October 2023 arXiv papers — page 126

Matthew Kenworthy, Simon Lock, Grant Kennedy, Richelle van Capelleveen

Planets grow in rotating disks of dust and gas around forming stars, some of which can subsequently collide in giant impacts after the gas component is removed from the disk. Monitoring programs with the warm Spitzer mission have recorded significant and rapid changes in mid-infrared output for several stars, interpreted as variations in the surface area of

Alidad Amirfazli, Miguel D. Bustamante, Yating Hu, Lennon Ó Náraigh

We consider the classical problem of droplet impact and droplet spread on a smooth surface in the case of an ideal inviscid fluid. We revisit the rim-lamella model of Roisman et al. [\textit{Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences}, 458(2022), pp.1411-1430.]. This model comprises a system of ordin

Peifeng Gao, Qianqian Xu, Yibo Yang, Peisong Wen

Neural Collapse (NC) is a well-known phenomenon of deep neural networks in the terminal phase of training (TPT). It is characterized by the collapse of features and classifier into a symmetrical structure, known as simplex equiangular tight frame (ETF). While there have been extensive studies on optimization characteristics showing the global optimality of n

Akihiro Higashitani

Let $Q$ be an affine monoid, $\Bbbk[Q]$ the associated monoid $\Bbbk$-algebra, and $\Bbbk[\overline{Q}]$ its normalization, where we let $\Bbbk$ be a field. In this paper, in the case where $\Bbbk[Q]$ is homogeneous (i.e., standard graded), a difference of the Hilbert series of $\Bbbk[Q]$ and $\Bbbk[\overline{Q}]$ is discussed. More precisely, we prove that

Gauthier Wissocq, Rémi Abgrall

We propose a numerical approach, of the BGK kinetic type, that is able to approximate with a given, but arbitrary, order of accuracy the solution of linear and non-linear convection-diffusion type problems: scalar advection-diffusion, non-linear scalar problems of this type and the compressible Navier-Stokes equations. Our kinetic model can use \emph{finite}

George Brian dos Reis, Rafael A. B. Suarez, Marcos R. R. Gesualdi

In this work, the experimental optical generation of the fractional Hankel-Bessel vortex beams were investigated through the holographic technique by means of computer generated holograms (CGHs) and reproduced in a spatial light modulator (SLMs). The intensity and phase profiles were simulated and the experimental results are presented in this work, as well

Yasin Qazi, Anvar Shukurov, Devika Tharakkal, Frederick A. Gent

Stratified disks with strong horizontal magnetic fields are susceptible to magnetic buoyancy instability (MBI). Modifying the magnetic field and gas distributions, this can play an important role in galactic evolution. The MBI and the Parker instability, in which cosmic rays exacerbate MBI, are often studied using an imposed magnetic field. However, in galax

Gianluca Biggi, Andrea Mina, Federico Tamagni

Using a firm-level dataset from the Spanish Technological Innovation Panel (2003-2016), this study explores the characteristics of environmentally innovative firms and quantifies the effects of pursuing different types of environmental innovation strategies (resource-saving, pollution-reducing, and regulation-driven innovations) on sales, employment, and pro

Ikrom Akramov, Sebastian Götschel, Michael Minion, Daniel Ruprecht

Spectral deferred corrections (SDC) are a class of iterative methods for the numerical solution of ordinary differential equations. SDC can be interpreted as a Picard iteration to solve a fully implicit collocation problem, preconditioned with a low-order method. It has been widely studied for first-order problems, using explicit, implicit or implicit-explic

L. Abou-Hamdan, A. Schmitt, R. Bretel, S. Rossetti

Under high electrical current, some materials can emit electromagnetic radiation beyond incandescence. This phenomenon, referred to as electroluminescence, leads to the efficient emission of visible photons and is the basis of domestic lighting devices (e.g., light-emitting diodes). In principle, electroluminescence can lead to mid-infrared (mid-IR) emission

Chengyang He, Tianze Yang, Tanishq Duhan, Yutong Wang

The multi-agent pathfinding (MAPF) problem seeks collision-free paths for a team of agents from their current positions to their pre-set goals in a known environment, and is an essential problem found at the core of many logistics, transportation, and general robotics applications. Existing learning-based MAPF approaches typically only let each agent make de

Sebastian Zezulka, Konstantin Genin

Deploying an algorithmically informed policy is a significant intervention in the structure of society. As is increasingly acknowledged, predictive algorithms have performative effects: using them can shift the distribution of social outcomes away from the one on which the algorithms were trained. Algorithmic fairness research is usually motivated by the wor

