April 2023 arXiv papers — page 8

Andrés J. Moreno, Julieth Saavedra

In this work, we approach the Laplacian coflow of a coclosed $G_2$-structure $\varphi$ using the formulae for the irreducible $G_2$-decomposition of the Hodge Laplacian and the Lie derivative of the Hodge dual $4$-form of $\varphi$. In terms of this decomposition, we characterise the conditions for a vector field as an infinitesimal symmetry of a coclosed $G

Zonglin Li, Matthew Welsh

We extend the geometric interpretation of the roots of the quadratic congruence $\mu^2 \equiv D \pmod m$ as the tops of certain geodesics in the hyperbolic plane to the case when $D$ is square-free and $D\equiv 1\pmod 4$. This allows us to establish limit laws for the fine-scale statistics of the roots using results by Marklof and the second author.

S. S. Seidov

In the present paper a method of finding the dynamics of the Wigner function of a particle in an infinite quantum well is developed. Starting with the problem of a reflection from an impenetrable wall, the obtained solution is then generalized to the case of a particle confined in an infinite well in arbitrary dimensions. It is known, that boundary value pro

Johannes Mich, Daniel Braig, Tobias Gustmann, Christian Hasse

Metals can serve as carbon-free energy carriers, e. g. in innovative metal-metal oxide cycles as proposed by Bergthorson (Prog. Energy Combust. Sci., 2018). Iron powder is a suitable candidate since it can be oxidized with air. Nevertheless, the combustion of iron powder in air is challenging especially with respect to flame stabilization which depends on th

Ricochet Collaboration, C. Augier, G. Baulieu, V. Belov

Coherent elastic neutrino-nucleus scattering (CE$\nu$NS) offers valuable sensitivity to physics beyond the Standard Model. The Ricochet experiment will use cryogenic solid-state detectors to perform a precision measurement of the CE$\nu$NS spectrum induced by the high neutrino flux from the Institut Laue-Langevin nuclear reactor. The experiment will employ a

Anant Sujatanagarjuna

The Circular Economy (CE) is regarded as a solution to the environmental crisis. However, mainstream CE measures skirt around challenging the ethos of ever-increasing economic growth, overlooking social impacts and under-representing solutions such as reducing overall consumption. Circular Societies (CS) address these concerns by challenging this ethos. They

Johannes Czech, Jannis Blüml, Kristian Kersting, Hedinn Steingrimsson

While transformers have gained recognition as a versatile tool for artificial intelligence (AI), an unexplored challenge arises in the context of chess - a classical AI benchmark. Here, incorporating Vision Transformers (ViTs) into AlphaZero is insufficient for chess mastery, mainly due to ViTs' computational limitations. The attempt to optimize their effici

Muhammad Y. Hanna, Muhammad Aziz Majidi, Ahmad R. T. Nugraha

We investigate the performance of thermoradiative (TR) cells using the III-V group of semiconductors, which include GaAs, GaSb, InAs, and InP, with the aim of determining their efficiency and finding the best TR cell materials among the III-V group. The TR cells generate electricity from thermal radiation, and their efficiency is influenced by several factor

Dongryul M. Kim, Hee Oh

Let $G$ be a connected semisimple real algebraic group. For a Zariski dense Anosov subgroup $\Gamma<G$ with respect to a parabolic subgroup $P_\theta$, we prove that any $\Gamma$-Patterson-Sullivan measure charges no mass on any proper subvariety of $G/P_\theta$. More generally, we prove that for a Zariski dense $\theta$-transverse subgroup $\Gamma<G$, any $

Ahmed Rabee Sayed, Cheng Wang, Tianshu Bi

Interactions between power and gas systems, which are both large and complex, have been gradually intensified during the last decades, predominantly due to the propagation of large fleet natural gas-fired power units (GPUs) and the technological developments of power-to-gas (P2G) facilities. These interactions not only bring significant economic benefits to

Frank E. Curtis, Vyacheslav Kungurtsev, Daniel P. Robinson, Qi Wang

A stochastic-gradient-based interior-point algorithm for minimizing a continuously differentiable objective function (that may be nonconvex) subject to bound constraints is presented, analyzed, and demonstrated through experimental results. The algorithm is unique from other interior-point methods for solving smooth nonconvex optimization problems since the

Arnold Sterle, Aaron Grapentin, Christian A. Hans, Jörg Raisch

In this paper, an offset-free bilinear model predictive control approach for wind turbines is presented. State-of-the-art controllers employ different control loops for pitch angle and generator torque which switch depending on wind conditions. In contrast, the presented controller is based on one unified control law that works for all wind conditions. The i

