November 2024 arXiv papers — page 169

David J Poland, Lemuel Puglisi, Daniele Ravi

This article introduces Transformer Quantile Regression Neural Networks (TQRNNs), a novel data-driven solution for real-time machine failure prediction in manufacturing contexts. Our objective is to develop an advanced predictive maintenance model capable of accurately identifying machine system breakdowns. To do so, TQRNNs employ a two-step approach: (i) a

Jannik Irmai, Lucas Fabian Naumann, Bjoern Andres

The $q$-chorded $k$-cycle inequalities are a class of valid inequalities for the clique partitioning polytope. It is known that for $q \in \{2, \tfrac{k-1}{2}\}$, these inequalities induce facets of the clique partitioning polytope if and only if $k$ is odd. Here, we characterize such facets for arbitrary $k$ and $q$. More specifically, we prove that the $q$

Ángel Morán Ledezma

In this work, we study the dynamics of complex systems with time-dependent transition rates, focusing on $p$-adic analysis in modeling such systems. Starting from the master equation that governs the stochastic dynamics of a system with a large number of interacting components, we generalize it by $p$-adically parametrizing the metabasins to account for stat

Sombit Dey, Ozan Unal, Christos Sakaridis, Luc Van Gool

3D visual grounding consists of identifying the instance in a 3D scene which is referred by an accompanying language description. While several architectures have been proposed within the commonly employed grounding-by-selection framework, the utilized losses are comparatively under-explored. In particular, most methods rely on a basic supervised cross-entro

Shizhao Peng, Tianrui Liu, Tianle Tao, Derun Zhao

Efficient multi-party secure matrix multiplication is crucial for privacy-preserving machine learning, but existing mixed-protocol frameworks often face challenges in balancing security, efficiency, and accuracy. This paper presents an efficient, verifiable and accurate secure three-party computing (EVA-S3PC) framework that addresses these challenges with el

Roberto Del Prete, Manuel Salvoldi, Domenico Barretta, Nicolas Longépé

Satellite-based onboard data processing is crucial for time-sensitive applications requiring timely and efficient rapid response. Advances in edge artificial intelligence are shifting computational power from ground-based centers to on-orbit platforms, transforming the "sensing-communication-decision-feedback" cycle and reducing latency from acquisition to d

Kristina Šekrst, Jeremy McHugh, Jonathan Rodriguez Cefalu

This paper explores the development of an ethical guardrail framework for AI systems, emphasizing the importance of customizable guardrails that align with diverse user values and underlying ethics. We address the challenges of AI ethics by proposing a structure that integrates rules, policies, and AI assistants to ensure responsible AI behavior, while compa

Aditya Dave, Mengchen Zhu, Dapeng Hu, Sachin Tiwari

Corporate Greenhouse Gas (GHG) emission targets are important metrics in sustainable investing [12, 16]. To provide a comprehensive view of company emission objectives, we propose an approach to source these metrics from company public disclosures. Without automation, curating these metrics manually is a labor-intensive process that requires combing through

Justin P. Miner, Sneha Prabha Narra

Previous work on fatigue prediction in Powder Bed Fusion - Laser Beam has shown that the estimate of the largest pore size within the stressed volume is correlated with the resulting fatigue behavior in porosity-driven failures. However, single value estimates for the largest pore size are insufficient to capture the experimentally observed scatter in fatigu

Matthew Jenssen, Alexandru Malekshahian, Jinyoung Park

Dedekind's problem, dating back to 1897, asks for the total number $\psi(n)$ of antichains contained in the Boolean lattice $B_n$ on $n$ elements. We study Dedekind's problem using a recently developed method based on the cluster expansion from statistical physics and as a result, obtain several new results on the number and typical structure of antichains i

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

An amplitude analysis of the $D_{s1}(2460)^+\to D_{s}^{+}\pi^{+}\pi^{-}$ transition is performed simultaneously in $B^{0}\to D^{-}D_{s}^{+}\pi^{+}\pi^{-}$, $B^{+}\to{\bar{D}}^{0} D_{s}^{+}\pi^{+}\pi^{-}$, and $B^{0}\to D^{*-}D_{s}^{+}\pi^{+}\pi^{-}$ decays. The study is based on a data sample of proton-proton collisions recorded with the LHCb detector at cen

Yingqi Cao, Anshu Gupta, Jason Liang, Yatish Turakhia

Dynamic programming (DP) based algorithms are essential yet compute-intensive parts of numerous bioinformatics pipelines, which typically involve populating a 2-D scoring matrix based on a recursive formula, optionally followed by a traceback step to get the optimal alignment path. DP algorithms are used in a wide spectrum of bioinformatics tasks, including

