July 2023 arXiv papers — page 104

Seyed Ali Hosseini Mansoori, Fereshteh Felegray, Alireza Talebian, Mohammad Sami

In this paper, we propose a novel mechanism in $\mathbb{T}^2$-inflation to enhance the power spectrum large enough to seed primordial black holes (PBHs) formation. To accomplish this, we consider the coupling function between the inflaton field and $\mathbb{T}^2= T_{\mu \nu}T^{\mu \nu}$ term. PBHs formed within this scenario can contribute partially or entir

Luigi Capogrosso, Alessio Mascolini, Federico Girella, Geri Skenderi

Industry 4.0 involves the integration of digital technologies, such as IoT, Big Data, and AI, into manufacturing and industrial processes to increase efficiency and productivity. As these technologies become more interconnected and interdependent, Industry 4.0 systems become more complex, which brings the difficulty of identifying and stopping anomalies that

Luyi Li, Jiayi Huang, Lang Feng, Zhongfeng Wang

Cache side channel attacks are increasingly alarming in modern processors due to the recent emergence of Spectre and Meltdown attacks. A typical attack performs intentional cache access and manipulates cache states to leak secrets by observing the victim's cache access patterns. Different countermeasures have been proposed to defend against both general and

Leonard Logarić, Shane Dooley, Silvia Pappalardi, John Goold

Dual-unitary circuits are a class of quantum systems for which exact calculations of various quantities are possible, even for circuits that are nonintegrable. The array of known exact results paints a compelling picture of dual-unitary circuits as rapidly thermalizing systems. However, in this Letter, we present a method to construct dual-unitary circuits f

Florian Felice

In this work, we present a methodology to estimate the strength of handball teams using a statistical method. We propose the use of the Conway-Maxwell-Poisson distribution to model the number of goals scored by a team as a flexible discrete distribution which can handle situations of non equi-dispersion. From its parameters, we derive a mathematical formula

Ruichong Zhang

The learning of Gaussian Mixture Models (also referred to simply as GMMs) plays an important role in machine learning. Known for their expressiveness and interpretability, Gaussian mixture models have a wide range of applications, from statistics, computer vision to distributional reinforcement learning. However, as of today, few known algorithms can fit or

Florian Galliot, Sylvain Gravier, Isabelle Sivignon

We define a $q$-linear path in a hypergraph $H$ as a sequence $(e_1,\ldots,e_L)$ of edges of $H$ such that $|e_i \cap e_{i+1}| \in [\![1,q]\!]$ and $e_i \cap e_j=\varnothing$ if $|i-j|>1$. In this paper, we study the connected components associated to these paths when $q=k-2$ where $k$ is the rank of $H$. If $k=3$ then $q=1$ which coincides with the well-kno

Gavriel Habib, Noa Barzilay, Or Shimshi, Rami Ben-Ari

Gait Recognition is a computer vision task aiming to identify people by their walking patterns. Although existing methods often show high performance on specific datasets, they lack the ability to generalize to unseen scenarios. Unsupervised Domain Adaptation (UDA) tries to adapt a model, pre-trained in a supervised manner on a source domain, to an unlabelle

Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel

This paper proposes a novel multi-agent reinforcement learning (MARL) method to learn multiple coordinated agents under directed acyclic graph (DAG) constraints. Unlike existing MARL approaches, our method explicitly exploits the DAG structure between agents to achieve more effective learning performance. Theoretically, we propose a novel surrogate value fun

Pierpaolo Zuddas, Fernando Lopes

The periodical degassing from CO2 over-pressured reservoirs may have serious consequences for the environment making urgent understanding the processes and forecasting the frequency. Prediction though needs methods that depends from temporal and spatial properties of hydro-chemical and physical reservoir characteristics that unfortunately are often lacking.

Chow-Choong Ngeow, Jia-Yu Ou, Anupam Bhardwaj, Josiah Purdum

Based on 14 Miras located in 7 globular clusters, we derived the first gr-band period-luminosity (PL) at maximum light for the large-amplitude Mira variables using the multi-year light-curve data collected from the Zwicky Transient Facility (ZTF). Since Miras are red variables, we applied a color-term correction to subsets of ZTF light curves, and found that

Alain Connes, Caterina Consani

In the present paper, dedicated to Yuri Manin, we investigate the general notion of rings of $\mathbb S[\mu_{n,+}]$-polynomials and relate this concept to the known notion of number systems. The Riemann-Roch theorem for the ring $\mathbb Z$ of the integers that we obtained recently uses the understanding of $\mathbb Z$ as a ring of polynomials $\mathbb S[X]$

