October 2023 arXiv papers — page 135

Leyou Xu, Bo Zhou

The well known Wagner's theorem states that a graph is a planar graph if and only if it is $K_5$-minor-free and $K_{3,3}$-minor-free. Denote by $AT(G)$ the Alon-Tarsi number of a graph $G$. We show that for any $K_{3,3}$-minor-free graph $G$, $AT(G)\le 5$, there exists a matching $M$ and a forest $F$ such that $AT(G-M)\le 4$ and $AT(G-E(F))\le 3$, extending

F. C. Correia, M. Fazion

The residential sector is responsible for approximately 20 percent of the world's energy-related greenhouse gas emissions. In order to improve this reality, it is essential to help and support the leading actor in this scene, the homeowner. In general, buildings are complex objects as each home may have very particular parameters: different materials (window

Maximilian R. Schuster, Nico Dirkes, Fabian Key, Stefanie Elgeti

Medical therapy for patients with severe heart disease often relies on left ventricular assist devices (LVADs). It is an ongoing topic of research how complications like stagnation and thrombosis can be prevented by using artificial pulsatility. We study a parametric pulse profile and its effect on the left ventricular washout using a computational flow mode

Andrea Radici, Daniele Bevacqua, Leonardo Miele, Davide Martinetti

Increasing cultivated lands, crop homogenization and global food trade have fostered the spread of crop pests and diseases. Optimizing crop protection is urgently needed to ensure food safety. One aspect of crop protection is surveillance, which focuses on the early detection of a parasite, and control, aiming to fight and possibly eradicate it. Network theo

Colm Kelleher, Mohammad Roomy, Frédéric Holweck

It is known that Mermin-Peres like proofs of quantum contextuality can furnish non-local games with a guaranteed quantum strategy, when classically no such guarantee can exist. This phenomenon, also called quantum pseudo-telepathy, has been studied in the case of the so-called Mermin Magic square game. In this paper we review in detail two different ways of

Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou, Xuelong Li

The challenge of image generation has been effectively modeled as a problem of structure priors or transformation. However, existing models have unsatisfactory performance in understanding the global input image structures because of particular inherent features (for example, local inductive prior). Recent studies have shown that self-attention is an efficie

Alexander Roskill, Marienza Caldarola, Sachiko Kuroyanagi, Savvas Nesseris

In this paper, we study the next-to-leading order corrections in the mass multipole expansion, i.e. the mass octupole and current quadrupole, to gravitational wave production by close hyperbolic encounters of compact objects. We find that the signal is again, as in the simple quadrupole case, a burst event with the majority of the released energy occurring d

Rezaul Karim, Soheil Mohamad Alizadeh Shabestary, Amir Rasouli

Predicting temporally consistent road users' trajectories in a multi-agent setting is a challenging task due to unknown characteristics of agents and their varying intentions. Besides using semantic map information and modeling interactions, it is important to build an effective mechanism capable of reasoning about behaviors at different levels of granularit

Chien Wang

A deep learning platform has been developed to forecast the occurrence of the low visibility events or hazes. It is trained by using multi-decadal daily regional maps of various meteorological and hydrological variables as input features and surface visibility observations as the targets. To better preserve the characteristic spatial information of different

Yafei Wang, Hongwei Hou, Wenjin Wang, Xinping Yi

This paper investigates symbol-level precoding (SLP) for high-order quadrature amplitude modulation (QAM) aimed at minimizing the average symbol error rate (SER), leveraging both constructive interference (CI) and noise power to gain superiority in full signal-to-noise ratio (SNR) ranges. We first construct the SER expression with respect to the transmitted

Jincheng Wang, Yue Gao

Time Series Forecasting (TSF) is a widely researched topic with broad applications in weather forecasting, traffic control, and stock price prediction. Extreme values in time series often significantly impact human and natural systems, but predicting them is challenging due to their rare occurrence. Statistical methods based on Extreme Value Theory (EVT) pro

Ivanna Kramer, Kevin Weirauch, Sabine Bauer, Mark Oliver Mints

Rollator walkers allow people with physical limitations to increase their mobility and give them the confidence and independence to participate in society for longer. However, rollator walker users often have poor posture, leading to further health problems and, in the worst case, falls. Integrating sensors into rollator walker designs can help to address th

Yuyang Liu, Weijun Dong, Yingdong Hu, Chuan Wen

Humans often acquire new skills through observation and imitation. For robotic agents, learning from the plethora of unlabeled video demonstration data available on the Internet necessitates imitating the expert without access to its action, presenting a challenge known as Imitation Learning from Observations (ILfO). A common approach to tackle ILfO problems

