and magnetic permeability, have Stieltjes integral representations involving spectral measures of self-adjoint random operators. The integral representations follow from resol

Laura Minkova, Jessica López Espejel, Taki Eddine Toufik Djaidja, Walid Dahhane

As businesses increasingly rely on automation to streamline operations, the limitations of Robotic Process Automation (RPA) have become apparent, particularly its dependence on expert knowledge and inability to handle complex decision-making tasks. Recent advancements in Artificial Intelligence (AI), particularly Generative AI (GenAI) and Large Language Mode

Haoning Wu, Ziheng Zhao, Ya Zhang, Yanfeng Wang

Training medical image segmentation models for rare yet clinically important imaging modalities is challenging due to the scarcity of annotated data, and manual mask annotations can be costly and labor-intensive to acquire. This paper investigates leveraging generative models to synthesize data, for training segmentation models for underrepresented modalitie

Songchen Liu

In this note, we solve the complex Monge-Amp\`ere equation for measures with a pluripolar part in compact K\"ahler manifolds. This result generalizes the classical results obtained by Cegrell in bounded hyperconvex domains. We also discuss the properties of the complex Monge-Amp\`ere operator in some special cases.

Xiaojing Yan, Xiao Sun, Mingming Du, Jiashan Tang

Fidelity is crucial for characterizing transformations of quantum states under various quantum channels, which can be served as a fundamental tool in resource theories. Firstly, we define an $\alpha$-$z$-fidelity as a significant quantity in quantum information theory and give the properties of the fidelity with orders $\alpha$ and $z$. Secondly, by analyzin

Xian Wu, Chenghong Zhu, Jingbo Wang, Xin Wang

Ion traps stand at the forefront of quantum hardware technology, presenting unparalleled benefits for quantum computing, such as high-fidelity gates, extensive connectivity, and prolonged coherence times. In this context, we explore the critical role of shuttling operations within these systems, especially their influence on the fidelity loss and elongated e

Clinton Cao, Agathe Blaise, Annibale Panichella, Sicco Verwer

Many works have studied the efficacy of state machines for detecting anomalies within NetFlows. These works typically learn a model from unlabeled data and compute anomaly scores for arbitrary traces based on their likelihood of occurrence or how well they fit within the model. However, these methods do not dynamically adapt their scores based on the traces

Dung Thuy Nguyen, Ngoc N. Tran, Taylor T. Johnson, Kevin Leach

In recent years, the rise of machine learning (ML) in cybersecurity has brought new challenges, including the increasing threat of backdoor poisoning attacks on ML malware classifiers. For instance, adversaries could inject malicious samples into public malware repositories, contaminating the training data and potentially misclassifying malware by the ML mod

Merlin Carl

We consider the computational strength of Power-OTMs, i.e., ordinal Turing machines equipped with a power set operator, and study a notion of realizability based on these machines. When parameters are allowed, these machines are, modulo access to a global well-ordering, equivalent to the Set Register Machines defined by Robert Passmann in \cite{Passmann}, an

Bryce Judy

The Harmonized Tariff System (HTS) classification industry, essential to e-commerce and international trade, currently lacks standardized benchmarks for evaluating the effectiveness of classification solutions. This study establishes and tests a benchmark framework for imports to the United States, inspired by the benchmarking approaches used in language mod

Nick Stracke, Stefan Andreas Baumann, Kolja Bauer, Frank Fundel

Internal features from large-scale pre-trained diffusion models have recently been established as powerful semantic descriptors for a wide range of downstream tasks. Works that use these features generally need to add noise to images before passing them through the model to obtain the semantic features, as the models do not offer the most useful features whe

Navdha, Philipp Busch, Simon D. M. White

We use the Millennium Simulation to study the relation of galaxies and dark matter haloes to the cosmic web. We define the web as the unique, fully connected, percolating object with (unsmoothed) matter density everywhere exceeding 5.25 times the cosmic mean. This object contains 35\% of all cosmic mass but occupies only 0.62\% of all cosmic volume. It conta

Alessandro V. Cigna

The Thurston norm of a closed oriented graph manifold is a sum of absolute values of linear functionals, and either each or none of the top-dimensional faces of its unit ball are fibered. We show that, conversely, every norm that can be written as a sum of absolute values of linear functionals with rational coefficients is the nonvanishing Thurston norm of s