Yazhe Niu, Yuan Pu, Zhenjie Yang, Xueyan Li

Building agents based on tree-search planning capabilities with learned models has achieved remarkable success in classic decision-making problems, such as Go and Atari. However, it has been deemed challenging or even infeasible to extend Monte Carlo Tree Search (MCTS) based algorithms to diverse real-world applications, especially when these environments in

Zhang Hangyue

In a $c$-mixed system, we study $c$-$cu$-states, which capture the structural characteristics of physical measures (in similar systems), having maximum $u$-entropy. It is shown that the maximum number of $c$-$cu$-states with pairwise distinct supports is finite, and Proposition~\ref{pro.con} is provided to construct such systems. Using a modified version of

Didrik Fosse, Steffen Oppermann, Torkil Stai

Happel and Seidel gave a classification of piecewise hereditary Nakayama algebras, where the relations are given by some power of the radical. Here we explore what happens for general relations. We develop techniques for showing that a given algebra is not piecewise hereditary, illustrating them on numerous mid-sized examples. Then we observe cases where the

Shesha Gopal Marehalli Srinivas, Francesco Avanzini, Massimiliano Esposito

The thermodynamic and dynamical conditions necessary to observe indefinite growth in homogeneous open chemical reaction networks (CRNs) satisfying mass action kinetics were presented in Srinivas et al. (2023): Unimolecular CRNs can only accumulate equilibrium concentrations of species while multimolecular CRNs are needed to produce indefinite growth with non

Pranab J Deka, Alexander Moriggl, Lukas Einkemmer

We present an open-source CUDA-based package that consists of a compilation of exponential integrators where the action of the matrix exponential or the $\varphi_l$ functions on a vector is approximated using the method of polynomial interpolation at Leja points. Using a couple of test examples on an NVIDIA A100 GPU, we show that one can achieve significant

Shai M. Chester, Ning Su

The paradigmatic example of deconfined quantum criticality is the Neel-VBS phase transition. The continuum description of this transition is the $N=2$ case of the $CP^{N-1}$ model, which is a field theory of $N$ complex scalars in 3d coupled to an Abelian gauge field with $SU(N)\times U(1)$ global symmetry. Lattice studies and duality arguments suggest the g

Paola F. Antonietti, Francesca Bonizzoni, Mattia Corti, Agnese Dall'Olio

Mathematical models of protein-protein dynamics, such as the heterodimer model, play a crucial role in understanding many physical phenomena. This model is a system of two semilinear parabolic partial differential equations describing the evolution and mutual interaction of biological species. An example is the neurodegenerative disease progression in some s

Stefano Mocatti, Giovanni Marini, Matteo Calandra

Femtosecond pulses have been used to reveal hidden broken symmetry states and induce transitions to metastable states. However, these states are mostly transient and disappear after laser removal. Photoinduced phase transitions towards crystalline metastable states with a change of topological order are rare and difficult to predict and realize experimentall

Masanori Hino, Arata Maki, Kouhei Matsuura

In this paper, we study discrete approximation of reflected Brownian motions on domains in Euclidean space. Our approximation is given by a sequence of Markov chains on partitions of the domain, where we allow uneven or random partitions. We provide sufficient conditions for the weak convergence of the Markov chains.

Eve Le Guillou, Michael Will, Pierre Guillou, Jonas Lukasczyk

This system paper documents the technical foundations for the extension of the Topology ToolKit (TTK) to distributed-memory parallelism with the Message Passing Interface (MPI). While several recent papers introduced topology-based approaches for distributed-memory environments, these were reporting experiments obtained with tailored, mono-algorithm implemen

Charles C. Onu, Samantha Latremouille, Arsenii Gorin, Junhao Wang

Since the 1960s, neonatal clinicians have known that newborns suffering from certain neurological conditions exhibit altered crying patterns such as the high-pitched cry in birth asphyxia. Despite an annual burden of over 1.5 million infant deaths and disabilities, early detection of neonatal brain injuries due to asphyxia remains a challenge, particularly i

Grigory Bartosh, Dmitry Vetrov, Christian A. Naesseth

Diffusion models have shown remarkable performance on many generative tasks. Despite recent success, most diffusion models are restricted in that they only allow linear transformation of the data distribution. In contrast, broader family of transformations can potentially help train generative distributions more efficiently, simplifying the reverse process a

Roman Y. Shopa, Kamil Dulski

We develop a positronium imaging method for the Jagiellonian PET (J-PET) scanners based on the time-of-flight maximum likelihood expectation maximisation (TOF MLEM). The system matrix elements are calculated on-the-fly for the coincidences comprising two annihilation and one de-excitation photons that originate from the ortho-positronium (o-Ps) decay. Using

