April 2023 arXiv papers — page 72

C. Mehlmann, G. Capodaglio, S. Danilov

Linear Kinematic Features (LKFs) are found everywhere in the Arctic sea-ice cover. They are strongly localized deformations often associated with the formation of leads and pressure ridges. Viscous-plastic sea-ice models start to produce LKFs at high spatial grid resolution, typically with a grid spacing below 5 km. A recent study showed that the placement o

Ludvig Sinander

I revisit the standard moral-hazard model, in which an agent's preference over contracts is rooted in costly effort choice. I characterise the behavioural content of the model in terms of empirically testable axioms, and show that the model's parameters are identified. I propose general behavioural definitions of relative (over)confidence and optimism, and c

Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li

Bayesian methods for solving inverse problems are a powerful alternative to classical methods since the Bayesian approach offers the ability to quantify the uncertainty in the solution. In recent years, data-driven techniques for solving inverse problems have also been remarkably successful, due to their superior representation ability. In this work, we inco

José Augusto Proença Maia Devienne

Twitter is a microblogging service for sending short, public text messages (tweets) that has recently received more attention in scientific comunity. In the works of Sasaki et al. (2010) and Earle et al., (2011) the authors explored the real-time interaction on Twitter for detecting natural hazards (e.g., earthquakes, typhoons) baed on users' tweets. An inhe

Clemens Todt, Sjoerd Telkamp, Filip Krizek, Christian Reichl

We present Nb thin films deposited in-situ on GaAs by combining molecular beam epitaxy and magnetron sputtering within an ultra-high vacuum cluster. Nb films deposited at varying power, and a reference film from a commercial system, are compared. The results show clear variation between the in-situ and ex-situ deposition which we relate to differences in mag

Michael Hallam

We show that if a compact K\"ahler manifold admits a weighted extremal metric for the action of a torus, so too does its blowup at a relatively stable point that is fixed by both the torus action and the extremal field. This generalises previous results on extremal metrics by Arezzo--Pacard--Singer and Sz\'ekelyhidi to many other canonical metrics, including

Jason Lynch, Evan Smith, Adam Alfieri, Baokun Song

Telecommunications and polarimetry both require the active control of the polarization of light, Currently, this is done by combining intrinsically anisotropic materials with tunable isotropic materials into heterostructures using complicated fabrication techniques due to the lack of scalable materials that possess both properties. Tunable birefringent and d

Jiaxing Liu, Ping Zhu, Dominique Franck Escande, Junli Zhang

A recently developed plasma-wall self-organization (PWSO) model predicts a significantly enhanced density limit, which may be attainable in tokamaks with ECRH-assisted ohmic startup and sufficiently high initial neutral density. Experiments have been conducted on J-TEXT to validate such a density limit scenario based on this model. Experimental results demon

Livia Betti, Irfan Durmić, Zoe McDonald, Jack B. Miller

We make progress on a conjecture made by [DM], which states that the $d$-dimensional frames of $m$-dimensional boxes resulting from a fragmentation process satisfy Benford's law for all $1 \leq d \leq m$. We provide a sufficient condition for Benford's law to be satisfied, namely that the maximum product of $d$ sides is itself a Benford random variable. Moti

Steve Huntsman

We develop tools for explicitly constructing categories enriched over generating data and that compose via ordinary scalar and matrix arithmetic arithmetic operations. We characterize meaningful size maps, weightings, and magnitude that reveal features analogous to outliers that these same notions have previously been shown to reveal in the context of metric

Zhencheng Li, Zhen Jiang, Xi-Long Fan, Yun Chen

An enormous number of compact binary systems, spanning from stellar to supermassive levels, emit substantial gravitational waves during their final evolutionary stages, thereby creating a stochastic gravitational wave background (SGWB). We calculate the merger rates of stellar compact binaries and massive black hole binaries using a semi-analytic galaxy form

Adamantios Ntakaris, Moncef Gabbouj, Juho Kanniainen

High-frequency trading requires fast data processing without information lags for precise stock price forecasting. This high-paced stock price forecasting is usually based on vectors that need to be treated as sequential and time-independent signals due to the time irregularities that are inherent in high-frequency trading. A well-documented and tested metho

Stefan Kindermann, Elena Resmerita, Tobias Wolf

The Multiscale Hierarchical Decomposition Method (MHDM) was introduced as an iterative method for total variation regularization, with the aim of recovering details at various scales from images corrupted by additive or multiplicative noise. Given its success beyond image restoration, we extend the MHDM iterates in order to solve larger classes of linear ill

