July 2023 arXiv papers — page 111

Fabian Brand, Alexander Kopte, Kristian Fischer, André Kaup

Adaptive block partitioning is responsible for large gains in current image and video compression systems. This method is able to compress large stationary image areas with only a few symbols, while maintaining a high level of quality in more detailed areas. Current state-of-the-art neural-network-based image compression systems however use only one scale to

Ruoyu Wang, Zixuan Guo, Yizhou Chen, Xinyi Wang

Autonomous navigation in unknown environments with obstacles remains challenging for micro aerial vehicles (MAVs) due to their limited onboard computing and sensing resources. Although various collision avoidance methods have been developed, it is still possible for drones to collide with unobserved obstacles due to unpredictable disturbances, sensor limitat

Philipp Foehn, Elia Kaufmann, Angel Romero, Robert Penicka

Autonomous, agile quadrotor flight raises fundamental challenges for robotics research in terms of perception, planning, learning, and control. A versatile and standardized platform is needed to accelerate research and let practitioners focus on the core problems. To this end, we present Agilicious, a co-designed hardware and software framework tailored to a

Ahmed Ghorbel, Wassim Hamidouche, Luce Morin

Over the last few years, neural image compression has gained wide attention from research and industry, yielding promising end-to-end deep neural codecs outperforming their conventional counterparts in rate-distortion performance. Despite significant advancement, current methods, including attention-based transform coding, still need to be improved in reduci

Ke Fan, Changan Wang, Yabiao Wang, Chengjie Wang

Glass-like objects are widespread in daily life but remain intractable to be segmented for most existing methods. The transparent property makes it difficult to be distinguished from background, while the tiny separation boundary further impedes the acquisition of their exact contour. In this paper, by revealing the key co-evolution demand of semantic and bo

Farkhod Eshmatov, Xabier García-Martínez, Zafar Normatov, Rustam Turdibaev

This paper presents a comprehensive description of the coordinate rings and Poisson brackets associated with the fourth Calogero-Moser space and invariant commuting pairs of matrices of size four. As an application, we compute their respective classes in the Grothendieck ring of the category of complex varieties and we offer some novel insights about the geo

Jin Guo, Ting Gao, Yufu Lan, Peng Zhang

Stochastic Gumbel graph networks are proposed to learn high-dimensional time series, where the observed dimensions are often spatially correlated. To that end, the observed randomness and spatial-correlations are captured by learning the drift and diffusion terms of the stochastic differential equation with a Gumble matrix embedding, respectively. In particu

Arun Kumar, Pascal Manuel, Sunil Nair

We report a comprehensive temperature-dependent investigation of the 1:2 ordered triple perovskite system Sr$_3$CaRu$_2$O$_9$. It crystallizes in the monoclinic structure with space group $P21/c$, consisting of corner-sharing CaO$_6$ and RuO$_6$ octahedra. Using DC magnetization and neutron diffraction measurements, we show that this system undergoes success

Edgar Arribas, Vicent Cholvi, Vincenzo Mancuso

In relay-enabled cellular networks, the intertwined nature of network agents calls for complex schemes to allocate wireless resources. Resources need to be distributed among mobile users while considering how relay resources are allocated, and constrained by the traffic rate achievable by base stations and over backhaul links. In this letter, we derive an ex

Meirav Amram, Cheng Gong, Jia-Li Mo

We investigate the topological structures of Galois covers of surfaces of minimal degree (i.e., degree n) in n+1 dimensional complex projective space. We prove that for n is greater than or equal to 5, the Galois covers of any surfaces of minimal degree are simply-connected surfaces of general type.

Jihao Andreas Lin, Javier Antorán, José Miguel Hernández-Lobato

The Laplace approximation provides a closed-form model selection objective for neural networks (NN). Online variants, which optimise NN parameters jointly with hyperparameters, like weight decay strength, have seen renewed interest in the Bayesian deep learning community. However, these methods violate Laplace's method's critical assumption that the approxim

Stefano Favaro, Boris Hanin, Domenico Marinucci, Ivan Nourdin

We study the distribution of a fully connected neural network with random Gaussian weights and biases in which the hidden layer widths are proportional to a large constant $n$. Under mild assumptions on the non-linearity, we obtain quantitative bounds on normal approximations valid at large but finite $n$ and any fixed network depth. Our theorems show both f