Shesha Gopal Marehalli Srinivas, Francesco Avanzini, Massimiliano Esposito

We identify the thermodynamic conditions necessary to observe indefinite growth in homogeneous open chemical reaction networks (CRNs) satisfying mass action kinetics. We also characterize the thermodynamic efficiency of growth by considering the fraction of the chemical work supplied from the surroundings that is converted into CRN free energy. We find that

Zhirui Pan, Guangzhong Wang, Zhaoning Li, Lifeng Chen

Financial crime detection using graph learning improves financial safety and efficiency. However, criminals may commit financial crimes across different institutions to avoid detection, which increases the difficulty of detection for financial institutions which use local data for graph learning. As most financial institutions are subject to strict regulatio

Jakini A. Kauba, Thomas Weighill

We apply persistent homology, the main method in topological data analysis, to the study of demographic data. Persistence diagrams efficiently summarize information about clusters or peaks in a region's demographic data. To illustrate how persistence diagrams can be used for exploratory analysis, we undertake a study of the 100 largest U.S.~cities and their

Theo Diamandis, Zachary Frangella, Shipu Zhao, Bartolomeo Stellato

We introduce the GEneralized Newton Inexact Operator Splitting solver (GeNIOS) for large-scale convex optimization. GeNIOS speeds up ADMM by approximately solving approximate subproblems: it uses a second-order approximation to the most challenging ADMM subproblem and solves it inexactly with a fast randomized solver. Despite these approximations, GeNIOS ret

Yishun Dou, Zhong Zheng, Qiaoqiao Jin, Bingbing Ni

We propose a novel compact and efficient neural BRDF offering highly versatile material representation, yet with very-light memory and neural computation consumption towards achieving real-time rendering. The results in Figure 1, rendered at full HD resolution on a current desktop machine, show that our system achieves real-time rendering with a wide variety

Valentina Zangirolami, Matteo Borrotti

Incomplete knowledge of the environment leads an agent to make decisions under uncertainty. One of the major dilemmas in Reinforcement Learning (RL) where an autonomous agent has to balance two contrasting needs in making its decisions is: exploiting the current knowledge of the environment to maximize the cumulative reward as well as exploring actions that

Kenichi L. Ishikawa, Kevin C. Prince, Kiyoshi Ueda

We report a theoretical investigation of photoionization by a pair of coherent, ultrashort fundamental and second-harmonic extreme-ultraviolet pulses, where the photon energies are selected to yield the same photoelectron energy for ionization of two different sub-shells. This choice implies that the fundamental energy is equal to the difference in energy of

Godofredo Iommi, Mario Ponce

It has been more than twenty years since Moshe Newman, based on work by Neil Calkin and Herbert Wilf, introduced an explicit bijection between the rational and natural numbers. Interestingly, this bijection is dynamic in nature. Indeed, Newman's map has the property that the orbit of zero provides the required bijection. Claudio Bonanno and Stefano Isola, us

Xiao Xu, Lei Zhang, Bailong Liu, Zhizhen Liang

As a core technology of Intelligent Transportation System (ITS), traffic flow prediction has a wide range of applications. Traffic flow data are spatial-temporal, which are not only correlated to spatial locations in road networks, but also vary with temporal time indices. Existing methods have solved the challenges in traffic flow prediction partly, focusin

Yu-Fang Chen, David Chocholatý, Vojtěch Havlena, Lukáš Holík

Z3-Noodler is a fork of Z3 that replaces its string theory solver with a custom solver implementing the recently introduced stabilization-based algorithm for solving word equations with regular constraints. An extensive experimental evaluation shows that Z3-Noodler is a fully-fledged solver that can compete with state-of-the-art solvers, surpassing them by f

Yuhao Dong, Zhuoyang Zhang, Yunze Liu, Li Yi

Understanding 4D point cloud sequences online is of significant practical value in various scenarios such as VR/AR, robotics, and autonomous driving. The key goal is to continuously analyze the geometry and dynamics of a 3D scene as unstructured and redundant point cloud sequences arrive. And the main challenge is to effectively model the long-term history w

Fuchuan Lei, Yi Sun, Óskar B. Helgason, Zhichao Ye

Narrow-linewidth yet tunable laser oscillators are one of the most important tools for precision metrology, optical atomic clocks, sensing and quantum computing. Commonly used tunable coherent oscillators are based on stimulated emission or stimulated Brillouin scattering; as a result, the operating wavelength band is limited by the gain media. Based on nonl

Francesca Guffanti

We study the meaning of "adding a constant to a language" for any doctrine, and "adding an axiom to a theory" for a primary doctrine, by showing how these are actually two instances of the same construction. We prove their universal properties, and how these constructions are compatible with additional structure on the doctrine. Existence of Kleisli object f

