October 2022 arXiv papers — page 6

Akira Ohnishi, Asanosuke Jinno, Koichi Murase, Yasushi Nara

We examine the $\Lambda$ potential from the chiral effective field theory ($\chi$EFT) via the $\Lambda$ directed flow from heavy-ion collisions. We implement the $\Lambda$ potential obtained from the $\chi$EFT in a vector potential version of relativistic quantum molecular dynamics. We find that the $\Lambda$ potentials obtained from the $\chi$EFT assuming w

Léonard Cadilhac, Éric Ricard

We give an alternative proof of a Marcinkiewicz interpolation theorem for non commutative maximal functions and positive maps, slightly refining earlier versions of the statement. The main novelty is that it provides a substitute for the maximal function of a martingale in $L_p$, $1<p\leq \infty$, losing very little on numerical constants. For non positive m

Swati Gavas, J S Bagla, Nishikanta Khandai, Girish Kulkarni

Sheth-Tormen mass function has been widely used to quantify the abundance of dark matter halos. It is a significant improvement over the Press-Schechter mass function as it uses ellipsoidal collapse in place of spherical collapse. Both of these mass functions can be written in a form that is universal, i.e., independent of cosmology and power spectrum when s

Lynn R. LaMotte

This paper establishes three properties of F-statistics for inference about the mean vector in multiple regression and analysis of variance. The extra SSE due to imposing a set of linear conditions on the model tests the estimable part of those conditions. All other possible numerator sums of squares that test the same have not-lesser degrees of freedom and

Gelu Paşa

We study the linear stability of the displacement of three Stokes fluids with constant viscosity in a porous medium when the middle fluid is contained in a bounded region. We use the Hele-Shaw model. The eigenfunctions of the stability system are the amplitudes of the linear perturbations. These amplitudes must be small. We get unbounded eigenfunctions. So t

Ayushi Singhania, Jeroen van den Brink, Satoshi Nishimoto

We study the interplay of disorder and Heisenberg interactions in Kitaev model on honeycomb lattice. The effect of disorder on the transition between Kitaev spin liquid and magnetic ordered states as well as the stability of magnetic ordering is investigated. Using Lanczos exact diagonalization we discuss the consequences of two types of disorder: (i) random

Kamran Shakoor, Johann Davidov

We find geometric conditions on a Hermitian-Weyl manifold under which the complex structure is a pseudo-harmonic map in the sense of G. Kokarev \cite{K09} from the manifold into its twistor space. This is done under the assumption that the dimension of the manifold is four or the Hermitian-Weyl structure is locally conformally K\"ahler.

Shuaijun Liu, Jiaying Yin, Zishu Zeng, Jingjin Wu

Fog computing is an emerging distributed computing model for the Internet of Things (IoT). It extends computing and caching functions to the edge of wireless networks. Uncrewed Aerial Vehicles (UAVs) provide adequate support for fog computing. UAVs can not only act as a relay between mobile users and physically remote edge devices to avoid costly long-range

Manohar Teja Kalluri, Vagesh D. Narasimhamurthy

This article aims to make a detailed analysis of co-flowing plane Couette flows. Particularly, the variation of flow quantities from the turbulent to non-turbulent region is studied. While the enstrophy exhibits a sharp jump, the other quantities (e.g., mean velocity, Reynolds normal stress, and kinetic energy) show a continuous variation across the interfac

Mohamad Arafeh, Hadi Otrok, Hakima Ould-Slimane, Azzam Mourad

Numerous research recently proposed integrating Federated Learning (FL) to address the privacy concerns of using machine learning in privacy-sensitive firms. However, the standards of the available frameworks can no longer sustain the rapid advancement and hinder the integration of FL solutions, which can be prominent in advancing the field. In this paper, w

Paul M Mannix, Calum S Skene, Didier Auroux, Florence Marcotte

Many physical questions in fluid dynamics can be recast in terms of norm constrained optimisation problems; which in-turn, can be further recast as unconstrained problems on spherical manifolds. Due to the nonlinearities of the governing PDEs, and the computational cost of performing optimal control on such systems, improving the numerical convergence of the

Serge Galam

I review and extend the set of unifying principles, which allow comparing all models of opinion dynamics within one single frame. Within the Global Unifying Frame (GUF), any specific update rule chosen to study opinion dynamics for discrete individual choices is recast into a probabilistic update formula. The associated dynamics is deployed using a general p