E. Karimi, S. Shahnooshi, E. Meshkati, T. Dragičević

Current ripple minimization is one of the challenges in parallel converters to increase the capacitor lifetime in various applications. In this paper, a deep neural network-based phase-shifting (PS) technique is proposed for parallel-connected buck converters to minimize the amplitude of a selective harmonic component and facilitate a classic optimum PS at t

Cheng Shu

For any complex reductive group $G$ and any compact Riemann surface with genus $g>0$, we show that every connected component of the associated character variety is $\mathbb{Q}$-factorial and has symplectic singularities, and classify the connected components that admit symplectic resolutions. When $g>1$, we use elliptic endoscopic groups to control the singu

Ameya Chavda, Macarena Lagos, Lam Hui

This study investigates the influence of initial conditions on the evolution and properties of linear quasi-normal modes (QNMs). Using a toy model in which the quasi-normal mode can be unambiguously identified, we highlight an aspect of QNMs that is long known yet often ignored: the amplitude of a QNM (after factoring out the corresponding exponential with a

Miguel Arturo Vega Torres, Anna Ribic, Borja García de Soto, André Borrmann

This paper introduces BIMCaP, a novel method to integrate mobile 3D sparse LiDAR data and camera measurements with pre-existing building information models (BIMs), enhancing fast and accurate indoor mapping with affordable sensors. BIMCaP refines sensor poses by leveraging a 3D BIM and employing a bundle adjustment technique to align real-world measurements

Alejandro Puente-Castro, Enrique Fernandez-Blanco, Daniel Rivero

Path Planning methods for autonomously controlling swarms of unmanned aerial vehicles (UAVs) are gaining momentum due to their operational advantages. An increasing number of scenarios now require autonomous control of multiple UAVs, as autonomous operation can significantly reduce labor costs. Additionally, obtaining optimal flight paths can lower energy co

Gaurav Goswami

Numerous observations on astrophysical and cosmological scales can be interpreted to mean that, in addition to the familiar kind of matter well described by the standard model of elementary particle physics, there exists Dark Matter (DM). The fundamental properties of the elementary particles which make up the DM e.g. particle mass, spin, couplings etc are c

Zheng Zhang, Jens Chluba

This paper presents 'SpyDust', an improved and extended implementation of the spinning dust emission model based on a Fokker-Planck treatment. 'SpyDust' serves not only as a Python successor to 'spdust', but also incorporates some corrections and extensions. Unlike 'spdust', which is focused on specific grain shapes, 'SpyDust' considers a wider range of grai

Yan Li, Ziya Zhou, Zhiqiang Wang, Wei Xue

Recent advancements in generative models have significantly enhanced talking face video generation, yet singing video generation remains underexplored. The differences between human talking and singing limit the performance of existing talking face video generation models when applied to singing. The fundamental differences between talking and singing-specif

Daniele Girolimetto, Tommaso Di Fonzo

Linearly constrained multiple time series may be encountered in many practical contexts, such as the National Accounts (e.g., GDP disaggregated by Income, Expenditure and Output), and multilevel frameworks where the variables are organized according to hierarchies or groupings, like the total energy consumption of a country disaggregated by region and energy

Wanting Zhang, Haodong Xiang, Zhichao Liao, Xiansong Lai

The reconstruction of indoor scenes remains challenging due to the inherent complexity of spatial structures and the prevalence of textureless regions. Recent advancements in 3D Gaussian Splatting have improved novel view synthesis with accelerated processing but have yet to deliver comparable performance in surface reconstruction. In this paper, we introduc

Matthias Christenson, Cove Geary, Brian Locke, Pranav Koirala

The success of precision medicine requires computational models that can effectively process and interpret diverse physiological signals across heterogeneous patient populations. While foundation models have demonstrated remarkable transfer capabilities across various domains, their effectiveness in handling individual-specific physiological signals - crucia

Jörn Krenzer, Felix Reichenbach, Jochen Schein

The ion-optic grid-system is the essential part of electrostatic ion thrusters governing performance and lifetime. Therefore reliable measurements of the grid and aperture geometry over the lifetime are necessary to understand and predict the behavior of the system. Many different methods of measurement were introduced over the years to tackle the challenges

Yaniv Almog

We study the pair interaction on flat tori of functions whose Fourier coefficients are positive and decay sufficiently rapidly. In dimension one we find that the minimizer, up to translation, is the equidistant point set. In dimension two, minimizing with respect to triplets we find that the minimizer is the triangular lattice.