Bareld Wit, Georg Gramse, Stefan Müllegger

We outline calibrated measurements of the microwave reflection coefficient from the tunnel junction of an ultra-high vacuum low temperature scanning tunneling microscope. The microwave circuit design is described in detail, including an interferometer for enhanced signal-to-noise and a demodulation scheme for lock-in detection. A quantitative, in-situ proced

Ying Liu, Andrea Turrini, Moritz Hahn, Bai Xue

In this paper, we propose an approximating framework for analyzing parametric Markov models. Instead of computing complex rational functions encoding the reachability probability and the reward values of the parametric model, we exploit the scenario approach to synthesize a relatively simple polynomial approximation. The approximation is probably approximate

Irene I. Bouw, Duc Khoi Do, Stefan Wewers

We study the Weil representation $\rho$ of a curve over a $p$-adic field with potential reduction of compact type. We show that $\rho$ can be reconstructed from its stable reduction. For superelliptic curves of the form $y^n=f(x)$ at primes $p$ whose residue characteristic is prime to the exponent $n$ we make this explicit.

José Augusto Proença Maia Devienne

The recent exploitation of natural resources and associated waste water injection in the subsurface have induced many small and moderate earthquakes in the tectonically quiet Central United States. This increase in seismic activity has produced an exponential growth of seismic data recording, which brings the necessity for efficient algorithms to reliably de

Yi-Pei Chen, An-Zi Yen, Hen-Hsen Huang, Hideki Nakayama

Lifelogging has gained more attention due to its wide applications, such as personalized recommendations or memory assistance. The issues of collecting and extracting personal life events have emerged. People often share their life experiences with others through conversations. However, extracting life events from conversations is rarely explored. In this pa

Andrey Kofnov, Ezio Bartocci, Efstathia Bura

We propose the K-series estimation approach for the recovery of unknown univariate and multivariate distributions given knowledge of a finite number of their moments. Our method is directly applicable to the probabilistic analysis of systems that can be represented as probabilistic loops; i.e., algorithms that express and implement non-deterministic processe

Ashish Kumar Meena, Jasjeet Singh Bagla

A source lying near hyperbolic umbilic (HU) leads to a ring-like image formation, constituting four images with high magnification factors and lying in a small region of the lens plane. Since (based on our earlier work) the observed number of HU image formations in cluster lenses is expected to increase in future, it is timely to investigate them in more det

Yuxuan Chen, Jing Sun, Boqi Meng

The working principle of a electric current transformer is based on electromagnetic induction, mainly composed of a closed iron core and windings. Its primary winding has relatively few turns and is connected in series with the current circuit to be measured. However, due to the frequent occurrence of full current passing through the current transformer duri

Babak Maboudi Afkham, Julianne Chung, Matthias Chung

In this work, we describe a new approach that uses variational encoder-decoder (VED) networks for efficient goal-oriented uncertainty quantification for inverse problems. Contrary to standard inverse problems, these approaches are \emph{goal-oriented} in that the goal is to estimate some quantities of interest (QoI) that are functions of the solution of an i

Viraj Kalsariya, Shibesh Kumar Jas Pacif

Our objective in this paper is to study the late-time behavior of the universe in a model resulting from a parametrization of the Hubble parameter ($H$) in $f(Q,T)$ gravity. We have considered the flat Friedmann-Lemaitre-Robertson-Walker (FLRW) as the background metric and discussed the model in $f(Q,T)$ gravity, where $Q$ and $T$ are non-metricity and the t

Zhanzhi Jiang, Su Kong Chong, Peng Zhang, Peng Deng

We report the implementation of a dilution-refrigerator-based scanning microwave impedance microscope (MIM) with a base temperature of ~ 100 mK. The vibration noise of our apparatus with tuning-fork feedback control is as low as 1 nm. Using this setup, we have demonstrated the imaging of quantum anomalous Hall states in magnetically (Cr and V) doped (Bi, Sb)

Akash Dhasade, Anne-Marie Kermarrec, Rafael Pires, Rishi Sharma

Decentralized learning (DL) has gained prominence for its potential benefits in terms of scalability, privacy, and fault tolerance. It consists of many nodes that coordinate without a central server and exchange millions of parameters in the inherently iterative process of machine learning (ML) training. In addition, these nodes are connected in complex and