Ki-Seok Kim

Black hole is well known to be a fast scrambler, responsible for physics of quantum chaos in dual holography. Recently, the Euclidean worm hole has been proposed to play a central role in the chaotic behavior of the spectral form factor. Furthermore, this phenomena was reinterpreted based on an effective field theory approach for quantum chaos. Since the gra

Susannah Kate Devitt

This chapter explores moral responsibility for civilian harms by human-artificial intelligence (AI) teams. Although militaries may have some bad apples responsible for war crimes and some mad apples unable to be responsible for their actions during a conflict, increasingly militaries may 'cook' their good apples by putting them in untenable decision-making e

Thomas Hotz, Huiling Le, Andrew T. A. Wood

We prove a central limit theorem (CLT) for the Frechet mean of independent and identically distributed observations in a compact Riemannian manifold assuming that the population Frechet mean is unique. Previous general CLT results in this setting have assumed that the cut locus of the Frechet mean lies outside the support of the population distribution. So f

Shubham Mittal, Preslav Nakov

We present our system for the two subtasks of the shared task on propaganda detection in Arabic, part of WANLP'2022. Subtask 1 is a multi-label classification problem to find the propaganda techniques used in a given tweet. Our system for this task uses XLM-R to predict probabilities for the target tweet to use each of the techniques. In addition to finding

Jiangyu Han, Yuhang Cao, Heng Lu, Yanhua Long

In recent years, speaker diarization has attracted widespread attention. To achieve better performance, some studies propose to diarize speech in multiple stages. Although these methods might bring additional benefits, most of them are quite complex. Motivated by spelling correction in automatic speech recognition (ASR), in this paper, we propose an end-to-e

Zi-Le Zhang, Zhan-Wei Liu, Si-Qiang Luo, Fu-Lai Wang

In this work, we treat $\Lambda_c(2910)^+$ and $\Lambda_c(2940)^+$ as the conventional $udc$ cores dressed with the $D^*N$ channel. We provide a possible interpretation to both $\Lambda_c(2910)^+$ and $\Lambda_c(2940)^+$ within the same framework. In the study, we consider not only the effects between the conventional triquark core and the $D^*N$ channel but

C. H. Bryan Liu, Emma J. McCoy

Digital technology organizations routinely use online experiments (e.g. A/B tests) to guide their product and business decisions. In e-commerce, we often measure changes to transaction- or item-based business metrics such as Average Basket Value (ABV), Average Basket Size (ABS), and Average Selling Price (ASP); yet it remains a common pitfall to ignore the d

Jiacheng Meng, Cheng Li, Houjun Mo, Yangyao Chen

We use the most recent data release (DR9) of the DESI legacy imaging survey and SDSS galaxy groups to measure the conditional luminosity function (CLF) for groups with halo mass $M_{\rm h}\ge 10^{12}M_{\odot}$ and redshift $0.01\le z\le 0.08$, down to a limiting $r$-band magnitude of $M_{\rm r}=-10\sim-12$. For a given halo mass we measure the CLF for the to

Ayush Tripathi, Lalan Kumar, Prathosh A. P., Suriya Prakash Muthukrishnan

Airwriting Recognition is the task of identifying letters written in free space with finger movement. Electromyography (EMG) is a technique used to record electrical activity during muscle contraction and relaxation as a result of movement and is widely used for gesture recognition. Most of the current research in gesture recognition is focused on identifyin

Tim Santens

We show that the Brauer-Manin obstruction is the only obstruction to strong approximation for all stacky curves over global fields with finite abelian fundamental groups. This includes all stacky curves of genus $g = \frac{1}{2}$, thus explaining a recent counterexample to the Hasse principle of Bhargava-Poonen. We will furthermore show that the elementary o

Junyan Jiang, Gus Xia

We propose a novel method to model hierarchical metrical structures for both symbolic music and audio signals in a self-supervised manner with minimal domain knowledge. The model trains and inferences on beat-aligned music signals and predicts an 8-layer hierarchical metrical tree from beat, measure to the section level. The training procedure does not requi

Hiroaki Nakamura, Densuke Shiraishi

The Galois action on the pro-$\ell$ \'etale fundamental groupoid of the projective line minus three points with rational base points gives rise to a non-commutative formal power series in two variables with $\ell$-adic coefficients, called the $\ell$-adic Galois associator. In the present paper, we focus on how Landen's functional equation of trilogarithms a

Na Yan, Kezhi Wang, Cunhua Pan, Kok Keong Chai

In this paper, we propose a device scheduling scheme for differentially private over-the-air federated learning (DP-OTA-FL) systems, referred to as S-DPOTAFL, where the privacy of the participants is guaranteed by channel noise. In S-DPOTAFL, the gradients are aligned by the alignment coefficient and aggregated via over-the-air computation (AirComp). The sch

