March 2023 arXiv papers — page 106

Tom Boot, Johannes W. Ligtenberg

Identification-robust hypothesis tests are commonly based on the continuous updating GMM objective function. When the number of moment conditions grows proportionally with the sample size, the large-dimensional weighting matrix prohibits the use of conventional asymptotic approximations and the behavior of these tests remains unknown. We show that the struct

Alexander Fuchs, Christian Knoll, Nima N. Moghadam, Alexey Pak Jinliang Huang

Multiple-Input Multiple-Output (MIMO) systems are essential for wireless communications. Sinceclassical algorithms for symbol detection in MIMO setups require large computational resourcesor provide poor results, data-driven algorithms are becoming more popular. Most of the proposedalgorithms, however, introduce approximations leading to degraded performance

Yifan Pu, Yiru Wang, Zhuofan Xia, Yizeng Han

Rotated object detection aims to identify and locate objects in images with arbitrary orientation. In this scenario, the oriented directions of objects vary considerably across different images, while multiple orientations of objects exist within an image. This intrinsic characteristic makes it challenging for standard backbone networks to extract high-quali

Quanling Deng, Samuel N. Stechmann, Nan Chen

Sea ice profoundly influences the polar environment and the global climate. Traditionally, Sea ice has been modeled as a continuum under Eulerian coordinates to describe its large-scale features, using, for instance, viscous-plastic rheology. Recently, Lagrangian particle models, also known as the discrete element method (DEM) models, have been utilized for

Adrien Weihs, Matthew Thorpe

Laplace learning is a popular machine learning algorithm for finding missing labels from a small number of labelled feature vectors using the geometry of a graph. More precisely, Laplace learning is based on minimising a graph-Dirichlet energy, equivalently a discrete Sobolev $\Wkp{2}{1}$ semi-norm, constrained to taking the values of known labels on a given

Yuki Takaha, Hideyuki Mizuno, Atsushi Ikeda

Usually, supercooled liquids and glasses are thermodynamically unstable against crystallization. Classical nucleation theory (CNT) has been used to describe the crystallization dynamics of supercooled liquids. However, recent studies on overcompressed hard spheres show that their crystallization dynamics are intermittent and mediated by avalanche-like rearra

Wang Dai, Archontis Politis, Tuomas Virtanen

This work proposes a learnable filterbank based on a multi-channel masking framework for multi-channel source separation. The learnable filterbank is a 1D Conv layer, which transforms the raw waveform into a 2D representation. In contrast to the conventional single-channel masking method, we estimate a mask for each individual microphone channel. The estimat

Roy Miles, Mehmet Kerim Yucel, Bruno Manganelli, Albert Saa-Garriga

This paper tackles the problem of semi-supervised video object segmentation on resource-constrained devices, such as mobile phones. We formulate this problem as a distillation task, whereby we demonstrate that small space-time-memory networks with finite memory can achieve competitive results with state of the art, but at a fraction of the computational cost

Adam Goldbraikh, Omer Shubi, Or Rubin, Carla M Pugh

Action segmentation is a challenging task in high-level process analysis, typically performed on video or kinematic data obtained from various sensors. This work presents two contributions related to action segmentation on kinematic data. Firstly, we introduce two versions of Multi-Stage Temporal Convolutional Recurrent Networks (MS-TCRNet), specifically des

Emilia Alvarez, Pierre Bousseyroux, Nina C. Snaith

This work computes the asymptotics of the non-integer moments of the logarithmic derivative of characteristic polynomials of matrices from the $SO(2N+1)$ ensemble. It follows from work of Alvarez and Snaith who computed the asymptotics of the integer moments of the same statistic over both $SO(N)$ ensembles as well as the $USp(2N)$ ensemble.

Roy Overbeek, Jörg Endrullis

We introduce a termination method for the algebraic graph transformation framework PBPO+, in which we weigh objects by summing a class of weighted morphisms targeting them. The method is well-defined in rm-adhesive quasitoposes (which include toposes and therefore many graph categories of interest), and is applicable to non-linear rules. The method is also d

Dawid Rymarczyk, Joost van de Weijer, Bartosz Zieliński, Bartłomiej Twardowski

Continual learning enables incremental learning of new tasks without forgetting those previously learned, resulting in positive knowledge transfer that can enhance performance on both new and old tasks. However, continual learning poses new challenges for interpretability, as the rationale behind model predictions may change over time, leading to interpretab

Lianghao Xia, Yizhen Shao, Chao Huang, Yong Xu

Social recommender systems have drawn a lot of attention in many online web services, because of the incorporation of social information between users in improving recommendation results. Despite the significant progress made by existing solutions, we argue that current methods fall short in two limitations: (1) Existing social-aware recommendation models on