Félicien Filleul, Antonella Caldarelli, Kazunori Takahashi, Rod Boswell

Waves propagating along a converging-diverging rf magnetoplasma having the characteristics of a bounded m=0 helicon mode are reported and characterised. The discharge features a 30 cm separation between the region of radiofrequency energy deposition by a single loop antenna and the region of maximum magnetic field applied by a pair of coils. With 200 W of rf

Shuai Wang, Xu-Guang Huang

We demonstrate that in a chiral plasma subject to an external magnetic field, the chiral vortical effect can induce a new type of magnetohydrodynamic instability which we refer to as the {\it chiral magnetovortical instability}. This instability arises from the mutual evolution of the magnetic and vortical fields. It can cause a rapid amplification of the ma

Neil T. Lewis, Nicholas A. Lombardo, Peter L. Read, Juan M. Lora

We investigate the characteristics of equatorial waves associated with the maintenance of superrotation in the stratosphere of a Titan general circulation model. A variety of equatorial waves are present in the model atmosphere, including equatorial Kelvin waves, equatorial Rossby waves, and mixed Rossby-gravity waves. In the upper stratosphere, acceleration

Jacopo Ghiglieri, Guy D. Moore, Philipp Schicho, Niels Schlusser

The in-medium dispersion of hard partons, encoded in their so-called asymptotic mass, receives large non-perturbative contributions from classical gluons, i.e. soft gluons with large occupation numbers. Here, we discuss how the analytical properties of thermal amplitudes allow for a non-perturbative determination of the infrared classical contribution throug

Ramlal Debnath, Deepak K. Pradhan, Jaydeb Sarkar

Orthogonal projections onto closed subspaces of $H^2(\mathbb{D}^n)$ of the form $\varphi H^2(\mathbb{D}^n)$ for inner functions $\varphi$ on $\mathbb{D}^n$ are referred to as inner projections, where $H^2(\mathbb{D}^n)$ denotes the Hardy space over the open unit polydisc $\mathbb{D}^n$. In this paper, we classify pairs of commuting inner projections. We also

Gabriela Viale Pereira, Lukas Daniel Klausner, Lucy Temple, Thomas Delissen

Smart city solutions require innovative governance approaches together with the smart use of technology, such as digital twins, by city managers and policymakers to manage the big societal challenges. The project Smart Cities aNd Digital Twins in Lower Austria (SCiNDTiLA) extends the state of the art of research in several contributing disciplines and uses t

Jinhua Si, Fang He, Xi Lin, Xindi Tang

The integrated development of city clusters has given rise to an increasing demand for intercity travel. Intercity ride-pooling service exhibits considerable potential in upgrading traditional intercity bus services by implementing demand-responsive enhancements. Nevertheless, its online operations suffer the inherent complexities due to the coupling of vehi

Wei-Xi Guo, Fang-Mei Yang, Fu-Quan Dou

Quantum batteries are energy storage devices that satisfy quantum mechanical principles. How to obtain analytical solutions for quantum battery systems and achieve a full charging is a crucial element of the quantum battery. Here, we investigate the Rosen-Zener Quantum batteries are energy storage devices that satisfy quantum mechanical principles. How to ob

Johan S. Wind, Vegard Antun, Anders C. Hansen

Understanding the implicit regularization imposed by neural network architectures and gradient based optimization methods is a key challenge in deep learning and AI. In this work we provide sharp results for the implicit regularization imposed by the gradient flow of Diagonal Linear Networks (DLNs) in the over-parameterized regression setting and, potentiall

Libor Barto, Antoine Mottet

We provide an internal characterization of those finite algebras (i.e., algebraic structures) $\mathbf A$ such that the number of homomorphisms from any finite algebra $\mathbf X$ to $\mathbf A$ is bounded from above by a polynomial in the size of $\mathbf X$. Namely, an algebra $\mathbf A$ has this property if, and only if, no subalgebra of $\mathbf A$ has

Ilan Livne

Analysis of high-dimensional data, where the number of covariates is larger than the sample size, is a topic of current interest. In such settings, an important goal is to estimate the signal level $\tau^2$ and noise level $\sigma^2$, i.e., to quantify how much variation in the response variable can be explained by the covariates, versus how much of the vari

Chavdar Dangalchev

Closeness is one of the most studied characteristics of networks. Residual closeness is a very sensitive measure of graphs robustness. Additional closeness is a measure of growth potentials of networks. In this article we calculate the closeness, vertex residual closeness, link residual closeness, and additional closeness of lollipop graphs.