Shlomo Neuberger, Niv Eckhaus, Uri Berger, Amir Taubenfeld

Many human interactions, such as political debates, are carried out in group settings, where there are arbitrarily many participants, each with different views and agendas. To explore such complex social settings, we present SAUCE: a customizable Python platform, allowing researchers to plug-and-play various LLMs participating in discussions on any topic cho

Nguyen Tran Gia Bao, Ton Nu Quynh Trang, Nam Thoai, Phan Bach Thang

Direct Z-scheme heterobilayers with enhanced redox potential are viewed as promising for solar-driven water splitting, arising from the synergy between intrinsic dipoles in Janus materials and interfacial electric fields across the layers. This study explores 20 two-dimensional Janus transition-metal dichalcogenide (TMDC) heterobilayers for efficient water s

Anil Palepu, Vikram Dhillon, Polly Niravath, Wei-Hung Weng

Large language models (LLMs) have shown remarkable progress in encoding clinical knowledge and responding to complex medical queries with appropriate clinical reasoning. However, their applicability in subspecialist or complex medical settings remains underexplored. In this work, we probe the performance of AMIE, a research conversational diagnostic AI syste

Alessandro Bellina, Giordano De Marzo, Vittorio Loreto

Macroevolutionary dynamics often display sudden, explosive surges, where systems remain relatively stable for extended periods before experiencing dramatic acceleration that frequently exceeds traditional exponential growth. This pattern is evident in biological evolution, cultural shifts, and technological progress and is often referred to as the emergence

Matthew Jenssen, Alexandru Malekshahian, Jinyoung Park

We establish a refined version of a graph container lemma due to Galvin and discuss several applications related to the hard-core model on bipartite expander graphs. Given a graph $G$ and $\lambda>0$, the hard-core model on $G$ at activity $\lambda$ is the probability distribution $\mu_{G,\lambda}$ on independent sets in $G$ given by $\mu_{G,\lambda}(I)\prop

Juan Carlos Gómez-Izquierdo, Catalina Espinoza, Lucia E. Gutiérrez Luna, Myriam Mondragón

The current neutrino experiments provide an opportunity for testing the inverse see-saw mechanism through charged lepton flavor violating processes and neutrinoless double beta decay. Motivated by this, in this paper we study the $\mathbf{S}_{3}\otimes \mathbf{Z}_{2}$ discrete symmetry in the $B-L$ gauge model where the active light neutrino mass matrix come

Sujit Sakharam Damase, Apoorva Khare

Belton-Guillot-Khare-Putinar [J. d'Analyse Math. 2023] classified the post-composition operators that preserve TP/TN kernels of each specified order. We explain how to extend this from preservers to transforms, and from one to several variables. Namely, given arbitrary nonempty totally ordered sets $X,Y$, we characterize the transforms that send each tuple o

Moses Charikar, Alexandra Lassota, Prasanna Ramakrishnan, Adrian Vetta

A cornerstone of social choice theory is Condorcet's paradox which says that in an election where $n$ voters rank $m$ candidates it is possible that, no matter which candidate is declared the winner, a majority of voters would have preferred an alternative candidate. Instead, can we always choose a small committee of winning candidates that is preferred to a

Alexander Mote, Todd Palmer, Lizhong Chen

Domain decomposition is a technique used to reduce memory overhead on large neutron transport problems. Currently, the optimal load-balanced processor allocation for these domains is typically determined through small-scale simulations of the problem, which can be time-consuming for researchers and must be repeated anytime a problem input is changed. We prop

Javier Cubillos-Cornejo, Miguel Escobar Mendoza, Ignacio Bordeu

In this work, we explore the influence of coupling strength, network size, and randomness on the collective dynamics of FitzHugh-Nagumo oscillators on complex networks. Using Watts-Strogatz small-world network connectivities, we identify four distinct dynamical phases: chaotic, intermittent, partially synchronized, and fully synchronized. The intermittent ph

Xiaoke Qin, Francesca Martella, Sanjeena Subedi

Cluster-weighted factor analyzers (CWFA) are a versatile class of mixture models designed to estimate the joint distribution of a random vector that includes a response variable along with a set of explanatory variables. They are particularly valuable in situations involving high dimensionality. This paper enhances CWFA models in two notable ways. First, it

Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar

Estimating causal quantities from observational data is crucial for understanding the safety and effectiveness of medical treatments. However, to make reliable inferences, medical practitioners require not only estimating averaged causal quantities, such as the conditional average treatment effect, but also understanding the randomness of the treatment effec

