November 2024 arXiv papers — page 44

Christopher Swenson, Ryan Revolinsky, Adam Brusstar, Emma Guerin

This research examines the stability of crossed-field amplifiers (CFAs) and characterizes their different modes of operation: amplification, driven oscillation, and self-excited oscillation. The CFA used in this paper is the Recirculating Planar Crossed-Field Amplifier (RPCFA), which is a high power (MW) pulsed (300 ns) amplifier that operates around 3 GHz.

Seongjoo Jung, Turan Birol

Antiferroelectrics, which host both polar and antipolar order parameters, are characterized by the double hysteresis loops which are advantageous for various applications such as high-density energy storage. In this study, we investigate the coupling between oxygen octahedral rotations and polarization in well-known perovskites, with a focus on SrTiO$_3$. Us

Peihua Deng, Jiehua Zhang, Xichun Sheng, Chenggang Yan

This paper explores the Class-Incremental Source-Free Unsupervised Domain Adaptation (CI-SFUDA) problem, where the unlabeled target data come incrementally without access to labeled source instances. This problem poses two challenges, the interference of similar source-class knowledge in target-class representation learning and the shocks of new target knowl

Yadi Cao, Yuxuan Liu, Liu Yang, Rose Yu

In-Context Operator Networks (ICONs) have demonstrated the ability to learn operators across diverse partial differential equations using few-shot, in-context learning. However, existing ICONs process each spatial point as an individual token, severely limiting computational efficiency when handling dense data in higher spatial dimensions. We propose Vision

Shester Gueuwou, Xiaodan Du, Greg Shakhnarovich, Karen Livescu

Sign language processing has traditionally relied on task-specific models, limiting the potential for transfer learning across tasks. Pre-training methods for sign language have typically focused on either supervised pre-training, which cannot take advantage of unlabeled data, or context-independent (frame or video segment) representations, which ignore the

Steven Finch

The problems and solutions contained here, all associated with nonlinear recurrences and long-term trends, are new (as far as is known).

Man Yao, Xuerui Qiu, Tianxiang Hu, Jiakui Hu

The ambition of brain-inspired Spiking Neural Networks (SNNs) is to become a low-power alternative to traditional Artificial Neural Networks (ANNs). This work addresses two major challenges in realizing this vision: the performance gap between SNNs and ANNs, and the high training costs of SNNs. We identify intrinsic flaws in spiking neurons caused by binary

M. H. Fauzi, M. Takahashi, T. Aono, K. Hashimoto

We study electron spin dynamics whose movement is restricted to the lowest one dimensional subband channel ($G \le 2e^2/h $), through nuclear spin relaxation rate measurement ($1/T_1$). We observe an unusual double-peak structure in the $1/T_1$ profile below the lowest subband level, where the up and down spin edge channel is still largely overlap. This prof

Maolin Dai, Bowen Liu, Yifan Ma, Ruoao Yang

High repetition rate ultrafast fiber lasers are important tools for both fundamental science and industry applications. However, achieving over GHz repetition rate in passively mode-locked fiber ring lasers is still challenging. Here, we demonstrate the first ring-cavity Er-doped fiber laser that achieves over GHz fundamental repetition rate by using an all-

Tinggui Chen, Matthieu Mallejac, Chuanxing Bi, Baizhan Xia

Achieving strongly nonreciprocal scattering in compact linear acoustic devices is a challenging task. One possible solution is the use of time-modulated resonators, however, their implementation in the realm of audible airborne acoustics is typically hindered by the difficulty to obtain large modulation depth and speeds while managing noise issues. Here, we

Genshiro Kitagawa

This paper explores a Bayesian self-organization method for state-space models, enabling simultaneous state and parameter estimation without repeated likelihood calculations. While efficient for low-dimensional models, high-dimensional cases like seasonal adjustment require many particles. Using Rao-Blackwellization and a 2-step approximation, the method red

Yanshu Song, Abdullah Nazir, Darwin Lau, Yun Hui Liu

This paper presents a robotic in-hand manipulation technique that can be applied to pick an object too large to grasp in a prehensile manner, by taking advantage of its contact interactions with a curved, passive end-effector, and two flat support surfaces. First, the object is tilted up while being held between the end-effector and the supports. Then, the e

Sungmun Cho, Taeyeoup Kang, Yuchan Lee

A main goal of this paper is to introduce a new description of the stable orbital integral for a regular semisimple element and for the unit element of the Hecke algebra in the case of $\mathfrak{gl}_{n,F}$, $\mathfrak{u}_{n,F}$, and $\mathfrak{sp}_{2n,F}$, by assigning a certain stratification and then smoothening each stratum, where $F$ is a non-Archimedea