Miroslav Purkrabek, Jiri Matas

Methods and datasets for human pose estimation focus predominantly on side- and front-view scenarios. We overcome the limitation by leveraging synthetic data and introduce RePoGen (RarE POses GENerator), an SMPL-based method for generating synthetic humans with comprehensive control over pose and view. Experiments on top-view datasets and a new dataset of re

Xiangqi Wang, Dilinuer Aishan, Qi Liu

The effectiveness of graphical recommender system depends on the quantity and quality of negative sampling. This paper selects some typical recommender system models, as well as some latest negative sampling strategies on the models as baseline. Based on typical graphical recommender model, we divide sample region into assigned-n areas and use AdaSim to give

Tianlong Zhao, Xiang Ma, Xuemei Li, Caiming Zhang

Time series forecasting has received wide interest from existing research due to its broad applications and inherent challenging. The research challenge lies in identifying effective patterns in historical series and applying them to future forecasting. Advanced models based on point-wise connected MLP and Transformer architectures have strong fitting power,

Tsung-Yu Chen, Po-Hao Chou, Chung-Yu Mou

Materials that can host macroscopic persistent current are important because they are useful for energy storage. However, there are very few examples of such materials in nature. Superconductors are known as an example in which flow of supercurrent can persist up to 100,000 years. The chiral magnetic current is possibly the second example predicted by the ch

Jorge M. Ramirez, Juan M. Restrepo, Valerio Lucarini, David Weston

This paper introduces a novel approach to quantifying ecological resilience in biological systems, particularly focusing on noisy systems responding to episodic disturbances with sudden adaptations. Incorporating concepts from non-equilibrium statistical mechanics, we propose a measure termed `ecological resilience through adaptation,' specifically tailored

Patrick Gérard, Alexander Pushnitski

We establish an explicit formula for the solution of the the cubic Szeg\H{o} equation on the real line. Using this formula, we prove that the evolution flow of this equation can be continuously extended to the whole Hardy class $H^2$ on the real line.

Milan Hladík

This paper introduces a concept of a derivative of the optimal value function in linear programming (LP). Basically, it is the the worst case optimal value of an interval LP problem when the nominal data the data are inflated to intervals according to given perturbation patterns. By definition, the derivative expresses how the optimal value can worsen when t

Vicky Zhu, Robert Rosenbaum

In computational neuroscience, fixed points of recurrent neural networks are commonly used to model neural responses to static or slowly changing stimuli. These applications raise the question of how to train the weights in a recurrent neural network to minimize a loss function evaluated on fixed points. A natural approach is to use gradient descent on the E

Yizhou Liu, Binghai Yan

The ability to selectively excite light with fixed handedness is crucial for circularly polarized light emission. It is commonly believed that the luminescent material chirality determines the emitted light handedness, regardless of the light emitting direction. In this work, we propose an anomalous circular polarized light emission (ACPLE) whose handedness

Ben De Bondt, Ilijas Farah, Alessandro Vignati

We introduce a general method for showing under weak forcing axioms that reduced products of countable models of a theory $T$ have as few automorphisms as possible. We show that such forcing axioms imply that reduced products of countably infinite or finite fields, linear orders, trees, or random graphs have only trivial automorphisms. We also show that Todo

Rashid. Momin

Small Modular Reactors (SMRs) are compact nuclear power plants that offer various advantages for energy generation in a sustainable way. With their smaller and simplified designs, SMRs provide increased flexibility, lower capital costs, and enhanced safety features compared to traditional large-scale reactors by reducing the area accommodation drastically. T

Aurore Finco, Vincent Jacques

Despite the considerable interest for antiferromagnets which appeared with the perspective of using them for spintronics, their experimental study, including the imaging of antiferromagnetic textures, remains a challenge. To address this issue, quantum sensors, and in particular the nitrogen-vacancy (NV) defects in diamond have become a widespread technical

Bryn Davies, Yiqi Lou

High-contrast scattering problems are special among classical wave systems as they allow for strong wave focusing and localisation at low frequencies. We use an asymptotic framework to develop a landscape theory for high-contrast systems that resonate in a subwavelength regime. Our from-first-principles asymptotic analysis yields a characterisation in terms

Xinliang Dai, Yingzhao Lian, Yuning Jiang, Colin N. Jones

This paper presents a novel distributed approach for solving AC power flow (PF) problems. The optimization problem is reformulated into a distributed form using a communication structure corresponding to a hypergraph, by which complex relationships between subgrids can be expressed as hyperedges. Then, a hypergraph-based distributed sequential quadratic prog

Ryo Takahashi, Naoki Wakasugi

Let $R$ be a commutative noetherian ring and $I$ an ideal of $R$. Assume that for all integers $i$ the local cohomology module $H_I^i(R)$ is $I$-cofinite. Suppose that $R_\mathfrak{p}$ is a regular local ring for all prime ideals $\mathfrak{p}$ that do not contain $I$. In this paper, we prove that if the $I$-cofinite modules forms an abelian category, then f