Yaofo Chen, Yong Guo, Daihai Liao, Fanbing Lv

Neural Architecture Search (NAS) aims to automatically find effective architectures within a predefined search space. However, the search space is often extremely large. As a result, directly searching in such a large search space is non-trivial and also very time-consuming. To address the above issues, in each search step, we seek to limit the search space

Chandranandan Gangopadhyay, Ronnie Sebastian

Let $C$ be a smooth projective curve over the field of complex numbers $\mathbb{C}$ of genus $g(C)>0$. Let $E$ be a locally free sheaf on $C$ of rank $r$ and degree $e$. Let $\mathcal{Q}:={\rm Quot}_{C/\mathbb{C}}(E,k,d)$ denote the Quot scheme of quotients of $E$ of rank $k$ and degree $d$. For $k>0$ and $d\gg 0$ we compute the Picard group of $\mathcal{Q}$

Longkang Li, Siyuan Liang, Zihao Zhu, Chris Ding

The permutation flow shop scheduling (PFSS), aiming at finding the optimal permutation of jobs, is widely used in manufacturing systems. When solving large-scale PFSS problems, traditional optimization algorithms such as heuristics could hardly meet the demands of both solution accuracy and computational efficiency, thus learning-based methods have recently

Benedikt Böck, Michael Baur, Valentina Rizzello, Wolfgang Utschick

One way to improve the estimation of time varying channels is to incorporate knowledge of previous observations. In this context, Dynamical VAEs (DVAEs) build a promising deep learning (DL) framework which is well suited to learn the distribution of time series data. We introduce a new DVAE architecture, called k-MemoryMarkovVAE (k-MMVAE), whose sparsity can

Chao Chen, Atsuhisa Ota, Hui-Yu Zhu, Yuhang Zhu

We find several missing one-loop-order contributions in previous considerations about secondary gravitational waves induced at nonlinear order in cosmological perturbations. We consider a consistent perturbative expansion to third-order in cosmological perturbations, including higher-order interactions and iterative solutions ignored in the previous literatu

Wenyu Zhao, Stephen M. Blackburn, Kathryn S. McKinley

Production garbage collectors make substantial compromises in pursuit of reduced pause times. They require far more CPU cycles and memory than prior simpler collectors. concurrent copying collectors (C4, ZGC, and Shenandoah) suffer from the following design limitations. 1) Concurrent copying. They only reclaim memory by copying, which is inherently expensive

Marcos K. Aguilera, Naama Ben-David, Rachid Guerraoui, Antoine Murat

We propose uBFT, the first State-Machine Replication (SMR) system to achieve microsecond-scale latency in data centers, while using only $2f{+}1$ replicas to tolerate $f$ Byzantine failures. The Byzantine Fault Tolerance (BFT) provided by uBFT is essential as pure crashes appear to be a mere illusion with real-life systems reportedly failing in many unexpect

Toshio Horiuchi

We will establish the Caffarelli-Kohn-Nirenberg type inequalities with non-doubling weights being permitted. The classical Caffarelli-Kohn-Nirenberg type inequalities are categorized into non-critical and critical cases, and it is known that there is some kind of mysterious relationship between them. Interestingly the new framework in this treatise allows th

Sophie Kollatzsch, Yannick Ulrich

We present a fully differential calculation of lepton pair production, taking into account the dominant next-to-next-to-leading order QED corrections as well as next-to-leading order electroweak and polarisation effects. We include all lepton masses, hard photon emission, as well as non-perturbative hadronic corrections. The corresponding matrix elements are

Giorgio Gubbiotti, Danilo Latini

In this paper, we classify all the variational discrete-time systems in quasi-standard form in $N$ degrees of freedom admitting coalgebra symmetry with respect to the generic realisation of the Lie-Poisson algebra $\mathfrak{sl}_{2}(\mathbb{R})$. This approach naturally yields several quasi-maximally and maximally superintegrable discrete-time systems, both

Zexuan Qiu, Qinliang Su, Jianxing Yu, Shijing Si

Efficient document retrieval heavily relies on the technique of semantic hashing, which learns a binary code for every document and employs Hamming distance to evaluate document distances. However, existing semantic hashing methods are mostly established on outdated TFIDF features, which obviously do not contain lots of important semantic information about d