Maurus Hans, Elinor Kath, Marius Sparn, Nikolas Liebster

Physical systems can be used as an information processing substrate and with that extend traditional computing architectures. For such an application the experimental platform must guarantee pristine control of the initial state, the temporal evolution and readout. All these ingredients are provided by modern experimental realizations of atomic Bose Einstein

Elena Danesi

In this paper we continue the analysis of the dispersive properties of the 2D and 3D massless Dirac-Coulomb equations that has been started in arXiv:1503.00945 and arXiv:2101.07185. We prove a priori estimates of the solution of the mentioned systems, in particular Strichartz estimates with an additional angular regularity, exploiting the tools developed in

Martial Dakoury, Justin Feuto

We use a molecular characterization of generalized Hardy-Morrey spaces, to provide a norm controls of Calder\'on-Zygmund operators and their associated commutators in the above mention spaces.

Mustafa Can Camur, Sandipp Krishnan Ravi, Shadi Saleh

The COVID 19 pandemic and ongoing political and regional conflicts have a highly detrimental impact on the global supply chain, causing significant delays in logistics operations and international shipments. One of the most pressing concerns is the uncertainty surrounding the availability dates of products, which is critical information for companies to gene

José Proença, Luc Edixhoven

This tool paper presents Caos: a methodology and a programming framework for computer-aided design of structural operational semantics for formal models. This framework includes a set of Scala libraries and a workflow to produce visual and interactive diagrams that animate and provide insights over the structure and the semantics of a given abstract model wi

Huidong Xie, Qiong Liu, Bo Zhou, Xiongchao Chen

As PET imaging is accompanied by substantial radiation exposure and cancer risk, reducing radiation dose in PET scans is an important topic. However, low-count PET scans often suffer from high image noise, which can negatively impact image quality and diagnostic performance. Recent advances in deep learning have shown great potential for recovering underlyin

Sanjib Basu, Debasish Sen

The concept of $\mathcal S$-topological $\sigma$-ideal in measurable space $(X, \mathcal S)$ was introduced by Hejduk and using a theorem of Wagner on convergence of measurable functions characterized $\mathcal S$-topological $\sigma$-ideals. In this paper, we give a general construction of $\mathcal S$-topological $\sigma$-ideals from structures induced by

Juan Augusto Maya, Leonardo Rey Vega, Andrea M. Tonello

In this article, we consider the problem of distributed detection of a localized radio source emitting a signal. We consider that geographically distributed sensor nodes obtain energy measurements and compute cooperatively a statistic to decide if the source is present or absent. We model the radio source as a stochastic signal and deal with spatially statis

Baoxing Zhai, Ruiqing Cheng, Tianxing Wang, Li Liu

Inspired by the neuro-synaptic frameworks in the human brain, neuromorphic computing is expected to overcome the bottleneck of traditional von-Neumann architecture and be used in artificial intelligence. Here, we predict a class of potential candidate materials, MCu$_3$X$_4$ (M = V, Nb, Ta; X = S, Se, Te), for neuromorphic computing applications through firs

G. D. A. Wood, D. D. Khalyavin, D. A. Mayoh, J. Bouaziz

$\text{GdRu}_{\text{2}}\text{Si}_{\text{2}}$ is a centrosymmetric magnet in which a skyrmion lattice has recently been discovered. Here, we investigate the magnetic structure of the zero field ground state using neutron diffraction on single crystal and polycrystalline $^{\text{160}}\text{GdRu}_{\text{2}}\text{Si}_{\text{2}}$. In addition to observing the pr

Kang Shuai, Shanshan Luo, Yue Zhang, Feng Xie

Assessing causal effects in the presence of unmeasured confounding is challenging. Although auxiliary variables, such as instrumental variables, are commonly used to identify causal effects, they are often unavailable in practice due to stringent and untestable conditions. To address this issue, previous researches have utilized linear structural equation mo

Weng-Tai Su, Yi-Chun Hung, Po-Jen Yu, Shang-Hua Yang

Terahertz (THz) tomographic imaging has recently attracted significant attention thanks to its non-invasive, non-destructive, non-ionizing, material-classification, and ultra-fast nature for object exploration and inspection. However, its strong water absorption nature and low noise tolerance lead to undesired blurs and distortions of reconstructed THz image

Lara C. Ortmanns, Janine Splettstoesser, Maarten R. Wegewijs

We analyze the time-evolution of a quantum dot which is proximized by a large-gap superconductor and weakly probed using the charge and heat currents into a wide-band metal electrode. We map out the full time dependence of these currents after initializing the system by a switch. We find that due to the proximity effect there are two simple yet distinct swit