Ahmed Ghorbel, Wassim Hamidouche, Luce Morin

Motivated by the efficiency investigation of the Tranformer-based transform coding framework, namely SwinT-ChARM, we propose to enhance the latter, as first, with a more straightforward yet effective Tranformer-based channel-wise auto-regressive prior model, resulting in an absolute image compression transformer (ICT). Current methods that still rely on Conv

Siddique Latif, Muhammad Usama, Mohammad Ibrahim Malik, Björn W. Schuller

Despite recent advancements in speech emotion recognition (SER) models, state-of-the-art deep learning (DL) approaches face the challenge of the limited availability of annotated data. Large language models (LLMs) have revolutionised our understanding of natural language, introducing emergent properties that broaden comprehension in language, speech, and vis

Patrick Ebel, Kim Julian Gülle, Christoph Lingenfelder, Andreas Vogelsang

User Experience (UX) professionals need to be able to analyze large amounts of usage data on their own to make evidence-based design decisions. However, the design process for In-Vehicle Information Systems (IVIS) lacks data-driven support and effective tools for visualizing and analyzing user interaction data. Therefore, we propose ICEBOAT, an interactive v

Shalini Shrivastava, Vivek Saraswat, Gayatri Dash, Samyak Chakrabarty

Training deep neural networks (DNNs) is computationally intensive but arrays of non-volatile memories like Charge Trap Flash (CTF) can accelerate DNN operations using in-memory computing. Specifically, the Resistive Processing Unit (RPU) architecture uses the voltage-threshold program by stochastic encoded pulse trains and analog memory features to accelerat

Quentin Salomé, Yair Krongold, Anna Lia Longinotti, Manuela Bischetti

We present the first systematic study of the molecular gas and star formation efficiency in a sample of ten narrow-line Seyfert 1 galaxies selected to have X-ray Ultra Fast Outflows and, therefore, to potentially show AGN feedback effects. CO observations were obtained with the IRAM 30m telescope in six galaxies and from the literature for four galaxies. We

Francesca Prinari, Anna Chiara Zagati

On a convex bounded open set, we prove that Poincar\'e-Sobolev constants for functions vanishing at the boundary can be bounded from below in terms of the norm of the distance function in a suitable Lebesgue space. This generalizes a result shown, in the planar case, by E. Makai, for the torsional rigidity. In addition, we compare the sharp Makai constants o

E. A. Meier Valdés, B. M. Morris, B. -O. Demory, A. Brandeker

55 Cnc e is an ultra-short period super-Earth transiting a Sun-like star. Previous observations in the optical range detected a time-variable flux modulation that is phased with the planetary orbital period, whose amplitude is too large to be explained by reflected light and thermal emission alone. The goal of the study is to investigate the origin of the va

Arianna Rubino, Matteo Cartiglia, Melika Payvand, Giacomo Indiveri

Mixed-signal neuromorphic systems represent a promising solution for solving extreme-edge computing tasks without relying on external computing resources. Their spiking neural network circuits are optimized for processing sensory data on-line in continuous-time. However, their low precision and high variability can severely limit their performance. To addres

A. Corsi, Y. Kubota, J. Casal, M. Gomez-Ramos

The dineutron correlation is systematically studied in three different Borromean nuclei near the neutron dripline, 11Li, 14Be and 17B, via the (p, pn) knockout reaction measured at the RIBF facility in RIKEN. For the three nuclei, the correlation angle between the valence neutrons is found to be largest in the same range of intrinsic momenta, which can be as

Raphael Schumann, Wanrong Zhu, Weixi Feng, Tsu-Jui Fu

Incremental decision making in real-world environments is one of the most challenging tasks in embodied artificial intelligence. One particularly demanding scenario is Vision and Language Navigation~(VLN) which requires visual and natural language understanding as well as spatial and temporal reasoning capabilities. The embodied agent needs to ground its und

Daniel Russo

In this paper, the adoption patterns of Generative Artificial Intelligence (AI) tools within software engineering are investigated. Influencing factors at the individual, technological, and societal levels are analyzed using a mixed-methods approach for an extensive comprehension of AI adoption. An initial structured interview was conducted with 100 software

Oğul Esen, Ayten Gezici, Miroslav Grmela, Hasan Gümral

We propose a conformal generalization of the reversible Vlasov equation of kinetic plasma dynamics, called conformal kinetic theory. In order to arrive at this formalism, we start with the conformal Hamiltonian dynamics of particles and lift it to the dynamical formulation of the associated kinetic theory. The resulting theory represents a simple example of