T. Takeda, T. Tamagawa, T. Enoto, T. Kitaguchi

We present a gas selection for Xe-based gas electron multiplier (GEM) detectors, Gas Multiplier Counters (GMCs) onboard the CubeSat X-ray observatory NinjaSat. To achieve an energy bandpass of 2-50 keV, we decided to use a Xe-based gas mixture at a pressure of 1.2 atm that is sensitive to high-energy X-rays. In addition, an effective gain of over 300 is requ

Tannan Xiao, Ying Chen, Han Diao, Shaowei Huang

Power system optimal dispatch with transient security constraints is commonly represented as Transient Security-Constrained Optimal Power Flow (TSC-OPF). Deep Reinforcement Learning (DRL)-based TSC-OPF trains efficient decision-making agents that are adaptable to various scenarios and provide solution results quickly. However, due to the high dimensionality

Elias Werner, Nishant Kumar, Matthias Lieber, Sunna Torge

Concept drift detection is crucial for many AI systems to ensure the system's reliability. These systems often have to deal with large amounts of data or react in real-time. Thus, drift detectors must meet computational requirements or constraints with a comprehensive performance evaluation. However, so far, the focus of developing drift detectors is on infe

Luke T. Maud, Andrés F. Pérez-Sánchez, Yoshiharu Asaki, Felix Stoehr

We present a long-term overview of the atmospheric phase stability at the Atacama Large Millimeter/submillimeter Array (ALMA) site, using >5 years of data, that acts as the successor to the studies summarized two decades ago by Evans et al 2003. Importantly, we explore the atmospheric variations, the `phase RMS', and associated metadata of over 17000 accrued

Carlos Hernandez-Suarez

The Lotka-Euler equation is a mathematical expression used to study population dynamics and growth, particularly in the context of demography and ecology. The growth rate $\lambda$ is the speed at which an individual produce their offspring. It is essentially a birth process, and here it is shown that by reversing the process to a death process, in which ind

José Augusto Proença Maia Devienne

In Geosciences a class of phenomena that is widely studied given its real impact on human life are the tectonic faults slip. These landslides have different ways to manifest, ranging from aseismic events of slow displacement (slow slips) to ordinary earthquakes. An example of continuous slow slip event was identified in Cascadia, near the island of Vancouver

Lucie-Aimée Kaffee, Arnav Arora, Zeerak Talat, Isabelle Augenstein

Dual use, the intentional, harmful reuse of technology and scientific artefacts, is a problem yet to be well-defined within the context of Natural Language Processing (NLP). However, as NLP technologies continue to advance and become increasingly widespread in society, their inner workings have become increasingly opaque. Therefore, understanding dual use co

Chen Qian, Jicheng Jin, Thomas Christensen, Li He

Highly spatially-squeezed polaritons, with propagation momentum significantly larger than free-space modes at the same frequency, enable varied and extreme control over light-matter interaction. Compared to other polaritons, surface magnon polaritons, the magnetic counterpart of surface phonon polaritons, have received relatively little attention. Here, we i

Ariel Davis, Tomer M. Schlank

Given a finite quandle $Q$, we study the average number of $Q$-colorings of the closure of a random braid in $B_n$ as $n$ varies. In particular we show that this number coincides with some polynomial $P_Q\in \mathbb{Q}[x]$ for $n\gg 0$. The degree of this polynomial is readily computed in terms of $Q$ as a quandle and these invariants are computed for all qu

Bosco García-Archilla, Volker John, Sarah Katz, Julia Novo

Reduced order methods (ROMs) for the incompressible Navier--Stokes equations, based on proper orthogonal decomposition (POD), are studied that include snapshots which approach the temporal derivative of the velocity from a full order mixed finite element method (FOM). In addition, the set of snapshots contains the mean velocity of the FOM. Both the FOM and t

Junyu Lin, Guanghua Chen, Mucan Jin, Zhaopeng Shi

Recent years have witnessed tremendous progresses in creating and manipulating ground-state ultracold polar molecules. However, the two-body loss regardless of the chemical reactivities is still a hurdle for many future explorations. Here, we investigate the loss suppression of non-reactive bosonic $^{23}$Na$^{87}$Rb molecules with a circular polarized micro

Giuseppe Gaeta, Epifanio G. Virga

In its most restrictive definition, an octupolar tensor is a fully symmetric traceless third-rank tensor in three space dimensions. So great a body of works have been devoted to this specific class of tensors and their physical applications that a review would perhaps be welcome by a number of students. Here, we endeavour to place octupolar tensors into a br