Jean-Philippe Banon, Ingve Simonsen, Rémi Carminati

Using a single-scattering theory, we derive the expression of the degree of polarization of the light scattered from a layer exhibiting both surface and volume scattering. The expression puts forward the intimate connection between the degree of polarization and the statistical correlation between surface and volume disorders. It also permits a quantitative

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

A study of the $B^+\to K^0_SK^+K^-\pi^+$ and $B^+\to K^0_SK^+K^+\pi^-$ decays is performed using proton-proton collisions at center-of-mass energies of 7, 8 and 13 TeV at the LHCb experiment. The $K^0_SK \pi$ invariant mass spectra from both decay modes reveal a rich content of charmonium resonances. New precise measurements of the $\eta_c$ and $\eta_c(2S)$

Francesco Caravelli

It has been recently noted that for a class of dynamical systems with explicit conservation laws represented via projector operators the dynamics can be understood in terms of lower dimensional equations This is the case for instance of memristive circuits Memristive systems are important classes of devices with wide ranging applications in electronic circui

Soumita Modak

A novel nonparametric clustering algorithm is proposed using the interpoint distances between the members of the data to reveal the inherent clustering structure existing in the given set of data, where we apply the classical nonparametric univariate kernel density estimation method to the interpoint distances to estimate the density around a data member. Ou

Gerrit Nolte, Maximilian Schlüter, Alnis Murtovi, Bernhard Steffen

TADS are a novel, concise white-box representation of neural networks. In this paper, we apply TADS to the problem of neural network verification, using them to generate either proofs or concise error characterizations for desirable neural network properties. In a case study, we consider the robustness of neural networks to adversarial attacks, i.e., small c

Doru Constantin

I present a simple derivation of the de Gennes narrowing phenomenon.

Bilgai Almeida Zamora, Enrique Carreon Martínez, Jorge Segovia, J. J. Cobos-Martínez

We construct a contact interaction model for the $\eta$ and $\eta'$ mesons in the SDE-BSE approach to QCD and compute several static properties of these mesons and their transition form factors. We find that this model gives an excellent description of the $\eta$ and $\eta'$ static properties, namely their masses, decay width and decay constants. However, a

Guy Scher, Sadra Sadraddini, Ariel Yadin, Hadas Kress-Gazit

Providing guarantees on the safe operation of robots against edge cases is challenging as testing methods such as traditional Monte-Carlo require too many samples to provide reasonable statistics. Built upon recent advancements in rare-event sampling, we present a model-based method to verify if a robotic system satisfies a Signal Temporal Logic (STL) specif

Henrique K. Miyamoto, Fábio C. C. Meneghetti, Julianna Pinele, Sueli I. R. Costa

The Fisher-Rao distance is the geodesic distance between probability distributions in a statistical manifold equipped with the Fisher metric, which is a natural choice of Riemannian metric on such manifolds. It has recently been applied to supervised and unsupervised problems in machine learning, in various contexts. Finding closed-form expressions for the F

Tobias Blickhan

We present a registration method for model reduction of parametric partial differential equations with dominating advection effects and moving features. Registration refers to the use of a parameter-dependent mapping to make the set of solutions to these equations more amicable for approximation using classical reduced basis methods. The proposed approach ut

Tobias Long, Robert Barnett, Richard Jefferson-Loveday, Giovanni Stabile

Problems with dominant advection, discontinuities, travelling features, or shape variations are widespread in computational mechanics. However, classical linear model reduction and interpolation methods typically fail to reproduce even relatively small parameter variations, making the reduced models inefficient and inaccurate. This work proposes a model orde

Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Alexander Barnhill

The ACM Multimedia 2023 Computational Paralinguistics Challenge addresses two different problems for the first time in a research competition under well-defined conditions: In the Emotion Share Sub-Challenge, a regression on speech has to be made; and in the Requests Sub-Challenges, requests and complaints need to be detected. We describe the Sub-Challenges,

Alexander Salganik, Sergey S. Tsygankov, Victor Doroshenko, Sergey V. Molkov

In the beginning of 2023 the Be transient X-ray pulsar RX J0440.9+4431 underwent a fist-ever giant outburst observed from the source peaking in the beginning of February and reaching peak luminosity of $\sim 4.3\times10^{37}$ erg s$^{-1}$. Here we present the results of a detailed spectral and temporal study of the source based on NuSTAR, INTEGRAL, Swift, an