Daniel Armstrong, Zlatko Joncev, Jeff Guo, Philippe Schwaller

Computer-aided synthesis planning (CASP) has made significant strides in generating retrosynthetic pathways for simple molecules in a non-constrained fashion. Recent work introduces a specialised bidirectional search algorithm with forward and retro expansion to address the starting material-constrained synthesis problem, allowing CASP systems to provide syn

Rémi Abgrall, Miaosen Jiao, Yongle Liu, Kailiang Wu

The PAMPA (Point-Average-Moment PolynomiAl-interpreted) method, proposed in [R. Abgrall, Commun. Appl. Math. Comput., 5: 370-402, 2023], combines conservative and non-conservative formulations of hyperbolic conservation laws to evolve cell averages and point values. Solutions to hyperbolic conservation laws typically have an invariant domain, and ensuring nu

Agostino Di Francescantonio, Alessandra Sabatti, Helena Weigand, Elise Bailly

Electro-optical modulation is widely employed for optical signal processing and in laser technology. To date, it is efficiently realized in integrated photonic systems as well as in bulk optics devices. Yet, the achievement of modulators exploiting Pockels effect in flat optics, essential to scale down the electric radiation-optical control in free space, cu

Laurent Hébert-Dufresne, Nicholas W. Landry, Juniper Lovato, Jonathan St-Onge

Democratic governments comprise a subset of a population whose goal is to produce coherent decisions, solving societal challenges while respecting the will of the people. New governance frameworks represent this as a social network rather than as a hierarchical pyramid with centralized authority. But how should this network be structured? We model the decisi

Clinton Cao, Annibale Panichella, Sicco Verwer

The rising popularity of the microservice architectural style has led to a growing demand for automated testing approaches tailored to these systems. EvoMaster is a state-of-the-art tool that uses Evolutionary Algorithms (EAs) to automatically generate test cases for microservices' REST APIs. One limitation of these EAs is the use of unit-level search heuris

Vishal Jadoliya, Jeewan C Pandey, Anandmayee Tej

This paper presents an investigation of the X-ray emission associated with the Wolf-Rayet star, WR 48-6, using observations from the XMM Newton and Chandra X-ray telescopes covering two epochs separated by eleven months. The X-ray spectrum of WR 48-6 is well explained by a two-temperature plasma model, with cool and hot plasma temperatures of $0.8_{-0.2}^{\,

F. Aryasetiawan, K. Karlsson

The quasiparticle wavefunction of a many-electron system is traditionally defined as the eigenfunction of the quasiparticle eigenvalue equation involving the self-energy. In this article a new concept of a quasiparticle wavefunction is derived from the general definition of the Green function without reference to self-energy. The proposed quasiparticle wavef

JiaLe Ren

With the rapid development of the Internet and social media, multi-modal data (text and image) is increasingly important in sentiment analysis tasks. However, the existing methods are difficult to effectively fuse text and image features, which limits the accuracy of analysis. To solve this problem, a multimodal sentiment analysis framework combining BERT an

Erkan Karabulut, Paul Groth, Victoria Degeler

Association Rule Mining (ARM) is the task of discovering commonalities in data in the form of logical implications. ARM is used in the Internet of Things (IoT) for different tasks including monitoring and decision-making. However, existing methods give limited consideration to IoT-specific requirements such as heterogeneity and volume. Furthermore, they do n

Shubham Kanodia

This paper presents a comparative analysis of the bulk properties (mass and radius) of transiting giant planets ($\gtrsim$ 8$R_{\oplus}$) orbiting FGKM stars. Our findings suggest that the average mass of M-dwarf Jupiters is lower than that of their solar-type counterparts, primarily due to the scarcity of super-Jupiters ( $\gtrsim$ 2 $M_J$) around M-dwarfs.