Jasleen Kaur, Aritra Ghosh, Sushanta Dattagupta, Subhash Chaturvedi

In this work, we study an Ericsson cycle whose working substance is a charged (quantum) oscillator in a magnetic field that is coupled to a heat bath. The resulting quantum Langevin equations with built-in noise terms encapsulate a thermodynamic structure and allow for the computation of the efficiency of the cycle. We numerically compute the efficiency of t

Diego Gosmar, Deborah A. Dahl, Emmett Coin, David Attwater

This paper presents a novel extension to the existing Multi-Agent Interoperability specifications of the Open Voice Interoperability Initiative (originally also known as OVON from the Open Voice Network). This extension enables AI agents developed with different technologies to communicate using a universal, natural language-based API or NLP-based standard A

Ushangi Goginava, Farrukh Mukhamedov

It is well-known that to establish the almost everywhere convergence of a sequence of operators on $L_1$-space, it is sufficient to obtain a weak $(1,1)$-type inequality for the maximal operator corresponding to the sequence of operators. However, in practical applications, the establishment of the mentioned inequality for the maximal operators is very trick

Ariel Neufeld, Philipp Schmocker

In this paper, we solve stochastic partial differential equations (SPDEs) numerically by using (possibly random) neural networks in the truncated Wiener chaos expansion of their corresponding solution. Moreover, we provide some approximation rates for learning the solution of SPDEs with additive and/or multiplicative noise. Finally, we apply our results in n

Yilber Fabian Bautista, Yu-Tin Huang, Jung-Wook Kim

In this paper we define absorptive Compton amplitudes, which captures the absorption factor for waves of spin-weight-$s$ scattering in black hole perturbation theory. At the leading order, in the $G M \omega$ expansion, such amplitudes are purely imaginary and expressible as contact terms. Equipped with these amplitudes we compute the mass change in black ho

Geir Agnarsson, Jim Lawrence

\emph{Minkowski rings} are certain rings of simple functions on the Euclidean space $W = {\mathbb{R}}^d$ with multiplicative structure derived from Minkowski addition of convex polytopes. When the ring is (finitely) generated by a set ${\cal{P}}$ of indicator functions of $n$ polytopes then the ring can be presented as ${\mathbb{C}}[x_1,\ldots,x_n]/I$ when v

Christian Northe

These notes were presented at the Young Researchers School (YRS) in Maynooth in April 2024 and provide an introduction to Conformal Field Theory CFT, Boundary Conformal Field Theory (BCFT) and Defect Conformal Field Theory (DCFT). This class is mostly self-contained and includes exercises with solutions. The first part of these notes is concerned with the ba

Ron Ofir, Michael Margaliot

We present a new sufficient condition for finite-gain $L_2$ input-to-output stability of a networked system. The condition requires a matrix, that combines information on the $L_2$ gains of the sub-systems and their interconnections, to be discrete-time diagonally stable (DTDS). We show that the new result generalizes the standard small gain theorem for the

Apoorv Srivastava, Shovan Dutta

Kinetically constrained spin chains serve as a prototype for structured ergodicity breaking in isolated quantum systems. We show that such a system exhibits a hierarchy of degenerate steady states when driven by incoherent pump and loss at the boundary. By tuning the relative pump and loss and how local the constraints are, one can stabilize mixed steady sta

Julius Lange, Leonid Komissarov, Rene Lang, Dennis Dimo Enkelmann

In materials and pharmaceutical development, rapidly and accurately determining the similarity between X-ray powder diffraction (XRPD) measurements is crucial for efficient solid form screening and analysis. We present SMolNet, a classifier based on a Siamese network architecture, designed to automate the comparison of XRPD patterns. Our results show that tr

Ushangi Goginava, Farrukh Mukhamedov

The aim of the current paper is to determine the necessary and sufficient conditions for the weights $\mathbf{q}=\{q_k\}$, ensuring that the sequence of operators $\left\{ T_{n}^{\left( \mathbf{q}\right) }f\right\} $ associated with Walsh system, is convergent almost everywhere for all integrable function $f$. The article also examines the convergence of a s

Reynier Leyva La O, Carlos A. Catania, Tatiana Parlanti

This work analyzes the use of large language models (LLMs) for detecting domain generation algorithms (DGAs). We perform a detailed evaluation of two important techniques: In-Context Learning (ICL) and Supervised Fine-Tuning (SFT), showing how they can improve detection. SFT increases performance by using domain-specific data, whereas ICL helps the detection