Yuya Yamakawa

In this paper, we present a stabilized sequential quadratic semidefinite programming (SQSDP) method for nonlinear semidefinite programming (NSDP) problems and prove its local convergence. The stabilized SQSDP method is originally developed to solve degenerate NSDP problems and is based on the stabilized sequential programming (SQP) methods for nonlinear prog

Xiaotian Zhang, Hang Yan, Yu Sun, Xipeng Qiu

Due to the ambiguity of homophones, Chinese Spell Checking (CSC) has widespread applications. Existing systems typically utilize BERT for text encoding. However, CSC requires the model to account for both phonetic and graphemic information. To adapt BERT to the CSC task, we propose a token-level self-distillation contrastive learning method. We employ BERT t

Marco Roveri, Franc Ivankovic, Luigi Palopoli, Daniele Fontanelli

There is a growing interest in modeling and analyzing the spread of diseases like the SARS-CoV-2 infection using stochastic models. These models are typically analyzed quantitatively and are not often subject to validation using formal verification approaches, nor leverage policy syntheses and analysis techniques developed in formal verification. In this pap

Si Sun, Chenyan Xiong, Yue Yu, Arnold Overwijk

In this paper, we investigate the instability in the standard dense retrieval training, which iterates between model training and hard negative selection using the being-trained model. We show the catastrophic forgetting phenomena behind the training instability, where models learn and forget different negative groups during training iterations. We then prop

Hubert Etienne, Onur Çelebi

Social media users who report content are key allies in the management of online misinformation, however, no research has been conducted yet to understand their role and the different trends underlying their reporting activity. We suggest an original approach to studying misinformation: examining it from the reporting users perspective at the content-level a

Sima T. Aghdam, Atefeh Javadi, Seyedazim Hashemi, Jacco Th. van Loon

NGC5128 galaxy is a giant elliptical galaxy located in the Centaurus group of galaxies at 3.8 Mpc. We aim to study the star formation history (SFH) of two different fields of the galaxy. The northeastern field (Field 1) is located at a distance of 18.8 kpc, while the southern field (Field 2) is at 9.9 kpc. We use a photometric method that is based on identif

Dilip Kumar, Soma Sanyal

The motion of cosmic strings in the universe leads to the generation of wakes behind them. We study magnetized wakes of cosmic strings moving in the post recombination plasma. We show that magnetic reconnection can occur in the post shock region. Since the width of the cosmic string wake is very small, the reconnection occurs over a very short lengthscale. T

Huanhuan Sheng, Alexander Bentkamp, Bohua Zhan

We present a tool for verification of hybrid systems expressed in the sequential fragment of HCSP (Hybrid Communicating Sequential Processes). The tool permits annotating HCSP programs with pre- and postconditions, invariants, and proof rules for reasoning about ordinary differential equations. Verification conditions are generated from the annotations follo

Chandrachur Chakraborty, Parthasarathi Majumdar

Inspired by the reported existence of substantive magnetic fields in the vicinity of the central supermassive black holes in Sagitarius A* and Messier 87*, we consider test particle motion in the spacetime close to a generic spherical black hole in the presence of magnetic fields in its vicinity. Modelling such a spacetime in terms of an axisymmetric, non-ro

Thokozile Manaka, Terence van Zyl, Deepak Kar

In many lower-and-middle income countries including South Africa, data access in health facilities is restricted due to patient privacy and confidentiality policies. Further, since clinical data is unique to individual institutions and laboratories, there are insufficient data annotation standards and conventions. As a result of the scarcity of textual data,

Bianka Bakullari, Wil M. P. van der Aalst

Process mining methods often analyze processes in terms of the individual end-to-end process runs. Process behavior, however, may materialize as a general state of many involved process components, which can not be captured by looking at the individual process instances. A more holistic state of the process can be determined by looking at the events that occ

Hua-Qing Liu, Shi-Teng Zheng, Rui Jiang, Junfang Tian

Accurate modeling of lower-level controller plays an important role in the traffic flow of automated vehicles (AVs). However, there lacks enough attention with this respect. To address this issue, we conduct a field experiment with two vehicles that are equipped with developable autonomous driving system, where one can customize the upper-level control algor

Yong-Min Shin, Sun-Woo Kim, Won-Yong Shin

Aside from graph neural networks (GNNs) attracting significant attention as a powerful framework revolutionizing graph representation learning, there has been an increasing demand for explaining GNN models. Although various explanation methods for GNNs have been developed, most studies have focused on instance-level explanations, which produce explanations t