Hendric Voß, Stefan Kopp

Due to their significance in human communication, the automatic generation of co-speech gestures in artificial embodied agents has received a lot of attention. Although modern deep learning approaches can generate realistic-looking conversational gestures from spoken language, they often lack the ability to convey meaningful information and generate contextu

Victor Schetinger, Sara Di Bartolomeo, Edirlei Soares de Lima, Christofer Meinecke

This paper presents a novel exploration of the interaction between generative AI models, visualization, and narrative generation processes, using OpenAI's GPT as a case study. We look at the question "Where Does Generativeness Comes From", which has a simple answer at the intersection of many domains. Drawing on Umberto Eco's "Six Walks in the Fictional Wood

Danila A. Barskiy, John W. Blanchard, Dmitry Budker, Quentin Stern

The combination of a powerful and broadly applicable nuclear hyperpolarization technique with emerging (near-)zero-field modalities offer novel opportunities in a broad range of nuclear magnetic resonance spectroscopy and imaging applications, including biomedical diagnostics, monitoring catalytic reactions within metal reactors and many others. These are di

Umang Bhaskar, Neeldhara Misra, Aditi Sethia, Rohit Vaish

In fair division problems, the notion of price of fairness measures the loss in welfare due to a fairness constraint. Prior work on the price of fairness has focused primarily on envy-freeness up to one good (EF1) as the fairness constraint, and on the utilitarian and egalitarian welfare measures. Our work instead focuses on the price of equitability up to o

Patrick Jentsch, Chiu Fan Lee

In active matter systems, non-Gaussian, exact scaling exponents have been claimed in a range of systems using perturbative renormalization group (RG) methods. This is unusual compared to equilibrium systems where non-Gaussian exponents can typically only be approximated, even using the exact (or functional/nonperturbative) renormalization group (ERG). Here,

Abdelbadie Belmouhcine, Jean-Christophe Burnel, Luc Courtrai, Minh-Tan Pham

Object detection in remote sensing is a crucial computer vision task that has seen significant advancements with deep learning techniques. However, most existing works in this area focus on the use of generic object detection and do not leverage the potential of multimodal data fusion. In this paper, we present a comparison of methods for multimodal object d

Nairen Cao, Shang-En Huang, Hsin-Hao Su

In this paper, we study parallel algorithms for the correlation clustering problem, where every pair of two different entities is labeled with similar or dissimilar. The goal is to partition the entities into clusters to minimize the number of disagreements with the labels. Currently, all efficient parallel algorithms have an approximation ratio of at least

Martina Toscani, Ollie Burke, Chang Liu, Nour Bou Zamel

In this work, we investigate detection rates and parameter estimation of strongly-lensed extreme mass-ratio inspirals (LEMRIs) in the context of the Laser Interferometer Space Antenna (LISA). Our results indicate that LEMRIs constitute a new gravitational-wave target signal for LISA, with detection rates ranging from zero to $\sim 40$ events over a four year

Sho Shimoyama, Tetsuro Morimura, Kenshi Abe, Toda Takamichi

Dialog policies, which determine a system's action based on the current state at each dialog turn, are crucial to the success of the dialog. In recent years, reinforcement learning (RL) has emerged as a promising option for dialog policy learning (DPL). In RL-based DPL, dialog policies are updated according to rewards. The manual construction of fine-grained

Minh-Tan Pham, Hugo Gangloff, Sébastien Lefèvre

This paper studies a reconstruction-based approach for weakly-supervised animal detection from aerial images in marine environments. Such an approach leverages an anomaly detection framework that computes metrics directly on the input space, enhancing interpretability and anomaly localization compared to feature embedding methods. Building upon the success o

Simon Casassus, Lucas Cieza, Miguel Cárcamo, Álvaro Ribas

Environmental effects, such as stellar fly-bys and external irradiation, are thought to affect the evolution of protoplanetary disks in clustered star formation. Previous ALMA images at 225 GHz of the ISO-Oph 2 binary revealed a peculiar morphology in the disk of the primary, perhaps due to a possible fly-by with the secondary. Here we report on new ALMA con

Yuhang Chen

In this paper we study equivariant moduli spaces of sheaves on a $ K3 $ surface $ X $ under a symplectic action of a finite group. We prove that under some mild conditions, equivariant moduli spaces of sheaves on $ X $ are irreducible symplectic manifolds deformation equivalent to Hilbert schemes of points on $ X $ via a connection between Gieseker and Bridg