Jochen Glück, Julian Hölz

We consider finite-dimensional real vector spaces $X$ ordered by a closed cone $X_+$ with non-empty interior and study eventual nonnegativity of matrix semigroups $(e^{tA})_{t \ge 0}$ with respect to this cone. Our first contribution is the observation that, for general cones, one needs to distinguish between different notions of eventual nonnegativity: (i)

Blair C. Connelly, Patrick J. Taylor, George J. de Coster

We observe enhanced three-fold symmetric helicity-dependent topological photocurrents using time-domain THz spectroscopy in epitaxially-grown Bi2Se3 with reduced crystallographic twinning. It is established how twinned crystal domains introduce competing responses that obscure inherent nonlinear optical responses of the intrinsic crystal structure. Minimizin

Claudio Zito

``A simple handshake would give them away''. This is how Anthony Hopkins' fictional character, Dr Robert Ford, summarises a particular flaw of the 2016 science-fiction \emph{Westworld}'s hosts. In the storyline, Westworld is a futuristic theme park and the hosts are autonomous robots engineered to be indistinguishable from the human guests, except for their

Zelin Peng, Guanchun Wang, Lingxi Xie, Dongsheng Jiang

Seed area generation is usually the starting point of weakly supervised semantic segmentation (WSSS). Computing the Class Activation Map (CAM) from a multi-label classification network is the de facto paradigm for seed area generation, but CAMs generated from Convolutional Neural Networks (CNNs) and Transformers are prone to be under- and over-activated, res

Alessandra Azzollini, Steven Neil Shore, Paul Kuin, Kim Page

To detail the development of RS Ophiuchi and the other Galactic Symbiotic-like Recurrent Novae throughout their outburst and quiescence, with a particular emphasis on the propagation of the shock wave during the outburst of the binaries. The spectral analysis has been performed using archival data according to the features of the individual datasets. Swift g

Arnau Brosa López, Filip Lemic, Jakob Struye, Jorge Torres Gómez

Nanoscale devices with Terahertz (THz) communication capabilities are envisioned to be deployed within human bloodstreams. Such devices will enable fine-grained sensing-based applications for detecting early indications (i.e., biomarkers) of various health conditions, as well as actuation-based ones such as targeted drug delivery. Associating the locations o

Daniele Giubergia, Elisa Bin, Marco Diana

The spread of COVID-19 disease affected people's lives worldwide, particularly their travel behaviours and how they performed daily activities. During the first wave of the pandemic, spring 2020, countries adopted different strategies to contain the spread of the virus. The aim of this paper is to analyse the changes in mobility behaviours, focusing on the s

D. A. Salamatin, V. N. Krasnorussky, A. V. Semeno, A. V. Bokov

The magnetic $H$-$T$ phase diagram and magnetocaloric effect in the recently discovered high-temperature heavy-fermion compound YbCoC$_2$ have been studied. With the increase in the external magnetic field YbCoC$_2$ experiences the metamagnetic transition and then transition to the ferromagnetic state. The dependencies of magnetic entropy change -$\Delta S_m

Subrata Chakraborty, Danilo Nikolić, Juan Carlos Cuevas, Francesco Giazotto

Recently gate-mediated supercurrent suppression in superconducting nano-bridges has been reported in many experiments. This could be either a direct or an indirect gate effect. The microscopic understanding of this observation is not clear till now. Using the quasiclassical Green's function method, we show that a small concentration of magnetic impurities at

Nikita Jain, Sucheta Dutt, Ranjeet Sehmi

The rings $Z_{4}+\nu Z_{4}$ have been classified into chain rings and non-chain rings on the basis of the values of $\nu^{2} \in Z_{4}+\nu Z_{4}.$ In this paper, the structure of cyclic codes of arbitrary length over the rings $Z_{4}+\nu Z_{4}$ for those values of $\nu^{2}$ for which these are non-chain rings has been established. A unique form of generators

Zeyu An, Xin Tao, Fulvio Zonca, Liu Chen

Electromagnetic ion cyclotron waves are known to exhibit frequency chirping, contributing to the rapid scattering and acceleration of energetic particles. However, the physical mechanism of chirping remains elusive. Here, we propose a new model to explain the chirping and provide direct observational evidence for validation. Our results relate the frequency

Karmesh Yadav, Arjun Majumdar, Ram Ramrakhya, Naoki Yokoyama

We present a single neural network architecture composed of task-agnostic components (ViTs, convolutions, and LSTMs) that achieves state-of-art results on both the ImageNav ("go to location in <this picture>") and ObjectNav ("find a chair") tasks without any task-specific modules like object detection, segmentation, mapping, or planning modules. Such general