Alexander J. H. Houston, Nigel J. Mottram

Incorporating the inherent heterogeneity of living systems into models of active nematics is essential to provide a more realistic description of biological processes such as bacterial growth, cell dynamics and tissue development. Spontaneous flow of a confined active nematic is a fundamental feature of these systems, in which the role of heterogeneity has n

Sam Gunn, Ramis Movassagh

The meteoric rise in power and popularity of machine learning models dependent on valuable training data has reignited a basic tension between the power of running a program locally and the risk of exposing details of that program to the user. At the same time, fundamental properties of quantum states offer new solutions to data and program security that can

Anish Bhattacharya, Marco Cannici, Nishanth Rao, Yuezhan Tao

We present the first static-obstacle avoidance method for quadrotors using just an onboard, monocular event camera. Quadrotors are capable of fast and agile flight in cluttered environments when piloted manually, but vision-based autonomous flight in unknown environments is difficult in part due to the sensor limitations of traditional onboard cameras. Event

Ryan Tiew, Nikolas P. Breuckmann

We generalise the implementation of logical quantum gates via Dehn twists from topological codes to the hypergraph and balanced products of cyclic codes. These generalised Dehn twists implement logical entangling gates with no additional qubit overhead and $\mathcal{O}(d)$ time overhead. Due to having more logical degrees of freedom in the codes, there is a

Alfredo Ricci Vasquez, Carmelo Mordini, Daniel Kienzler, Jonathan Home

In this work we study the interaction of trapped ions with a state-dependent, high-intensity optical lattice formed above an ion trap chip using integrated photonics. We use a single ion to map the optical potential landscape over many periods of the standing-wave field. For a single ion sitting in the centre of the lattice we observe a state-dependent trap-

Mathieu Lamarre, Patrick Anderson, Étienne Danvoye

Accurate stabilization of facial motion is essential for applications in photoreal avatar construction for 3D games, virtual reality, movies, and training data collection. For the latter, stabilization must work automatically for the general population with people of varying morphology. Distinguishing rigid skull motion from facial expressions is critical si

Rajkumar Ramamurthy, Meghana Arakkal Rajeev, Oliver Molenschot, James Zou

Large language models (LLMs) often fail to synthesize information from their context to generate an accurate response. This renders them unreliable in knowledge intensive settings where reliability of the output is key. A critical component for reliable LLMs is the integration of a robust fact-checking system that can detect hallucinations across various for

Monika Henzinger, Roodabeh Safavi, Salil Vadhan

Many intended uses of differential privacy involve a $\textit{continual mechanism}$ that is set up to run continuously over a long period of time, making more statistical releases as either queries come in or the dataset is updated. In this paper, we give the first general treatment of privacy against $\textit{adaptive}$ adversaries for mechanisms that suppo

Luis Fernando Galicia Cruztitla, Diego Mauricio Gomez Coral

This work reviews the current state of the antideuteron ($\bar{d}$) production cross-sections in cosmic ray interactions and its uncertainties, considering the coalescence model and measurements in accelerator experiments. These cross-sections have been included in a simulation of cosmic rays propagation in the Galaxy using GALPROP v.57, with updated paramet

Alexandre Serantes, David Travieso Mayo, Javier Mas

We investigate the nonlinear stability of global Anti-de Sitter space in the presence of multitrace deformations utilizing an Einstein-Klein-Gordon system with a top-down scalar potential. Our numerical simulations show that marginal and irrelevant deformations retain the nonlinear instability originally found by Bizo\'n and Rostworowski, while relevant defo

Mika Göös, Tom Gur, Siddhartha Jain, Jiawei Li

We exhibit a total search problem with classically verifiable solutions whose communication complexity in the quantum SMP model is exponentially smaller than in the classical two-way randomized model. Our problem is a bipartite version of a query complexity problem recently introduced by Yamakawa and Zhandry (JACM 2024). We prove the classical lower bound us

Farhana Shahid, Maximilian Dittgen, Mor Naaman, Aditya Vashistha

This paper examines if large language models (LLMs) can help people write constructive comments on divisive social issues due to the difficulty of expressing constructive disagreement online. Through controlled experiments with 600 participants from India and the US, who reviewed and wrote constructive comments on threads related to Islamophobia and homophob

George Jiayuan Gao, Tianyu Li, Nadia Figueroa

We propose an object-centric recovery (OCR) framework to address the challenges of out-of-distribution (OOD) scenarios in visuomotor policy learning. Previous behavior cloning (BC) methods rely heavily on a large amount of labeled data coverage, failing in unfamiliar spatial states. Without relying on extra data collection, our approach learns a recovery pol