Yu-Song Cao, YanXia Liu, Rong Zhang

We study the Landauer's principle of an Unruh-DeWitt detector linearly coupled to Dirac field in $1 + 1$ dimensional cavity. When the initial state of the field is vacuum, we obtain the heat transfer and von Neumann entropy change perturbatively. For the thermal state, the heat transfer and entropy change are approximately obtained in the case where the inte

Xingran Chen, Ge Zhang, Adam Nik, Mingyu Li

In this paper, we present our approach and empirical observations for Cause-Effect Signal Span Detection -- Subtask 2 of Shared task 3~\cite{tan-etal-2022-event} at CASE 2022. The shared task aims to extract the cause, effect, and signal spans from a given causal sentence. We model the task as a reading comprehension (RC) problem and apply a token-level RC-b

Alex Arenas, Antonio Garijo, Sergio Gómez, Jordi Villadelprat

The dynamics of many epidemic compartmental models for infectious diseases that spread in a single host population present a second-order phase transition. This transition occurs as a function of the infectivity parameter, from the absence of infected individuals to an endemic state. Here, we study this transition, from the perspective of dynamical systems,

Lourens E. Veen, Sara Shakeri, Paola Grosso

Secure, privacy-preserving sharing of scientific or business data is currently a popular topic for research and development, both in academia and outside of it. Systems have been proposed for sharing individual facts about individuals and sharing entire data sets, for sharing data through trusted third parties, for obfuscating sensitive data by anonymisation

Andreas Jonas Fuglsig, Jesper Jensen, Zheng-Hua Tan, Lars Søndergaard Bertelsen

The intelligibility and quality of speech from a mobile phone or public announcement system are often affected by background noise in the listening environment. By pre-processing the speech signal it is possible to improve the speech intelligibility and quality -- this is known as near-end listening enhancement (NLE). Although, existing NLE techniques are ab

Anusha Prakash, S Umesh, Hema A Murthy

End-to-end (E2E) systems synthesise high-quality speech, but this typically requires a large amount of data. As E2E synthesis progressed from Tacotron to FastSpeech2, it became evident that features representing prosody, particularly sub-word durations, are important for error-free synthesis. Variants of FastSpeech use a teacher model or forced alignments fo

Ernie Chu, Ju-Ting Chen, Chia-Ping Chen

We propose a novel approach for time-scale modification of audio signals. Unlike traditional methods that rely on the framing technique or the short-time Fourier transform to preserve the frequency during temporal stretching, our neural network model encodes the raw audio into a high-level latent representation, dubbed Neuralgram, where each vector represent

Deokki Hong

This work is for designing one-stage lightweight detectors which perform well in terms of mAP and latency. With baseline models each of which targets on GPU and CPU respectively, various operations are applied instead of the main operations in backbone networks of baseline models. In addition to experiments about backbone networks and operations, several fea

Ran Ben-Moshe, Sergiu Hart, Noam Nisan

Maximizing the revenue from selling two or more goods has been shown to require the use of $nonmonotonic$ mechanisms, where a higher-valuation buyer may pay less than a lower-valuation one. Here we show that the restriction to $monotonic$ mechanisms may not just lower the revenue, but may in fact yield only a $negligible$ $fraction$ of the maximal revenue; m

Mohamed Z. Variawa, Terence L. Van Zyl, Matthew Woolway

Real-world optimisation problems typically have objective functions which cannot be expressed analytically. These optimisation problems are evaluated through expensive physical experiments or simulations. Cheap approximations of the objective function can reduce the computational requirements for solving these expensive optimisation problems. These cheap app

Ning Li, Hui-Zhen He, Wei Liang, Qi-Fang Lü

We adopt the quark pair creation model to investigate the light meson emissions of several charmonium-like states. The quark pair creation model is applied to the four-body systems, and we calculate the pion/kaon emissions of the $X(4700)$, $Z_c(4430)$, $Y(4230)$, $Y(4360)$, $Y(4390)$ and $Y(4660)$ within the compact tetraquark assumptions. It is found that

Kenta Mori

The perfectly matchable subgraph polytope of a graph is a (0,1)-polytope associated with the vertex sets of matchings in the graph. In this paper, we study algebraic properties (compressedness, Gorensteinness) of the toric rings of perfectly matchable subgraph polytopes. In particular, we give a complete characterization of a graph whose perfectly matchable

Ling Sun, Guiqiong Liu, Xunping Jiang, Junrui Liu

With the demand for standardized large-scale livestock farming and the development of artificial intelligence technology, a lot of research in area of animal face recognition were carried on pigs, cattle, sheep and other livestock. Face recognition consists of three sub-task: face detection, face normalizing and face identification. Most of animal face recog