Lianghao Xia, Chao Huang, Chunzhen Huang, Kangyi Lin

Graph neural networks (GNNs) have emerged as the state-of-the-art paradigm for collaborative filtering (CF). To improve the representation quality over limited labeled data, contrastive learning has attracted attention in recommendation and benefited graph-based CF model recently. However, the success of most contrastive methods heavily relies on manually ge

Bence Borda

In this paper, we show how quantum modular forms naturally arise in the ergodic theory of circle rotations. Working with the classical Birkhoff sum $S_N(\alpha)=\sum_{n=1}^N (\{ n \alpha \}-1/2)$, we prove that the maximum and the minimum as well as certain exponential moments of $S_N(r)$ as functions of $r \in \mathbb{Q}$ satisfy a direct analogue of Zagier

Artur Slobodeniuk, Tomáš Novotný, Radim Filip

Quantum coherence is a crucial prerequisite for quantum technologies. Therefore, the robust generation, as autonomous as possible, of quantum coherence remains the essential problem for developing this field. We consider a method of synthesizing and multiplexing quantum coherence from spin systems without any direct drives only coupled to bosonic baths. The

Hongfei Wang

Recent advancements in generative models have shown remarkable progress in music generation. However, most existing methods focus on generating monophonic or homophonic music, while the generation of polyphonic and multi-track music with rich attributes is still a challenging task. In this paper, we propose a novel approach for multi-track, multi-attribute s

Nguyen Quang Huy, Nguyen Mau Nam, Nguyen Dong Yen

In this paper, we introduce new properties of the relative interior calculus for nearly convex sets, functions, and set-valued mappings. These properties are important for the development of duality theory in optimization. Then we investigate optimal value functions defined by nearly convex functions and nearly convex set-valued mappings, and derive the near

Ioannis Gavras, Md Atiqul Islam, Besma Smida, George C. Alexandropoulos

This paper presents an in-band Full Duplex (FD) integrated sensing and communications system comprising a holographic Multiple-Input Multiple-Output (MIMO) base station, which is capable to simultaneously communicate with multiple users in the downlink direction, while sensing targets being randomly distributed within its coverage area. Considering near-fiel

Jian Han, Changpeng Lin, Ce-wen Nan, Yuan-hua Lin

SrTiO$_3$ has been extensively investigated owing to its abundant degrees of freedom for modulation. However, the microscopic mechanism of thermal transport especially the relationship between phonon scattering and lattice distortion during the phase transition are missing and unclear. Based on deep-potential molecular dynamics and self-consistent \textit{ab

Øyvind Meinich-Bache, Kjersti Engan, Ivar Austvoll, Trygve Eftestøl

Birth asphyxia is a major newborn mortality problem in low-resource countries. International guideline provides treatment recommendations; however, the importance and effect of the different treatments are not fully explored. The available data is collected in Tanzania, during newborn resuscitation, for analysis of the resuscitation activities and the respon

Alaeddine Zahir, Khalide Jbilou, Ahmed Ratnani

Multi-view clustering has been widely used in recent years in comparison to single-view clustering, for clear reasons, as it offers more insights into the data, which has brought with it some challenges, such as how to combine these views or features. Most of recent work in this field focuses mainly on tensor representation instead of treating the data as si

Øyvind Meinich-Bache, Simon Lennart Austnes, Kjersti Engan, Ivar Austvoll

Objective: Birth asphyxia is one of the leading causes of neonatal deaths. A key for survival is performing immediate and continuous quality newborn resuscitation. A dataset of recorded signals during newborn resuscitation, including videos, has been collected in Haydom, Tanzania, and the aim is to analyze the treatment and its effect on the newborn outcome.

Edgar Knobloch, Arik Yochelis

We study the existence and stability of propagating fronts in Meinhardt's multivariable reaction-diffusion model of branching in one spatial dimension. We identify a saddle-node-infinite-period (SNIPER) bifurcation of fronts that leads to episodic front propagation in the parameter region below propagation failure and show that this state is stable. Stable c

Jinxin Yang, Hui Li, Yiming Si, Hui Zhang

Shared-nothing architecture has been widely adopted in various commercial distributed RDBMSs. Thanks to the architecture, query can be processed in parallel and accelerated by scaling up the cluster horizontally on demand. In spite of that, load balancing has been a challenging issue in all distributed RDBMSs, including shared-nothing ones, which suffers muc

Petra Tschuchnig, Manfred Mayr, Maximilian Tschuchnig, Peter Haber

The network economical sharing economy, with direct exchange as a core characteristic, is implemented both, on a commons and platform economical basis. This is due to a gain in importance of trust, collaborative consumption and democratic management as well as technological progress, in the form of near zero marginal costs, open source contributions and digi