Guangzhao Dai, Jian Zhao, Yuantao Chen, Yusen Qin

Vision-and-Language Navigation (VLN), where an agent follows instructions to reach a target destination, has recently seen significant advancements. In contrast to navigation in discrete environments with predefined trajectories, VLN in Continuous Environments (VLN-CE) presents greater challenges, as the agent is free to navigate any unobstructed location an

Koji Hashimoto, Koshiro Matsuo, Masaki Murata, Gakuto Ogiwara

We introduce a novel interpretable Neural Network (NN) model designed to perform precision bulk reconstruction under the AdS/CFT correspondence. According to the correspondence, a specific condensed matter system on a ring is holographically equivalent to a gravitational system on a bulk disk, through which tabletop quantum gravity experiments may be possibl

Yu Feng, Hao Wu

Radial BPZ equations come naturally when one solves Dub\'{e}dat's commutation relation in the radial setting. We construct positive solutions to radial BPZ equations and show that partition functions of FK-Ising interfaces in a polygon conditional on a one-arm event are positive solutions to radial BPZ equations.

Valeri P. Frolov, Alex Koek, Jose Pinedo Soto, Andrei Zelnikov

Recently it was demonstrated that by adding to the Einstein-Hilbert action a series in powers of the curvature invariants with specially chosen coefficients one can obtain a theory of gravity which has spherically symmetric solutions describing regular black holes. Its reduced action depends on a function of one of the basic curvature invariants of the corre

Hossein Kashiani, Niloufar Alipour Talemi, Fatemeh Afghah

Recent advancements in anomaly detection have shifted focus towards Multi-class Unified Anomaly Detection (MUAD), offering more scalable and practical alternatives compared to traditional one-class-one-model approaches. However, existing MUAD methods often suffer from inter-class interference and are highly susceptible to domain shifts, leading to substantia

Wei Wang, Zhifei Zhang

In this paper, we study the stationary solutions of semilinear elliptic equation with singular nonlinearity $$ \Delta u=u^{-p}+f,\,\,u\geq 0\text{ in }\Omega\subset\mathbb{R}^n, $$ where $ n\geq 2 $, $ p>1 $, $ \Omega $ is a bounded domain, and $ f\in L^q(\Omega) $ with $ \frac{1}{2}+\frac{1}{2p}<\frac{q}{n} $. We establish a sharp estimate for the Minkowski

Yuecong Liu, Mengjun Ou, Yi Wang, Hai-Hu Wen

Through Sr and Ca doping to the La sites, we successfully obtained the hole doped La$_{3-x}$A$_x$Ni$_2$O$_7$ (A = Sr and Ca) thin films by using the pulsed-laser deposition technique. Temperature dependent resistivity shows an upturn at low temperatures, but some clear instabilities, either due to structure or the releasing of strain between the film and sub

Rajib Rana, Niall Higgins, Kazi Nazmul Haque, John Reilly

Ensuring accurate call prioritisation is essential for optimising the efficiency and responsiveness of mental health helplines. Currently, call operators rely entirely on the caller's statements to determine the priority of the calls. It has been shown that entirely subjective assessment can lead to errors. Furthermore, it is a missed opportunity not to util

Qing Gao, Zhiqian Peng, Shengqing Gao, Yungui Gong

To elucidate the robustness of the baryon acoustic oscillation (BAO) data measured by the Dark Energy Spectroscopic Instrument (DESI) in capturing the dynamical behavior of dark energy, we assess the model dependence of the evidence for dynamical dark energy inferred from the DESI BAO data. While the DESI BAO data slightly tightens the constraints on model p

Yubin He

In this paper, we investigate the Hausdorff measure of shrinking target sets in $\beta$-dynamical systems. These sets are dynamically defined in analogy to the classical theory of weighted and multiplicative approximation. While the Lebesgue measure and Hausdorff dimension theories for these sets are well-understood, the Hausdorff measure theory in even one-

Haozhan Shen, Kangjia Zhao, Tiancheng Zhao, Ruochen Xu

Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in vision-language understanding. Recently, with the integration of test-time scaling techniques, these models have also shown strong potential in visual reasoning. However, most existing reasoning approaches remain text-level in nature: MLLMs are prompted to explore various c

Rajesh Shrestha, Mingjie Shao, Mingyi Hong, Wing-Kin Ma

In frequency division duplex (FDD) massive MIMO systems, a major challenge lies in acquiring the downlink channel state information}\ (CSI) at the base station (BS) from limited feedback sent by the user equipment (UE). To tackle this fundamental task, our contribution is twofold: First, a simple feedback framework is proposed, where a compression and Gaussi