M. Hinderling, S. C. ten Kate, D. Z. Haxell, M. Coraiola

Properties of superconducting devices depend sensitively on the parity (even or odd) of the quasiparticles they contain. Encoding quantum information in the parity degree of freedom is central in several emerging solid-state qubit architectures. Yet, accurate, non-destructive, and time-resolved parity measurement is a challenging and long-standing issue. Her

Jan Robert Schmidt, Arnd Bäcker, Roland Ketzmerick

We demonstrate that quantum dynamical localization in the Arnold web of higher-dimensional Hamiltonian systems is destroyed by an intrinsic classical drift. Thus quantum wave packets and eigenstates may explore more of the intricate Arnold web than previously expected. Such a drift typically occurs, as resonance channels widen toward a large chaotic region o

Hao Liu, Chao Wang, Wen Liang Tan, Lars Thomsen

We present a "one-step" approach to modify ZnO electron transport layers (ETLs) used in organic solar cells. This approach involves adding benzoic acid (BZA) derivatives directly to the ZnO precursor solution, which are then present at the surface of the resulting ZnO film. We demonstrate this approach for three different BZA derivatives, namely benzoic acid

Philippe Ratajczak, Eric Séguenot, Dinh-Thuy Phan-Huy

Reconfigurable intelligent surface (RIS) is a promising solution to boost coverage sustainably by reflecting waves from a transmitter to a receiver and acting as a low-power and passive relay. In this paper, for the first time, we demonstrate experimentally that a reconfigurable intelligent surface designed for sub6GHz, and using varactor technology, can per

M. Coraiola, D. Z. Haxell, D. Sabonis, M. Hinderling

Harnessing spin and parity degrees of freedom is of fundamental importance for the realization of emergent quantum devices. Nanostructures embedded in superconductor--semiconductor hybrid materials offer novel and yet unexplored routes for addressing and manipulating fermionic modes. Here we spectroscopically probe the two-dimensional band structure of Andre

Zheyu Wu, Junjie Ma, Ya-Feng Liu, A. Lee Swindlehurst

A promising approach to deal with the high hardware cost and energy consumption of massive MIMO transmitters is to use low-resolution digital-to-analog converters (DACs) at each antenna element. This leads to a transmission scheme where the transmitted signals are restricted to a finite set of voltage levels. This paper is concerned with the analysis and opt

Lautaro Estienne, Luciana Ferrer, Matías Vera, Pablo Piantanida

A wide variety of natural language tasks are currently being addressed with large-scale language models (LLMs). These models are usually trained with a very large amount of unsupervised text data and adapted to perform a downstream natural language task using methods like fine-tuning, calibration or in-context learning. In this work, we propose an approach t

Bernard Helffer, Ayman Kachmar, Mikael Persson Sundqvist

Motivated by the analysis of the tunneling effect for the magnetic Laplacian, we introduce an abstract framework for the spectral reduction of a self-adjoint operator to a hermitian matrix. We illustrate this framework by three applications, firstly the electro-magnetic Laplacian with constant magnetic field and three equidistant potential wells, secondly a

Ilya Sychugov

It is shown that reciprocity of the optical path can be violated through asymmetric strength coupling via near-field from resonant Mie scatterers to total internal reflection modes in a dielectric slab. Numerical simulations for silicon nanospheres separated by a nanogap from the glass substrate reveal that at least two orders of magnitude rectification rati

Chellasamy Jebarathinam, Gautam Sharma, Sk Sazim, Remigiusz Augusiak

Self-testing of quantum devices based on observed measurement statistics is a method to certify quantum systems using minimal resources. In Ref. [Phys. Rev. \textbf{A} 101, 032106 (2020)], a scheme based on observing measurement statistics that demonstrate Kochen-Specker contextuality has been shown to certify two-qubit entangled states and measurements with

Ousmane Touat, Julian Stier, Pierre-Edouard Portier, Michael Granitzer

A wide variety of generative models for graphs have been proposed. They are used in drug discovery, road networks, neural architecture search, and program synthesis. Generating graphs has theoretical challenges, such as isomorphic representations -- evaluating how well a generative model performs is difficult. Which model to choose depending on the applicati

Christopher Weiss, Frauke Kreuter, Ivan Habernal

Although the NLP community has adopted central differential privacy as a go-to framework for privacy-preserving model training or data sharing, the choice and interpretation of the key parameter, privacy budget $\varepsilon$ that governs the strength of privacy protection, remains largely arbitrary. We argue that determining the $\varepsilon$ value should no