Sayan Deb Sarkar, Ondrej Miksik, Marc Pollefeys, Daniel Barath

Building 3D scene graphs has recently emerged as a topic in scene representation for several embodied AI applications to represent the world in a structured and rich manner. With their increased use in solving downstream tasks (eg, navigation and room rearrangement), can we leverage and recycle them for creating 3D maps of environments, a pivotal step in age

Robert C. Kirby

Finite element discretization of time dependent problems also require effective time-stepping schemes. While implicit Runge-Kutta methods provide favorable accuracy and stability problems, they give rise to large and complicated systems of equations to solve for each time step. These algebraic systems couple all Runge-Kutta stages together, giving a much lar

Mario Berta, Marco Tomamichel

Entropy is a fundamental concept in quantum information theory that allows to quantify entanglement and investigate its properties, for example its monogamy over multipartite systems. Here, we derive variational formulas for relative entropies based on restricted measurements of multipartite quantum systems. By combining these with multivariate matrix trace

Lloyd A. Demetrius

Self-organization is the autonomous assembly of a network of interacting components into a stable, organized pattern. This article shows that the process of self-assembly can be encoded in terms of evolutionary entropy, a statistical measure of the cooperativity of the interacting components. Evolutionary entropy describes the rate at which a network of inte

WenXuan Zhang, HongTao An, Duojie Jia

Inspired by the observation of a resonant state $X(6600)$ of fully charm tetraquark by the CMS experiment of LHCb Collaboration in double $J/\psi $ decay channel, we perform a systematical study of all configurations of fully heavy pentaquarks $P_{Q_{1}Q_{2}Q_{3}Q_{{4}}\bar{Q_{5}}}$ ($Q_{i}=c,b$%, $i=1,2,3,4,5$) in their ground states in unified framework of

Jannis Kreß, Jens Rau, Hektor Hebert, Fernando Perez-Peña

This paper investigates the performance of a lowcost Throttle-by-Wire-System (TbWS) for two-wheeler applications. Mopeds/scooters are still restricted environmentally harmful. Throttle-by-Wire-Systems can contribute to environmental protection by replacing conventional restrictors. Its consisting of an anisotropic magnetoresistance (AMR) throttle position se

Yuejian Wu, Linqing Zhao, Jiwen Lu, Haibin Yan

In this paper, we present a dense hybrid proposal modulation (DHPM) method for lane detection. Most existing methods perform sparse supervision on a subset of high-scoring proposals, while other proposals fail to obtain effective shape and location guidance, resulting in poor overall quality. To address this, we densely modulate all proposals to generate top

Lloyd Demetrius

The origin of cellular life can be described in terms of the transition from inorganic matter: solids, liquids and gases, to the emergence of cooperative assemblies of organic matter, DNA and proteins,capable of replication and metabolism. Directionality Theory is a mathematical model of the collective behavior of populations of organic matter: cells and hig

Shubhaditya Burela, Philipp Krah, Julius Reiss

Parametric model order reduction techniques often struggle to accurately represent transport-dominated phenomena due to a slowly decaying Kolmogorov n-width. To address this challenge, we propose a non-intrusive, data-driven methodology that combines the shifted proper orthogonal decomposition (POD) with deep learning. Specifically, the shifted POD technique

Stefano Tomasin, Raphael Hasler, Antonia M. Tulino, Matilde Sánchez-Fernández

We consider a cellular network, where the uplink transmissions to a base station (BS) are interferenced by other devices, a condition that may occur, e.g., in cell-free networks or when using non-orthogonal multiple access (NOMA) techniques. Assuming that the BS treats this interference as additional noise, we focus on the problem of estimating the interfere

Sungwoo Kang, Jong-Kook Kim

Despite the efficient market hypothesis, many studies suggest the existence of inefficiencies in the stock market leading to the development of techniques to gain above-market returns. Systematic trading has undergone significant advances in recent decades with deep learning schemes emerging as a powerful tool for analyzing and predicting market behavior. In

Saurab Chhachhi, Fei Teng

We provide an exact expressions for the 1-Wasserstein distance between independent location-scale distributions. The expressions are represented using location and scale parameters and special functions such as the standard Gaussian CDF or the Gamma function. Specifically, we find that the 1-Wasserstein distance between independent univariate location-scale

Moritz Mühlenthaler, Benjamin Peyrille, Zoltán Szigeti

The orientation theorem of Nash-Williams states that an undirected graph admits a $k$-arc-connected orientation if and only if it is $2k$-edge-connected. Recently, Ito et al. showed that any orientation of an undirected $2k$-edge-connected graph can be transformed into a $k$-arc-connected orientation by reorienting one arc at a time without decreasing the ar