Lauritz Streck

In this paper, we consider the self-similar measure $\nu_\lambda=\mathrm{law}\left(\sum_{j \geq 0} \xi_j \lambda^j\right)$ on $\mathbb{R}$, where $|\lambda|<1$ and the $\xi_j \sim \nu$ are independent, identically distributed with respect to a measure $\nu$ finitely supported on $\mathbb{Z}$. One example of this is the classical Bernoulli convolution. It is

Ignasi Mundet i Riera

In this paper we survey some recent results on actions of finite groups on topological manifolds. Given an action of a finite group $G$ on a manifold $X$, these results provide information on the restriction of the action to a subgroup of $G$ of index bounded above by a number depending only on $X$. Some of these results refer to the algebraic structure of t

Mira Küpper, Armin Seyfried

To investigate the impact of social groups on waiting behaviour of passengers at railway platforms a method to identify social groups through the monitoring of distances between pedestrians and the stability of those distances over time is introduced. The method allows the recognition of groups using trajectories only and thus opens up the possibility of stu

Sara Saeidian, Giulia Cervia, Tobias J. Oechtering, Mikael Skoglund

This paper introduces a paradigm shift in the way privacy is defined, driven by a novel interpretation of the fundamental result of Dwork and Naor about the impossibility of absolute disclosure prevention. We propose a general model of utility and privacy in which utility is achieved by disclosing the value of low-entropy features of a secret $X$, while priv

Lauritz Streck

This paper generalizes the result of Sarnak and Ubis \cite{sarnak-ubis} about non-concentration of primes in horocycle orbits on $PSL_2(\mathbb{Z}) \backslash PSL_2(\mathbb{R})$ to any lattice in $PSL_2(\mathbb{R})$. The proof combines the asymptotic result of Str\"ombergsson \parencite{strombergsson} and Venkatesh's method \parencite{venkatesh} with the app

Daniel W. Boutros, John D. Gibbon

The fractional Navier-Stokes equations on a periodic domain $[0,\,L]^{3}$ differ from their conventional counterpart by the replacement of the $-\nu\Delta\mathbf{u}$ Laplacian term by $\nu_{s}A^{s}\mathbf{u}$, where $A= - \Delta$ is the Stokes operator and $\nu_{s} = \nu L^{2(s-1)}$ is the viscosity parameter. Four critical values of the exponent $s\geq 0$ h

Minghe Wang, Trever Schirmer, Tobias Pfandzelter, David Bermbach

Publish-subscribe systems are a popular approach for edge-based IoT use cases: Heterogeneous, constrained edge devices can be integrated easily, with message routing logic offloaded to edge message brokers. Message processing, however, is still done on constrained edge devices. Complex content-based filtering, the transformation between data representations,

Linxuan Song, Wenxuan Tu, Sihang Zhou, Xinwang Liu

Graph neural networks (GNNs) have been widely investigated in the field of semi-supervised graph machine learning. Most methods fail to exploit adequate graph information when labeled data is limited, leading to the problem of oversmoothing. To overcome this issue, we propose the Graph Alignment Neural Network (GANN), a simple and effective graph neural arch

Congzao Dong, Elena Dyakonova, Vladimir Vatutin

Let $\{S_n,n\geq 0\} $ be a random walk whose increments belong without centering to the domain of attraction of an $\alpha$-stable law $\{Y_t,t\geq 0\}$, i.e. $S_{nt}/a_n\Rightarrow Y_t,t\geq 0,$ for some scaling constants $a_n$. Assuming that $S_0=o(a_{n})$ and $S_n\leq \varphi (n)=o(a_n),$ we prove several conditional limit theorems for the distribution o

Abhra Chaudhuri, Ayan Kumar Bhunia, Yi-Zhe Song, Anjan Dutta

Rising concerns about privacy and anonymity preservation of deep learning models have facilitated research in data-free learning (DFL). For the first time, we identify that for data-scarce tasks like Sketch-Based Image Retrieval (SBIR), where the difficulty in acquiring paired photos and hand-drawn sketches limits data-dependent cross-modal learning algorith

Arun Jambulapati, Hilaf Hasson, Youngsuk Park, Yuyang Wang

Determining causal relationship between high dimensional observations are among the most important tasks in scientific discoveries. In this paper, we revisited the \emph{linear trace method}, a technique proposed in~\citep{janzing2009telling,zscheischler2011testing} to infer the causal direction between two random variables of high dimensions. We strengthen