Chen Ran, Yuri Ozhigov

The chemical dynamics scene is the most important application of computer simulation. We show that electrons jump between potential holes of different depths (new molecular orbits, hybrid atomic orbits with different energies) under the influence of temperature (phonons) and photon phenomena. To overcome exponentially increasing computational complexity. In

Carlos Matamala, Luis Badesa, Rodrigo Moreno, Goran Strbac

The reduction in system inertia is creating an important market for frequency-containment Ancillary Services (AS) such as enhanced frequency response (e.g.,~provided by battery storage), traditional primary frequency response and inertia itself. This market presents an important difference with the energy-only market: while the need for energy production is

P. S. Alekseev, A. P. Dmitriev

In high-quality conductors, the hydrodynamic regime of electron transport has been recently realized. In this work we theoretically investigate magnetotransport of a viscous electron fluid in samples with electron-impermeable obstacles. We use the two approaches to describe the fluid flow. The first one is based on the equations of hydrodynamics of a charged

Armando Bermudez Martinez

Two main frameworks for defining transverse momentum dependent (TMD) parton densities are the Collins-Soper-Sterman (CSS) formalism, and the Parton Branching (PB) approach. While PB-TMDs have an explicit dependence on a single scale which is used to evolve PB-TMDs in momentum space, TMDs defined in CSS formalism present a double-scale evolution in renormaliz

Wentao Deng, Jiahuan Pei, Zhaochun Ren, Zhumin Chen

Answer selection in open-domain dialogues aims to select an accurate answer from candidates. Recent success of answer selection models hinges on training with large amounts of labeled data. However, collecting large-scale labeled data is labor-intensive and time-consuming. In this paper, we introduce the predicted intent labels to calibrate answer labels in

Sthitadhi Roy

Many-body localised phases of disordered, interacting quantum systems allow for exotic localisation protected quantum order in eigenstates at arbitrarily high energy densities. In this work, we analyse the manifestation of such order on the Hilbert-space anatomy of eigenstates. Quantified in terms of non-local Hilbert-spatial correlations of eigenstate ampli

Mohammad Adiban, Kalin Stefanov, Sabato Marco Siniscalchi, Giampiero Salvi

We address the video prediction task by putting forth a novel model that combines (i) a novel hierarchical residual learning vector quantized variational autoencoder (HR-VQVAE), and (ii) a novel autoregressive spatiotemporal predictive model (AST-PM). We refer to this approach as a sequential hierarchical residual learning vector quantized variational autoen

Reijo Jaakkola, Tomi Janhunen, Antti Kuusisto, Masood Feyzbakhsh Rankooh

We investigate explainability via short Boolean formulas in the data model based on unary relations. As an explanation of length k, we take a Boolean formula of length k that minimizes the error with respect to the target attribute to be explained. We first provide novel quantitative bounds for the expected error in this scenario. We then also demonstrate ho

Nicolas Nisse, Lucas Picasarri-Arrieta, Ignasi Sau

Given a digraph $D=(V,A)$ on $n$ vertices and a vertex $v\in V$, the cycle-degree of $v$ is the minimum size of a set $S \subseteq V(D) \setminus \{v\}$ intersecting every directed cycle of $D$ containing $v$. From this definition of cycle-degree, we define the $c$-degeneracy (or cycle-degeneracy) of $D$, which we denote by $\delta^*_c(D)$. It appears to be

Jacob Collard, Valeria de Paiva, Eswaran Subrahmanian

Mathematics is a highly specialized domain with its own unique set of challenges that has seen limited study in natural language processing. However, mathematics is used in a wide variety of fields and multidisciplinary research in many different domains often relies on an understanding of mathematical concepts. To aid researchers coming from other fields, w

Thiviyan Thanapalasingam, Emile van Krieken, Peter Bloem, Paul Groth

Knowledge Graph Embedding (KGE) models are used to learn continuous representations of entities and relations. A key task in the literature is predicting missing links between entities. However, Knowledge Graphs are not just sets of links but also have semantics underlying their structure. Semantics is crucial in several downstream tasks, such as query answe

G. J. Groenewald, S. ter Horst, J. J. Jaftha, A. C. M. Ran

In a recent paper (Groenewald et al.\ {\em Complex Anal.\ Oper.\ Theory} \textbf{15:1} (2021)) we considered an unbounded Toeplitz-like operator $T_\Omega$ generated by a rational matrix function $\Omega$ that has poles on the unit circle $\mathbb{T}$ of the complex plane. A Wiener-Hopf type factorization was proved and this factorization was used to determi

Liming Ling, Xuan Sun

We present elliptic-rogue wave solutions for integrable nonlinear soliton equations in theta functions. Unlike solutions generated on the plane wave background, these solutions depict rogue waves emerging on elliptic function backgrounds. By refining the modified squared wave function method in tandem with the Darboux-B\"acklund transformation, we establish