Shankar Bhamidi, Rick Durrett, Xiangying Huang

In 1999, Zhang proved that, for first passage percolation on the square lattice $\mathbb{Z}^2$ with i.i.d. non-negative edge weights, if the probability that the passage time distribution of an edge $P(t_e = 0) =1/2 $, the critical value for bond percolation on $\mathbb{Z}^2$, then the passage time from the origin $0$ to the boundary of $[-n,n]^2$ may conver

Wenyi Wang, Hisham A. Alyahya, Dylan R. Ashley, Oleg Serikov

Language-based agentic systems have shown great promise in recent years, transitioning from solving small-scale research problems to being deployed in challenging real-world tasks. However, optimizing these systems often requires substantial manual labor. Recent studies have demonstrated that these systems can be represented as computational graphs, enabling

Jan Nino G. Tinio, Mokhtar Z. Alaya, Salim Bouzebda

Locally stationary (LSPs) constitute an essential modeling paradigm for capturing the nuanced dynamics inherent in time series data whose statistical characteristics, including mean and variance, evolve smoothly across time. In this paper, we introduce a novel conditional probability distribution estimator specifically tailored for LSPs, employing the Nadara

Andrea Asperti, Ali Aydogdu, Angelo Greco, Fabio Merizzi

Sea Surface Temperature (SST) reconstructions from satellite images affected by cloud gaps have been extensively documented in the past three decades. Here we describe several Machine Learning models to fill the cloud-occluded areas starting from MODIS Aqua nighttime L3 images. To tackle this challenge, we employed a type of Convolutional Neural Network mode

Joachim Galiana, Michèle Desouter-Lecomte, Benjamin Lasorne

Excitation-energy transfer (EET) and relaxation in an optically excited building block of poly(phenylene ethynylene) (PPE) dendrimers are simulated using wavepackets with the multilayer multiconfiguration time-dependent Hartree (ML-MCTDH) method and reduced-density matrices with the hierachical equations of motion (HEOM) approach. The dynamics of the ultrafa

Rafael Luque, Brandon Park Coy, Qiao Xue, Adina D. Feinstein

We report JWST NIRSpec/G395H observations of TOI-1685 b, a hot rocky super-Earth orbiting an M2.5V star, during a full orbit. We obtain transmission and emission spectra of the planet and characterize the properties of the phase curve, including its amplitude and offset. The transmission spectrum rules out clear H$_2$-dominated atmospheres, while secondary a

Cruz I. Velasco, F. Javier García de Abajo

The coherent interaction between free electrons and optical fields can produce free-electron compression and push the temporal resolution of ultrafast electron microscopy to the attosecond regime. However, a large electron-light interaction is required to attain a strong compression, generally necessitating short light and electron pulses combined with optic

Ao Wang, Hui Chen, Jiaxin Li, Jianchao Tan

Recently, large vision-language models (LVLMs) have rapidly gained popularity for their strong generation and reasoning capabilities given diverse multimodal inputs. However, these models incur significant computational and memory overhead during inference, which greatly hinders the efficient deployment in practical scenarios. The extensive key-value (KV) ca

Martin Olsson, Rachel Webb

We introduce a new notion of generalized log twisted curves, which are marked nodal curves with additional data at the marked points. In the case when the markings are distinct this notion agrees with the notion of twisted curve introduced by Abramovich and Vistoli. In addition to developing the basic notions and results, we study in this article the moduli

Aron Fóthi, Bence Fazekas, Natabara Máté Gyöngyössy, Kristian Fenech

In this paper, we present an approach for monocular open-set novel view synthesis (NVS) that leverages object skeletons to guide the underlying diffusion model. Building upon a baseline that utilizes a pre-trained 2D image generator, our method takes advantage of the Objaverse dataset, which includes animated objects with bone structures. By introducing a sk

Shuo Xu, Song Huang, Alexie Leauthaud, Benedikt Diemer

Recent observations suggest that the extended stellar halos of low-redshift massive galaxies are tightly connected to the assembly of their dark matter halos. In this paper, we use the Illustris, IllustrisTNG100, and IllustrisTNG300 simulations to compare how different stellar aperture masses trace halo mass. For massive central galaxies ($M_\star\geq 10^{11

Peihong Yuan, Ken R. Duffy, Muriel Médard

We introduce an algorithm for approximating the codebook probability that is compatible with all successive cancellation (SC)-based decoding algorithms, including SC list (SCL) decoding. This approximation is based on an auxiliary distribution that mimics the dynamics of decoding algorithms with an SC decoding schedule. Based on this codebook probability and