Yu-An Liu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke

Neural ranking models (NRMs) have attracted considerable attention in information retrieval. Unfortunately, NRMs may inherit the adversarial vulnerabilities of general neural networks, which might be leveraged by black-hat search engine optimization practitioners. Recently, adversarial attacks against NRMs have been explored in the paired attack setting, gen

Jie Chen, Fan Gu, Boling Guo

In this paper, we study the global well-posedness of the stochastic S-KdV system in $H^1(\mathbb{R})\times H^1(\mathbb{R})$, which are driven by additive noises. It is difficult to show the global well-posedness of a related perturbation system even for smooth datum and stochastic forces. To overcome it, we introduce a new sequence of approximation equations

Yaru Ren, Pengzhi Lin, Chi Zhang, Xiangyu Hu

In this paper, a new efficient and generalized consistency correction method for weakly-compressible smoothed particle hydrodynamics is proposed and successfully implemented in the simulation of violent free-surface flow exhibiting breaking and impact events for the first time. It's well known that the original kernel gradient correction (KGC) encounters num

Georgii Mikriukov, Gesina Schwalbe, Christian Hellert, Korinna Bade

Analysis of how semantic concepts are represented within Convolutional Neural Networks (CNNs) is a widely used approach in Explainable Artificial Intelligence (XAI) for interpreting CNNs. A motivation is the need for transparency in safety-critical AI-based systems, as mandated in various domains like automated driving. However, to use the concept representa

Yihan Liu, Ruisheng Zheng, Liang Zhang, Hengyuan Wei

Context. Solar extreme ultraviolet (EUV) waves are propagating disturbances in the corona, and they usually accompany with various solar eruptions, from large-scale coronal mass ejections to small-scale coronal jets. Aims. Generally, it is believed that EUV waves are driven by the rapid expansion of coronal loops overlying the erupting cores. In this Letter,

Marie Cloet, Louise Arno, Desmond Kabus, Joeri Van der Veken

Excitable media are ubiquitous in nature, and in such systems the local excitation tends to self-organize in traveling waves, or in rotating spiral-shaped patterns in two or three spatial dimensions. Examples include waves during a pandemic or electrical scroll waves in the heart. Here we show that such phenomena can be extended to a space of four or more di

Xiaozhou Zan, Xiangdong Guo, Aolin Deng, Zhiheng Huang

Stacking order plays a crucial role in determining the crystal symmetry and has significant impacts on electronic, optical, magnetic, and topological properties. Electron-phonon coupling, which is central to a wide range of intriguing quantum phenomena, is expected to be intricately connected with stacking order. Understanding the stacking order-dependent el

Ruisheng Zheng, Yihan Liu, Wenlong Liu, Bing Wang

Solar coronal waves frequently appear as bright disturbances that propagate globally from the eruption center in the solar atmosphere, just like the tsunamis in the ocean on Earth. Theoretically, coronal waves can sweep over the underlying chromosphere and leave an imprint in the form of Moreton wave, due to the enhanced pressure beneath their coronal wavefr

Juha Kinnunen, Antonella Nastasi, Cintia Pacchiano Camacho

We study local and global higher integrability properties for quasiminimizers of a class of double-phase integrals characterized by nonstandard growth conditions. We work purely on a variational level in the setting of a metric measure space with a doubling measure and a Poincar\'e inequality. The main novelty is an intrinsic approach to double-phase Sobolev

Shengchao Chen, Ting Shu, Huan Zhao, Yuan Yan Tang

Weather recognition is an essential support for many practical life applications, including traffic safety, environment, and meteorology. However, many existing related works cannot comprehensively describe weather conditions due to their complex co-occurrence dependencies. This paper proposes a novel multi-label weather recognition model considering these d

Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke

Knowledge-intensive language tasks (KILTs) benefit from retrieving high-quality relevant contexts from large external knowledge corpora. Learning task-specific retrievers that return relevant contexts at an appropriate level of semantic granularity, such as a document retriever, passage retriever, sentence retriever, and entity retriever, may help to achieve

Mao-Jun Yan, Fang-Zheng Peng, Manuel Pavon Valderrama

The spectrum of the $c qq$ baryons contains a few states whose nature is not clearly a three-quark composite and which might have a sizable baryon-meson component. Examples include the $\Sigma_c(2800)$ or the $\Lambda_c(2940)$. Here we explore the spectrum of two-body systems composed of a light, octet baryon and a charmed meson (or antimeson) within a simpl