Jessica Bariffi, Violetta Weger

This paper provides new and improved Singleton-like bounds for Lee metric codes over integer residue rings. We derive the bounds using various novel definitions of generalized Lee weights based on different notions of a support of a linear code. In this regard, we introduce three main different support types for codes in the Lee metric and analyze their util

Miles Timpe, Christian Reinhardt, Thomas Meier, Joachim Stadel

In the leading theory of lunar formation, known as the giant impact hypothesis, a collision between two planet-size objects resulted in a young Earth surrounded by a circumplanetary debris disk from which the Moon later accreted. The range of giant impacts that could conceivably explain the Earth-Moon system is limited by the set of known physical and geoche

Fidae El Morer, Stefan Wittek, Andreas Rausch

The degradation of sewer pipes poses significant economical, environmental and health concerns. The maintenance of such assets requires structured plans to perform inspections, which are more efficient when structural and environmental features are considered along with the results of previous inspection reports. The development of such plans requires degrad

Tomáš Masařík, Grzegorz Pierczyński, Piotr Skowron

We consider a voting model, where a number of candidates need to be selected subject to certain feasibility constraints. The model generalises committee elections (where there is a single constraint on the number of candidates that need to be selected), various elections with diversity constraints, the model of public decisions (where decisions needs to be t

Karthik Shenoy, Akshit Saradagi, Ramkrishna Pasumarthy, Vijaysekhar Chellaboina

Data-driven control has gained significant attention in recent years, particularly regarding feedback linearization of nonlinear systems. However, existing approaches face limitations when it comes to implementing them on hardware. The main challenges include the need for very small sampling times, which strain hardware capabilities, and the requirement of a

M. Sagebaum, M. Aehle, N. R. Gauger

In operator overloading algorithmic differentiation, it can be beneficial to create custom derivative functions for some parts of the code base. For manual implementations of the derivative functions, it can be quite cumbersome to derive, implement, test, and maintain these. The process can be automated with source transformation algorithmic differentiation

Siddhartha Mukherjee, Sugan D. Murugan, Ritwik Mukherjee, Samriddhi Sankar Ray

The Frisch-Parisi multifractal formalism remains the most compelling rationalisation for anomalous scaling in fully developed turbulence. We now show that this formalism can be adapted locally to reveal the spatial distribution of generalized dimensions and of how multifractal the energy dissipation field is. In particular, we show that most regions of the f

A. J. Han Vinck, Fatma Rouissi

The classical Binary Symmetric Channel has a fixed transition probability. We discuss the Binary Symmetric Channel with a variable transition probability that depends on a Poisson distribution. The error rate for this channel is determined and we also give bounds for the channel capacity. We give a motivation for the model based on the Class-A impulse noise

Tomonori Kouya

Efficient multiple precision linear numerical computation libraries such as MPLAPACK are critical in dealing with ill-conditioned problems. Specifically, there are optimization methods for matrix multiplication, such as the Strassen algorithm and the Ozaki scheme, which can be used to speed up computation. For complex matrix multiplication, the 3M method can

Tristan Bozec, Maxime Fairon, Anne Moreau

For any double Poisson algebra, we produce a double Poisson vertex algebra using the jet algebra construction. We show that this construction is compatible with the representation functor which associates to any double Poisson (vertex) algebra and any positive integer a Poisson (vertex) algebra. We also consider related constructions, such as Poisson reducti

Dimitrios Krommydas, Fabio Scardigli

In this paper we present phenomenological evidence for the validity of an exponential distance relation (also known as generalized Titius-Bode law) in the 32 planetary systems (31 extra solar, plus our Solar System) containing at least 5 planets each (known up to July 2023). We produce the semi-log fittings of the data, and we check them against the statisti

Johannes Berger, Azat M. Gainutdinov, Ingo Runkel

We consider the link and three-manifold invariants from arXiv:1912.02063, which are defined in terms of certain non-semisimple finite ribbon categories $\mathcal{C}$ together with a choice of tensor ideal and modified trace. If the ideal is all of $\mathcal{C}$, these invariants agree with those defined by Lyubashenko in the 90's. We show that in that case t

Swayamprabha Tiwari, Sameena Saba

The generalization of new mock theta functions of Andrews and Bringmann et al are given. Further we have given the expansion of these bilateral generalized new mock theta functions as 2 phi 1 series by Slaters transformation. After that we have given the continued fraction representation of these generalized mock theta functions.