Julian Ruddick, Luis Ramirez Camargo, Muhammad Andy Putratama, Maarten Messagie

Energy management systems (EMS) have traditionally been implemented using rule-based control (RBC) and model predictive control (MPC) methods. However, recent research has explored the use of reinforcement learning (RL) as a promising alternative. This paper introduces TreeC, a machine learning method that utilizes the covariance matrix adaptation evolution

Agustinus Kristiadi, Alexander Immer, Runa Eschenhagen, Vincent Fortuin

The linearized-Laplace approximation (LLA) has been shown to be effective and efficient in constructing Bayesian neural networks. It is theoretically compelling since it can be seen as a Gaussian process posterior with the mean function given by the neural network's maximum-a-posteriori predictive function and the covariance function induced by the empirical

Maximilian Heisinger, Irfansha Shaik, Martina Seidl, Jaco van de Pol

In many QBF encodings, sequences of Boolean variables stand for binary representations of integer variables. Examples are state labels in bounded model checking or actions in planning problems. Often not the full possible range is used, e.g., for representing six different states, three Boolean variables are required, rendering two of the eight possible assi

Stanislav Motyka, Paul Weiser, Beata Bachrata, Lukas Hingerl

Subject movement during the magnetic resonance examination is inevitable and causes not only image artefacts but also deteriorates the homogeneity of the main magnetic field (B0), which is a prerequisite for high quality data. Thus, characterization of changes to B0, e.g. induced by patient movement, is important for MR applications that are prone to B0 inho

Polina Shaban, Igor Lobanov, Valerii Uzdin, Ivan Iorsh

We consider a twisted magnetic bilayer subject to the perpendicular electric field. The interplay of induced Dzyaloshinskii - Moriya interaction and spatially varying moir\'e exchange potential results in complex non-collinear magnetic phases in these structures. We numerically demonstrate the coexistence of intralayer skyrmions and bound interlayer skyrmion

Daniel Cao Labora, Francisco Javier Fernández, Fernando Adrián F. Tojo, Carlos Villanueva

When dealing with certain mathematical problems, it is sometimes necessary to show that some function induces a metric on a certain space. When this function is not a well renowned example of a distance, one has to develop very particular arguments that appeal to the concrete expression of the function in order to do so. The main purpose of this paper is to

Harold N. Ward

This note intertwines the concepts of degeneration and contraction of algebras and quadratic forms defined on a vector space V . The general linear group GL(V ) acts regularly on the spaces of these two objects. The base field is taken to be infinite of characteristic not 2. It is unrestricted otherwise, as in the first cited paper of Ivanova and Pallikaros.

Binglu Ren, Jianqin Yin

In the perception task of autonomous driving, multi-modal methods have become a trend due to the complementary characteristics of LiDAR point clouds and image data. However, the performance of multi-modal methods is usually limited by the sparsity of the point cloud or the noise problem caused by the misalignment between LiDAR and the camera. To solve these

Claude Bardos, Xin Liu, Edriss S. Titi

This paper is devoted to investigating the rotating Boussinesq equations of inviscid, incompressible flows with both fast Rossby waves and fast internal gravity waves. The main objective is to establish a rigorous derivation and justification of a new generalized quasi-geostrophic approximation in a channel domain with no normal flow at the upper and lower s

Yongxing Zhu

We derive rigorously the reduced dynamical laws for quantized vortex dynamics of the complex Ginzburg-Landau equation on torus when the core size of vortex $\varepsilon\to 0$. The reduced dynamical laws of the complex Ginzburg-Landau equation are governed by a mixed flow of gradient flow and Hamiltonian flow which are both driven by a renormalized energy on

Bo Jiang, Hamid Krim, Tianfu Wu, Derya Cansever

The power and flexibility of Optimal Transport (OT) have pervaded a wide spectrum of problems, including recent Machine Learning challenges such as unsupervised domain adaptation. Its essence of quantitatively relating two probability distributions by some optimal metric, has been creatively exploited and shown to hold promise for many real-world data challe

Xiaolong Gong, Yue Fang, Tonghua Liu, Shuo Cao

Quantum coherence is the basic concept of superposition of quantum states and plays an important role in quantum metrology. We show how a pair of uniformly accelerated observers with a local two-mode Gaussian quantum state affects the Gaussian quantum coherence. We find that the quantum coherence decreases with increasing acceleration, which is due to the Un