Jiaxing Song, Olga Shishkina, Xiaojue Zhu

The geostrophic turbulence in rapidly rotating thermal convection exhibits characteristics shared by many highly turbulent geophysical and astrophysical flows. In this regime, the convective length and velocity scales, heat flux, and kinetic and thermal dissipation rates are all diffusion-free, meaning that they are independent of the viscosity and thermal d

Shashank Manjunath, Jose A. Perea, Aarti Sathyanarayana

Topological data analysis (TDA) is an emerging technique for biological signal processing. TDA leverages the invariant topological features of signals in a metric space for robust analysis of signals even in the presence of noise. In this paper, we leverage TDA on brain connectivity networks derived from electroencephalogram (EEG) signals to identify statist

Keanu Sisouk, Julie Delon, Julien Tierny

This paper presents a computational framework for the concise encoding of an ensemble of persistence diagrams, in the form of weighted Wasserstein barycenters [100], [102] of a dictionary of atom diagrams. We introduce a multi-scale gradient descent approach for the efficient resolution of the corresponding minimization problem, which interleaves the optimiz

Z. H. Chen, X. H. Yang, G. B. Zhang, Y. Y. Ma

The non-local heat transport of hot electrons during high-intensity lasers interaction with plasmas can preheat the fuel and limit the heat flow in inertial confinement fusion. It increases the entropy of the fuel and decreases the final compression. In this paper, the non-local electron transport model that is based on the improved SNB algorithm has been em

Samira Mansourzadeh, Tim Vogel, Mostafa Shalaby, Clara J. Saraceno

As high-average power ultrafast lasers become increasingly available for nonlinear conversion, the temperature dependence of the material properties of nonlinear crystals becomes increasingly relevant. Here, we present temperature-dependent THz complex refractive index measurements of the organic crystal BNA over a wide range of temperatures from 300 K down

T. H. Kokkeler, Chunli Huang, F. S. Bergeret, I. V. Tokatly

Motivated by recent discoveries of superconductivity in lightly-doped multilayer graphene systems, we present a low-energy model to study superconductivity in 2D materials whose Fermi surface consists of two valleys at $\pm \vec{K}$-points. We assume a triplet odd-valley superconducting order with a pair potential that is isotropic in each valley but has a d

Emmanouil Karystinaios, Francesco Foscarin, Gerhard Widmer

This paper targets the perceptual task of separating the different interacting voices, i.e., monophonic melodic streams, in a polyphonic musical piece. We target symbolic music, where notes are explicitly encoded, and model this task as a Multi-Trajectory Tracking (MTT) problem from discrete observations, i.e., notes in a pitch-time space. Our approach build

Jianxing Chen, Francesco R. Ferraro, Maurizio Salaris, Mario Cadelano

Recently, a new class of white dwarfs (dubbed ``slowly cooling WDs'') has been identified in two globular clusters (namely M13 and NGC 6752) showing a horizontal branch (HB) morphology with an extended blue tail. The cooling rate of these WDs is reduced by stable thermonuclear hydrogen burning in their residual envelope, and they are thought to be originated

He Liu, Ke Wang, Fei Gao, Jin Leng

Hole spin qubits based on germanium (Ge) have strong tunable spin orbit interaction (SOI) and ultrafast qubit operation speed. Here we report that the Rabi frequency (f_Rabi) of a hole spin qubit in a Ge hut wire (HW) double quantum dot (DQD) is electrically tuned through the detuning energy and middle gate voltage (V_M). f_Rabi gradually decreases with incr

Fei Xue, Ignas Budvytis, Roberto Cipolla

Visual localization is a fundamental task for various applications including autonomous driving and robotics. Prior methods focus on extracting large amounts of often redundant locally reliable features, resulting in limited efficiency and accuracy, especially in large-scale environments under challenging conditions. Instead, we propose to extract globally r

Miguel A. González-Santamarta, Laura Fernández-Becerra, David Sobrín-Hidalgo, Ángel Manuel Guerrero-Higueras

The deployment of autonomous robots in various domains has raised significant concerns about their trustworthiness and accountability. This study explores the potential of Large Language Models (LLMs) in analyzing ROS 2 logs generated by autonomous robots and proposes a framework for log analysis that categorizes log files into different aspects. The study e

Lorenzo Bastianello, Alain Chateauneuf, Bernard Cornet

Two acts are comonotonic if they yield high payoffs in the same states of nature. The main purpose of this paper is to derive a new characterization of Cumulative Prospect Theory (CPT) through simple properties involving comonotonicity. The main novelty is a concept dubbed gain-loss hedging: mixing positive and negative acts creates hedging possibilities eve