Andrea Santonocito, Dario Zappala

A class of scalar models with non-polynomial interaction, which naturally admits an analytical resummation of the series of tadpole diagrams is studied in perturbation theory. In particular, we focus on a model containing only one renormalizable coupling that appear as a multiplicative coefficient of the squared field. A renormalization group analysis of the

V. Srinivasa, J. M. Taylor, J. R. Petta

We consider a pair of quantum dot-based spin qubits that interact via microwave photons in a superconducting cavity, and that are also parametrically driven by separate external electric fields. For this system, we formulate a model for spin qubit entanglement in the presence of mutually off-resonant qubit and cavity frequencies. We show that the sidebands g

Irum Rauf, Tamara Lopez, Thein Tun, Marian Petre

Secure software is a cornerstone to safe and resilient digital ecosystems. It offers strong foundation to protect users' sensitive data and guard against cyber-threats. The rapidly increasing landscape of digital economy has encouraged developers from different socio-technical and socio-economic backgrounds to join online freelance marketplaces. While, secur

Mete Ahishali, Mehmet Yamac, Serkan Kiranyaz, Moncef Gabbouj

In this work, we propose a novel approach called Operational Support Estimator Networks (OSENs) for the support estimation task. Support Estimation (SE) is defined as finding the locations of non-zero elements in sparse signals. By its very nature, the mapping between the measurement and sparse signal is a non-linear operation. Traditional support estimators

Arun Kumar Jaiswal, Robert Eder, Di Wang, Vanessa Wollersen

With its potential for drastically reduced operation power of information processing devices, electric field control of magnetism has generated huge research interest. Recently, novel perspectives offered by the inherently large spin-orbit coupling of 5d transition metals have emerged. Here, we demonstrate non-volatile electrical control of the proximity ind

Sagar S. Goyary, Kanak Saha, H. Shanjit Singh, Suchira Sarkar

A self-gravitating, differentially rotating galactic disc under vertical hydrostatic equilibrium is supported by the vertical pressure gradient force against the gravitational collapse. Such discs are known to support various bending modes e.g., warps, corrugation, or scalloping (typically, higher order bending modes) of which m=1 bending modes (warps) are t

D. I. Palade

A fast artificial neural network is developed for the prediction of cosmic ray transport in turbulent astrophysical magnetic fields. The setup is trained and tested on bespoke datasets that are constructed with the aid of test-particle numerical simulations of relativistic cosmic ray dynamics in synthetic stochastic fields. The neural network uses, as input,

Máté Józsa, Zsolt I. Lázár, Mária Ercsey-Ravasz

Axonal connections in the mouse brain show exponential scaling in the number of connections with their length, recently referred to as the exponential distance rule (EDR). This work investigates the theoretical and experimental background for extending this rule to the brain connectomes of other species, including drosophila, mouse, macaque and human. Our ma

Anna Munoz-Farre, Antonios Poulakakis-Daktylidis, Dilini Mahesha Kothalawala, Andrea Rodriguez-Martinez

We propose a novel approach for interpreting deep embeddings in the context of patient clustering. We evaluate our approach on a dataset of participants with type 2 diabetes from the UK Biobank, and demonstrate clinically meaningful insights into disease progression patterns.

Lu Shen, Guilin Liu, Zhicheng He, Nadia L. Zakamska

Quasar-driven outflows on galactic scales are a routinely invoked ingredient for galaxy formation models. We report the discovery of ionized gas nebulae as traced by [O III] $\lambda$5007 AA emission surrounding three luminous red quasars at $z \sim 0.4$ from Gemini Integral Field Unit (IFU) observations. All these nebulae feature unprecedented pairs of "sup

Hayato Imamura, Eiichi Matsuhashi, Yoshiyuki Oshima

We prove some theorems on decomposable continua. In particular, we prove; (i) the property of being a Wilder continuum is not a Whitney reversible property, (ii) inverse limits of D**-continua with surjective monotone upper semi-continuous bonding functions are D**, and (iii) there exists a D**-continuum which contains neither Wilder continua nor D*-continua

Georg Köstenberger, Thomas Stark

We analyze the stability of (strong) laws of large numbers in Hadamard spaces with respect to distributional perturbations. For the inductive means of a sequence of independent, but not necessarily identically distributed random variables, we provide a concentration inequality in quadratic mean, as well as a strong law of large numbers, generalizing a classi

Vibha Bharilya, Neetesh Kumar

Autonomous Vehicles (AVs) have emerged as a promising solution by replacing human drivers with advanced computer-aided decision-making systems. However, for AVs to effectively navigate the road, they must possess the capability to predict the future behavior of nearby traffic participants, similar to the predictive driving abilities of human drivers. Buildin