Tim Tanida, Philip Müller, Georgios Kaissis, Daniel Rueckert

The automatic generation of radiology reports has the potential to assist radiologists in the time-consuming task of report writing. Existing methods generate the full report from image-level features, failing to explicitly focus on anatomical regions in the image. We propose a simple yet effective region-guided report generation model that detects anatomica

V. P. Jovanović, H. Raffy, Z. Z. Li, G. Reményi

We studied the in-plane angular magnetoresistance (AMR), in the normal state, of underdoped superconducting Sr1-xLaxCuO2 , which has the simplest crystal structure among cuprates. The measurements of two underdoped thin films with different dopings were performed in intense magnetic field H (up to 22 T). The longitudinal magnetoresistance at temperature T is

Florence Smith Nicholls, Michael Cook

Procedural content generation has been applied to many domains, especially level design, but the narrative affordances of generated game environments are comparatively understudied. In this paper we present our first attempt to study these effects through the lens of what we call a generative archaeology game that prompts the player to archaeologically inter

Jakob Salzer

Carrollian conformal field theories (carrollian CFTs) are natural field theories on null infinity of an asymptotically flat spacetime or, in general, geometries with conformal carrollian structure. Using a basis transformation, gravitational S-matrix elements can be brought into the form of correlators of a carrollian CFT. Therefore, it has been suggested th

Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund

This work aims to improve the applicability of diffusion models in realistic image restoration. Specifically, we enhance the diffusion model in several aspects such as network architecture, noise level, denoising steps, training image size, and optimizer/scheduler. We show that tuning these hyperparameters allows us to achieve better performance on both dist

Dmitry Kramkov, Mihai Sîrbu

We consider an optimal transport problem with backward martingale constraint. The objective function is given by the scalar product of a pseudo-Euclidean space $S$. We show that the supremums over maps and plans coincide, provided that the law $\nu$ of the input random variable $Y$ is atomless. An optimal map $X$ exists if $\nu$ does not charge any $c-c$ sur

Hubert Baty

Physics informed neural networks (PINNs) are nowadays used as efficient machine learning methods for solving differential equations. However, vanilla-PINNs fail to learn complex problems as ones involving stiff ordinary differential equations (ODEs). This is the case of some initial value problems (IVPs) when the amount of training data is too small and/or t

Md Mostafizur Rahman, Daisuke Kikuta, Satyen Abrol, Yu Hirate

Lookalike models are based on the assumption that user similarity plays an important role towards product selling and enhancing the existing advertising campaigns from a very large user base. Challenges associated to these models reside on the heterogeneity of the user base and its sparsity. In this work, we propose a novel framework that unifies the custome

Jiexin Wang, Jiahao Chen, Bing Su

Auto-evaluation aims to automatically evaluate a trained model on any test dataset without human annotations. Most existing methods utilize global statistics of features extracted by the model as the representation of a dataset. This ignores the influence of the classification head and loses category-wise confusion information of the model. However, ratios o

Waldemar Martens, Michael Khan, Jean-Baptiste Bayle

Within its Voyage 2050 planning cycle, the European Space Agency (ESA) is considering long-term large class science mission themes. Gravitational-wave astronomy is among the topics under study. Building on previous work by other authors, this paper studies a gravitational-wave interferometer concept, dubbed "LISAmax", consisting of three spacecraft, each loc

Malin Palö Forsström, Fredrik Viklund

We revisit the cluster expansion for Ising lattice gauge theory on $\mathbb{Z}^m, \, m \ge 3,$ with Wilson action, at a fixed inverse temperature \( \beta\) in the low-temperature regime. We prove existence and analyticity of the infinite volume limit of the free energy and compute the first few terms in its expansion in powers of $e^{-\beta}$. We further an

Aamod Khatiwada, Roee Shraga, Renée J. Miller

We demonstrate a novel table discovery pipeline called DIALITE that allows users to discover, integrate and analyze open data tables. DIALITE has three main stages. First, it allows users to discover tables from open data platforms using state-of-the-art table discovery techniques. Second, DIALITE integrates the discovered tables to produce an integrated tab