Mats Boij, Emanuela De Negri, Alessandro De Stefani, Maria Evelina Rossi

The rate of a standard graded $K$-algebra $A$ is a measure of the growth of the shifts in a minimal free resolution of $K$ as an $A$-module. In particular $A$ has rate one if and only if it is Koszul. It is known that a generic Artinian Gorenstein algebra of embedding dimension $n \geq 3$ and socle degree $s=3$ is Koszul. We prove that a generic Artinian Gor

Thomas P. Ilett, Omer Yuval, Thomas Ranner, Netta Cohen

3D shape reconstruction typically requires identifying object features or textures in multiple images of a subject. This approach is not viable when the subject is semi-transparent and moving in and out of focus. Here we overcome these challenges by rendering a candidate shape with adaptive blurring and transparency for comparison with the images. We use the

Luke Chamandy, Jonathan Carroll-Nellenback, Eric G. Blackman, Adam Frank

We perform 3D hydrodynamical simulations to study recombination and ionization during the common envelope (CE) phase of binary evolution, and develop techniques to track the ionic transitions in time and space. We simulate the interaction of a $2\,M_\odot$ red giant branch primary and a $1\,M_\odot$ companion modeled as a particle. We compare a run employing

Fei Xue, Ignas Budvytis, Roberto Cipolla

Previous methods solve feature matching and pose estimation using a two-stage process by first finding matches and then estimating the pose. As they ignore the geometric relationships between the two tasks, they focus on either improving the quality of matches or filtering potential outliers, leading to limited efficiency or accuracy. In contrast, we propose

Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros

We consider control of uncertain linear time-varying stochastic systems from the perspective of regret minimization. Specifically, we focus on the problem of designing a feedback controller that minimizes the loss relative to a clairvoyant optimal policy that has foreknowledge of both the system dynamics and the exogenous disturbances. In this competitive fr

Abel Milor

After introducing the simplicial manifolds, such as the different ways of defining the differential forms on them, we summarized a canonical way of calculating the characteristic classes of a $G$-principal bundle by computing them on the classifying bundle $EG\longrightarrow BG$. Finally, we calculated the first Pontryagin class on the classifying bundle of

Cecilia Cormick, Leonardo Ermann

We consider a system of composite bosons given by strongly bound fermion pairs tunneling through sites that form a low-dimensional network. It has been shown that the ground state of this system can have condensate-like properties in the very dilute regime for two-dimensional lattices but displays fermionization for one-dimensional lattices. Studying graphs

Jochen Wambach

Properties of high-density strong-interaction matter of relevance for astrophysical scenarios that involve neutron stars are discussed. It is argued that theoretical and experimental insights from the small baryo-chemical potential ($\mu_B$) and high-temperature regions of the QCD phase diagram can guide realistic model building at high density, as this regi

Isabelle Kuhlmann, Anna Gessler, Vivien Laszlo, Matthias Thimm

We present algorithms based on satisfiability problem (SAT) solving, as well as answer set programming (ASP), for solving the problem of determining inconsistency degrees in propositional knowledge bases. We consider six different inconsistency measures whose respective decision problems lie on the first level of the polynomial hierarchy. Namely, these are t

Jing Li, Yuangang Pan, Yueming Lyu, Yinghua Yao

Many machine learning applications encounter a situation where model providers are required to further refine the previously trained model so as to gratify the specific need of local users. This problem is reduced to the standard model tuning paradigm if the target data is permissibly fed to the model. However, it is rather difficult in a wide range of pract

Lukas Böhme, Dominik J. Schwarz, Francesco de Gasperin, Huub J. A. Röttgering

Aims. With the recent preliminary release of the LOFAR LBA Sky Survey (LoLSS), the first wide-area, ultra-low frequency observations from LOFAR were published. Our aim is to combine this data set with other surveys at higher frequencies to study the spectral properties of a large sample of radio sources. Methods. We present a new cross-matching algorithm tak

Zhendong Wang, Yi Wang, David Redmiles

Small-scale automation services in Software Engineering, known as SE Bots, have gradually infiltrated every aspect of daily software development with the goal of enhancing productivity and well-being. While leading the OSS development, elite developers have often burned out from holistic responsibilities in projects and looked for automation support. Buildin

Chunkit Chan, Jiayang Cheng, Weiqi Wang, Yuxin Jiang

This paper aims to quantitatively evaluate the performance of ChatGPT, an interactive large language model, on inter-sentential relations such as temporal relations, causal relations, and discourse relations. Given ChatGPT's promising performance across various tasks, we proceed to carry out thorough evaluations on the whole test sets of 11 datasets, includi