Christopher Oliver, Denis Nabari, Hannah M. Price, Leonardo Ricci

We propose the use of networks of standard, commercially-available coaxial cables as a platform to realize photonic lattice models. As a specific example, we consider a brick wall lattice formed from coaxial cables and T-shaped connectors. We calculate the dispersion of photonic Bloch waves in the lattice: we find a repeated family of three bands, which incl

Snehanshu Maiti, Harishankar Ramachandran

A steady-state distribution is obtained that approximately yields the observed plasma density profile of the inner Van Allen radiation belt. The model assumes a collisionless, magnetized plasma with zero electric field present. The inner Van Allen belt consists of a plasma comprising high-energy protons and relativistic electrons. The particle trajectories a

Benjamin Winkler, Mohammad Abu Hamed, Alexander A. Nepomnyashchy, Falko Ziebert

We propose and study a simple, physical model for phagocytosis, i.e. the active, actin-mediated uptake of micron-sized particles by biological cells. The cell is described by the phase field method and the driving mechanisms of uptake are actin ratcheting, modeled by a dynamic vector field, as well as cell-particle adhesion due to receptor-ligand binding. We

Dominik Hintersdorf, Lukas Struppek, Daniel Neider, Kristian Kersting

The proliferation of large AI models trained on uncurated, often sensitive web-scraped data has raised significant privacy concerns. One of the concerns is that adversaries can extract information about the training data using privacy attacks. Unfortunately, the task of removing specific information from the models without sacrificing performance is not stra

Xueguang Ma, Liang Wang, Nan Yang, Furu Wei

The effectiveness of multi-stage text retrieval has been solidly demonstrated since before the era of pre-trained language models. However, most existing studies utilize models that predate recent advances in large language models (LLMs). This study seeks to explore potential improvements that state-of-the-art LLMs can bring. We conduct a comprehensive study

David Muñoz-Lahoz, Pedro Tradacete

We introduce inner band projections in the space of regular operators on a Dedekind complete Banach lattice and study some structural properties of this class. In particular, we provide a new characterization of atomic order continuous Banach lattices as those for which all band projections in the corresponding space of regular operators are inner. We also c

Andrea Alessandrini, Carola Ciaramelletti, Simone Paganelli

We study the Quantum Zeno Effect (QZE) on a single qubit on IBM Quantum Experience devices under the effect of multiple measurements. We consider two possible cases: the Rabi evolution and the free decay. SPAM error mitigations have also been applied. In both cases we observe the occurrence of the QZE as an increasing of the survival probability with the num

Magnus Malmström, Anton Kullberg, Isaac Skog, Daniel Axehill

This paper considers the problem of detecting and tracking objects in a sequence of images. The problem is formulated in a filtering framework, using the output of object-detection algorithms as measurements. An extension to the filtering formulation is proposed that incorporates class information from the previous frame to robustify the classification, even

Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson

This paper considers the problem of sequential fusion of predictions from neural networks (NN) and fusion of predictions from multiple NN. This fusion strategy increases the robustness, i.e., reduces the impact of one incorrect classification and detection of outliers the \nn has not seen during training. This paper uses Laplacian approximation of Bayesian N

Svenja M. Griesbach, Martin Hoefer, Max Klimm, Tim Koglin

We study a novel approach to information design in the standard traffic model of network congestion games. It captures the natural condition that the demand is unknown to the users of the network. A principal (e.g., a mobility service) commits to a signaling strategy, observes the realized demand and sends a (public) signal to agents (i.e., users of the netw

Johannes Rau, Arthur Renaudineau, Kris Shaw

This paper generalises the homeomorphism theorem behind Viro's combinatorial patchworking of hypersurfaces in toric varieties to arbitrary codimension using tropical geometry. We first define the patchwork of a polyhedral space equipped with a real phase structure. When the polyhedral subspace is tropically non-singular, we show that the patchwork is a topol

Mohamed Ashraf Abdelsalam, Samrudhdhi B. Rangrej, Isma Hadji, Nikita Dvornik

We study the problem of future step anticipation in procedural videos. Given a video of an ongoing procedural activity, we predict a plausible next procedure step described in rich natural language. While most previous work focus on the problem of data scarcity in procedural video datasets, another core challenge of future anticipation is how to account for

Mateen Ashraf, Anna Gaydamaka, Bo Tan, Dmitri Moltchanov

The inherent support of sixth-generation (6G) systems enabling integrated sensing and communications (ISAC) paradigm greatly enhances the application area of intelligent transportation systems (ITS). One of the mission-critical applications enabled by these systems is disaster management, where ISAC functionality may not only provide localization but also pr