Marcus C Christiansen

A common problem in various applications is the additive decomposition of the output of a function with respect to its input variables. Functions with binary arguments can be axiomatically decomposed by the famous Shapley value. For the decomposition of functions with real arguments, a popular method is the pointwise application of the Shapley value on the d

Rebecca Killick, Marina I. Knight, Guy P. Nason, Matthew A. Nunes

Accurate forecasting of the U.K. gross value added (GVA) is fundamental for measuring the growth of the U.K. economy. A common nonstationarity in GVA data, such as the ABML series, is its increase in variance over time due to inflation. Transformed or inflation-adjusted series can still be challenging for classical stationarity-assuming forecasters. We adopt

Y. Aimuratov, L. M. Becerra, C. L. Bianco, C. Cherubini

The observations of supernovae (SNe) Ic occurring after the prompt emission of long gamma-ray bursts (GRBs) are addressed within the binary-driven hypernova (BdHN) model where GRBs originate from a binary composed of a $\sim10M_\odot$ carbon-oxygen (CO) star and a neutron star (NS). The CO core collapse gives the trigger, leading to a hypernova with a fast-s

Rao Muhammad Umer, Armin Gruber, Sayedali Shetab Boushehri, Christian Metak

Accurate morphological classification of white blood cells (WBCs) is an important step in the diagnosis of leukemia, a disease in which nonfunctional blast cells accumulate in the bone marrow. Recently, deep convolutional neural networks (CNNs) have been successfully used to classify leukocytes by training them on single-cell images from a specific domain. M

Chan Gao, Bin Yang, Dong Zheng, Xiaohong Jiang

This paper investigates the covert communications via cooperative jamming and relay selection in a wireless relay system, where a source intends to transmit a message to its destination with the help of a selected relay, and a warden attempts to detect the existence of wireless transmissions from both the source and relay, while friendly jammers send jamming

Kalin V. Staykov, Daniela D. Doneva, Lavinia Heisenberg, Nikolaos Stergioulas

The merger remnant of a binary neutron star coalescence is initially strongly differentially rotating. Some properties of these remnants can be accurately modeled through building equilibrium neutron star models. In the present paper, we study how a modification of general relativity, namely scalar-tensor theory with a massive scalar field, will alter the pi

Dina Faneva Andriantsiory, Joseph Ben Geloun, Mustapha Lebbah

Several methods for triclustering three-dimensional data require the cluster size or the number of clusters in each dimension to be specified. To address this issue, the Multi-Slice Clustering (MSC) for 3-order tensor finds signal slices that lie in a low dimensional subspace for a rank-one tensor dataset in order to find a cluster based on the threshold sim

Bernd Wolf, Theresa Lundbeck, Jan Zimmermann, Marius Peters

We present results of the magnetic susceptibility on high-quality single crystals of EuPd$_2$(Si$_{1-x}$Ge$_x$)$_2$ for Ge concentrations 0 $\leq x \leq$ 0.105 performed under varying hydrostatic (He-gas) pressure 0 $\leq p \leq$ 0.5 GPa. The work extends on recent studies at ambient pressure demonstrating the drastic change in the magnetic response from val

Roshni Bhaumik, Sourav Dutta, Subenoy Chakraborty

In the framework of $f(T)$-gravity theory, classical and quantum cosmology has been studied in the present work for FLRW space-time model. The Noether symmetry, a point-like symmetry of the Lagrangian is used to the physical system and a specific functional form of $f(T)$ is determined. A point transformation in the 2D augmented space restricts one of the va

Yue Zhao

This paper is concerned with the inverse moving source problems for parabolic equations. Given the temporal function, we prove the uniqueness of the nonlinear inverse problem of determining the orbit function by final data measured in a bounded domain. On the other hand, given the orbit function we also show that the profile function can be uniquely determin

Shuai S. A. Yuan, Xiaoming Chen, Chongwen Huang, Wei E. I. Sha

The holographic multiple-input-multiple-output (MIMO) communications refer to the MIMO systems built with ultra-dense antenna arrays, whose channel models and potential applications have attracted increasing attentions recently. When the spacing between adjacent array elements is larger than half wavelength, the effect of mutual coupling can generally be neg

Deborah Neuß, Ingrid E. McCarroll, Siyuan Zhang, Eric Woods

In this study, the structure and composition of the native oxide forming on the basal plane (0001) of Mg-2Al-0.1Ca is investigated by a correlative approach, combining scanning transmission electron microscopy (STEM) and atom probe tomography (APT). Atom probe specimens were prepared conventionally in a Ga focused ion beam (FIB) as well as a Xe plasma FIB in