Boštjan Brešar, María Gracia Cornet, Tanja Dravec, Michael Henning

While a number of bounds are known on the zero forcing number $Z(G)$ of a graph $G$ expressed in terms of the order of a graph and maximum or minimum degree, we present two bounds that are related to the (upper) total domination number $\gamma_t(G)$ (resp. $\Gamma_t(G)$) of $G$. We prove that $Z(G)+\gamma_t(G)\le n(G)$ and $Z(G)+\frac{\Gamma_t(G)}{2}\le n(G)

V. H. Bui, A. A. Margun

This paper proposes a new algorithm for compensating external disturbances for class of multi-channel linear systems. The solution to this problem is based on the use of the internal model principle and the extended error adaptation algorithm. It is assumed that the disturbance is the output of an autonomous linear generator with unknown parameters. At the f

Seonghyun Park, Narae Ryu, Gahee Kim, Dongyeop Woo

The celebrated message-passing updates for graph neural networks allow representing large-scale graphs with local and computationally tractable updates. However, the updates suffer from backtracking, i.e., a message flowing through the same edge twice and revisiting the previously visited node. Since the number of message flows increases exponentially with t

Samuel T. Spencer, Alison M. W. Mitchell, Brian Reville

Recent results from LHAASO and Tibet AS$\gamma$ suggest that the Crab Nebula's gamma-ray spectrum extends to the PeV energy range, however the production mechanisms of this highest energy emission remain unclear. It has been postulated that a secondary component of hadronic emission could explain the highest energy gamma-ray flux points, however the origin a

Natalie Chung, Rafael I. Nepomechie

Two indispensable algorithms in an introductory course on Quantum Computing are Grover's search algorithm and quantum phase estimation. Quantum counting is a simple yet beautiful blend of these two algorithms, and it is therefore an attractive topic for a student project in such a course. However, a sign that is irrelevant when implementing Grover's algorith

Zhengmeng Xu, Yujie Wang, Xiaotong Feng, Yilin Wang

We propose a time series forecasting method named Quantum Gramian Angular Field (QGAF). This approach merges the advantages of quantum computing technology with deep learning, aiming to enhance the precision of time series classification and forecasting. We successfully transformed stock return time series data into two-dimensional images suitable for Convol

C. Joly, S. Berthelot, S. Blivet, F. Chatelet

Within the framework of the first phase of MYRRHA (Multi-purpose hYbrid Research Reactor for High-tech Applications) project, called MINERVA, IJCLab was in charge of a fully equipped Spoke cryomodule prototype development, tested at 2K. It integrates two superconducting single spoke cavities, the RF power couplers and the Cold Tuning Systems associated. On t

Fernando L. Metz, Cristian Bonatto, Sandra D. Prado

The statistical properties of speckle patterns have important applications in optics, oceanography, and transport phenomena in disordered systems. Here we obtain closed-form analytic results for the amplitude distribution of speckle patterns formed by a random number of partial waves characterized by an arbitrary phase distribution, generalizing classical re

Peiyu Liao, Yuxuan Zhao, Dawei Guo, Yibo Lin

In this paper, we present a new analytical 3D placement framework with a bistratal wirelength model for F2F-bonded 3D ICs with heterogeneous technology nodes based on the electrostatic-based density model. The proposed framework, enabled GPU-acceleration, is capable of efficiently determining node partitioning and locations simultaneously, leveraging the ded

Atharva Kulkarni, Ajinkya Kulkarni, Miguel Couceiro, Hanan Aldarmaki

Recently, large pre-trained multilingual speech models have shown potential in scaling Automatic Speech Recognition (ASR) to many low-resource languages. Some of these models employ language adapters in their formulation, which helps to improve monolingual performance and avoids some of the drawbacks of multi-lingual modeling on resource-rich languages. Howe

Hao Wu

Recently, Ivan Mihajlin and Alexander Smal proved a composition theorem of a universal relation and some function via so called xor composition, that is there exists some function $f:\{0,1\}^n \rightarrow \{0,1\}$ such that $\textsf{CC}(\text{U}_n \diamond \text{KW}_f) \geq 1.5n-o(n)$ where $\textsf{CC}$ denotes the communication complexity of the problem. I

Martin Tancer

Markov proved that there exists an unrecognizable 4-manifold, that is, a 4-manifold for which the homeomorphism problem is undecidable. In this paper we consider the question how close we can get to S^4 with an unrecognizable manifold. One of our achievements is that we show a way to remove so-called Markov's trick from the proof of existence of such a manif