Xiaofeng Wang, Henry Edison, Dron Khanna, Usman Rafiq

[Context] Systematic Literature Review (SLR) has been a major type of study published in Software Engineering (SE) venues for about two decades. However, there is a lack of understanding of whether an SLR is really needed in comparison to a more conventional literature review. Very often, SE researchers embark on an SLR with such doubts. We aspire to provide

Jihao Andreas Lin, Joe Watson, Pascal Klink, Jan Peters

Bayesian deep learning approaches assume model parameters to be latent random variables and infer posterior distributions to quantify uncertainty, increase safety and trust, and prevent overconfident and unpredictable behavior. However, weight-space priors are model-specific, can be difficult to interpret and are hard to specify. Instead, we apply a Dirichle

Ron Gray, J. Robert Johnson

Suppose that the vertices of a regular graph are coloured red and blue with an equal number of each (we call this a balanced colouring). Since the graph is undirected, the number of edges from a red vertex to a blue vertex is clearly the same as the number of edges from a blue vertex to a red vertex. However, if instead of edges we count walks of length 2 wh

Gennaro Infante, Giovanni Mascali, Jorge Rodríguez-López

We provide new results regarding the localization of the solutions of nonlinear operator systems. We make use of a combination of Krasnosel'ski\u{\i} cone compression-expansion type methodologies and Schauder-type ones. In particular we establish a localization of the solution of the system within the product of a conical shell and of a closed convex set. By

Joao P C Bertoldo, David Arrustico

This paper introduces a simplified variation of the PaDiM (Pixel-Wise Anomaly Detection through Instance Modeling) method for anomaly detection in images, fitting a single multivariate Gaussian (MVG) distribution to the feature vectors extracted from a backbone convolutional neural network (CNN) and using their Mahalanobis distance as the anomaly score. We i

Xiaotian Ding, Shiqing Xu, Yuqing Xie, Martijn van den Ende

Multiple lines of evidence indicate that the 2023 Mw 7.8 Turkey earthquake started on a splay fault, then branched bilaterally onto the nearby East Anatolian Fault (EAF). This rupture pattern includes one feature deemed implausible, called backward rupture branching: rupture propagating from the splay fault onto the SW EAF segment through a sharp corner (wit

Sunsoo Choi, Ganbat Tsend

This study aims to determine the appropriate size of the Mongolian general corpus. This study used the Heaps function and Type Token Ratio to determine the appropriate size of the Mongolian general corpus. The sample corpus of 906,064 tokens comprised texts from 10 domains of newspaper politics, economy, society, culture, sports, world articles and laws, mid

Manuel de León, Manuel Lainz, Asier López-Gordón, Juan Carlos Marrero

The nonholonomic dynamics can be described by the so-called nonholonomic bracket on the constrained submanifold, which is a non-integrable modification of the Poisson bracket of the ambient space, in this case, of the canonical bracket on the cotangent bundle of the configuration manifold. On the other hand, another bracket, also called nonholonomic bracket,

Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos, Simon Bussy

We study multi-product inventory control problems where a manager makes sequential replenishment decisions based on partial historical information in order to minimize its cumulative losses. Our motivation is to consider general demands, losses and dynamics to go beyond standard models which usually rely on newsvendor-type losses, fixed dynamics, and unreali

Rohit K. Shukla, Levan Chotorlishvili, Vipin Vijayan, Harshit Verma

Exploiting the effect of nonreciprocal magnons in a system with no inversion symmetry, we propose a concept of a quantum information diode, {\it i.e.}, a device rectifying the amount of quantum information transmitted in the opposite directions. We control the asymmetric left and right quantum information currents through an applied external electric field a

Jincheng Zhou, Beatrice Bevilacqua, Bruno Ribeiro

The task of inductive link prediction in (discrete) attributed multigraphs infers missing attributed links (relations) between nodes in new test multigraphs. Traditional relational learning methods face the challenge of limited generalization to test multigraphs containing both novel nodes and novel relation types not seen in training. Recently, under the on

Minghuan Zeng, Xiang Li, Yongjun Wang, Shiping Feng

The microwave surface impedance measurements on cuprate superconductors provide the crucial information of the effect of the impurity scattering on the quasiparticle transport, however, the full understanding of the effect of the impurity scattering on the quasiparticle transport is still a challenging issue. Here based on the microscopic octet scattering mo

Sarika Mishra, Ali Anwar, R. P. Singh

We demonstrate an experimental method to generate arbitrary non-separable states of light using polarization and orbital angular momentum (OAM) degrees of freedom. We observe the intensity distribution corresponding to OAM modes of the light beam by projecting the non-separable state into different polarization states. We further verify the presence of non-s

Joseph Chuang, Andrey Lazarev

The notion of one-sided localization in the homotopy invariant context is developed for dg algebras and dg categories. Applications include a simple construction of derived localization of dg algebras and dg categories, and a refinement of Drinfeld's quotient of pretriangulated dg categories.