Pablo Guillermo Carmona Rufo, Anupam Mazumdar, Carlos Sabín

We demonstrate the existence of genuine tripartite non-Gaussian entanglement in a quantum gravitational system formed by a quantum harmonic oscillator coupled to a single frequency of a quantized gravitational wave. For this purpose, we introduce a new entanglement witness, well-suited for the graviton-matter interaction Hamiltonian analysed here. We show th

Jingyu Xiao, Yuxuan Wan, Yintong Huo, Zixin Wang

Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance on the design-to-code task, i.e., generating UI code from UI mock-ups. However, existing benchmarks only contain static web pages for evaluation and ignore the dynamic interaction, limiting the practicality, usability and user engagement of the generated webpages. To bridge the

W. Spencer Smith, Jingyi Lin

Research software engineers can use Assurance Cases (ACs) to guide Verification and Validation (VnV) efforts. An AC is a structured argument that a property like correctness holds. We illustrate how ACs can guide VnV activities via a case study of software for automatically extracting the 3D segmentation of the aorta from medical images of the chest. The AC

Daniel Marris, Pol Fernández-López, Frederic Bartumeus, Luca Giuggioli

Behavioral heterogeneities in animals, also known as syndromes, play a crucial role in understanding how natural populations flexibly adapt to environmental changes. In ant species like \textit{Aphaenogaster senilis}, two key roles in collective foraging are commonly recognised: scouts, who discover food patches, and recruits, who exploit these patches and t

Ananya Trivedi, Sarvesh Prajapati, Anway Shirgaonkar, Mark Zolotas

Traditional approaches to motion modeling for skid-steer robots struggle with capturing nonlinear tire-terrain dynamics, especially during high-speed maneuvers. In this paper, we tackle such nonlinearities by enhancing a dynamic unicycle model with Gaussian Process (GP) regression outputs. This enables us to develop an adaptive, uncertainty-informed navigati

Adam M Tahir

A model predictive control scheme to stabilize desired configurations of collinear Coulomb spacecraft formations is derived in this paper. The nonlinearities of the dynamics with respect to the input make this problem difficult to solve, computationally. It is shown that the nonlinearities in the input lead to a finite horizon optimization problem which is a

Souren Pashangpour, Goldie Nejat

The potential use of large language models (LLMs) in healthcare robotics can help address the significant demand put on healthcare systems around the world with respect to an aging demographic and a shortage of healthcare professionals. Even though LLMs have already been integrated into medicine to assist both clinicians and patients, the integration of LLMs

Kunyu Feng, Yue Ma, Bingyuan Wang, Chenyang Qi

Despite recent advances in UNet-based image editing, methods for shape-aware object editing in high-resolution images are still lacking. Compared to UNet, Diffusion Transformers (DiT) demonstrate superior capabilities to effectively capture the long-range dependencies among patches, leading to higher-quality image generation. In this paper, we propose DiT4Ed

Jian Yao, Yi-Zhuang You

We propose ShadowGPT, a novel approach for solving quantum many-body problems by learning from randomized measurement data collected from quantum experiments. The model is a generative pretrained transformer (GPT) trained on simulated classical shadow data of ground states of quantum Hamiltonians, obtained through randomized Pauli measurements. Once trained,

Dawei Li, Zhen Tan, Peijia Qian, Yifan Li

While multi-agent systems have been shown to significantly enhance the performance of Large Language Models (LLMs) across various tasks and applications, the dense interaction between scaling agents potentially hampers their efficiency and diversity. To address these challenges, we draw inspiration from the sparse mixture-of-agents (SMoE) and propose a spars

Yizi Chen, Hussein Mourtada, Wenhao Zhu

We develop algorithms to compute two versions of the motivic Hilbert zeta function for curve singularities: the classical version, applicable to singularities with a monomial valuation semigroup or to singular curves defined by \(y^{k}=x^{n}\) with \(\gcd(k,n)=1\), and a finer version introduced by the first and third authors together with Mounir Hajli, whic

Kåre Fridell

Leptoquarks are known to generate a wide range of potentially observable phenomena, and have been searched for in different experiments. We show that the observed baryon asymmetry and neutrino mass scale can both be simultaneously produced in a model featuring scalar leptoquarks while avoiding existing experimental constraints and potentially leading to futu

David Burghoff

Integrated frequency combs based on active cavities are of interest for a wide range of applications. An elegant description of these cavities is based on mean-field theory, which averages the effect of internal dynamics occurring within a round trip. Lasers based on media with slow gain dynamics can be described by solving the population over many round tri