Shimpei Makida, Atsushi Nakayasu

This study investigated the stability of Hamilton--Jacobi equation on general metric spaces with a perturbation in some whole space. This type of stability appears in the domain perturbation problem. We find that the stability holds when the set converges in the Hausdorff sense and when the metric converges in some uniform sense. Examples of the perturbed sp

Hazarapet Tunanyan, Dejia Xu, Shant Navasardyan, Zhangyang Wang

Recent advances in text-to-image diffusion models have enabled the photorealistic generation of images from text prompts. Despite the great progress, existing models still struggle to generate compositional multi-concept images naturally, limiting their ability to visualize human imagination. While several recent works have attempted to address this issue, t

Guozheng Ma, Lu Li, Sen Zhang, Zixuan Liu

Plasticity, the ability of a neural network to evolve with new data, is crucial for high-performance and sample-efficient visual reinforcement learning (VRL). Although methods like resetting and regularization can potentially mitigate plasticity loss, the influences of various components within the VRL framework on the agent's plasticity are still poorly und

Pedro Giesteira Cotovio, Ernesto Jimenez-Ruiz, Catia Pesquita

Knowledge Graphs (KG) are the backbone of many data-intensive applications since they can represent data coupled with its meaning and context. Aligning KGs across different domains and providers is necessary to afford a fuller and integrated representation. A severe limitation of current KG alignment (KGA) algorithms is that they fail to articulate logical t

Ahmed Alia, Mohammed Maree, Mohcine Chraibi, Armin Seyfried

Analyzing the microscopic dynamics of pushing behavior within crowds can offer valuable insights into crowd patterns and interactions. By identifying instances of pushing in crowd videos, a deeper understanding of when, where, and why such behavior occurs can be achieved. This knowledge is crucial to creating more effective crowd management strategies, optim

Zhanqiang Bai, Minyan Fang, Zhaojun Wang

Let $\mathfrak{g}$ be a simple complex Lie algebra.A generalized Verma module induced from a one-dimensional representation of a parabolic subalgebra of $\mathfrak{g}$ is called a scalar generalized Verma module of $\mathfrak{g}$. In this article, we use Gelfand-Kirillov dimension to determine the reducibility of scalar generalized Verma modules of $\mathfra

Jon Ayerdi, Asier Iriarte, Pablo Valle, Ibai Roman

Autonomous Driving Systems (ADSs) are complex Cyber-Physical Systems (CPSs) that must ensure safety even in uncertain conditions. Modern ADSs often employ Deep Neural Networks (DNNs), which may not produce correct results in every possible driving scenario. Thus, an approach to estimate the confidence of an ADS at runtime is necessary to prevent potentially

Jarred Gershon Green, Alessandro Carosi, Lara Nava, Barbara Patricelli

The detection of gravitational waves from a binary neutron star merger by Advanced LIGO and Advanced Virgo (GW170817), along with the discovery of the electromagnetic counterparts of this gravitational wave event, ushered in a new era of multimessenger astronomy, providing the first direct evidence that BNS mergers are progenitors of short gamma-ray bursts (

Belle Collaboration, S. Maity, R. Garg, S. Bahinipati

We search for the baryon and lepton number violating charm decays, $D \rightarrow p\ell$, where $D$ is either a $D^0$ or a $\overline{D}^0$ and $\ell$ is a muon or an electron, using a data sample of $921\,\mathrm{fb}^{-1}$ collected by the Belle detector at the KEKB asymmetric energy $e^{+}e^{-}$ collider. In the absence of significant signals, we set upper

Tong Xuan Nguyen, Giuseppe Scola, Dimitrios Tsagkarogiannis

We consider a binary system of small and large spheres of finite size in a continuous medium interacting via a non-negative potential. We work in the canonical ensemble and compute upper and lower bound for the free energy at finite and infinite volume by first integrating over the small spheres and then treating the effective system of the large ones which

Himanshu Chaudhary, Niyaz Uddin Molla, Madhur Khurana, Ujjal Debnath

In this work, we assume the FRLW Universe which is filled with dark matter along with dark energy in the framework of Horava-Lifshitz (HL) gravity. The dark energy is considered as the Linear (Model I) and CPL (Model II) parametrizations of the equation of state parameter. For both models, we express the Hubble parameter $H(z)$ in terms of the model paramete

Rubén Gómez González, Vicente Garzó

The Enskog kinetic equation is considered to determine the mobility $\lambda$ and diffusion $D$ transport coefficients of intruders immersed in a granular gas of inelastic hard spheres (grains). Intruders and grains are in contact with a thermal bath, which plays the role of a background gas. As usual, the influence of the latter on the dynamics of intruders