Siyuan Zhang, Linbo Xie, Ying Chen

In the past few years, Softmax has become a common component in neural network frameworks. In this paper, a gradient decay hyperparameter is introduced in Softmax to control the probability-dependent gradient decay rate during training. By following the theoretical analysis and empirical results of a variety of model architectures trained on MNIST, CIFAR-10/

Jun Yang, Jianzhu Li, Amin Bahrami, Noushin Nasiri

In this work, we demonstrate the performance of a silicon-compatible high-performance self-powered photodetector.A wide detection range from visible (405 nm) to near-infrared (1550 nm) light was enabled by the vertical p-n heterojunction between the p-type antimony telluride (Sb2Te3) thin film and the n-type silicon (Si) substrates. A Sb2Te3 film with a good

Eungbeom Kim, Jinhee Kim, Yoori Oh, Kyungsu Kim

In this paper, we aim to unveil the impact of data augmentation in audio-language multi-modal learning, which has not been explored despite its importance. We explore various augmentation methods at not only train-time but also test-time and find out that proper data augmentation can lead to substantial improvements. Specifically, applying our proposed audio

Tiehua Zhang, Yuze Liu, Yao Yao, Youhua Xia

Heterogeneous graph neural network has unleashed great potential on graph representation learning and shown superior performance on downstream tasks such as node classification and clustering. Existing heterogeneous graph learning networks are primarily designed to either rely on pre-defined meta-paths or use attention mechanisms for type-specific attentive

Nana Arizumi

Recently, self-attention (SA) structures became popular in computer vision fields. They have locally independent filters and can use large kernels, which contradicts the previously popular convolutional neural networks (CNNs). CNNs success was attributed to the hard-coded inductive biases of locality and spatial invariance. However, recent studies have shown

Jian Vora, Pranay Reddy Samala

Deep neural networks are susceptible to adversarial inputs and various methods have been proposed to defend these models against adversarial attacks under different perturbation models. The robustness of models to adversarial attacks has been analyzed by first constructing adversarial inputs for the model, and then testing the model performance on the constr

Tim S. Lyon

Intuitionistic grammar logics fuse constructive and multi-modal reasoning while permitting the use of converse modalities, serving as a generalization of standard intuitionistic modal logics. In this paper, we provide definitions of these logics as well as establish a suitable proof theory thereof. In particular, we show how to apply the structural refinemen

Marton Szep, Leander Lauenburg, Kevin Farkas, Xiyan Su

In recent years, reinforcement learning (RL) has shown great potential for solving tasks in well-defined environments like games or robotics. This paper aims to solve the robotic reaching task in a simulation run on the Neurorobotics Platform (NRP). The target position is initialized randomly and the robot has 6 degrees of freedom. We compare the performance

Sreedev Manikoth

The singular Bj\" orling problem and its solution for timelike minimal surfaces is a well-known result in minimal surface theory. In this article, we give a different proof of this theorem using split-harmonic maps. This is motivated by a similar solution of the singular Bj\"orling problem for maximal surfaces using harmonic maps. As an application, we study

Giovanni Ziarelli, Luca Dede', Nicola Parolini, Marco Verani

In the context of SARS-CoV-2 pandemic, mathematical modelling has played a fundamental role for making forecasts, simulating scenarios and evaluating the impact of preventive political, social and pharmaceutical measures. Optimal control theory can be a useful tool based on solid mathematical bases to plan the vaccination campaign in the direction of eradica

Pan-Pan Wang, Wei-Liang Qian, Han-Zhong Wu, Yu-Jie Tan

A crucial challenge to the ongoing endeavor of spaceborne gravitational wave (GW) detection resides in the laser phase noise, typically 7 to 8 orders of magnitude above the inevitable noise. The arm locking technique was proposed to suppress the noise in pre-stabilized laser beams. Based on the feedback control theory, it is implemented by appropriate design

Nicholas D. Alikakos, Zhiyuan Geng

We investigate the Allen-Cahn system \begin{equation*} \Delta u-W_u(u)=0,\quad u:\mathbb{R}^2\rightarrow\mathbb{R}^2, \end{equation*} where $W\in C^2(\mathbb{R}^2,[0,+\infty))$ is a potential with three global minima. We establish the existence of an entire solution $u$ which possesses a triple junction structure. The main strategy is to study the global min

H. -B. Yuan, L. Yang, P. Cruz, F. Jiménez-Esteban

With a unique set of 54 overlapping narrow-band and two broader filters covering the entire optical range, the incoming Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will provide a great opportunity for stellar physics and near-field cosmology. In this work, we use the miniJPAS data in 56 J-PAS filters and 4 complementary SDSS-