Paul Bungert, Pascal Peter, Joachim Weickert

Image blending is an integral part of many multi-image applications such as panorama stitching or remote image acquisition processes. In such scenarios, multiple images are connected at predefined boundaries to form a larger image. A convincing transition between these boundaries may be challenging, since each image might have been acquired under different c

Albert Rico, Felix Huber

We provide a systematic method for nonlinear entanglement detection based on trace polynomial inequalities. In particular, this allows to employ multi-partite witnesses for the detection of bipartite states, and vice versa. We identify witnesses for which linear detection of an entangled state fails, but for which nonlinear detection succeeds. With the trace

J. A. Rueda, R. Ruffini

It has been thought for decades that rotating black holes (BHs) power the energetic gamma-ray bursts (GRBs) and active galactic nuclei (AGNs), but the mechanism that extracts the BH energy has remained elusive. We here show that the solution to this problem arises when the BH is immersed in an external magnetic field and ionized low-density matter. For a mag

Xianda Guo, Wenjie Yuan, Yunpeng Zhang, Tian Yang

Depth estimation has been widely studied and serves as the fundamental step of 3D perception for robotics and autonomous driving. Though significant progress has been made in monocular depth estimation in the past decades, these attempts are mainly conducted on the KITTI benchmark with only front-view cameras, which ignores the correlations across surround-v

Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring

The global trends of urbanization and increased personal mobility force us to rethink the way we live and use urban space. The Traffic4cast competition series tackles this problem in a data-driven way, advancing the latest methods in machine learning for modeling complex spatial systems over time. In this edition, our dynamic road graph data combine informat

Dina Faneva Andriantsiory, Joseph Ben Geloun, Mustapha Lebbah

We propose a new method of multiway clustering for 3-order tensors via affinity matrix (MCAM). Based on a notion of similarity between the tensor slices and the spread of information of each slice, our model builds an affinity/similarity matrix on which we apply advanced clustering methods. The combination of all clusters of the three modes delivers the desi

Pierre Houédry

We introduce new concepts in order to develop a general formalism for twisted differential operators in several variables. We investigate the notion of twisted coordinates on Huber rings that allows us to build various rings of twisted differential operators and compare them. We show that there exists an equivalence between modules endowed with a twisted con

Sara Conti, Andrey Chaves, Tribhuwan Pandey, Lucian Covaci

We explore the flatness of conduction and valence bands of interlayer excitons in MoS$_2$/WSe$_2$ van der Waals heterobilayers, tuned by interlayer twist angle, pressure, and external electric field. We employ an efficient continuum model where the moir\'e pattern from lattice mismatch and/or twisting is represented by an equivalent mesoscopic periodic poten

Deepak Iyer, Yuyi Wan

The linked cluster expansion has been shown to be highly efficient in calculating equilibrium and nonequilibrium properties of a variety of 1D and 2D classical and quantum lattice models. In this article, we extend the linked cluster method to the Cayley tree and its boundaryless cousin the Bethe lattice. We aim to (a) develop the linked cluster expansion fo

Nan Gao, Julian Külshammer, Sondre Kvamme, Chrysostomos Psaroudakis

We investigate the (separated) monomorphism category $\operatorname{mono}(Q,\Lambda)$ of a quiver $Q$ over an Artin algebra $\Lambda$. We construct an epivalence from $\overline{\operatorname{mono}}(Q,\Lambda)$ to $\operatorname{rep}(Q,\overline{\operatorname{mod}}\, \Lambda)$, where $\operatorname{mod}\Lambda$ is the category of finitely generated modules a

Priya Hasan, Mudasir Raja, Md Saifuddin, S N Hasan

The Serpens Molecular Cloud is one of the most active sites of ongoing star formation at a distance of about 300 pc, and hence is very well-suited for studies of young low-mass stars and sub-stellar objects. In this paper, for the Serpens star forming region, we find potential members of the Young Stellar Objects population from the Gaia DR3 data and study t

O. de Groot, L. Ferranti, D. Gavrila, J. Alonso-Mora

Navigating mobile robots through environments shared with humans is challenging. From the perspective of the robot, humans are dynamic obstacles that must be avoided. These obstacles make the collision-free space nonconvex, which leads to two distinct passing behaviors per obstacle (passing left or right). For local planners, such as receding-horizon traject

Tuomo Nyyssonen, Azdiar A. Gazder, Ralf Hielscher, Frank Niessen

This study details the development and validation of a new algorithm that determines the dominant habit plane of a transformed child phase from orientation maps of a single planar cross-section. The method describes the habit plane in terms of its five-parameter grain boundary character and couples it to the specific orientation relationship of the identifie