Liu Tailiang, Shen Yuliang

In this paper, we introduce a class of vanishing Carleson measures with conformal invariance and corresponding strongly vanishing symmetric homeomorphisms on the real line and prove that they can be mutually generated under quasiconformal mappings. This is motivated by constructing a nice VMO-Teichmuller space on the real line, which completely removes the o

Nanjun Yang

Witt group of real algebraic curves has been studied since Knebusch in 1970s. But few results are known if the base field is non-Archimedean except the hyperelliptic case by works of Parimala, Arason et al.. In this paper, we compute the derived Witt groups of smooth proper curves over nondyadic local fields with $char\neq2$ by reduction, with a general stud

Jun Jiang

In this paper, we construct a categorical solution $(\huaC, R)$ of the Yang-Baxter equation, i.e. $\huaC$ is a small category and $R: \huaC\times\huaC\lon\huaC\times\huaC$ is an invertible functor satisfying $$ (R\times\Id_\huaC)(\Id_\huaC\times R)(R\times\Id_\huaC)=(\Id_\huaC\times R)(R\times\Id_\huaC)(\Id_\huaC\times R), $$ where $\huaC\times\huaC$ is the

Yan Shi, Denghui Zhao, Jingyi Yu, Wei Ni

Intraoperative visualization of hemodynamics is crucial for accurate diagnosis and informed surgical decision-making. In neurosurgery, indocyanine green fluorescence imaging (ICG-FI) is the gold standard for assessing blood flow and identifying vascular structures. However, it is limited by time-consuming data acquisition, mandatory waiting periods, potentia

Yanlu Lian, Qun Mo, Yu Xia

The Tammes problem delves into the optimal arrangement of $N$ points on the surface of the $n$-dimensional unit sphere (denoted as $\mathbb{S}^{n-1}$), aiming to maximize the minimum distance between any two points. In this paper, we articulate the sufficient conditions requisite for attaining the optimal value of the Tammes problem for arbitrary $n, N \in \

I. R. Rahmonov, Yu. M. Shukrinov, O. A. Kibardina, S. A. Abdelmoneim

The possibility of magnetization resonant control in a Josephson superconductor-ferromagnet-superconductor $\varphi_{0}$ junction shunted by an $LC$ circuit is demonstrated. As a result of the resonance of Josephson oscillations with oscillations in the circuit, a time-independent superconducting current arises in the junction. Due to the coupling of the Jos

Motohiko Ezawa

A prominent feature of $d$-wave altermagnets is the pure spin current generated in the absence of spin-orbit interactions. In the context of symmetry, there are the $s$-wave, the $p$-wave, the $d$-wave, the $f$-wave, the $g$-wave and the $i$-wave magnets. In this paper, making an analytic study of two-band Hamiltonian systems coupled with electrons, we demon

Charlie Snell, Eric Wallace, Dan Klein, Sergey Levine

A fundamental open challenge in modern LLM scaling is the lack of understanding around emergent capabilities. In particular, language model pretraining loss is known to be highly predictable as a function of compute. However, downstream capabilities are far less predictable -- sometimes even exhibiting emergent jumps -- which makes it challenging to anticipa

Wang Bill Zhu, Deqing Fu, Kai Sun, Yi Lu

Existing recommendation systems either rely on user interaction logs, such as online shopping history for shopping recommendations, or focus on text signals. However, item-based histories are not always accessible, and are not generalizable for multimodal recommendation. We hypothesize that a user's visual history -- comprising images from daily life -- can

Rak-Kyeong Seong

We introduce a generative AI model to obtain Type IIB brane configurations that realize toric phases of a family of 4d N=1 supersymmetric gauge theories. These 4d N=1 quiver gauge theories are worldvolume theories of a D3-brane probing a toric Calabi-Yau 3-fold. The Type IIB brane configurations are given by the coamoeba projection of the mirror curve associ

Adam Rycerz

Peculiar electronic properties of graphene, including the universal dc conductivity and the pseudodiffusive shot noise, are usually attributed to a small vicinity of the charge-neutrality point, away from which electron's effective mass raises, and nanostructures in graphene start to behave similarly to familiar Sharvin contacts in semiconducting heterostruc

Antonino Ferraro, Antonio Galli, Valerio La Gatta, Marco Postiglione

Agent-Based Modelling (ABM) has emerged as an essential tool for simulating social networks, encompassing diverse phenomena such as information dissemination, influence dynamics, and community formation. However, manually configuring varied agent interactions and information flow dynamics poses challenges, often resulting in oversimplified models that lack r

Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley

Algorithms with (machine-learned) predictions is a powerful framework for combining traditional worst-case algorithms with modern machine learning. However, the vast majority of work in this space assumes that the prediction itself is non-probabilistic, even if it is generated by some stochastic process (such as a machine learning system). This is a poor fit

Qiuye Jia, Junyong Zhang

We study the pointwise decay estimates for the Schrödinger and wave equations on a product cone $(X,g)$, where the metric $g=dr^2+r^2 h$ and $X=C(Y)=(0,\infty)\times Y$ is a product cone over the closed Riemannian manifold $(Y,h)$ with metric $h$. Under the assumption that the {conjugate radius} $\conR$ of $Y$ satisfies $\conR>π$, we prove the pointwise disp

Patrick Bennett

A $q$-ary code $C$ of length $n$ is a set of $n$-dimensional vectors (code words) with entries in $\{0, \ldots, q-1\}$. We say $C$ has constant weight $w$ if each code word has exactly $w$ nonzero entries. We say $C$ has minimum distance $d$ if any two distinct code words in $C$ differ in at least $d$ entries. We let $A_q(n, d, w)$ be the largest possible ca

Yan Miao, Georgios Fainekos, Bardh Hoxha, Hideki Okamoto

Testing Automated Driving Systems (ADS) in simulation with realistic driving scenarios is important for verifying their performance. However, converting real-world driving videos into simulation scenarios is a significant challenge due to the complexity of interpreting high-dimensional video data and the time-consuming nature of precise manual scenario recon

Tomo Munehisa

Spontaneous symmetry breaking is well known to be a macroscopic phenomenon in quantum physics in many body systems. The essential features of this phenomenon are the energy degeneracy and the existence of the local operator that can modify the degenerate states. Due to these properties the lowest energy state is not stable. In order to obtain the stable grou

Chen Zhuang, Lingqi Zhang, Du Wu, Peng Chen

Graph Convolutional Networks (GCNs), particularly for large-scale graphs, are crucial across numerous domains. However, training distributed full-batch GCNs on large-scale graphs suffers from inefficient memory access patterns and high communication overhead. To address these challenges, we introduce \method{}, an efficient and scalable distributed GCN train

Ke Sun, Iñaki Esnaola, H. Vincent Poor

Data injection attacks (DIAs) pose a significant cybersecurity threat to the Smart Grid by enabling an attacker to compromise the integrity of data acquisition and manipulate estimated states without triggering bad data detection procedures. To mitigate this vulnerability, the moving target defense (MTD) alters branch admittances to mismatch the system infor

Yu-Fu Shen, Yan Xu

Advanced radio telescopes such as the Five-hundred-meter Aperture Spherical radio Telescope (FAST) can provide high-sensitivity and high-time-resolution data of a large number of radio sources, offering an excellent opportunity for studying radio pulse profiles. However, studying pulse profiles requires the analysis of dispersion measurement (DM). The fittin

Manuel Mañas, Miguel Rojas

General Geronimus transformations, defined by regular matrix polynomials that are neither required to be monic nor restricted by the rank of their leading coefficients, are applied through both right and left multiplication to a rectangular matrix of measures associated with mixed multiple orthogonal polynomials. These transformations produce Christoffel-typ

The LHAASO Collaboration, Zhen Cao, F. Aharonian, Y. X. Bai

The diffuse Galactic gamma-ray emission is a very important tool used to study the propagation and interaction of cosmic rays in the Milky Way. In this work, we report the measurements of the diffuse emission from the Galactic plane, covering Galactic longitudes from $15^{\circ}$ to $235^{\circ}$ and latitudes from $-5^{\circ}$ to $+5^{\circ}$, in an energy

Huanqi Yang, Rucheng Wu, Weitao Xu

The incorporation of Large Language Models (LLMs) into smart transportation systems has paved the way for improving data management and operational efficiency. This study introduces TransCompressor, a novel framework that leverages LLMs for efficient compression and decompression of multimodal transportation sensor data. TransCompressor has undergone thoroug

Youngmin Oh, Jinje Park, Seunggeun Kim, Taejin Paik

Recent advancements in reinforcement learning (RL) for analog circuit optimization have demonstrated significant potential for improving sample efficiency and generalization across diverse circuit topologies and target specifications. However, there are challenges such as high computational overhead, the need for bespoke models for each circuit. To address t

Niloufar Alipour Talemi, Hossein Kashiani, Fatemeh Afghah

Pre-trained Vision-language (VL) models, such as CLIP, have shown significant generalization ability to downstream tasks, even with minimal fine-tuning. While prompt learning has emerged as an effective strategy to adapt pre-trained VL models for downstream tasks, current approaches frequently encounter severe overfitting to specific downstream data distribu