MicroBooNE collaboration, P. Abratenko, O. Alterkait, D. Andrade Aldana

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generator

Shafi Goldwasser, Jonathan Shafer, Neekon Vafa, Vinod Vaikuntanathan

As society grows more reliant on machine learning, ensuring the security of machine learning systems against sophisticated attacks becomes a pressing concern. A recent result of Goldwasser, Kim, Vaikuntanathan, and Zamir (2022) shows that an adversary can plant undetectable backdoors in machine learning models, allowing the adversary to covertly control the

Jiawei An

Fix a prime $p\geq5$, an integer $N\geq1$ relatively prime to $p$, and an irreducible residual global Galois representation $\bar{r}: Gal_{\mathbb{Q}}\rightarrow GL_2(\mathbb{F}_p)$. In this paper, we utilize ghost series to study $p$-adic slopes of $\mathscr{L}$-invariants for $\bar{r}$-newforms. More precisely, under a locally reducible and strongly generi

Wouter Jongeneel

Suppose that two vector fields on a smooth manifold render some equilibrium point globally asymptotically stable (GAS). We show that there exists a homotopy between the corresponding semiflows such that this point remains GAS along this homotopy.

David Wittman, Scott Adler, Rodrigo Stancioli

In collisions of galaxy clusters, the lack of displacement between dark matter and galaxies suggests that the dark matter scattering depth is small. This yields an upper limit on the dark matter cross section if the dark matter column density is known. We investigate a bias in such constraints: the measured column density (along the line of sight, using grav

Yahang Qi, Bernhard Schölkopf, Zhijing Jin

As Artificial Intelligence (AI) systems increasingly influence decision-making across various fields, the need to attribute responsibility for undesirable outcomes has become essential, though complicated by the complex interplay between humans and AI. Existing attribution methods based on actual causality and Shapley values tend to disproportionately blame

Zhidan Feng, Henning Fernau, Pamela Fleischmann, Kevin Mann

The literature on word-representable graphs is quite rich, and a number of variations of the original definition have been proposed over the years. We are initiating a systematic study of such variations based on formal languages. In our framework, we can associate a graph class to each language over the binary alphabet \{0,1\}. All graph classes that are la

Farid Bozorgnia, Yassine Belkheiri, Abderrahim Elmoataz

This paper presents an approach to semi-supervised learning for the classification of data using the Lipschitz Learning on graphs. We develop a graph-based semi-supervised learning framework that leverages the properties of the infinity Laplacian to propagate labels in a dataset where only a few samples are labeled. By extending the theory of spatial segrega

M. Pursiainen, T. L. Killestein, H. Kuncarayakti, P. Charalampopoulos

We present the analysis of optical data of a bright and extremely-rapidly evolving transient, AT2024wpp, whose properties are similar to the enigmatic AT2018cow (aka the Cow). AT2024wpp rose to a peak brightness of c=-21.9mag in 4.3d and remained above the half-maximum brightness for only 6.7d. The blackbody fits to the multi-band photometry show that the ev

Suiyi He, Maziar Zamanpour, Jianshe Guo, Michael W. Levin

Red light violation is a major cause of traffic collisions and resulting injuries and fatalities. Despite extensive prior work to reduce red light violations, they continue to be a major problem in practice, partly because existing systems suffer from the flaw of providing the same guidance to all drivers. As a result, some violations are avoided, but other

Shiyun Lin, Simon Mauras, Nadav Merlis, Vianney Perchet

We study matching markets with ties, where workers on one side of the market may have tied preferences over jobs, determined by their matching utilities. Unlike classical two-sided markets with strict preferences, no single stable matching exists that is utility-maximizing for all workers. To address this challenge, we introduce the \emph{Optimal Stable Shar

Mattys Pouyez, Thomas Grismayer, Mickael Grech, Caterina Riconda

A complete, kinetic description of electron-seeded strong-field QED showers in crossed electromagnetic fields is derived. The kinetic structure of the shower and its temporal evolution are shown to be a function of two parameters: the initial shower quantum parameter and radiation time. The latter determines the short and long time evolution of the shower. E

Oleg Gutik, Maksym Shchypel

We study algebraic properties of the semigroup $\mathscr{O\!\!I\!}_n(L)$ of finite partial order isomorphisms of the rank $\leq n$ of an infinite linearly ordered set $(L,\leqslant)$. In particular we describe its idempotents, the natural partial order and Green's relations on $\mathscr{O\!\!I\!}_n(L)$. It is proved that the semigroup $\mathscr{O\!\!I\!}_n(L