Jonatan Stava

Consider the smooth sections of the tangent bundle of a reductive homogeneous space. This is a vector space over the field of real numbers. The canonical connection acts as a linear binary operator on this vector space, making it an algebra. If we include another binary operator defined as the negative of the torsion, the resulting algebraic structure is a p

Nandikanti Siva Sai Syam, Akshay Sunil, Subbarao Pichuka, Anirban Mandal

In this study, the statistical downscaling model (SDSM) is employed for downscaling the precipitation (PREC), maximum temperature (T max ) and minimum temperature (T min ) over Krishna River Basin (KRB). The Canadian Earth System Model, version 2 (CanESM2) General Circulation Model (GCM) outputs were considered as predictor variables. First, the SDSM is cali

Zhe Yang, Damai Dai, Peiyi Wang, Zhifang Sui

Large Language Models (LLMs) have recently gained the In-Context Learning (ICL) ability with the models scaling up, allowing them to quickly adapt to downstream tasks with only a few demonstration examples prepended in the input sequence. Nonetheless, the current practice of ICL treats all demonstration examples equally, which still warrants improvement, as

Sayat Ibrayev, Arman Ibrayeva, Ayaulym Rakhmatullina, Aizhan Ibrayeva

Typical leg exoskeletons employ open-loop kinematic chains with motors placed directly on movable joints; while this design offers flexibility, it leads to increased costs and heightened control complexity due to the high number of degrees of freedom. The use of heavy servo-motors to handle torque in active joints results in complex and bulky designs, as hig

Deepesh Khushwani, Priya Batra, V. R. Krithika, T. S. Mahesh

The quasiprobability distribution of the discrete Wigner function provides a complete description of a quantum state and is, therefore, a useful alternative to the usual density matrix description. Moreover, the experimental quantum state tomography in discrete Wigner phase space can also be implemented. We observe that for a certain class of states, such as

J. Ruiz-Zapatero, D. Alonso, C. García-García, A. Nicola

We present LimberJack.jl, a fully auto-differentiable code for cosmological analyses of 2 point auto- and cross-correlation measurements from galaxy clustering, CMB lensing and weak lensing data written in Julia. Using Julia's auto-differentiation ecosystem, LimberJack.jl can obtain gradients for its outputs up to an order of magnitude faster than traditiona

Jan Schering, Sander Keemink, Johannes Textor

Stochastic lattice models (sLMs) are computational tools for simulating spatiotemporal dynamics in physics, computational biology, chemistry, ecology, and other fields. Despite their widespread use, it is challenging to fit sLMs to data, as their likelihood function is commonly intractable and the models non-differentiable. The adjacent field of agent-based

Arpit Mittal, Harshil Jhaveri, Swapnil Mallick, Abhishek Ajmera

Few-shot object classification is the task of classifying objects in an image with limited number of examples as supervision. We propose a one-shot/few-shot classification model that can classify an object of any unseen class into a relatively general category in an hierarchically based classification. Our model uses a three-level hierarchical contrastive lo

Yuxin Mao, Jing Zhang, Mochu Xiang, Yiran Zhong

We propose an Explicit Conditional Multimodal Variational Auto-Encoder (ECMVAE) for audio-visual segmentation (AVS), aiming to segment sound sources in the video sequence. Existing AVS methods focus on implicit feature fusion strategies, where models are trained to fit the discrete samples in the dataset. With a limited and less diverse dataset, the resultin

N. Brun, G. Lambert, L. Bocher

Spatially resolved Electron Energy-Loss Spectroscopy (EELS) conducted in a Scanning Transmission Electron Microscope (STEM) enables the acquisition of hyperspectral images (HSIs). Spectral unmixing (SU) is the process of decomposing each spectrum of an HSI into a combination of representative spectra (endmembers) corresponding to compounds present in the sam

A. Cogo, S. Lynch, O. Vičánek Martínez

We address the classification of ancient solutions to fully nonlinear curvature flows for hypersurfaces. Under natural conditions on the speed of motion we classify ancient solutions which are convex, noncollapsing, uniformly two-convex and noncompact. There are exactly two possibilities -- every such solution is either a self-similarly shrinking cylinder, o

Da Rong Cheng

We extend Struwe's result (Acta Math., 1988) on the existence of free boundary constant mean curvature disks to almost every prescribed boundary contact angle in $(0, \pi)$. Specifically, let $\Sigma$ be a surface in $\mathbb{R}^3$ diffeomorphic to the sphere, and let $\Sigma'$ be a convex surface enclosing $\Sigma$. Given $\tau \in (-1, 1)$ and a constant $