Ruqiu Lin, Zhen-Ya Zheng, Jun-Xian Wang, Fang-Ting Yuan

Although double-peaked narrow emission-line galaxies have been studied extensively in the past years, only a few are reported with the green pea galaxies (GPs). Here we present our discovery of five GPs with double-peaked narrow [OIII] emission lines, referred to as DPGPs, selected from the LAMOST and SDSS spectroscopic surveys. We find that these five DPGPs

Jinpeng Liao, Tianyu Zhang, Yilong Zhang, Chunhui Li

Optical coherence tomography angiography (OCTA) is a non-invasive imaging modality that extends the functionality of OCT by extracting moving red blood cell signals from surrounding static biological tissues. OCTA has emerged as a valuable tool for analyzing skin microvasculature, enabling more accurate diagnosis and treatment monitoring. Most existing OCTA

Marius E. Yamakou, Mathieu Desroches, Serafim Rodrigues

Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by spike-timing-dependent plasticity (STDP) and temporal networks subject to homeostatic structural plasticity (HS

Marvin Klimke, Benjamin Völz, Michael Buchholz

Reinforcement learning has received high research interest for developing planning approaches in automated driving. Most prior works consider the end-to-end planning task that yields direct control commands and rarely deploy their algorithm to real vehicles. In this work, we propose a method to employ a trained deep reinforcement learning policy for dedicate

Chaoyue Song, Jiacheng Wei, Tianyi Chen, Yiwen Chen

In this paper, we focus on the challenges of modeling deformable 3D objects from casual videos. With the popularity of neural radiance fields (NeRF), many works extend it to dynamic scenes with a canonical NeRF and a deformation model that achieves 3D point transformation between the observation space and the canonical space. Recent works rely on linear blen

Benjie Wang, Marta Kwiatkowska

Probabilistic circuits (PCs) are a class of tractable probabilistic models, which admit efficient inference routines depending on their structural properties. In this paper, we introduce md-vtrees, a novel structural formulation of (marginal) determinism in structured decomposable PCs, which generalizes previously proposed classes such as probabilistic sente

Ruochen Ma

We employ an $n$-replica Keldysh field theory to investigate the effects of measurements and decoherence on long distance behaviors of quantum critical states. We classify different measurements and decoherence based on their timescales and symmetry properties, and demonstrate that they can be described by $n$-replica Keldysh field theories with distinct phy

F. Anders, P. Gispert, B. Ratcliffe, C. Chiappini

Over the last few years, many studies have found an empirical relationship between the abundance of a star and its age. Here we estimate spectroscopic stellar ages for 178 825 red-giant stars observed by the APOGEE survey with a median statistical uncertainty of 17%. To this end, we use the supervised machine learning technique XGBoost, trained on a high-qua

Conrad Sanderson, David Douglas, Qinghua Lu

Many sets of ethics principles for responsible AI have been proposed to allay concerns about misuse and abuse of AI/ML systems. The underlying aspects of such sets of principles include privacy, accuracy, fairness, robustness, explainability, and transparency. However, there are potential tensions between these aspects that pose difficulties for AI/ML develo

Khanh Chau Le

An asymptotically exact first-order shear deformation theory for functionally graded elastic plates is derived using the variational-asymptotic method. As an application, an analytical solution to the problem of wave propagation in a sandwich plate is found in accordance with this refined theory. Comparison between the dispersion curves obtained by 2-D plate

N. Menci, F. Fiore, F. Shankar, L. Zanisi

To tackle the still unsolved and fundamental problem of the role of Active Galactic Nuclei (AGN) feedback in shaping galaxies, in this work we implement a new physical treatment of AGN-driven winds into our semi-analytic model of galaxy formation. To each galaxy in our model, we associate solutions for the outflow expansion and the mass outflow rates in diff

Justina Stark, Ivo F. Sbalzarini

We present a versatile open-source pipeline for simulating inhomogeneous reaction-diffusion processes in highly resolved, image-based geometries of porous media with reactive boundaries. Resolving realistic pore-scale geometries in numerical models is challenging and computationally demanding, as the scale differences between the sizes of the interstitia and

Jing Li, Hongfei Wang, Shiyin Jia, Peng Zhan

Topological phases based on tight-binding models have been extensively studied in recent decades. By mimicking the linear combination of atomic orbitals in tight-binding models based on the evanescent couplings between resonators in classical waves, numerous experimental demonstrations of topological phases have been successfully conducted. However, in diele