Pex Tufvesson, Frida Heskebeck

This article discusses practical and theoretical aspects of real-time brain computer interface control methods based on Bayesian statistics. We investigate and improve the performance of automatic control and feedback algorithms of a reactive brain computer interface based on a visual oddball paradigm for faster statistical convergence. We introduce transfer

Hongyi Cao, Yunfeng Shi, Zhifei Zhang

In this paper, we establish the Anderson localization, strong dynamical localization and the $(\frac 12-)$-H\"older continuity of the integrated density of states (IDS) for some multi-dimensional discrete quasi-periodic (QP) Schr\"odinger operators with asymmetric $C^2$-cosine type potentials. We extend both the iteration scheme of \cite{CSZ23a} and the inte

Jorge García-Beni, Gian Luca Giorgi, Miguel C. Soriano, Roberta Zambrini

Squeezing is known to be a quantum resource in many applications in metrology, cryptography, and computing, being related to entanglement in multimode settings. In this work, we address the effects of squeezing in neuromorphic machine learning for time series processing. In particular, we consider a loop-based photonic architecture for reservoir computing an

Deyou Zhang, Ming Xiao, Zhibo Pang, Lihui Wang

We consider a broadband over-the-air computation empowered model aggregation approach for wireless federated learning (FL) systems and propose to leverage an intelligent reflecting surface (IRS) to combat wireless fading and noise. We first investigate the conventional node-selection based framework, where a few edge nodes are dropped in model aggregation to

Minchan Kang

In this paper, we give an elementary proof on the existence of an effective uniform upper bound on the size of integral periodic orbits of a single endomorphism in an affine space, dependent solely on its dimension. In fact, we derive a formula relating the primitive period to the local primitive period obtained through reduction modulo prime number. In part

Qingkai Fang, Yan Zhou, Yang Feng

Direct speech-to-speech translation (S2ST) translates speech from one language into another using a single model. However, due to the presence of linguistic and acoustic diversity, the target speech follows a complex multimodal distribution, posing challenges to achieving both high-quality translations and fast decoding speeds for S2ST models. In this paper,

Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang

Recent research on time-series self-supervised models shows great promise in learning semantic representations. However, it has been limited to small-scale datasets, e.g., thousands of temporal sequences. In this work, we make key technical contributions that are tailored to the numerical properties of time-series data and allow the model to scale to large d

Jinzhu Jia, Zhiqing Wei, Ruiyun Zhang, Lin Wang

Despite the millimeter wave technology fulfills the low-latency and high data transmission, it will cause severe Doppler Frequency Shift (DFS) for high-speed vehicular network, which tremendously damages the communication performance. In this paper, we propose an Integrated Sensing and Communication (ISAC) enabled DFS estimation and compensation algorithm. F

C. Hanser, R. Adam, P. Ade, H. Ajeddig

High-resolution mapping of the hot gas in galaxy clusters is a key tool for cluster-based cosmological analyses. Taking advantage of the NIKA2 millimeter camera operated at the IRAM 30-m telescope, the NIKA2 SZ Large Program seeks to get a high-resolution follow-up of 38 galaxy clusters covering a wide mass range at intermediate to high redshift. The measure

Nawaf Bou-Rabee, Tore Selland Kleppe

We introduce $5/2$- and $7/2$-order $L^2$-accurate randomized Runge-Kutta-Nystr\"{o}m methods, tailored for approximating Hamiltonian flows within non-reversible Markov chain Monte Carlo samplers, such as unadjusted Hamiltonian Monte Carlo and unadjusted kinetic Langevin Monte Carlo. We establish quantitative $5/2$-order $L^2$-accuracy upper bounds under gra

Mohammed Attrash, Sergei Masis, Sergey Hazanov, Oleg Shtempluck

Frequency mixing processes in spin systems have a variety of applications in meteorology and in quantum data processing. Spin spectroscopy based on frequency mixing offers some advantages, including the ability to eliminate crosstalk between driving and detection. We experimentally explore nonlinear frequency mixing processes with negatively charged nitrogen

Jian Wang, Yi Cheng, Dongding Lin, Chak Tou Leong

Target-oriented dialogue systems, designed to proactively steer conversations toward predefined targets or accomplish specific system-side goals, are an exciting area in conversational AI. In this work, by formulating a <dialogue act, topic> pair as the conversation target, we explore a novel problem of personalized target-oriented dialogue by considering pe

Masato Hoshino

The reconstruction theorem and the multilevel Schauder estimate have central roles in the analytic theory of regularity structures [17]. Inspired by [26], we provide elementary proofs for them by using the semigroup of operators. Essentially, we use only the semigroup property and the upper estimates of kernels. Moreover, we refine the several types of Besov