Guilai Liu, Chengming Bai

There are two kinds of splittings of operations, namely, the classical splitting which is interpreted operadically as taking successors and another splitting which we call the second splitting giving the anti-structures of the successors' algebras. The algebraic structures corresponding to them respectively are characterized in terms of representations. Due

Shuhui Wu, Yongliang Shen, Zeqi Tan, Wenqi Ren

Distantly supervised named entity recognition (DS-NER) aims to locate entity mentions and classify their types with only knowledge bases or gazetteers and unlabeled corpus. However, distant annotations are noisy and degrade the performance of NER models. In this paper, we propose a noise-robust prototype network named MProto for the DS-NER task. Different fr

Jun Chen, Xuemei Deng

We study the equations in divergence form with piecewise $C^{\ga}$ coefficients. The domains contain corners and the discontinuity surfaces are attached to edges of the corners. We obtain piecewise $C^{1,\ga}$ estimates across the discontinuity surfaces and provide an example to illustrate the issue about the regularity at the corners.

Johannes G. Borgqvist, Fredrik Ohlsson, Xingjian Zhou, Ruth E. Baker

Certain solutions of autonomous PDEs without any boundary conditions describing the spatiotemporal evolution of a dependent variable in an unbounded spatial domain can be characterised as a travelling wave moving with constant speed. In the simplest case, such PDEs can be reduced to a single autonomous second order ODE with one dependent variable. For certai

Reneira Seeamber, Cosmin Badea

As Artificial Intelligence (AI) becomes pervasive in most fields, from healthcare to autonomous driving, it is essential that we find successful ways of building morality into our machines, especially for decision-making. However, the question of what it means to be moral is still debated, particularly in the context of AI. In this paper, we highlight the di

Paul Holst, Jens D. M. Rademacher, Jichen Yang

Numerical simulations of large scale geophysical flows typically require unphysically strong dissipation for numerical stability. Towards energetic balance various schemes have been devised to re-inject this energy, in particular by horizontal kinetic energy backscatter. In a set of papers, some of the authors have studied this scheme through its continuum f

Jürgen Hausen, Katharina Király

A full intrinsic quadric is a normal complete variety with a finitely generated Cox ring defined by a single quadratic relation of full rank. We describe all surfaces of this type explicitly via local Gorenstein indices. As applications, we present upper and lower bounds in terms of the Gorenstein index for the degree, the log canonicity and the Picard index

Ruinan Ma, Canjie Zhu, Mingfeng Lu, Yunjie Li

Electronic countermeasures involving radar signals are an important aspect of modern warfare. Traditional electronic countermeasures techniques typically add large-scale interference signals to ensure interference effects, which can lead to attacks being too obvious. In recent years, AI-based attack methods have emerged that can effectively solve this proble

Dong Yang, Xu Wang, Remzi Celebi

Knowledge base construction entails acquiring structured information to create a knowledge base of factual and relational data, facilitating question answering, information retrieval, and semantic understanding. The challenge called "Knowledge Base Construction from Pretrained Language Models" at International Semantic Web Conference 2023 defines tasks focus

Wafa Ahmedi, Akram Ben Aissa

In this paper, we embark on a captivating exploration of the stabilization of locally transmitted problems within the realm of two interconnected wave systems. To begin, we wield the formidable Arendt-Batty criteria\cite{AW} to affirm the resolute stability of our system. Then, with an artful fusion of a frequency domain approach and the multiplier method, w

Mohammad Soleymani, Ignacio Santamaria, Aydin Sezgin, Eduard Jorswieck

Reconfigurable intelligent surface (RIS) is a promising technology to enhance the spectral efficiency of wireless communication systems. By optimizing the RIS elements, the performance of the overall system can be improved. Yet, in contrast to single-carrier systems, in multi-carrier systems, it is not possible to independently optimize RIS elements at each

D. K. Weiss, Shruti Puri, S. M. Girvin

Quantum random access memory (QRAM) is a common architecture resource for algorithms with many proposed applications, including quantum chemistry, windowed quantum arithmetic, unstructured search, machine learning, and quantum cryptography. Here we propose two bucket-brigade QRAM architectures based on high-coherence superconducting resonators, which differ

Olivier Laurent, Emanuel Aldea, Gianni Franchi

The distribution of the weights of modern deep neural networks (DNNs) - crucial for uncertainty quantification and robustness - is an eminently complex object due to its extremely high dimensionality. This paper proposes one of the first large-scale explorations of the posterior distribution of deep Bayesian Neural Networks (BNNs), expanding its study to rea