Elena Rodriguez-Lois, Fernando Perez-Gonzalez

The growing popularity of Deep Neural Networks, which often require computationally expensive training and access to a vast amount of data, calls for accurate authorship verification methods to deter unlawful dissemination of the models and identify the source of the leak. In DNN watermarking the owner may have access to the full network (white-box) or only

P. Swaczyna, M. Bzowski, J. Heerikhuisen, M. A. Kubiak

In situ observations of interstellar neutral (ISN) helium atoms by the IBEX-Lo instrument onboard the Interstellar Boundary Explorer (IBEX) mission are used to determine the velocity and temperature of the pristine very local interstellar medium (VLISM). Most ISN helium atoms penetrating the heliosphere, known as the primary population, originate in the pris

Leandro Lanzieri, Peter Kietzmann, Goerschwin Fey, Holger Schlarb

Ageing detection and failure prediction are essential in many Internet of Things (IoT) deployments, which operate huge quantities of embedded devices unattended in the field for years. In this paper, we present a large-scale empirical analysis of natural SRAM wear-out using 154 boards from a general-purpose testbed. Starting from SRAM initialization bias, wh

O. C. Jones, P. J. Kavanagh, M. J. Barlow, T. Temim

Supernova (SN) 1987A is the nearest supernova in $\sim$400 years. Using the {\em JWST} MIRI Medium Resolution Spectrograph, we spatially resolved the ejecta, equatorial ring (ER) and outer rings in the mid-infrared 12,927 days after the explosion. The spectra are rich in line and dust continuum emission, both in the ejecta and the ring. Broad emission lines

Julian Parsert, Elizabeth Polgreen

Program synthesis is the task of automatically generating code based on a specification. In Syntax-Guided Synthesis (SyGuS) this specification is a combination of a syntactic template and a logical formula, and the result is guaranteed to satisfy both. We present a reinforcement-learning guided algorithm for SyGuS which uses Monte-Carlo Tree Search (MCTS) to

Madhavan Mukund, Adwitee Roy, B Srivathsan

Negotiations, introduced by Esparza et al., are a model for concurrent systems where computations involving a set of agents are described in terms of their interactions. In many situations, it is natural to impose timing constraints between interactions -- for instance, to limit the time available to enter the PIN after inserting a card into an ATM. To model

Tianjun Gan, Charles Cadieux, Farbod Jahandar, Allona Vazan

Observations and statistical studies have shown that giant planets are rare around M dwarfs compared with Sun-like stars. The formation mechanism of these extreme systems remains under debate for decades. With the help of the TESS mission and ground based follow-up observations, we report the discovery of TOI-4201b, the most massive and densest hot Jupiter a

Mohammad Enayati, Jean-Pierre Gazeau, Mariano A. del Olmo, Hamed Pejhan

We elaborate the definition and properties of "massive" elementary systems in the $(1+3)$-dimensional Anti-de Sitter (AdS$_4$) spacetime, on both classical and quantum levels. We fully exploit the symmetry group {isomorphic to} Sp$(4,R)$, that is, the two-fold covering of SO$_0(2,3)$ (Sp$(4,\mathbb R) \sim$ SO$_0(2,3)\times \mathbb Z_2$), recognized as the r

Kai Su, Yoichi Tomioka, Qiangfu Zhao, Yong Liu

In the realm of Tiny AI, we introduce ``You Only Look at Interested Cells" (YOLIC), an efficient method for object localization and classification on edge devices. Through seamlessly blending the strengths of semantic segmentation and object detection, YOLIC offers superior computational efficiency and precision. By adopting Cells of Interest for classificat

Andrew Alexander Vekinis, Stavros Perantonis

Heading towards navigational autonomy in unmanned surface vehicles (USVs) in the maritime sector can fundamentally lead towards safer waters as well as reduced operating costs, while also providing a range of exciting new capabilities for oceanic research, exploration and monitoring. However, achieving such a goal is challenging. USV control systems must, sa

Kai Li, Billy Pik Lik Lau, Xin Yuan, Wei Ni

In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which leverages advanced semantic understanding and representation to enable seamless, context-aware interactions within mixed-reality environments. This survey focuses on the intellig

Atsuhide Ishida

Different from the usual harmonic oscillator, the time-decaying harmonic oscillator accelerates particles and generates scattering states. We study one of the multidimensional inverse scatterings in this two-body quantum system perturbed by short-range potential functions that have a bounded part and a locally singular part. Applying the Enss--Weder time-dep