A. V. Slunyaev, V. I. Shrira

Rogue waves are known to be much more common on jet currents. A possible explanation was put forward in [ [V. Shrira and A. Slunyaev, Nonlinear dynamics of trapped waves on jet currents and rogue waves, Phys. Rev. E 89, 041002, 2014]]: for the waves trapped on a current robust long-lived envelope solitary waves localized in both horizontal directions become

Ke Jin, Wankou Yang

The large-scale pretrained model CLIP, trained on 400 million image-text pairs, offers a promising paradigm for tackling vision tasks, albeit at the image level. Later works, such as DenseCLIP and LSeg, extend this paradigm to dense prediction, including semantic segmentation, and have achieved excellent results. However, the above methods either rely on CLI

Matteo El-Hariry, Antoine Richard, Miguel Olivares-Mendez

Nowadays, realistic simulation environments are essential to validate and build reliable robotic solutions. This is particularly true when using Reinforcement Learning (RL) based control policies. To this end, both robotics and RL developers need tools and workflows to create physically accurate simulations and synthetic datasets. Gazebo, MuJoCo, Webots, Pyb

Deepak Raina, SH Chandrashekhara, Richard Voyles, Juan Wachs

Ultrasound is a commonly used medical imaging modality that requires expert sonographers to manually maneuver the ultrasound probe based on the acquired image. Autonomous Robotic Ultrasound (A-RUS) is an appealing alternative to this manual procedure in order to reduce sonographers' workload. The key challenge to A-RUS is optimizing the ultrasound image qual

D. Bhattacharjee, P. K. Chattopadhyay

In this article, a new class of exact solutions for anisotropic compact objects is presented. Admitting the modified Chaplygin equation of state $p=H\rho-\frac{K}{\rho^{n}}$, where $H$, $K$ and $n$ are constants with $0<n\leq1$, and employing the Buchdahl-I metric within the framework of the general relativity stellar model is obtained. Recent observations o

Mingrui Liu, Xinyang Tang, Yeqiang Qian, Jiming Chen

Precise and long-term stable localization is essential in parking lots for tasks like autonomous driving or autonomous valet parking, \textit{etc}. Existing methods rely on a fixed and memory-inefficient map, which lacks robust data association approaches. And it is not suitable for precise localization or long-term map maintenance. In this paper, we propose

Nikolina Čović, Jochen L. Cremer, Hrvoje Pandžić

Accelerated development of demand response service provision by the residential sector is crucial for reducing carbon-emissions in the power sector. Along with the infrastructure advancement, encouraging the end users to participate is crucial. End users highly value their privacy and control, and want to be included in the service design and decision-making

Hiroko Miyamoto, Matteo Battisti, Alexander Belov, Mario Bertaina

The second generation Extreme Universe Space Observatory on a Super-Pressure Balloon (EUSO-SPB2) mission is a stratospheric balloon mission developed within the Joint Exploratory Missions for Extreme Universe Space Observatory (JEM-EUSO) program. The Fluorescence Telescope (FT) is one of the two separate Schmidt telescopes of EUSO-SPB2, which aims at measuri

Stuart Semple, Ramon Ferrer-i-Cancho, Morgan L. Gustison

Linguistic laws, the common statistical patterns of human language, have been investigated by quantitative linguists for nearly a century. Recently, biologists from a range of disciplines have started to explore the prevalence of these laws beyond language, finding patterns consistent with linguistic laws across multiple levels of biological organisation, fr

Wontae Kim, Lauri Särkiö

We prove a local higher integrability result for the gradient of a weak solution to parabolic double-phase systems of $p$-Laplace type when $\tfrac{2n}{n+2}< p\le2$. The result is based on a reverse H\"older inequality in intrinsic cylinders combining $p$-intrinsic and $(p,q)$-intrinsic geometries. A singular scaling deficits affects the range of $q$.

S. Metayer, S. Teber

We review several variants of three-dimensional quantum electrodynamics (QED$_3$) with $N_f$ fermion (or boson) flavors including fermionic (or spinorial) QED$_3$, bosonic (or scalar) QED$_3$, $\mathcal{N}=1$ supersymmetric QED and also models of reduced QED (supersymmetric or not). We begin with an introduction to these models and their flow to a stable inf

Teppei Okumura, Atsushi Taruya, Toshiki Kurita, Takahiro Nishimichi

We present an analytic model of nonlinear correlators of galaxy/halo ellipticities in redshift space. The three-dimensional ellipticity field is not affected by the redshift-space distortion (RSD) at linear order, but by the nonlinear one, known as the Finger-of-God effect, caused by the coordinate transformation from real to redshift space. Adopting a simpl