Kahraman Kostas, Rabia Yasa Kostas, Mike Just, Michael A. Lones

With the proliferation of devices on the Internet of Things (IoT), ensuring their security has become paramount. Device identification (DI), which distinguishes IoT devices based on their traffic patterns, plays a crucial role in both differentiating devices and identifying vulnerable ones, closing a serious security gap. However, existing approaches to DI t

Momin Y. Khan, Barbara G. Castanheria

Sirius is the brightest star in the night sky and, despite its proximity, this binary system still imposes intriguing questions about its current characteristics and past evolution. Bond et. al. (arXiv:1703.10625) published decades of astrometric measurements of the Sirius system, determining the dynamical masses for Sirius A and B, and the orbital period. W

Renier Jansen, Muhammad Qasim, Walter Tholen

For a morphism f in a category C with sufficiently many finite limits and colimits, we discuss an elementary construction of a decomposition of f through objects P and N which, if C happens to have a zero object, amounts to the standard decomposition of f through P = Coker(ker f) and N = Ker(coker f). In this way we obtain natural notions of normal monomorph

Boris Khesin, Gerard Misiołek, Klas Modin

The study of diffeomorphism groups and their applications to problems in analysis and geometry has a long history. In geometric hydrodynamics, pioneered by V.~Arnold in the 1960s, one considers an ideal fluid flow as the geodesic motion on the infinite-dimensional group of volume-preserving diffeomorphisms of the fluid domain with respect to the metric defin

Zhaonan Dong, Lorenzo Mascotto, Zuodong Wang

We establish fully-discrete a priori and semi-discrete in time a posteriori error estimates for a discontinuous-continuous Galerkin discretization of the wave equation in second order formulation; the resulting method is a Petrov-Galerkin scheme based on piecewise polynomial test functions and continuous piecewise polynomial trial functions in time, respecti

Sabina J. Sloman, Julien Martinelli, Samuel Kaski

Generalization outside the scope of one's training data requires leveraging prior knowledge about the effects that transfer, and the effects that don't, between different data sources. Transfer learning is a framework for specifying and refining this knowledge about sets of source (training) and target (prediction) data. A challenging open problem is address

Pascal Dreher, Alexander Neuhaus, David Janoschka, Alexandra Roedl

Topology is the study of geometrical properties and spatial relations unaffected by continuous changes, and has become an important tool for understanding complex physical systems. Although recent optical experiments have inferred the existence of vector fields with the topologies of merons, the inability to extract the full three dimensional vectors misses

Igor Volovich

In this note, we show that the Schrodinger equation in quantum mechanics is mathematically equivalent to the Euler-Bernoulli equation for vibrating beams and plates in elasticity theory, with dependent initial data. Remarks are made on potential applications of this equivalence for symplectic and quantum computing, the two-slit experiment using vibrating bea

Xiujin Zhu, Chee-Onn Chow, Joon Huang Chuah

Image shadow removal is a typical low-level vision task. Shadows cause local brightness shifts, which reduce the performance of downstream vision tasks. Currently, Transformer-based shadow removal methods suffer from quadratic computational complexity due to the self-attention mechanism. To improve efficiency, many approaches use local attention, but this li

Yuming Zhao

We give an operator-algebraic formulation of robust self-testing in terms of states on C*-algebras. We show that a quantum correlation p is a robust self-test only if among all (abstract) states, there is a unique one achieving p. We show that the "if" direction of this statement also holds, provided that p is optimal/perfect for a nonlocal game that has a r

J. P. Carvajal, F. E. Bauer, I. Reyes-Jainaga, F. Förster

A significant challenge in the study of transient astrophysical phenomena is the identification of bogus events, among which human-made satellites and debris in Earth orbit remain major contaminants. Existing pipelines effectively identify satellite trails but can miss more complex signatures, such as collections of satellite glints. In the Rubin Observatory

Noah Porcelli, Ivan Smith

In \cite{PS}, for a stably framed Liouville manifold $X$ we defined a Donaldson-Fukaya category $\mathcal{F}(X;\mathbb{S})$ over the sphere spectrum, and developed an obstruction theory for lifting quasi-isomorphisms from $\mathcal{F}(X;\mathbb{Z})$ to $\mathcal{F}(X;\mathbb{S})$. Here, we define a spectral Donaldson-Fukaya category for any `graded tangentia