Luca Scofano, Alessio Sampieri, Giuseppe Re, Matteo Almanza

Forecasting players in sports has grown in popularity due to the potential for a tactical advantage and the applicability of such research to multi-agent interaction systems. Team sports contain a significant social component that influences interactions between teammates and opponents. However, it still needs to be fully exploited. In this work, we hypothes

Jinheng Xie, Zhaochuan Luo, Yuexiang Li, Haozhe Liu

While remarkable success has been achieved in weakly-supervised object localization (WSOL), current frameworks are not capable of locating objects of novel categories in open-world settings. To address this issue, we are the first to introduce a new weakly-supervised object localization task called OWSOL (Open-World Weakly-Supervised Object Localization). Du

Grigalius Taujanskas, Juan A. Valiente Kroon

We study the relationship between asymptotic characteristic initial data at past null infinity and the regularity of solutions at future null infinity for the massless linear spin-s field equations on Minkowski space. By quantitatively controlling the solutions on a causal rectangle reaching the conformal boundary, we relate the (generically singular) behavi

Qian Zhang, Tongda Xu, Yanghao Li, Yan Wang

In this paper, we first propose the concept of strong idempotent codec based on idempotent codec. The idempotence of codec refers to the stability of codec to re-compression. Similarly, we define the strong idempotence of codec as the stability of codec to multiple quality re-compression, which is an important feature of codec in the context of cloud transco

Emilien Valat, Loth Valat

Machine-learning methods rely on sufficiently large dataset to learn data distributions. They are widely used in research in X-Ray Computed Tomography, from low-dose scan denoising to optimisation of the reconstruction process. The lack of datasets prevents the scalability of these methods to realistic 3D problems. We develop a 3D procedural dataset in order

You-Yang Xu, Jiangbin Gong, Wu-Ming Liu

Quantum thermodynamic quantities, normally formulated with the assumption of weak system-bath coupling (SBC), can often be contested in physical circumstances with strong SBC. This work presents an alternative treatment that enables us to use standard concepts based on weak SBC to tackle with quantum thermodynamics with strong SBC. Specifically, via a physic

Wenhao Tang, Daniel Hillerström, James McKinna, Michel Steuwer

Structural subtyping and parametric polymorphism provide similar flexibility and reusability to programmers. For example, both features enable the programmer to provide a wider record as an argument to a function that expects a narrower one. However, the means by which they do so differs substantially, and the precise details of the relationship between them

M. Frelek-Kozak, Ł. Kurpaska, K. Mulewska, M. Zieliński

In the present work, authors focused on verifying structural and mechanical properties of Oxide Dispersed Strengthening (ODS) steels strengthened by three different types of refractory oxides submitted to ion-irradiation. Three materials strengthened with Y2O3 or Al2O3 or ZrO2 were produced by mechanical alloying and Spark Plasma Sintering technique. Specime

A. Kudlis, A. Aharony, O. Entin-Wohlman

The phase diagram of a system with two order parameters, with ${\it n_1}$ and $n_2$ components, respectively, contains two phases, in which these order parameters are non-zero. Experimentally and numerically, these phases are often separated by a first-order "flop" line, which ends at a bicritical point. For $n=n_1+n_2=3$ and $d=3$ dimensions (relevant e.g.

Fang Chen, Heiko Balzter, Peng Ren, Huiyu Zhou

Effective oil spill segmentation in Synthetic Aperture Radar (SAR) images is critical for marine oil pollution cleanup, and proper image representation is helpful for accurate image segmentation. In this paper, we propose an effective oil spill image segmentation network named SRCNet by leveraging SAR image representation and the training for oil spill segme

Zeyu Wang, Qitong Wang, Peng Wang, Themis Palpanas

Data series indexes are necessary for managing and analyzing the increasing amounts of data series collections that are nowadays available. These indexes support both exact and approximate similarity search, with approximate search providing high-quality results within milliseconds, which makes it very attractive for certain modern applications. Reducing the

Dung Le

We establish certain maximum principles for a class of strongly coupled elliptic (or cross diffusion) systems of $m\ge2$ equations. The reaction parts can be non cooperative. These new results will be crucial in obtaining coexistence and persistence for many models with cross diffusion effects.