Jan Erik H. Weber, Yiyi Whitchelo, Jon A. Pirolt, Kai H. Christensen

An experimental study of long interfacial gravity waves was conducted in a closed wave tank containing two layers of viscous immiscible fluids. The study focuses on the development in time of the mean particle drift that occurs close to the interface where the two fluids meet. From a theoretical analysis by Weber & Christensen (Eur. J. Mech.-B/Fluids, vol. 7

Rui Yao, Kenan Zhang

Mobility-as-a-service (MaaS) provides seamless door-to-door trips by integrating different transport modes. Although many MaaS platforms have emerged in recent years, most of them remain at a limited integration level. This study investigates the assignment and pricing problem for a MaaS platform as an intermediary in a multi-modal transportation network, wh

Fredi Šarić, Stjepan Begušić, Andro Merćep, Zvonko Kostanjčar

Statistical arbitrage methods identify mispricings in securities with the goal of building portfolios which are weakly correlated with the market. In pairs trading, an arbitrage opportunity is identified by observing relative price movements between a pair of two securities. By simultaneously observing multiple pairs, one can exploit different arbitrage oppo

Milana Golich, D. B. McReynolds

We establish an analog of a theorem of Stallings which asserts the homomorphisms between the universal nilpotent quotients induced by a homomorphism $G \to H$ of groups are isomorphisms provided a pair of homological conditions are satisfied. Our analogy does not have a homomorphism between $G$ and $H$ but instead $G,H \leq G_0$ that satisfies a similar homo

Ruyi Tao, Ningning Tao, Yi-zhuang You, Jiang Zhang

Multiscale modeling of complex systems is crucial for understanding their intricacies. Data-driven multiscale modeling has emerged as a promising approach to tackle challenges associated with complex systems. On the other hand, self-similarity is prevalent in complex systems, hinting that large-scale complex systems can be modeled at a reduced cost. In this

Alessia Ciccotelli, Robert B. Appleby, Francesco Cerutti, Kevin Buffet

The Upgrade II of the LHCb experiment is proposed to be installed during the CERN Long Shutdown 4, aiming to operate LHCb at 1.5x$10^{34}cm^{-2}s^{-1}$ that is 75 times its design luminosity and reaching an integrated luminosity of about $400 fb^{-1}$ by the end of the High Luminosity LHC era. This increase of the data sample at LHCb is an unprecedented oppo

Monnie Parida, Manjira Sinha, Anupam Basu, Pabitra Mitra

This study aims to conduct an extensive detailed analysis of the Odia Braille reading comprehension among students with visual disability. Specifically, the study explores their reading speed and hand or finger movements. The study also aims to investigate any comprehension difficulties and reading errors they may encounter. Six students from the 9th and 10t

S. R. Mane

Kostadinova and Minkova published an expression for the probability mass function (pmf) of the Poisson distribution of order $k$, as a combinatorial sum ($\mathit{Pliska~Stud.~Math.~Bulgar.}\ {\bf 22},\ 117-128\ (2013)$). Inspired by their elegant solution, this note presents an alternative combinatorial sum for the pmf of the Poisson distribution of order $

Rui Yang, Jiahao Zhu, Jianping Man, Li Fang

The design and development of text-based knowledge graph completion (KGC) methods leveraging textual entity descriptions are at the forefront of research. These methods involve advanced optimization techniques such as soft prompts and contrastive learning to enhance KGC models. The effectiveness of text-based methods largely hinges on the quality and richnes

Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Hena Ghonia

Over the past years, foundation models have caused a paradigm shift in machine learning due to their unprecedented capabilities for zero-shot and few-shot generalization. However, despite the success of foundation models in modalities such as natural language processing and computer vision, the development of foundation models for time series forecasting has

Kohei Saijo, Wangyou Zhang, Zhong-Qiu Wang, Shinji Watanabe

We propose a multi-task universal speech enhancement (MUSE) model that can perform five speech enhancement (SE) tasks: dereverberation, denoising, speech separation (SS), target speaker extraction (TSE), and speaker counting. This is achieved by integrating two modules into an SE model: 1) an internal separation module that does both speaker counting and sep

Qing Ma, Jiancheng Pan, Cong Bai

Image-text retrieval has developed rapidly in recent years. However, it is still a challenge in remote sensing due to visual-semantic imbalance, which leads to incorrect matching of non-semantic visual and textual features. To solve this problem, we propose a novel Direction-Oriented Visual-semantic Embedding Model (DOVE) to mine the relationship between vis

Puzhuo Liu, Chengnian Sun, Yaowen Zheng, Xuan Feng

This paper proposes LATTE, the first static binary taint analysis that is powered by a large language model (LLM). LATTE is superior to the state of the art (e.g., Emtaint, Arbiter, Karonte) in three aspects. First, LATTE is fully automated while prior static binary taint analyzers need rely on human expertise to manually customize taint propagation rules an