Rômulo Damasclin Chaves dos Santos

In this work, we investigate the long-time behavior of solutions to the non-cutoff Boltzmann equation on compact Riemannian manifolds with bounded Ricci curvature. The paper introduces new results on the exponential decay of hydrodynamic quantities, such as density, momentum, and energy fields, influenced by both the curvature of the manifold and singulariti

Youngkyu Lee, Shanqing Liu, Jerome Darbon, George Em Karniadakis

We design two classes of ultra-fast meta-solvers for linear systems arising after discretizing PDEs by combining neural operators with either simple iterative solvers, e.g., Jacobi and Gauss-Seidel, or with Krylov methods, e.g., GMRES and BiCGStab, using the trunk basis of DeepONet as a coarse preconditioner. The idea is to leverage the spectral bias of neur

Serban Cicortas

This is the second paper of a two part work that establishes a definitive quantitative nonlinear scattering theory for asymptotically de Sitter vacuum solutions $(M,g)$ in $(n+1)$ dimensions with $n\geq4$ even, which are determined by small scattering data at $\mathscr{I}^{\pm}.$ In this paper we prove quantitative estimates for systems of wave equations on

Jincheng Yu, Jiachen Li, Tianyu Zhu, Weitao Yang

Double excitations are crucial to understanding numerous chemical, physical, and biological processes, but accurately predicting them remains a challenge. In this work, we explore the particle-particle random phase approximation (ppRPA) as an efficient and accurate approach for computing double excitation energies. We benchmark ppRPA using various exchange-c

Giuseppe Bisicchia, Giuseppe Clemente, Jose Garcia-Alonso, Juan Manuel Murillo Rodríguez

NISQ (Noisy Intermediate-Scale Quantum) era constraints, high sensitivity to noise and limited qubit count, impose significant barriers on the usability of QPUs (Quantum Process Units) capabilities. To overcome these challenges, researchers are exploring methods to maximize the utility of existing QPUs despite their limitations. Building upon the idea that t

Amandine Aftalion, Philippe Gravejat, Etienne Sandier

The specific geometry of a strip provides connections between solitons and solitonic vortices, which are vortices with a solitonic behaviour in the infinite direction of the strip. We show that there exist stationary solutions to the Gross-Pitaevskii equation with k vortices on a transverse line, which bifurcate from the soliton solution as the width of the

Yucheng Liu

We consider the convolution equation $(δ- J) * G = g$ on $\mathbb R^d$, $d>2$, where $δ$ is the Dirac delta function and $J,g$ are given functions. We provide conditions on $J, g$ that ensure the deconvolution $G(x)$ to decay as $( x \cdot Σ^{-1} x)^{-(d-2)/2}$ for large $|x|$, where $Σ$ is a positive-definite diagonal matrix. This extends a recent deconvolu

Ljubomir Rokvic, Panayiotis Danassis, Sai Praneeth Karimireddy, Boi Faltings

In Federated Learning, it is crucial to handle low-quality, corrupted, or malicious data. However, traditional data valuation methods are not suitable due to privacy concerns. To address this, we propose a simple yet effective approach that utilizes a new influence approximation called &#34;lazy influence&#34; to filter and score data while preserving privac

Xiangyi Meng, Yu Tian

Immersion minor is an important variant of graph minor, defined through an injective mapping from vertices in a smaller graph $H$ to vertices in a larger graph $G$ where adjacent elements of the former are connected in the latter by edge-disjoint paths. Here, we consider the immersion problem in the emerging field of hypergraphs. We first define hypergraph i

Hariharan Ragothaman, Harihar M, SK Guhananthan

With continual advancements in technology, efforts to develop robots simulating human behavior have intensified. Cognitive robotics, combined with artificial intelligence (AI), has proven effective in surveying and research analysis. However, despite progress, human intervention remains necessary, and incorporating AI into robotic systems continues to pose c

Wenzhi Gao, Huikang Liu, Yinyu Ye, Madeleine Udell

The primal-dual interior point method (IPM) is widely regarded as the most efficient IPM variant for linear optimization. In this paper, we demonstrate that the improved stability of the pure primal IPM can allow speedups relative to a primal-dual solver, particularly as the IPM approaches convergence. The stability of the primal scaling matrix makes it poss

M. Heinz, T. Miyagi, S. R. Stroberg, A. Tichai

The in-medium similarity renormalization group (IMSRG) is a powerful and flexible many-body method to compute the structure of nuclei starting from nuclear forces. Recent developments have extended the IMSRG from its standard truncation at the normal-ordered two-body level, the IMSRG(2), to a precision approximation including normal-ordered three-body operat