Victor M. Buchstaber, Alexander P. Veselov

In 1956 Hirzebruch found an explicit formula for the denominators of the Todd polynomials, which was proved later in his joint work with Atiyah. We present a new formula for the Todd polynomials in terms of the ``forgotten symmetric functions", which follows from our previous work on complex cobordisms. In particular, this leads to a simpler proof of the Hir

Ghada Dushaq, Solomon Serunjogi, Srinivasa R. Tamalampudi, Mahmoud Rasras

Tunable optical materials are indispensable elements in modern optoelectronics, especially in integrated photonics circuits where precise control over the effective refractive index is essential for diverse applications. Two-dimensional materials like Transition Metal Dichalcogenides (TMDs) and graphene exhibit remarkable optical responses to external stimul

Leonhard Grosse, Sara Saeidian, Tobias Oechtering

Data publishing under privacy constraints can be achieved with mechanisms that add randomness to data points when released to an untrusted party, thereby decreasing the data's utility. In this paper, we analyze this privacy-utility tradeoff for the pointwise maximal leakage privacy measure and a general class of convex utility functions. Pointwise maximal le

Sankalp Vyas, Amar Nath Patra, Raj Mani Shukla

Healthcare is one of the foremost applications of machine learning (ML). Traditionally, ML models are trained by central servers, which aggregate data from various distributed devices to forecast the results for newly generated data. This is a major concern as models can access sensitive user information, which raises privacy concerns. A federated learning (

Junho Kim, Byung-Kwan Lee, Yong Man Ro

Unsupervised semantic segmentation aims to achieve high-quality semantic grouping without human-labeled annotations. With the advent of self-supervised pre-training, various frameworks utilize the pre-trained features to train prediction heads for unsupervised dense prediction. However, a significant challenge in this unsupervised setup is determining the ap

Linfeng Liang, Yao Deng, Kye Morton, Valtteri Kallinen

Automated Uncrewed Aerial Vehicle (UAV) landing is crucial for autonomous UAV services such as monitoring, surveying, and package delivery. It involves detecting landing targets, perceiving obstacles, planning collision-free paths, and controlling UAV movements for safe landing. Failures can lead to significant losses, necessitating rigorous simulation-based

Rob Silversmith

The cross-ratio degree problem counts configurations of n points on P^1 with n-3 prescribed cross-ratios. Cross-ratio degrees arise in many corners of combinatorics and geometry, but their structure is not well-understood in general. Interestingly, examining various special cases of the problem can yield combinatorial structures that are both diverse and ric

Kosuke Nakayama, Hiroto Fukuta, Hiroshi Watanabe

The digitalization of society is rapidly developing toward the realization of the digital twin and metaverse. In particular, point clouds are attracting attention as a media format for 3D space. Point cloud data is contaminated with noise and outliers due to measurement errors. Therefore, denoising and outlier detection are necessary for point cloud processi

Gayatri Das, S. Saha Ray

This manuscript studies the numerical solution of the time-fractional Burgers-Huxley equation in a reproducing kernel Hilbert space. The analytical solution of the equation is obtained in terms of a convergent series with easily computable components. It is observed that the approximate solution uniformly converges to the exact solution for the aforementione

Hiroko Miyamoto, Matteo Battisti, Dario Barghini, Alexander Belov

Mini-EUSO is a wide Field-of-View (FoV, 44$^{\circ}$) telescope currently in operation from a nadia-facing UV-transparent window in the Russian Zvezda module on the International Space Station (ISS). It is the first detector of the JEM-EUSO program deployed on the ISS, launched in August 2019. The main goal of Mini-EUSO is to measure the UV emissions from th

Beatrice Pozzetti, Andrés Sambarino

We interpret the Hilbert entropy of a convex projective structure on a closed higher-genus surface as the Hausdorff dimension of the non-differentiability points of the limit set in the full flag space $\mathcal F(\mathbb R^3)$. Generalizations for regularity properties of boundary maps between locally conformal representations are also discussed. An ingredi

Eduardo G. Altmann, Jonathan Spreer

We propose a Monte Carlo method to efficiently find, count, and sample abstract triangulations of a given manifold M. The method is based on a biased random walk through all possible triangulations of M (in the Pachner graph), constructed by combining (bi-stellar) moves with suitable chosen accept/reject probabilities (Metropolis-Hastings). Asymptotically, t