Arun Govind Neelan

Von Neumann stability analysis, a well-known Fourier-based method, is a widely used technique for assessing stability in numerical computations. However, as noted in "Numerical Solution of Partial Differential Equations: Finite Difference Methods" by Smith (1985, pp. 67-68), this approach faces limitations when applied to multi-level methods employing scheme

A. Aberfelds, J. Šteinbergs, I. Shmeld, R. A. Burns

We present the results of a 5-year monitoring program of 42 sources targeted at 6.7 GHz methanol masers, conducted from March 2017 to October 2022 using the Irbene 32 and 16 meter radio telescopes. Sources were observed with irregular intervals where time between two consecutive observation ranged from twenty four hours to thirty five days. We found that mor

Wen-Yuan Ai, Ankit Beniwal, Angelo Maggi, David J. E. Marsh

Scalar dark matter (DM), and axions in particular, have an irreducible abundance of particles produced by freeze-in due to portal interactions with the Standard Model plasma in the early Universe. In addition, vacuum misalignment and other mechanisms can lead to the presence of a cold, oscillating condensate. Therefore, generically, the evolution of the DM i

Leilei Yu, Yunghsiang S. Han, Jiasheng Yuan, Zhongpei Zhang

Binary array codes are widely used in storage systems to prevent data loss, such as the Redundant Array of Independent Disks~(RAID). Most designs for such codes, such as Blaum-Roth~(BR) codes and Independent-Parity~(IP) codes, are carried out on the polynomial ring F_2[x]/<\sum_{i=0}^{p-1}x^i >, where F_2 is a binary field, and p is a prime number. In this p

Basant Sharma, Aditya Sharma, K. Madhava Krishna, Arun Kumar Singh

Safe autonomous driving critically depends on how well the ego-vehicle can predict the trajectories of neighboring vehicles. To this end, several trajectory prediction algorithms have been presented in the existing literature. Many of these approaches output a multi-modal distribution of obstacle trajectories instead of a single deterministic prediction to a

Dekui Peng

For an infinite group $G$, the poset $\mathcal{L}_G$ of group topologies constitutes a complete lattice. Although $\mathcal{L}_G$ is modular when $G$ is abelian, this property fails to persist for nilpotent groups. Extending Arnautov's 2010 work on the semi-modularity of $\mathcal{L}_G$ for nilpotent groups, we present an alternative proof with enhanced stru

Yuzhao Zhang, Jingnan Zhang, Yifan Sun, Junhui Wang

Dynamic networks consist of a sequence of time-varying networks, and it is of great importance to detect the network change points. Most existing methods focus on detecting abrupt change points, necessitating the assumption that the underlying network probability matrix remains constant between adjacent change points. This paper introduces a new model that a

Boyu Pang, Ruizhi Liao, Yinyu Ye

In recent years, innovative roadside parking vacancy crowdsensing solutions have emerged as a cost-effective alternative to traditional methods, which can significantly reduce sensor installation and maintenance expenses. This crowdsensing scheme relies on vehicles equipped with sensors, such as buses and taxis, roaming around urban streets to detect on-stre

Zhibin Zhang, Stiven Forti, Wanqing Meng, Sergio Pezzini

Two-dimensional (2D) materials have received extensive research attentions over the past two decades due to their intriguing physical properties (such as the ultrahigh mobility and strong light-matter interaction at atomic thickness) and a broad range of potential applications (especially in the fields of electronics and optoelectronics). The growth of singl

Sajal Barman, Pramod Bhakuni, Shuvam Sarkar, Joydipto Bhattacharya

Stanene, a two-dimensional counterpart to graphene, has the potential to exhibit novel quantum phenomena when grown on a magnetic topological insulator (MTI). This work demonstrates the formation of up to bilayer stanene on 30\% Sb-doped MnBi$_{2}$Te$_4$ (MBST), a well known MTI, albeit with a buffer layer (BL) in between. Angle-resolved photoemission spectr

Genggeng Huang, Yating Niu

In this paper, we classify the solutions of the following critical Choquard equation \[ (-\Delta)^{\frac{n}{2}} u(x) = \int_{\mathbb{R}^n} \frac{e^{\frac{2n- \mu}{2}u(y)}}{|x-y|^{\mu}}dy e^{\frac{2n- \mu}{2}u(x)}, \ \text{in} \ \mathbb{R}^n, \] where $ 0<\mu < n$, $ n\ge 2$. Suppose $ u(x) = o(|x|^2) \ \text{at} \ \infty $ for $ n \geq 3$ and satisfies \[ \i