Luciano S. Martinez-Rau, José O. Chelotti, Mariano Ferrero, Julio R. Galli

Farmers must continuously improve their livestock production systems to remain competitive in the growing dairy market. Precision livestock farming technologies provide individualized monitoring of animals on commercial farms, optimizing livestock production. Continuous acoustic monitoring is a widely accepted sensing technique used to estimate the daily rum

Joyjit Mukherjee, Ankit Chatterjee, Shreeshan Jena, Nitesh Kumar

This paper proposes an adaptive gravity compensation (AGC) control strategy for a cable-driven upper-limb exosuit intended to assist the wearer with lifting tasks. Unlike most model-based control techniques used for this human-robot interaction task, the proposed control design does not assume knowledge of the anthropometric parameters of the wearer's arm an

Ethan T. Ritz, Henrik S. Røising, Morten H. Christensen, Turan Birol

Recent experiments have shown that the phase diagrams of the kagome superconductors $A\mathrm{V}_3\mathrm{Sb}_5$ are strongly impacted by changes in the $c$-axis lattice parameter. Here, we show that $c$-axis deformations impact primarily the Sb apical bonds and thus the overlap between their $p_z$ orbitals. Changes in the latter, in turn, substantially affe

Jan A. Bergstra, Alban Ponse

Three-valued conditional logic (CL) is defined by Guzm\'an and Squier (1990), and based on McCarthy's noncommutative connectives, axiomatises a short-circuit logic (SCL) that defines more identities than three-valued MSCL (Memorising SCL, which also has a two-valued variant). This follows from the fact that the definable connective that prescribes full left-

Rajes Ghosh, Sreejith Nair, Lalit Pathak, Sudipta Sarkar

The second postulate of special relativity states that the speed of light in vacuum is independent of the emitter's motion. The test of this postulate so far remains unexplored for gravitational radiation. We analyze data from the LIGO-Virgo detectors to test this postulate within the ambit of a model where the speed of the emitted GWs ($c'$) from a binary d

Dmitry Karpov, Kenza Djeghdi, Mirko Holler, S. Narjes Abdollahi

Highly periodic structures are often said to convey the beauty of nature. However, most material properties are strongly influenced by the defects they contain. On the mesoscopic scale, molecular self-assembly exemplifies this interplay; thermodynamic principles determine short-range order, but long-range order is mainly impeded by the kinetic history of the

Qi-Bo Zeng, Rong Lü

We study a one-dimensional system subjected to a linearly varying imaginary vector potential, which is described by the single-particle continuous Schr\"odinger equation and is analytically solved. The eigenenergy spectrum is found to be real under open boundary condition (OBC) but forms a parabola in the complex energy plane under periodic boundary conditio

Giuliano Rosella, Jan Sprenger

Causal Modeling Semantics (CMS, e.g., Galles and Pearl 1998; Pearl 2000; Halpern 2000) is a powerful framework for evaluating counterfactuals whose antecedent is a conjunction of atomic formulas. We extend CMS to an evaluation of the probability of counterfactuals with disjunctive antecedents, and more generally, to counterfactuals whose antecedent is an arb

Mobasshir Mahbub, Raed M. Shubair

The Internet of Things (IoT) is going to be a few of the most influential and critical role spectators in the post-5G and 6G wireless networking paradigm because IoT is being deployed in a variety of applications and services such as smart towns, smart homes, savvy environment monitoring, smart medical care, smart factories, savvy agri-business, and so on, w

Christopher D. Marcotte, Matthew J. Hoffman, Flavio H. Fenton, Elizabeth M. Cherry

The reconstruction of electrical excitation patterns through the unobserved depth of the tissue is essential to realizing the potential of computational models in cardiac medicine. We have utilized experimental optical-mapping recordings of cardiac electrical excitation on the epicardial and endocardial surfaces of a canine ventricle as observations directin

Niccolò Sellati, Francesco Gabriele, Claudio Castellani, Lara Benfatto

Layered superconductors like High-Tc cuprates display out-of-plane plasma oscillations between layers sustained by the weak Josephson coupling among the superconducting sheets, the so-called Josephson plasmons. Bilayer cuprates hosts two of such modes, but due to the anisotropy of the electronic response their description at generic wavevector cannot be sepa

Motokazu Abe, Okuto Morikawa, Soma Onoda, Hiroshi Suzuki

In lattice compact gauge theories, we must impose the admissibility condition to have well-defined topological sectors. The admissibility condition, however, usually forbids the presence of magnetic operators, and it is not so trivial if one can study the monopole physics depending on the topological term, such as the Witten effect, on the lattice. In this p