Yizhi Wang, Shichuan Xue, Yaxuan Wang, Jiangfang Ding

Variational quantum algorithms (VQAs) combining the advantages of parameterized quantum circuits and classical optimizers, promise practical quantum applications in the Noisy Intermediate-Scale Quantum era. The performance of VQAs heavily depends on the optimization method. Compared with gradient-free and ordinary gradient descent methods, the quantum natura

Nizar Demni, Hachem Kadri

Random features have been introduced to scale up kernel methods via randomization techniques. In particular, random Fourier features and orthogonal random features were used to approximate the popular Gaussian kernel. Random Fourier features are built in this case using a random Gaussian matrix. In this work, we analyze the bias and the variance of the kerne

Stephen Lynch

We prove a differential Harnack inequality for noncompact convex hypersurfaces flowing with normal speed equal to a symmetric function of their principal curvatures. This extends a result of Andrews for compact hypersurfaces. We assume that the speed of motion is one-homogeneous, uniformly elliptic, and suitably 'uniformly' inverse-concave as a function of t

Elisa Maggio

Gravitational waves open the possibility to investigate the nature of compact objects and probe the horizons of black holes. Some models of modified gravity predict the presence of horizonless and singularity-free compact objects. Such dark compact objects would emit a gravitational-wave signal which differs from the standard black hole scenario. In this cha

Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu

In this paper, we revisit the problem of sparse linear regression in the local differential privacy (LDP) model. Existing research in the non-interactive and sequentially local models has focused on obtaining the lower bounds for the case where the underlying parameter is $1$-sparse, and extending such bounds to the more general $k$-sparse case has proven to

Daniel Hodgson

In this chapter we examine the quantised electromagnetic (EM) field in the context of a Schr\"odinger equation for single photons. For clarity we consider only a one-dimensional system. As a universal tool for calculating the time-evolution of quantum states, a Schr\"odinger equation must exist that describes the propagation of single photons. Being inherent

Yun Zhu, Yaoke Wang, Haizhou Shi, Zhenshuo Zhang

Graph-structured data is ubiquitous in the world which models complex relationships between objects, enabling various Web applications. Daily influxes of unlabeled graph data on the Web offer immense potential for these applications. Graph self-supervised algorithms have achieved significant success in acquiring generic knowledge from abundant unlabeled grap

Yunyi Zhang

Independent or i.i.d. innovations is an essential assumption in the literature for analyzing a vector time series. However, this assumption is either too restrictive for a real-life time series to satisfy or is hard to verify through a hypothesis test. This paper performs statistical inference on a sparse high-dimensional vector autoregressive time series, a

Sebastian J. Schlecht, Karolina Prawda, Rudolf Rabenstein, Maximilian Schäfer

The image-source method is widely applied to compute room impulse responses (RIRs) of shoebox rooms with arbitrary absorption. However, with increasing RIR lengths, the number of image sources grows rapidly, leading to slow computation. In this paper, we derive a closed-form expression for the damping density, which characterizes the overall multi-slope ener

Niccolo Fonio, Pierre Sagaut, Giuseppe Di Molfetta

Lattice Gas Cellular Automata (LGCA) is a classical numerical method widely known and applied to simulate several physical phenomena. In this paper, we study the translation of LGCA on quantum computers (QC) using computational basis encoding (CBE), developing methods for different purposes. In particular, we clarify and discuss some fundamental limitations

Mateusz Michalkiewicz, Masoud Faraki, Xiang Yu, Manmohan Chandraker

Overfitting to the source domain is a common issue in gradient-based training of deep neural networks. To compensate for the over-parameterized models, numerous regularization techniques have been introduced such as those based on dropout. While these methods achieve significant improvements on classical benchmarks such as ImageNet, their performance diminis

Wei Zhang

We give a conditional lower bound on the number of non-trivial simple zeros for the Dedekind zeta function $\zeta_{K}(s)$, where $K$ is a quadratic number field. The conditional result is given by assuming a Lindel\"of on average (in the $L^{6}$ sense) for both $\zeta(s)$ and $L(s,\chi)$, which can be seen as a stronger version of Conrey-Gonek-Ghosh's \cite{

Masood Hamed Saghayan, Mohammad Hossein Zolfagharnasab, Ali Khadem, Farzam Matinfar

Bipolar Disorder (BD) is a psychiatric condition diagnosed by repetitive cycles of hypomania and depression. Since diagnosing BD relies on subjective behavioral assessments over a long period, a solid diagnosis based on objective criteria is not straightforward. The current study responded to the described obstacle by proposing a hybrid GAN-CNN model to diag