K. E. Castoria, N. R. Beysengulov, G. Koolstra, H. Byeon

Electrons trapped on the surface of cryogenic substrates (liquid helium, solid neon or hydrogen) are an emerging platform for quantum information processing made attractive by the inherent purity of the electron environment, the scalability of trapping devices and the predicted long lifetime of electron spin states. Here we demonstrate the spatial control an

L. Ruks, K. E. Ballantine, J. Ruostekoski

The quest to manipulate light propagation in ways not possible with natural media has driven the development of artificially structured metamaterials. One of the most striking effects is negative refraction, where the light beam deflects away from the boundary normal. However, due to material characteristics, the applications of this phenomenon, such as lens

N. G. Stefanis

The data behavior of the pion-photon transition form factor (TFF) is discussed using a nonlinear mathematical model with two parameters $B$ and $C$. Analysis shows that the model's inherent inhibition provides a precondition for the asymptotic saturation of the TFF in agreement with perturbative QCD. Integral to this derivation is the use of a novel fundamen

Robert Sansom, Juan A. Valiente Kroon

We provide a characterisation of the Kerr spacetime close to future null infinity using the asymptotic characteristic initial value problem in a conformally compactified spacetime. Stewart's gauge is used to set up the past-oriented characteristic initial value problem. By a theorem of M. Mars characterising the Kerr spacetime, we provide conditions for the

Ronald L. P. D. de Jong, Yasmina al Khalil, Tim J. M. Jaspers, Romy C. van Jaarsveld

Esophageal cancer is among the most common types of cancer worldwide. It is traditionally treated using open esophagectomy, but in recent years, robot-assisted minimally invasive esophagectomy (RAMIE) has emerged as a promising alternative. However, robot-assisted surgery can be challenging for novice surgeons, as they often suffer from a loss of spatial ori

Feng He, Chao Zhang, Zhixue Zhao

Implicit assumptions and priors are often necessary in text-to-image generation tasks, especially when textual prompts lack sufficient context. However, these assumptions can sometimes reflect outdated concepts, inaccuracies, or societal bias embedded in the training data. We present Embedding-only Editing (Embedit), a method designed to efficiently adjust i

Yongxin Zeng, Andrew J. Millis

Systems such as Wigner crystals and incommensurate charge density waves that spontaneously break a continuous translation symmetry have unusual transport properties arising from their ability to slide coherently in space. Recent experimental and theoretical studies suggest that spontaneous translation symmetry breaking in some two-dimensional materials with

Yaoyao Chang, Lei Cui, Li Dong, Shaohan Huang

Pre-training Large Language Models (LLMs) on high-quality, meticulously curated datasets is widely recognized as critical for enhancing their performance and generalization capabilities. This study explores the untapped potential of Common Crawl as a comprehensive and flexible resource for pre-training LLMs, addressing both general-purpose language understan

Guilherme G. D. Fernandes, Vitor S. P. P. Oliveira, João P. I. Astolfo

The mapping of ocean floor layers is a current challenge for the oil industry. Existing solution methods involve mapping through seismic methods and wave inversion, which are complex and computationally expensive. The introduction of artificial neural networks, specifically UNet, to predict velocity models based on seismic shots reflected from the ocean floo

Karthekeyan Chandrasekaran, Yuri Faenza, Chengyue He, Jay Sethuraman

Scarf's algorithm--a pivoting procedure that finds a dominating extreme point in a down-monotone polytope--can be used to show the existence of a fractional stable matching in hypergraphs. The problem of finding a fractional stable matching in a hypergraph, however, is PPAD-complete. In this work, we study the behavior of Scarf's algorithm on arborescence hy

Liam Urban

In this paper, we study the past asymptotics of $(2+1)$-dimensional solutions to the Einstein scalar-field Vlasov system which are close to Friedman-Lema\^itre-Robertson-Walker spacetimes on an initial hypersurface diffeomorphic to a closed orientable surface $M$ of arbitrary genus. We prove that such solutions are past causally geodesically incomplete, form

Feiran You, Hongyang Du, Kaibin Huang, Abbas Jamalipour

Large Language Models (LLMs) are increasingly integrated into mobile services over wireless networks to support complex user requests. This trend has led to longer prompts, which improve LLMs' performance but increase data transmission costs and require more processing time, thereby reducing overall system efficiency and negatively impacting user experience.