Kenji Bekki

We discuss the mechanism(s) of bar formation in isolated and tidally interacting disk galaxies using the results of idealized collisionless Nbody simulations of the galaxies. In order to better understand the mechanism, we investigate orbital eccentricities (e), epochs of apocenter passages (t_a), azimuthal angles at t_a (varphi_a), precession rates (Omega_p

David Cabezas, María Cueto-Avellaneda, Yuta Enami, Takeshi Miura

In 2022, Hatori gave a sufficient condition for complex Banach spaces to have the complex Mazur--Ulam property. In this paper, we introduce a class of complex Banach spaces $B$ that do not satisfy the condition but enjoy the property that every surjective isometry on the unit sphere of such $B$ admits an extension to a surjective real linear isometry on the

Atsushi Kikuchi, Kotaro Uchida, Masaki Waga, Kohei Suenaga

Explaining a classification result produced by an image- and video-classification model is one of the important but challenging issues in computer vision. Many methods have been proposed for producing heat-map--based explanations for this purpose, including ones based on the white-box approach that uses the internal information of a model (e.g., LRP, Grad-CA

Lin Zichao, Zhang Hongming, Wang Fudi, Bae Chenonho

Impurity degrades tokamak plasmas confinement by causing energy loss, diluting the fuel concentration, even terminating the discharges in some extreme cases. Previously, the suppression effects of on-axis Electron Cyclotron Resonance Heating (ECRH) on the impurity accumulation have been investigated on EAST by the extreme ultraviolet (EUV) spectroscopy. Howe

Heng-Wei Chang

We analytically and numerically show that the acceleration of the cosmic expansion could be explained by a Quadratic Gravity model which is known to be able to trigger sufficient inflation, with neither negative pressure matter nor cosmological constant. Furthermore, we exactly show that this model differs greatly from Einstein's gravity in radiation and mat

Shuhan Zheng, Nontawat Charoenphakdee

Missing value imputation in machine learning is the task of estimating the missing values in the dataset accurately using available information. In this task, several deep generative modeling methods have been proposed and demonstrated their usefulness, e.g., generative adversarial imputation networks. Recently, diffusion models have gained popularity becaus

Zhaochen Su, Zecheng Tang, Xinyan Guan, Juntao Li

Recent research has revealed that neural language models at scale suffer from poor temporal generalization capability, i.e., the language model pre-trained on static data from past years performs worse over time on emerging data. Existing methods mainly perform continual training to mitigate such a misalignment. While effective to some extent but is far from

Alexander Koch, Hongyan Mei, Jura Rensberg, Martin Hafermann

We demonstrate heavy and hyper doping of ZnO by a combination of gallium (Ga) ion implantation using a focused ion beam (FIB) system and post-implantation laser annealing. Ion implantation allows for the incorporation of impurities with nearly arbitrary concentrations, and the laser-annealing process enables dopant activation close to or beyond the solid-sol

Qian Chen, Han-Sheng Wang, Guo-Liang Ma

We calculate the cumulants and correlation functions of net-kaon multiplicity distributions in Au+Au collisions at $\sqrt{s_{NN}} = 7.7$ GeV using a multiphase transport model (AMPT) with both a new coalescence mechanism and all charge conservation laws. The AMPT model can qualitatively describe the centrality dependences of the net-kaon cumulants and cumula

Wen Zhao, Xueshi Guo, Xiaoying Li

Pulsed pumped four-wave mixing process via $\chi^{(3)}$ non-linearity in optical fiber can generate optical pulses with continuous variable quantum correlation. However, pair-wise correlation of the generated pulses in this system has not been studied. Here we report a time-domain measurement of an intensity difference squeezed state generated in fiber. With

Robert Seiringer

We consider a class of polaron models, including the Fr\"ohlich model, at zero total momentum, and show that at sufficiently weak coupling there are no excited eigenvalues below the essential spectrum.