Sivaguru S. Sritharan, Saba Mudaliar

In this paper we study a large class of nonlinear stochastic wave equations that arise in laser generation models and models for propagation in random media in a unified mathematical framework. Continuous and pulse-wave propagation models, free electron laser generation models, as well as laser-plasma interaction models have been cast in a convenient and uni

J. Olivares, H. Bouy, Trevor Z. Dorn-Wallenstein, A. Berihuete

Context: Star-forming regions, stellar associations, and open clusters are fundamental stellar systems where predictions from star-formation theories can be robustly contrasted with observations. Aims: We aim to provide the astrophysical community with a free and open-source code to infer the phase-space (i.e. positions and velocities) parameters of stellar

Jackson K. Wilt, Nico Schramma, Jan-Willem Bottermans, Maziyar Jalaal

Marangoni surfers are simple, cost-effective tabletop experiments that, despite their simplicity, exhibit rich dynamics and collective behaviors driven by physicochemical mechanisms, hydrodynamic interactions, and inertial motion. This work introduces self-propelled particles designed and manufactured through 3D printing to move on the air-water interface. W

Jaime Gómez, David Kalaj, Petar Melentijević, João P. G. Ramos

We prove a sharp quantitative version of recent Faber-Krahn inequalities for the continuous Wavelet transforms associated to a certain family of Cauchy wavelet windows . Our results are uniform on the parameters of the family of Cauchy wavelets, and asymptotically sharp in both directions. As a corollary of our results, we are able to recover not only the or

Liam Quinn, Yiqing Xu, Julien Fatome, Gian-Luca Oppo

Time-multiplexed networks of degenerate optical parametric oscillators have demonstrated remarkable success in simulating coupled Ising spins, thus providing a promising route to solving complex combinatorial optimization problems. In these systems $\unicode{x2014}$ referred to as coherent Ising machines $\unicode{x2014}$ the spins are encoded in the phases

Fakrul Islam Tushar

Purpose: This study investigated how nodule segmentation and surrounding peritumoral regions influence radionics-based lung cancer classification. Methods: Using 3D CT scans with bounding box annotated nodules, we generated 3D segmentations using four techniques: Otsu, Fuzzy C-Means (FCM), Gaussian Mixture Model (GMM), and K-Nearest Neighbors (KNN). Radiomic

Mohanad Odema, Luke Chen, Hyoukjun Kwon, Mohammad Abdullah Al Faruque

We study the application of emerging chiplet-based Neural Processing Units to accelerate vehicular AI perception workloads in constrained automotive settings. The motivation stems from how chiplets technology is becoming integral to emerging vehicular architectures, providing a cost-effective trade-off between performance, modularity, and customization; and

Grazyna Stasinska, Natalia Vale Asari, Anna Wojtowicz, Dorota Koziel-Wierzbowska

We use the ROGUE I and II catalogues of radio sources associated with optical galaxies to revisit the characterization of radio active galactic nuclei (AGNs) in terms of radio luminosities and properties derived from the analyses of the optical spectra of their associated galaxies. We propose a physically based classification of radio galaxies into `opticall

Sai Peng, Xiang Li, Li Yu, Xiaoru Zhuang

The present study numerically investigates the vortex shedding and heat transfer characteristics of a heated circular cylinder immersed in Bingham plastic fluids.The effects of three parameters, i.e., (i) plastic Reynolds number ($10 \leq Re \leq 180$), (ii) Prandtl number ($1\leq Pr \leq 100$), and (iii) the Bingham number ($0 \leq Bn \leq 10,000$), are eva

Georgios Billis, Johannes K. L. Michel, Frank J. Tackmann

We provide state-of-the-art precision QCD predictions for the fiducial $W$ and $Z$ boson transverse momentum spectra at the LHC at N$^3$LL$'$ and approximate N$^4$LL in resummed perturbation theory, matched to available $\mathcal{O}(\alpha_s^3)$ fixed-order results. Our predictions consistently combine all information from across the spectrum in a unified wa

Shengwen Ding, Chenhui Hu

Large Language Models (LLMs) herald a transformative era in artificial intelligence (AI). However, the expansive scale of data and parameters of LLMs requires high-demand computational and memory resources, restricting their accessibility to a broader range of users and researchers. This paper introduces an effective approach that enhances the operational ef

Haoyan Yang, Yixuan Wang, Keyue Tong, Hongjin Zhu

This paper proposes a detailed prompting flow, termed Table-Logic, to investigate the performance contrasts between bigger and smaller language models (LMs) utilizing step-by-step reasoning methods in the TableQA task. The method processes tasks by sequentially identifying critical columns and rows given question and table with its structure, determining nec