T. Souverin, J. Neveu, M. Betoule, S. Bongard

The number of type Ia supernova (SNe Ia) observations will grow significantly within the next decade, mainly thanks to the Legacy Survey of Space and Time (LSST) undertaken by the Vera Rubin Observatory in Chile. With this improvement, statistical uncertainties will decrease, and flux calibration will become the main uncertainty for the characterization of d

Zerui Wang, Yan Liu, Jun Huang

This article presents the design of an open-API-based explainable AI (XAI) service to provide feature contribution explanations for cloud AI services. Cloud AI services are widely used to develop domain-specific applications with precise learning metrics. However, the underlying cloud AI services remain opaque on how the model produces the prediction. We arg

Simon Prunet, Claude Aime, André Ferrari, Céline Theys

The design of starshades, i.e. external occulters for stellar coronography, relies on the fast and precise computation of their associated diffraction patterns of incoming plane waves in the telescope aperture plane. We present here a method based on a polygonal approximation of the occulter's shape, that allows fast computation of their diffraction patterns

Ryosuke Takata, Atsushi Masumori, Takashi Ikegami

We study the emergence of agency from scratch by using Large Language Model (LLM)-based agents. In previous studies of LLM-based agents, each agent's characteristics, including personality and memory, have traditionally been predefined. We focused on how individuality, such as behavior, personality, and memory, can be differentiated from an undifferentiated

Patrick Schillings, Johannes Erdmann

Newtonian noise in gravitational wave detectors originates from density fluctuations in the adjacency of the interferometer mirrors. At the Einstein Telescope, this noise source is expected to be dominant for low frequencies. Its impact is proposed to be reduced with the help of an array of seismometers that will be placed around the interferometer endpoints

Ying Zhou, Xinyao Wang, Yulei Niu, Yaojie Shen

Recent advancements in large language models (LLMs) have significantly enhanced their knowledge and generative capabilities, leading to a surge of interest in leveraging LLMs for high-quality data synthesis. However, synthetic data generation via prompting LLMs remains challenging due to LLMs' limited understanding of target data distributions and the comple

Ting-Ou Liang, MinXuan Xu, Wenwei Yu, Shao Ying Huang

Permanent magnet array (PMA) is a popular option to provide the main magnetic field in a dedicated portable magnetic resonance imaging (MRI) system because it does not need power or a cooling system and has a much stronger field strength compared to a resistive magnet. Aside from the popular Halbach array that has a transversal field direction, the Inward-Ou

Hauke Maathuis, Saullo G. P. Castro, Roeland De Breuker

The design and optimisation of aircraft wings are critical tasks in aerospace engineering, requiring a balance between structural integrity, aerostructural performance, and manufacturability. This multifaceted challenge involves the interplay of various disciplines, each with distinct parameters and constraints. Traditional design approaches often fall short

E. Yushkov, I. N. Pashchenko, D. D. Sokoloff, G. Chumarin

Radio interferometric observations of Active Galactic Nuclei (AGN) jets reveal the significant linear polarization of their synchrotron radiation that changes with frequency due to the Faraday rotation. It is generally assumed that such depolarization could be a powerful tool for studying the magnetized plasma in the vicinity of the jet. However, depolarizat

Angus Mingare, Anastasia Moroz, Marcell D Kovacs, Andrew G Green

Implementing many important sub-circuits on near-term quantum devices remains a challenge due to the high levels of noise and the prohibitive depth on standard nearest-neighbour topologies. Overcoming these barriers will likely require quantum error mitigation (QEM) strategies. This work introduces the notion of efficient, high-fidelity verifier circuit arch

Duong Dinh

On a Riemann surface of genus $> 1$, we discuss how to construct opers with apparent singularities from $SL_2(\mathbb{C})$ $\lambda$-connections $(E, \nabla_\lambda)$ and sub-line bundles $L$ of $E$. This construction defines a rational map from a space which captures important data of triples $(E, L, \nabla_\lambda)$ to a space which parametrises the positi

Gabriela Panta Zorzo, João Vitor Dall Agnol Fernandes, Soraia Raupp Musse

Games represent a significant part of modern culture, which demonstrates the importance of ensuring that everyone can participate and play in order to feel included in our society. However, most digital games end up being inaccessible to people with disabilities. Part of the problem when thinking about inclusive game design is that there is no single solutio

Donghoon Jang

For a circle action on a compact almost complex manifold with a fixed point, the lower bound on the number of fixed points is known in dimension up to 12 except 10. In this paper, we show that if the circle group acts on a 10-dimensional compact almost complex manifold with a fixed point, then there are at least 6 fixed points. This minimum is attained by $\