Andreas Darmann, Janosch Döcker, Britta Dorn

We show that Not-All-Equal 3-Sat remains NP-complete when restricted to instances that simultaneously satisfy the following properties: (i) The clauses are given as the disjoint union of k partitions, for any fixed $k \geq 4$, of the variable set into subsets of size 3, and (ii) each pair of distinct clauses shares at most one variable. Property (i) implies

Takashi Furuya, Michael Puthawala, Maarten V. de Hoop, Matti Lassas

We consider the problem of discretization of neural operators between Hilbert spaces in a general framework including skip connections. We focus on bijective neural operators through the lens of diffeomorphisms in infinite dimensions. Framed using category theory, we give a no-go theorem that shows that diffeomorphisms between Hilbert spaces or Hilbert manif

Marius Zimand

We show that one-way functions exist if and only if there exists an efficient distribution relative to which almost-optimal compression is hard on average. The result is obtained by combining a theorem of Ilango, Ren, and Santhanam and one by Bauwens and Zimand.

Murat Sensoy, Lance M. Kaplan, Simon Julier, Maryam Saleki

Autonomous and semi-autonomous systems are using deep learning models to improve decision-making. However, deep classifiers can be overly confident in their incorrect predictions, a major issue especially in safety-critical domains. The present study introduces three foundational desiderata for developing real-world risk-aware classification systems. Expandi

Ge Zheng, Alexandra Brintrup

A key stumbling block in effective supply chain risk management for companies and policymakers is a lack of visibility on interdependent supply network relationships. Relationship prediction, also called link prediction is an emergent area of supply chain surveillance research that aims to increase the visibility of supply chains using data-driven techniques

Giulia Ricciardi, Natascia Vignaroli, Francesco Vissani

We discuss the accuracy of the evaluation of the cross section for inverse beta decay at low energies and its relevance in the current experimental framework.

Jiaxuan Liu, Zhaoci Liu, Yajun Hu, Yingying Gao

Human speech exhibits rich and flexible prosodic variations. To address the one-to-many mapping problem from text to prosody in a reasonable and flexible manner, we propose DiffStyleTTS, a multi-speaker acoustic model based on a conditional diffusion module and an improved classifier-free guidance, which hierarchically models speech prosodic features, and co

Xin Ye, Karl Handwerker, Sören Hohmann

The physical coupling between robots has the potential to improve the capabilities of multi-robot systems in challenging manufacturing processes. However, the path tracking accuracy of physically coupled robots is not studied adequately, especially considering the uncertain kinematic parameters, the mechanical elasticity, and the built-in controllers of off-

J. L. Sánchez Toural, J. García-Pérez, R. Bernardo-Gavito, D. Granados

The interplay between ion beam modification techniques in the MeV range and the controlled generation of negatively charged nitrogen-vacancy (NV-) centers in nitrogen-doped synthetic diamond crystals is explored. An experimental approach employing both light (H+) and heavy (Br+6) ions was followed to assess their respective impacts on the creation of NV- cen

Ivan Čilić, Anna Lackinger, Pantelis Frangoudis, Ivana Podnar Žarko

Deploying a Hierarchical Federated Learning (HFL) pipeline across the computing continuum (CC) requires careful organization of participants into a hierarchical structure with intermediate aggregation nodes between FL clients and the global FL server. This is challenging to achieve due to (i) cost constraints, (ii) varying data distributions, and (iii) the v

Raffaello Foldes, Raffaele Marino, Silvio Sergio Cerri, Enrico Camporeale

Recent studies based on simulations of the Boussinesq equations indicate that stratified turbulent flows can develop large-scale intermittency in the velocity and temperature fields, as detected in the atmosphere and oceans. In particular, emerging powerful vertical drafts were found to generate local turbulence, proving necessary for stratified flows to dis

Changhao Yi, Kai Zhou, Zhibo Hou, Guo-Yong Xiang

Collective measurements on identical and independent quantum systems can offer advantages in information extraction compared with individual measurements. However, little is known about the distinction between restricted collective measurements and genuine collective measurements in the multipartite setting. In this work we establish a rigorous performance g