Ira W. Herbst, Jesper Møller, Anne Marie Svane

Let $X_1,X_2,...$ be the digits in the base-$q$ expansion of a random variable $X$ defined on $[0,1)$ where $q\ge2$ is an integer. For $n=1,2,...$, we study the probability distribution $P_n$ of the (scaled) remainder $T^n(X)=\sum_{k=n+1}^\infty X_k q^{n-k}$: If $X$ has an absolutely continuous CDF then $P_n$ converges in the total variation metric to the Le

Longben Wei, Zhiwen Duan, Hui Xu

We provide necessary and sufficient geometric conditions for the exact observability of the Schr\"odinger equation with inverse-square potentials on the half-line. These conditions are derived from a Logvinenko-Sereda type theorem for generalized Fourier transform. Specifically, the generalized Fourier transform associated with the Schr\"odinger operator wit

Susan Athey, Lisa K. Simon, Oskar N. Skans, Johan Vikstrom

Using rich Swedish administrative data, we apply causal machine learning methods to study how earnings losses after job displacement vary with observable characteristics that may be relevant for targeting policy interventions for workers. Heterogeneity in effects is as large within as across worker groups defined by age and schooling, and as large within as

Akshansh Mishra, Vijaykumar S Jatti

In this study, we investigate the application of supervised machine learning algorithms for estimating the Ultimate Tensile Strength (UTS) of Polylactic Acid (PLA) specimens fabricated using the Fused Deposition Modeling (FDM) process. A total of 31 PLA specimens were prepared, with Infill Percentage, Layer Height, Print Speed, and Extrusion Temperature serv

Dylan Lewis, Stephan Eidenbenz, Balasubramanya Nadiga, Yiğit Subaşı

We investigate the limitations of quantum computers for solving nonlinear dynamical systems. In particular, we tighten the worst-case bounds of the quantum Carleman linearisation (QCL) algorithm [Liu et al., PNAS 118, 2021] answering one of their open questions. We provide a further significant limitation for any quantum algorithm that aims to output a quant

Raimund Preusser

Leavitt path algebras of bi-separated graphs have been recently introduced by R. Mohan and B. Suhas. These algebras provide a common framework for studying various generalisations of Leavitt path algebras. In this paper we obtain modules for the Leavitt path algebra $L(\dot E)$ of a finitely bi-separated graph $\dot{E}=(E,C,D)$ by introducing the notion of a

Charalampos Antonakos, Andreas F. Terzis

This paper presents a hydrodynamical view of the Aharonov-Bohm effect, using Nelson's formulation of quantum mechanics. Our aim is to compare our results with other systems and gain a better understanding of the mysteries behind this effect, such as why the motion of a particle is affected in a region where there is no magnetic field. Some theories suggest t

Claire Birnie, Matteo Ravasi

The presence of coherent noise in seismic data leads to errors and uncertainties, and as such it is paramount to suppress noise as early and efficiently as possible. Self-supervised denoising circumvents the common requirement of deep learning procedures of having noisy-clean training pairs. However, self-supervised coherent noise suppression methods require

Kyrre Ness Sjobak, Hikmet Bursali, Antonio Gillardi, Reidar Lillestøl

The Wake Field Monitor (WFM) system installed on the CLIC prototype accelerating structure in CERN Linear Accelerator for Research (CLEAR) has two channels for each horizontal/vertical plane, operating at different frequencies. When moving the beam relative to the aperture of the structure, a disagreement is observed between the center position of the struct

Maxime Grosso, Pierre Riedinger, Jamal Daafouz, Serge Pierfederici

In this paper, we propose a harmonic-model based control approach for the three-phase grid-tied AC-DC converter. We derive a nonlinear harmonic domain model and demonstrate its efficacy in designing harmonic control with global stability guarantees. Furthermore, we establish that this harmonic control design can be translated into a periodic nonlinear contro

Saulo V. Moreira, Peter Samuelsson, Patrick P. Potts

In nano-scale systems coupled to finite-size reservoirs, the reservoir temperature may fluctuate due to heat exchange between the system and the reservoirs. To date, a stochastic thermodynamic analysis of heat, work and entropy production in such systems is however missing. Here we fill this gap by analyzing a single-level quantum dot tunnel coupled to a fin

Mitchell Lee

We define an abelian group homomorphism $\mathscr{F}$, which we call the Frobenius transform, from the ring of symmetric functions to the ring of the symmetric power series. The matrix entries of $\mathscr{F}$ in the Schur basis are the restriction coefficients $r_\lambda^\mu = \dim \operatorname{Hom}_{\mathfrak{S}_n}(V_\mu, \mathbb{S}^\lambda \mathbb{C}^n)$