Lei Zhang, Zhenghua Li, Shilin Zhou, Chen Gong

Inspired by early research on exploring naturally annotated data for Chinese word segmentation (CWS), and also by recent research on integration of speech and text processing, this work for the first time proposes to mine word boundaries from parallel speech/text data. First we collect parallel speech/text data from two Internet sources that are related with

Linsui Deng, Kejun He, Xianyang Zhang

Clustered effects are often encountered in multiple hypothesis testing of spatial signals. In this paper, we propose a new method, termed \textit{two-dimensional spatial multiple testing} (2d-SMT) procedure, to control the false discovery rate (FDR) and improve the detection power by exploiting the spatial information encoded in neighboring observations. The

Ayal Schwartz, Sharon Gannot, Shlomo E. Chazan

In this work we present a new single-microphone speech dereverberation algorithm. First, a performance analysis is presented to interpret that algorithms focused on improving solely magnitude or phase are not good enough. Furthermore, we demonstrate that few objective measurements have high correlation with the clean magnitude while others with the clean pha

Atsushi Sakaguchi, Shunya Konno, Fumiya Hanamura, Warit Asavanant

Measurement-based quantum computation with optical time-domain multiplexing is a promising method to realize a quantum computer from the viewpoint of scalability. Fault tolerance and universality are also realizable by preparing appropriate resource quantum states and electro-optical feedforward that is altered based on measurement results. While a linear fe

Maheshya Weerasinghe, Verena Biener, Jens Grubert, Jordan Aiko Deja

A critical component of user studies is gaining access to a representative sample of the population researches intend to investigate. Nevertheless, the vast majority of human-computer interaction (HCI)studies, including augmented reality (AR) studies, rely on convenience sampling. The outcomes of these studies are often based on results obtained from univers

Yan Zhou Zhu

We first characterize all faithful arc-transitive covers of complete graphs and we give a general construction of such covers. For a counterpart of cover, we say a graph $\Gamma$ is a pseudocover of its quotient $\Sigma$ if they have the same valency and $\Gamma$ is not a cover of $\Sigma$.As the second result of this paper, we prove that the complete graph

Mohammad Sarhil, Lisa Scheunemann, Jörg Schröder, Patrizio Neff

In this paper we model the size-effects of metamaterial beams under bending with the aid of the relaxed micromorphic continuum. We analyze first the size-dependent bending stiffness of heterogeneous fully discretized metamaterial beams subjected to pure bending loads. Two equivalent loading schemes are introduced which lead to a constant moment along the bea

Chau Dao, Jeffrey C. Everts, Miha Ravnik, Yaroslav Tserkovnyak

Adopting a spintronics-inspired approach, we study the reciprocal coupling between ionic charge currents and nematic texture dynamics in a uniaxial nematic electrolyte. Assuming quenched fluid dynamics, we develop equations of motion analogously to spin torque and spin pumping. Based on the principle of least dissipation of energy, we derive the adiabatic "n

Mani L. Bhaumik

Erwin Schr\"odinger is famous for presenting his wave equation of motion that jump-started quantum mechanics. His disenchantment with the Copenhagen interpretation of quantum mechanics led him to unveil the Schr\"odinger's cat paradox, which did not get much attention for nearly half a century. In the meantime, disappointment with quantum mechanics turned hi

Zhenzhe Hechen, Wei Huang, Yixin Zhao

Transformers have demonstrated a competitive performance across a wide range of vision tasks, while it is very expensive to compute the global self-attention. Many methods limit the range of attention within a local window to reduce computation complexity. However, their approaches cannot save the number of parameters; meanwhile, the self-attention and inner

Wei Kang, Liyong Guo, Fangjun Kuang, Long Lin

The transducer architecture is becoming increasingly popular in the field of speech recognition, because it is naturally streaming as well as high in accuracy. One of the drawbacks of transducer is that it is difficult to decode in a fast and parallel way due to an unconstrained number of symbols that can be emitted per time step. In this work, we introduce

Shira Guskin, Moshe Wasserblat, Chang Wang, Haihao Shen

Limited computational budgets often prevent transformers from being used in production and from having their high accuracy utilized. A knowledge distillation approach addresses the computational efficiency by self-distilling BERT into a smaller transformer representation having fewer layers and smaller internal embedding. However, the performance of these mo

Yiming Cui, Jiajia Guo, Zheng Cao, Huaze Tang

Deep learning has shown promise in enhancing channel state information (CSI) feedback. However, many studies indicate that better feedback performance often accompanies higher computational complexity. Pursuing better performance-complexity tradeoffs is crucial to facilitate practical deployment, especially on computation-limited devices, which may have to u

Hiroki Asami, Chul-Moon Yoo, Ryo Kitaku, Keiya Uemichi

We investigate solutions of the $5$--dimensional rotating Einstein-Vlasov system with an $R \times SU(2) \times U(1)$ isometry group. In a five-dimensional spacetime, there are two independent planes of rotation, thus, considering $U(1)$ symmetry on each rotation plane, we may impose an $R\times U(1) \times U(1)$ isometry to a stationary spacetime. Furthermo