Mahdi Eskandari, Kangda Zhi, Huiling Zhu, Cunhua Pan

The objective of this paper is to evaluate the effectiveness of a two-timescale transmission design in cell-free massive multi-input multiple-output (MIMO) systems incorporating reconfigurable intelligent surfaces (RISs) under the assumption of imperfect channel state information (CSI). We examine the Rician channel model and formulate the passive beamformin

Sun-Sig Byun, Kyeongbae Kim, Deepak Kumar

We study a class of nonlocal double phase problems with discontinuous coefficients. A local self-improving property and a higher H\"older continuity result for weak solutions to such problems are obtained under the assumptions that the associated coefficient functions are of type VMO (vanishing mean oscillation) and that the principal coefficient depends not

Xing Cheng, Xiangyu Wu, Dong Shen, Hezheng Lin

Video grounding aims to locate the timestamps best matching the query description within an untrimmed video. Prevalent methods can be divided into moment-level and clip-level frameworks. Moment-level approaches directly predict the probability of each transient moment to be the boundary in a global perspective, and they usually perform better in coarse groun

Dan Andrei Iliescu, Devang Savita Ram Mohan, Tian Huey Teh, Zack Hodari

We address the problem of human-in-the-loop control for generating prosody in the context of text-to-speech synthesis. Controlling prosody is challenging because existing generative models lack an efficient interface through which users can modify the output quickly and precisely. To solve this, we introduce a novel framework whereby the user provides partia

Xiaowen Ma, Mengting Ma, Chenlu Hu, Zhiyuan Song

Remote sensing images are known of having complex backgrounds, high intra-class variance and large variation of scales, which bring challenge to semantic segmentation. We present LoG-CAN, a multi-scale semantic segmentation network with a global class-aware (GCA) module and local class-aware (LCA) modules to remote sensing images. Specifically, the GCA modul

Lorenzo Caprini, Hartmut Löwen

Within a simple model of attractive active Brownian particles, we predict flocking behavior and challenge the widespread idea that alignment interactions are necessary to observe this collective phenomenon. Here, we show that even non-aligning attractive interactions can lead to a flocking state. Monitoring the velocity polarization as the order parameter, w

Andrea Poiatti

We consider the nonlocal Cahn-Hilliard equation with singular (logarithmic) potential and constant mobility in three-dimensional bounded domains and we establish the validity of the instantaneous strict separation property. This means that any weak solution, which is not a pure phase initially, stays uniformly away from the pure phases $\pm1$ from any positi

Lili Bao, Jiahao Lu, Shihui Ying, Stefan Sommer

In this paper, we propose a new approach to deformable image registration that captures sliding motions. The large deformation diffeomorphic metric mapping (LDDMM) registration method faces challenges in representing sliding motion since it per construction generates smooth warps. To address this issue, we extend LDDMM by incorporating both zeroth- and first

David Oechsler

Analogue to the well-known Langevin Monte Carlo method, in this article we provide a method to sample from a target distribution \(\pi\) by simulating a solution of a stochastic differential equation. Hereby, the stochastic differential equation is driven by a general L\'evy process which - other than in the case of Langevin Monte Carlo - allows for non-smoo

Alexander Heimerl, Pooja Prajod, Silvan Mertes, Tobias Baur

We present a multi-modal stress dataset that uses digital job interviews to induce stress. The dataset provides multi-modal data of 40 participants including audio, video (motion capturing, facial recognition, eye tracking) as well as physiological information (photoplethysmography, electrodermal activity). In addition to that, the dataset contains time-cont

Keitaro Takahashi

Faraday tomography is a new method of the study of cosmic magnetic fields enabled by broadband low-frequency radio observations. By Faraday tomography, it is possible to obtain the Faraday dispersion function which contains information on the line-of-sight distributions of magnetic fields, thermal electron density, and cosmic-ray electron density by measurin

Min Cao, Yang Bai, Jingyao Wang, Ziqiang Cao

Under the flourishing development in performance, current image-text retrieval methods suffer from $N$-related time complexity, which hinders their application in practice. Targeting at efficiency improvement, this paper presents a simple and effective keyword-guided pre-screening framework for the image-text retrieval. Specifically, we convert the image and

Pieter De Clercq, Jill Kries, Ramtin Mehraram, Jonas Vanthornhout

[Objective]. After a stroke, one-third of patients suffer from aphasia, a language disorder that impairs communication ability. The standard behavioral tests used to diagnose aphasia are time-consuming and have low ecological validity. Neural tracking of the speech envelope is a promising tool for investigating brain responses to natural speech. The speech e