Jacob B. Fiedler, D. M. Stull

We investigate variants of Marstrand's projection theorem that hold for sets of directions and classes of sets in $\mathbb{R}^2$. We say that a set of directions $D \subseteq\mathcal{S}^1$ is $\textit{universal}$ for a class of sets if, for every set $E$ in the class, there is a direction $e\in D$ such that the projection of $E$ in the direction $e$ has maxi

Jayanta Sadhu, Ayan Antik Khan, Noshin Nawal, Sanju Basak

Theory of Mind (ToM) refers to the cognitive ability to infer and attribute mental states to oneself and others. As large language models (LLMs) are increasingly evaluated for social and cognitive capabilities, it remains unclear to what extent these models demonstrate ToM across diverse languages and cultural contexts. In this paper, we introduce a comprehe

Jonathan Light, Sixue Xing, Yuanzhe Liu, Weiqin Chen

Effective extraction of the world knowledge in LLMs for complex decision-making tasks remains a challenge. We propose a framework PIANIST for decomposing the world model into seven intuitive components conducive to zero-shot LLM generation. Given only the natural language description of the game and how input observations are formatted, our method can genera

Redwan Ibne Seraj Khan, Kunal Jain, Haiying Shen, Ankur Mallick

In a multi-tenant large language model (LLM) serving platform hosting diverse applications, some users may submit an excessive number of requests, causing the service to become unavailable to other users and creating unfairness. Existing fairness approaches do not account for variations in token lengths across applications and multiple LLM calls, making them

Tomasz Serafin, Bartosz Uniejewski

In this study, we introduced various statistical performance metrics, based on the pinball loss and the empirical coverage, for the ranking of probabilistic forecasting models. We tested the ability of the proposed metrics to determine the top performing forecasting model and investigated the use of which metric corresponds to the highest average per-trade p

Eldar Knar

This article analyses the structural and institutional barriers hindering the development of scientific systems in transition economies, such as Kazakhstan. The main focus is on the concept of the "middle science trap," which is characterized by steady growth in quantitative indicators (publications, grants) but a lack of qualitative advancement. Excessive b

Risto Uuk, Carlos Ignacio Gutierrez, Daniel Guppy, Lode Lauwaert

Through a systematic review of academic literature, we propose a taxonomy of systemic risks associated with artificial intelligence (AI), in particular general-purpose AI. Following the EU AI Act's definition, we consider systemic risks as large-scale threats that can affect entire societies or economies. Starting with an initial pool of 1,781 documents, we

Hui Zhou, Xiaolan Liu, Sangarapillai Lambotharan

In 6G communications, it is envisioned to equip the traditional access point (AP) with sensing capability to fully benefit the existing wireless communication infrastructures. Thus, sensing-assisted communication has attracted significant attention from both industry and academia. However, most existing works focused on sensing-assisted communication in line

Chandrodoy Chattopadhyay, Josh Ott, Thomas Schaefer, Vladimir V. Skokov

We describe a numerical method for simulating stochastic fluid dynamics near a critical point in the Ising universality class. This theory is known as model H, and is expected to govern the non-equilibrium dynamics of Quantum Chromodynamics (QCD) near a possible critical endpoint of the phase transition between a hadron liquid and the quark-gluon plasma. The

Lifu Tu, Rui Meng, Shafiq Joty, Yingbo Zhou

Large language models (LLMs) have demonstrated strong capabilities in text understanding and generation. However, they often lack factuality, producing a mixture of true and false information, especially in long-form generation. In this work, we investigates the factuality of long-form text generation across various large language models (LLMs), including GP

E. Yu. Lerner

Given a simple biconnected planar cubic graph, we associate each its vertex among $2n$ ones with the so-called spin, i.e., a variable which takes on values $\pm 1$. P. J. Heawood has proved that a Tait coloring, accurate to the choice of a color for one edge, is equivalent to the choice of spin values so as to make the sum of these value at vertices of any f

Nikesh Patel, Benyam Dejen, Stephen Church, Philip Dolan

Quantitative and reproducible optical characterization of single quantum emitters is crucial for quantum photonic materials research, yet controlling for experimental conditions remains challenging due to a lack of an established reference standard. We propose nanodiamonds containing single nitrogen vacancy (NV$^{-}$) color centers as reliable, stable and ro

Alec Dektor, Lukas Einkemmer

We introduce two novel interpolatory dynamical low-rank (DLR) approximation methods for the efficient time integration of the Boltzmann-BGK equation. Both methods overcome limitations of classic DLR schemes based on orthogonal projections for nonlinear equations. In particular, we demonstrate that the proposed methods can efficiently compute solutions to the