Chi Zhang, Amir Hossein Kalantari, Yue Yang, Zhongjun Ni

Predicting pedestrian behavior when interacting with vehicles is one of the most critical challenges in the field of automated driving. Pedestrian crossing behavior is influenced by various interaction factors, including time to arrival, pedestrian waiting time, the presence of zebra crossing, and the properties and personality traits of both pedestrians and

Yu Su, Zi-Hao Chen, Yao Wang, Xiao Zheng

In this paper, we present an extended dissipaton equation of motion for studying the dynamics of electronic impurity systems. Compared with the original theoretical formalism, the quadratic couplings are introduced into the Hamiltonian accounting for the interaction between the impurity and its surrounding environment. By exploiting the quadratic fermionic d

Ali Pedram, Vira R. Besaga, Lea Gassab, Frank Setzpfandt

Classical polarimetry is a well-established discipline with diverse applications across different branches of science. The burgeoning interest in leveraging quantum resources to achieve highly sensitive measurements has spurred researchers to elucidate the behavior of polarized light within a quantum mechanical framework, thereby fostering the development of

Jiasheng Wang

This paper presents a framework for learning player embeddings in competitive games and events. Players and their win-loss relationships are modeled as a skill gap graph, which is an undirected weighted graph. The player embeddings are learned from the graph using a random walk-based graph embedding method and can reflect the relative skill levels among play

Shin'ichi Nojiri, Sergei D. Odintsov, Diego Sáez-Chillón Gómez

In the era of precision cosmology, different observational data has led to precise measurements of the Hubble constant that differ significantly, what has been called the Hubble tension problem. In order to solve such a discrepancy, many different solutions have been proposed, from systematic errors on the observational data to theoretical proposals that ass

Denny M. Oliveira

Interplanetary (IP) shocks are disturbances commonly observed in the solar wind. IP shock impacts can cause a myriad of space weather effects in the Earth's magnetopause, inner magnetosphere, ionosphere, thermosphere, and ground magnetic field. The shock impact angle, measured as the angle the shock normal vector performs with the Sun-Earth line, has been sh

Yizhen Luo, Xing Yi Liu, Kai Yang, Kui Huang

In recent years, AI models that mine intrinsic patterns from molecular structures and protein sequences have shown promise in accelerating drug discovery. However, these methods partly lag behind real-world pharmaceutical approaches of human experts that additionally grasp structured knowledge from knowledge bases and unstructured knowledge from biomedical l

Sanne Vrijenhoek

The MIND dataset is at the moment of writing the most extensive dataset available for the research and development of news recommender systems. This work analyzes the suitability of the dataset for research on diverse news recommendations. On the one hand we analyze the effect the different steps in the recommendation pipeline have on the distribution of art

Nhat Hao Truong, Huu Thien Mai, Tuan Anh Tran, Minh Quang Tran

End-to-end deep learning approaches has been proven to be efficient in autonomous driving and robotics. By using deep learning techniques for decision-making, those systems are often referred to as a black box, and the result is driven by data. In this paper, we propose PaaS (Planning as a Service), a vanilla module to generate local trajectory planning for

Theo Nommay

Nowadays there are more and more items available online, this makes it hard for users to find items that they like. Recommender systems aim to find the item who best suits the user, using his historical interactions. Depending on the context, these interactions may be more or less sensitive and collecting them brings an important problem concerning the users

Nouar Chorfi, Salem Abdelmalek, Samir Bendoukha

In this article, we consider an HIV/AIDS epidemic model with four classes of individuals. We have discussed about basic properties of the system and found the basic reproduction number $R_0$ of the system. The stability analysis of the model shows that the system is locally as well as globally asymptotically stable at disease-free equilibrium $E_{0}$ when $R

Sharon Lavie, Yuli Goshen, Eli Kraisler

Calculations in Kohn-Sham density functional theory crucially rely on high-quality approximations for the exchange-correlation (xc) functional. Standard local and semi-local approximations fail to predict the ionization potential (IP) and the fundamental gap, departing from the Kohn-Sham orbital energies, due to the deviation of the total energy from piecewi

Huiwen Zhang, Kai Mi, Zhijun Zhang

Base placement optimization (BPO) is a fundamental capability for mobile manipulation and has been researched for decades. However, it is still very challenging for some reasons. First, compared with humans, current robots are extremely inflexible, and therefore have higher requirements on the accuracy of base placements (BPs). Second, the BP and task constr

Kangkang Deng, Jiang Hu

We consider the problem of decentralized nonconvex optimization over a compact submanifold, where each local agent's objective function defined by the local dataset is smooth. Leveraging the powerful tool of proximal smoothness, we establish local linear convergence of the projected gradient descent method with a unit step size for solving the consensus prob