Thomas Celora

This work is concerned with advancing multi-fluid models in General Relativity, and in particular focuses on the modelling of dissipative fluids and turbulent flows. Such models are required for an accurate description of neutron star phenomenology, and binary neutron star mergers in particular. In fact, the advent of multi-messenger astronomy offers excitin

Roman Novikov, Basant Lal Sharma

We consider scattering for the discrete Schr\"{o}dinger operator on the square lattice $\mathbb{Z}^d$, $d \ge 1$, with compactly supported potential. We give formulas for finding the phased scattering amplitude from phaseless near-field scattering data.

Benjamin van Niekerk, Marc-André Carbonneau, Herman Kamper

Voice conversion aims to transform source speech into a different target voice. However, typical voice conversion systems do not account for rhythm, which is an important factor in the perception of speaker identity. To bridge this gap, we introduce Urhythmic-an unsupervised method for rhythm conversion that does not require parallel data or text transcripti

Kenta Suzuki

We relate the field of definition of representations $\sigma$ of the group of units $D^\times$ of a non-archimedean division algebra $D/F$ to that of its L-parameter $\varphi_\sigma\colon W_F\to \mathrm{GL}_n(\mathbb C)$, extending results of [Prasad-Ramakrishnan]. The field of definitions are controlled by division algebras $\mathcal D_{\sigma}$ and $\mathc

Jinwei Ren, Jianke Zhu

Accurately recovering the dense 3D mesh of both hands from monocular images poses considerable challenges due to occlusions and projection ambiguity. Most of the existing methods extract features from color images to estimate the root-aligned hand meshes, which neglect the crucial depth and scale information in the real world. Given the noisy sensor measurem

Ofir Blumer, Shlomi Reuveni, Barak Hirshberg

Metadynamics is a powerful method to accelerate molecular dynamics simulations, but its efficiency critically depends on the identification of collective variables that capture the slow modes of the process. Unfortunately, collective variables are usually not known a priori, and finding them can be very challenging. We recently presented a collective variabl

Lennart Brüggemann

Low-code development platforms provide an accessible infrastructure for the creation of software by domain experts, also called "citizen developers", without the need for formal programming education. Development is facilitated through graphical user interfaces, although traditional programming can still be used to extend low-code applications, for example w

Nikita Shanin, Simone Clochiatti, Kenneth M. Mayer, Laura Cottatellucci

In this paper, we study THz simultaneous wireless information and power transfer (SWIPT) systems. Since coherent information detection is challenging at THz frequencies and Schottky diodes may not be efficient for THz energy harvesting (EH) and information detection, we employ unipolar amplitude shift keying (ASK) modulation at the transmitter (TX) and a res

Yunhui Wu

A basic feature of Teichm\"uller theory of Riemann surfaces is the interplay of two dimensional hyperbolic geometry, the behavior of geodesic-length functions and Weil-Petersson geometry. Let $\mathcal{T}_g$ $(g\geq 2)$ be the Teichm\"uller space of closed Riemann surfaces of genus $g$. Our goal in this paper is to study the gradients of geodesic-length func

Adityanarayan Pandey, Amritesh Kumar, Pravin Varade, K. Miriyala

This study investigates the temperature-dependent quasi-static magnetoelectric (ME) response of electrically poled lead-free Na$_{0.4}$K$_{0.1}$Bi$_{0.5}$TiO$_3$-NiFe$_2$O$_4$ (NKBT-NFO) laminated composites. The aim is to understand the temperature stability of ME-based sensors and devices. The relaxor ferroelectric nature of NKBT is confirmed through imped

Amy Smith, Michael Cook

While the term `art' defies any concrete definition, this paper aims to examine how digital images produced by generative AI systems, such as Midjourney, have come to be so regularly referred to as such. The discourse around the classification of AI-generated imagery as art is currently somewhat homogeneous, lacking the more nuanced aspects that would apply