Miguel Alvarado, Pablo Burset, Alfredo Levy Yeyati

Recent experiments have demonstrated the possibility to design highly controllable junctions on magic angle twisted bilayer graphene, enabling the test of its superconducting transport properties. We show that the presence of chiral pairing in such devices manifests in the appearance of an anomalous Josephson effect ($\phi_0$ behavior) even in the case of sy

Francesco Buscemi, Kodai Kobayashi, Shintaro Minagawa

We construct a resource theory of sharpness for finite-dimensional positive operator-valued measures (POVMs), where the sharpness-non-increasing operations are given by quantum preprocessing channels and convex mixtures with POVMs whose elements are all proportional to the identity operator. As required for a sound resource theory of sharpness, we show that

K. G. Managave, H. A. Redekar, R. B. Kumbhar, S. P. Das

We have analyzed the thermodynamics of slowly rotating magnetized Kerr black-hole, with typical spin parameter $a\le 0.1$ (nearly static) in the background of non-linear electrodynamics. In particular we have studied the Bekenstein-Hawking entropy, Hawking temperature, angular momentum, specific heats and identified regions of parameters for possible phase-t

Alberto Testolin

Creating learning models that can exhibit sophisticated reasoning skills is one of the greatest challenges in deep learning research, and mathematics is rapidly becoming one of the target domains for assessing scientific progress in this direction. In the past few years there has been an explosion of neural network architectures, data sets, and benchmarks sp

Olivier Mathieu

Given a field $K$, we investigate which subgroups of the group Aut$\mathbb{A}^2_K$ of polynomial automorphisms of the plane are linear or not. The results are contrasted. The group Aut$\mathbb{A}^2_K$ itself is nonlinear, except if $K$ is finite, but it contains some large "finite-codimensional" subgroups which are linear. This phenomenon is specific to dime

Kota Yoshiyama, Koji Hukushima

Phase transitions of the $J_1$-$J_2$ Ising model on a square lattice are studied using the higher-order tensor renormalization group(HOTRG) method. This system involves a competition between the ferromagnetic interaction $J_1$ and antiferromagnetic interaction $J_2$. Furthermore, weak first-order and second-order transitions are observed near the ratio $g=J_

Luc Blanchet, Geoffrey Compère, Guillaume Faye, Roberto Oliveri

In our previous work, we proposed an algorithm to transform the metric of an isolated matter source in the multipolar post-Minkowskian approximation in harmonic (de Donder) gauge to the Newman-Unti gauge. We then applied this algorithm at linear order and for specific quadratic interactions known as quadratic tail terms. In the present work, we extend this a

Koun Shirai

In glass physics, order parameters have long been used in the thermodynamic description of glasses, but the nature is not yet clear. The difficulty is how to find order in disordered systems. The usual treatment of glass as an exceptional case causes serious internal inconsistencies in thermodynamics. The issue turns out to be ascribed to a fundamental probl

Federica Bertolotti, Roberto Frigerio

We show that the integral filling volume of a Dehn twist $f$ on a closed oriented surface vanishes, i.e. that the integral simplicial volume of the mapping torus with monodromy $f^n$ grows sublinearly with respect to $n$. We deduce a complete characterization of mapping classes on surfaces with vanishing integral filling volume and, building on results by Pu

Omid Amini, Lucas Gierczak, Harry Richman

In this paper, we study tropical Weierstrass points. These are the analogues for tropical curves of ramification points of line bundles on algebraic curves. For a divisor on a tropical curve, we associate intrinsic weights to the connected components of the locus of tropical Weierstrass points. These are obtained by analyzing the slopes of rational functions

S. Ali, H. Arnold, S. L. Auwens, L. A. Beresford

The High Granularity Timing Detector (HGTD) will be installed in the ATLAS experiment to mitigate pile-up effects during the High Luminosity (HL) phase of the Large Hadron Collider (LHC) at CERN. Low Gain Avalanche Detectors (LGADs) will provide high-precision measurements of the time of arrival of particles at the HGTD, improving the particle-vertex assignm

Lloyd Fung, Adam Konkol, Takuji Ishikawa, Ben Larson

The recent discovery of the striking sheet-like multicellular choanoflagellate species $Choanoeca~flexa$ that dynamically interconverts between two hemispherical forms of opposite orientation raises fundamental questions in cell and evolutionary biology, as choanoflagellates are the closest living relatives of animals. It similarly motivates questions in flu

Jungjun Kim, Changjin Han, Gyuhyeon Nam, Gyeongsu Chae

Most Chinese Grapheme-to-Phoneme (G2P) systems employ a three-stage framework that first transforms input sequences into character embeddings, obtains linguistic information using language models, and then predicts the phonemes based on global context about the entire input sequence. However, linguistic knowledge alone is often inadequate. Language models fr