Shulei Ni, Yichao Li, Xin Zhang

The cosmic microwave background (CMB) stands as a pivotal source for studying weak gravitational lensing. While the lensed CMB aids in constraining cosmological parameters, it simultaneously smooths the original CMB's features. The angular power spectrum of the unlensed CMB showcases sharper acoustic peaks and more pronounced damping tails, enhancing the pre

K. Wimmer, P. Ruotsalainen, S. M. Lenzi, A. Poves

Excited states in the $T_z = 0, -1$ nuclei $^{62}$Ga and $^{62}$Ge were populated in direct reactions of relativistic radioactive ion beams at the RIBF. Coincident \grays were measured with the DALI2$^+$ array and uniquely assigned to the $A=62$ isobars. In addition, $^{62}$Ge was also studied independently at JYFL-ACCLAB using the ${}^{24}$Mg(${}^{40}$Ca,$2

Archie Cable, Arttu Rajantie

The stochastic effective theory approach, often called stochastic inflation, is widely used in cosmology to describe scalar field dynamics during inflation. The existing formulations are, however, more qualitative than quantitative because the connection to the underlying quantum field theory (QFT) has not been properly established. A concrete sign of this i

Che Liu, Sibo Cheng, Miaojing Shi, Anand Shah

In the field of medical Vision-Language Pre-training (VLP), significant efforts have been devoted to deriving text and image features from both clinical reports and associated medical images. However, most existing methods may have overlooked the opportunity in leveraging the inherent hierarchical structure of clinical reports, which are generally split into

Lochana Telugu Rajesh, Tapadhir Das, Raj Mani Shukla, Shamik Sengupta

The rapid growth in Internet of Things (IoT) technology has become an integral part of today's industries forming the Industrial IoT (IIoT) initiative, where industries are leveraging IoT to improve communication and connectivity via emerging solutions like data analytics and cloud computing. Unfortunately, the rapid use of IoT has made it an attractive targ

Vladimir Mikhailets, Olena Atlasiuk

The aim of the paper is to develop a general theory of solvability of linear inhomogeneous boundary-value problems for systems of ordinary differential equations of arbitrary order in Sobolev spaces. Boundary conditions are allowed to be overdetermined or underdetermined. They may contain derivatives, of the unknown vector-valued function, whose integer or f

Yujia Li, Feng Qiu, Yixuan Chen, Yunhe Hou

When deploying fast charging stations (FCSs) to support long-distance trips of electric vehicles (EVs), there exist indirect network effects: while the gradual diffusion of EVs directly influences the timing and capacities of FCS allocation, the decisions for FCS allocations, in turn, impact the drivers' willingness to adopt EVs. This interplay, if neglected

Wentao Yu, Shuo Chen, Chen Gong, Gang Niu

Recently, Graph Transformer (GT) models have been widely used in the task of Molecular Property Prediction (MPP) due to their high reliability in characterizing the latent relationship among graph nodes (i.e., the atoms in a molecule). However, most existing GT-based methods usually explore the basic interactions between pairwise atoms, and thus they fail to

Sergey Komech, Andrey Kupavskii, Alexei Vezolainen

We consider several basic questions on distributed routing in directed graphs with multiple additive costs, or metrics, and multiple constraints. Distributed routing in this sense is used in several protocols, such as IS-IS and OSPF. A practical approach to the multi-constraint routing problem is to, first, combine the metrics into a single `composite' metri

Siham Aouissi, Daniel C. Mayer

Let (k1,k2,k3,k4) be a quartet of cyclic cubic number fields sharing a common conductor c=pqr divisible by exactly three prime(power)s p,q,r. For those components k of the quartet whose 3-class group Cl(3,k) = Z/3Z x Z/3Z is elementary bicyclic, the automorphism group M = Gal(F(3,2,k)/k) of the maximal metabelian unramified 3-extension of k is determined by

Erkan Karabulut, Victoria Degeler, Paul Groth

Digital Twins (DT) are a promising concept in cyber-physical systems research due to their advanced features including monitoring and automated reasoning. Semantic technologies such as Knowledge Graphs (KG) are recently being utilized in DTs especially for information modelling. Building on this move, this paper proposes a pipeline for semantic association r

Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang

ELECTRA pre-trains language models by detecting tokens in a sequence that have been replaced by an auxiliary model. Although ELECTRA offers a significant boost in efficiency, its potential is constrained by the training cost brought by the auxiliary model. Notably, this model, which is jointly trained with the main model, only serves to assist the training o

Philipp Schaer, Svetlana Myshkina, Jüri Keller

The German Information Retrieval community is located in two different sub-fields: Information and computer science. There are no current studies that investigate these communities on a scientometric level. Available studies only focus on the information scientific part of the community. We generated a data set of 401 recent IR-related publications extracted