Luca Cappelli, Francesco Tacchino, Giuseppe Murante, Stefano Borgani

Cosmological simulations describing the evolution of density perturbations of a self-gravitating collisionless Dark Matter (DM) fluid in an expanding background, provide a powerful tool to follow the formation of cosmic structures over wide dynamic ranges. The most widely adopted approach, based on the N-body discretization of the collisionless Vlasov-Poisso

Maryam Nezami, Dimitrios S. Karachalios, Georg Schildbach, Hossam S. Abbas

In this study, we are concerned with autonomous driving missions when a static obstacle blocks a given reference trajectory. To provide a realistic control design, we employ a model predictive control (MPC) utilizing nonlinear state-space dynamic models of a car with linear tire forces, allowing for optimal path planning and tracking to overtake the obstacle

Yoav Vered, Stephen J. Elliott

This paper describes the design of a robust controller for position control in systems with sandwiched backlash. The backlash, which is nonsmooth and nonlinear, is inevitable in the operation of many systems, but it can have destructive effects on the stability and performance of feedback systems. In this work, a robust controller is designed using a modifie

Yuzhuang Xu, Shuo Wang, Peng Li, Xuebo Liu

Although neural machine translation (NMT) models perform well in the general domain, it remains rather challenging to control their generation behavior to satisfy the requirement of different users. Given the expensive training cost and the data scarcity challenge of learning a new model from scratch for each user requirement, we propose a memory-augmented a

Wen-Liang Li, Hai-Jing Song, Tie-Ling Song, D. L. Zhou

Motivated by the recent experimental developments on ultracold molecules and atoms, we propose a simplest theoretical model to address the disassociation, reflection and transmission probability of a 1-dimensional cold molecule via quantum scattering. First, we give the Born approximation results in the weak interaction regime. Then, employing the Lippmann-S

Xiaoyi Liu, Haotai Liang, Zhicheng Bao, Chen Dong

Point cloud, as a 3D representation, is widely used in autonomous driving, virtual reality (VR), and augmented reality (AR). However, traditional communication systems think that the point cloud's semantic information is irrelevant to communication, which hinders the efficient transmission of point clouds in the era of artificial intelligence (AI). This pape

Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee

eXplanation Based Learning (XBL) is a form of Interactive Machine Learning (IML) that provides a model refining approach via user feedback collected on model explanations. Although the interactivity of XBL promotes model transparency, XBL requires a huge amount of user interaction and can become expensive as feedback is in the form of detailed annotation rat

Sanjay Kumar, Avijeet Prasad, Sushree S. Nayak, Satyam Agarwal

Magnetic flux ropes (MFRs) play an important role in high-energetic events like solar flares and coronal mass ejections in the solar atmosphere. Importantly, solar observations suggest an association of some flaring events with quadrupolar magnetic configurations. However, the formation and subsequent evolution of MFRs in such magnetic configurations still n

Roman Vodička

The developed computational approach is capable of initiating and propagating cracks inside materials and along material interfaces of general multi-domain structures under quasi-static conditions. Special attention is paid to particular situation of a solid with inhomogeneities. Description of the fracture processes are based on the theory of material damag

Tal Sarig, Tal Galili, Roee Eilat

Surveys are an important research tool, providing unique measurements on subjective experiences such as sentiment and opinions that cannot be measured by other means. However, because survey data is collected from a self-selected group of participants, directly inferring insights from it to a population of interest, or training ML models on such data, can le

Xuesong Pan, Zhong Zheng, Xueqing Huang, Zesong Fei

In this paper, we investigate the uplink signal detection approaches in the cell-free massive MIMO systems with unmanned aerial vehicles (UAVs) serving as aerial access points (APs). The ground users are equipped with multiple antennas and the ground-to-air propagation channels are subject to correlated Rician fading. To overcome huge signaling overhead in t

Chenlu Zhang, Huaqiao Wang

In this paper, we mainly consider the global solvability of smooth solutions for the Cauchy problem of the three-dimensional Landau-Lifshitz-Slonczewski equation in the Morrey space. We derive the covariant complex Ginzburg-Landau equation by using moving frames to address the nonlinear parts. Applying the semigroup estimates and energy methods, we extend lo

Takuro Abe, Lukas Kühne, Paul Mücksch, Leonie Mühlherr

A graphic arrangement is a subarrangement of the braid arrangement whose set of hyperplanes is determined by an undirected graph. A classical result due to Stanley, Edelman and Reiner states that a graphic arrangement is free if and only if the corresponding graph is chordal, i.e., the graph has no chordless cycle with four or more vertices. In this article