Reza Zakerian, Hadi Gholami

With the rapid advancement of devices requiring intensive computation, such as Internet of Things (IoT) devices, smart sensors, and wearable technology, the computational demands on individual platforms with limited resources have escalated, necessitating the offloading of the generated tasks by the devices to edge. These tasks are often real-time with stric

Sabarnya Mitra, Frithjof Karsch, Sipaz Sharma

In order to quantify the universal properties of the chiral phase transition in (2+1)-flavor QCD, we make use of an improved, renormalized order parameter for chiral symmetry breaking which is obtained as a suitable difference of the $2$-flavor light quark chiral condensate and its corresponding light quark susceptibility. Having no additive ultraviolet as w

Emilio Parini

We prove that for a discrete, countable, and amenable group $G$, if the direct product $G^2=G \times G$ is finitely colored then $\{ g \in G : \text{exists } (x,y) \in G^2 \text{ such that } \{ (x,y),(xg,y),(xg,yg)\} \text{ is monochromatic} \}$, is left IP$^{\ast}$. This partially solves a conjecture of V. Bergelson and R. McCutcheon. Moreover, we prove tha

Romain Pascual

This report presents a set-theoretic framework for the instantiation of rule schemes in the Jerboa platform, a tool for developing domain-specific geometric modelers. Jerboa enables the design of geometric modeling operations as graph transformation rules generalized to rule schemes for genericity over the topological content of the operations. Current appro

Rakesh Arora, Jacques Giacomoni, Arshi Vaishnavi

In this work, we study the existence, non-existence, and uniqueness results for nonlocal elliptic equations involving logarithmic Laplacian, and subcritical, critical, and supercritical logarithmic nonlinearities. The Poho\u zaev's identity and D\'iaz-Saa type inequality are proved, which are of independent interest and can be applied to a larger class of pr

Emanuele Galiffi, Diego Martinez Solís, Shixiong Yin, Nader Engheta

Exotic forms of wave control have been emerging by engineering matter in space and time. In this framework, temporal photonic interfaces, i.e., abrupt changes in the electromagnetic properties of a material, have been shown to induce temporal scattering phenomena dual to spatial reflection and refraction, at the basis of photonic time crystals and space-time

Caihao Qiu, David J. Srolovitz, Gregory S. Rohrer, Jian Han

Grain growth in polycrystals is traditionally considered a capillarity-driven process, where grain boundaries (GBs) migrate toward their centers of curvature (i.e., mean curvature flow) with a velocity proportional to the local curvature (including extensions to account for anisotropic GB energy and mobility). Experimental and simulation evidence shows that

Alireza Bahraini

We introduce a new class of singular complex manifolds and we develop a degenerate Kodaira-Hodge theory for this class of singular manifolds.

Chao Fang, Man Shi, Robin Geens, Arne Symons

The widely-used, weight-only quantized large language models (LLMs), which leverage low-bit integer (INT) weights and retain floating-point (FP) activations, reduce storage requirements while maintaining accuracy. However, this shifts the energy and latency bottlenecks towards the FP activations that are associated with costly memory accesses and computation

Carlo R. Laing, Bernd Krauskopf

We consider a pair of identical theta neurons in the excitable regime, each coupled to the other via a delayed Dirac delta function with the same delay. This simple network can support different periodic solutions, and we concentrate on two important types: those for which the neurons are perfectly synchronous, and those where the neurons are exactly half a

Depeng Chen, Hao Chen, Hulin Jin, Jie Cui

Membership inference attacks (MIAs) are critical tools for assessing privacy risks and ensuring compliance with regulations like the General Data Protection Regulation (GDPR). However, their potential for auditing unauthorized use of data remains under explored. To bridge this gap, we propose a novel clean-label backdoor-based approach for MIAs, designed spe

Fulvio Melia

The conventional picture of supermassive black-hole growth in the standard model had already been seriously challenged by the emergence of $\sim 10^9\;M_\odot$ quasars at $z\sim 7.5$, conflicting with the predicted formation of structure in the early $\Lambda$CDM Universe. But the most recent {\it JWST} discovery of a $\sim 10^8\;M_\odot$ source at $z\sim 10

K. Schoeffler, N. Shukla, L. O. Silva

Dark matter has been theorized to be charged under its own "dark electromagnetism" (dark-EM). Under this hypothesis, dark matter can behave like a cold collisionless plasma of self-interacting dark matter particles, and exhibit plasma-like instabilities with observational consequences. Using the results published in [1], which studied the degree of slowdown