Katharine Turner

Time-series of persistence diagrams, known as vineyards, have shown to be useful in diverse applications. A natural algebraic version of vineyards is a time series of persistence modules equipped with interleaving maps between the persistence modules at different time values. We call this a vineyard module. In this paper we will set up the framework for repr

Pierre Vallet, Jérôme Cayssol

In superconductors (SC), the Higgs amplitude mode is a coherent oscillation of the order parameter typically generated by THz laser irradiation. In this paper we propose to probe the Higgs mode using electronic transport in ballistic superconducting hybrid devices. We first confirm the existence of a non-zero amplitude mode in the clean case using the Keldys

Xiangpeng Wei, Haoran Wei, Huan Lin, Tianhao Li

Large language models (LLMs) demonstrate remarkable ability to comprehend, reason, and generate following nature language instructions. However, the development of LLMs has been primarily focused on high-resource languages, such as English, thereby limiting their applicability and research in other languages. Consequently, we present PolyLM, a multilingual L

Klaus E. Hermann

The shape of crystalline nanoparticles (NP) can often be described by polyhedra with flat facet surfaces. Thus, structural studies of polyhedral bodies can help to describe geometric details of NPs. Here we consider compact polyhedra of cubic point symmetry Oh.as simple models. Their surfaces are described by facets with normal vectors along selected directi

Udi Boker, Thomas A. Henzinger, Nicolas Mazzocchi, N. Ege Saraç

Safety and liveness stand as fundamental concepts in formal languages, playing a key role in verification. The safety-liveness classification of boolean properties characterizes whether a given property can be falsified by observing a finite prefix of an infinite computation trace (always for safety, never for liveness). In the quantitative setting, properti

André de Laire, Philippe Gravejat, Didier Smets

As a sequel to our previous analysis in [9] arXiv:2202.09411 on the Gross-Pitaevskii equation on the product space $\mathbb{R} \times \mathbb{T}$, we construct a branch of finite energy travelling waves as minimizers of the Ginzburg-Landau energy at fixed momentum. We deduce that minimizers are precisely the planar dark solitons when the length of the transv

Maria Virginia Catalisano, Giuseppe Favacchio, Elena Guardo, Yong-Su Shin

A $\Bbbk$-configuration of type $(d_1,\dots,d_s)$ is a specific set of points in $\mathbb P^2$ that has a number of algebraic and geometric properties. For example, the graded Betti numbers and Hilbert functions of all $\Bbbk$-configurations in $\mathbb P^2$ are determined by the type $(d_1,\dots,d_s)$. However the Waldschmidt constant of a $\Bbbk$-configura

Li Cai, Xin Mao, Youshao Xiao, Changxu Wu

Entity alignment (EA) aims to find the equivalent entity pairs between different knowledge graphs (KGs), which is crucial to promote knowledge fusion. With the wide use of temporal knowledge graphs (TKGs), time-aware EA (TEA) methods appear to enhance EA. Existing TEA models are based on Graph Neural Networks (GNN) and achieve state-of-the-art (SOTA) perform

Pavel S. Gevorgyan

A general equivariant shape theory for arbitrary $G$-spaces in the case of a compact group $G$ is constructed by using the method of pseudometrics suggested by Yu. M. Smirnov as early as in 1985 at the fifth Tiraspol symposium on general topology and its applications.

Simon Cléry, Pascal Anastasopoulos, Yann Mambrini

We study the reheating and non-thermal leptogenesis in the case of a vector inflaton. We concentrate on particle production during the phase of oscillating background, especially gravitational production induced by the presence of non-minimal coupling imposed by an isotropic and homogeneous Universe. Including processes involving the exchange of graviton, we

William S. DeWitt, Steven N. Evans, Ella Hiesmayr, Sebastian Hummel

Multi-type birth-death processes underlie approaches for inferring evolutionary dynamics from phylogenetic trees across biological scales, ranging from deep-time species macroevolution to rapid viral evolution and somatic cellular proliferation. A limitation of current phylogenetic birth-death models is that they require restrictive linearity assumptions tha

Paolo Fittipaldi, Anastasios Giovanidis, Frédéric Grosshans

Quantum Internetworking is a recent field that promises numerous interesting applications, many of which require the distribution of entanglement between arbitrary pairs of users. This work deals with the problem of scheduling in an arbitrary entanglement swapping quantum network - often called first generation quantum network - in its general topology, mult