November 2022 arXiv papers — page 118

Bran G. Wilson, Jean-Christophe Pain

A formula for supershell partition functions, which play a major role in the Super Transition Array approach to radiative-opacity calculations, is derived as a functional of the distribution of energies within the supershell. It consists in an alternative expansion for an arbitrary number of electrons or holes which also allows for quick approximate evaluati

S. Anishchenko, V. Baryshevsky, A. Gurinovich, E. Gurnevich

In this paper, we review and compare HPM sources operating without a magnetic field to guide the electron beam that are capable of producing high-power microwave (HPM) pulses with a duration of about 100 ns. The proposed analysis summarizes multi-year research carried with three types of HPM sources: a split-cavity oscillator (SCO); an axial vircator; and a

Shayan Dodge, Mojtaba Shafiee, Babak Shokri

Since numerical computing with MATLAB offers a wide variety of advantages, such as easier developing and debugging of computational codes rather than lower-level languages, the popularity of this tool is significantly increased in the past decade. However, MATLAB is slower than other languages. Moreover, utilizing MATLAB parallel computing toolbox on the Gra

J. -V. Harre, A. M. S. Smith, S. C. C. Barros, G. Boué

Tidal orbital decay is suspected to occur especially for hot Jupiters, with the only observationally confirmed case of this being WASP-12 b. By examining this effect, information on the properties of the host star can be obtained using the so-called stellar modified tidal quality factor $Q_*'$, which describes the efficiency with which kinetic energy of the

Julia Lindberg, Jose Rodriguez

In this paper we study the Shor relaxation of quadratic programs by fixing a feasible set and considering the space of objective functions for which the Shor relaxation is exact. We first give conditions under which this region is invariant under the choice of generators defining the feasible set. We then describe this region when the feasible set is invaria

P. R. Protachevicz, F. S. Borges, A. M. Batista, M. S. Baptista

The brain is formed by cortical regions that are associated with different cognitive functions. Neurons within the same region are more likely to connect than neurons in distinct regions, making the brain network to have characteristics of a network of subnetworks. The values of synaptic delays between neurons of different subnetworks are greater than those

Yu Cheng, Shao-Feng Ge, Xiao-Gang He, Jie Sheng

The forbidden dark matter cannot annihilate into a pair of heavier partners, either SM particles or its partners in the dark sector, at the late stage of cosmological evolution by definition. We point out the possibility of reactivating the forbidden annihilation channel around supermassive black holes. Being attracted towards a black hole, the forbidden dar

Karim Makki, Adrien Bartoli

We show that for a plane imaged by an endoscope the specular isophotes are concentric circles on the scene plane, which appear as nested ellipses in the image. We show that these ellipses can be detected and used to estimate the plane's normal direction, forming a normal reconstruction method, which we validate on simulated data. In practice, the anatomical

Lawrence Stewart, Francis Bach, Quentin Berthet, Jean-Philippe Vert

Neural networks can be trained to solve regression problems by using gradient-based methods to minimize the square loss. However, practitioners often prefer to reformulate regression as a classification problem, observing that training on the cross entropy loss results in better performance. By focusing on two-layer ReLU networks, which can be fully characte

Ridwane Aissaoui, Jean-Christophe Deneuville, Christophe Guerber, Alain Pirovano

Unmanned Aerial Systems (UAS) have a wide variety of applications, and their development in terms of capabilities is continuously evolving. Many missions performed by an Unmanned Aerial Vehicle (UAV) require flying in public airspace. This requires very high safety standards, similar to those mandatory in commercial civil aviation. A safe UAV Traffic Managem

Tim Martin, Thomas B. Schön, Frank Allgöwer

Data-driven control of nonlinear systems with rigorous guarantees is a challenging problem as it usually calls for nonconvex optimization and requires often knowledge of the true basis functions of the system dynamics. To tackle these drawbacks, this work is based on a data-driven polynomial representation of general nonlinear systems exploiting Taylor polyn

Babak Ghaffarzadeh Bakhshayesh, Hamed Kebriaei

This paper presents the equilibrium analysis of a game composed of heterogeneous electric vehicles (EVs) and a power distribution system operator (DSO) as the players, and charging station operators (CSOs) and a transportation network operator (TNO) as coordinators. Each EV tries to pick a charging station as its destination and a route to get there at the s

Christian Cachin, Giuliano Losa, Luca Zanolini

Fail-prone systems, and their quorum systems, are useful tools for the design of distributed algorithms. However, fail-prone systems as studied so far require every process to know the full system membership in order to guarantee safety through globally intersecting quorums. Thus, they are of little help in an open, permissionless setting, where such knowled

Ilaria Gianani, Claudia Benedetti

The characterization of the Hamiltonian parameters defining a quantum walk is of paramount importance when performing a variety of tasks, from quantum communication to computation. When dealing with physical implementations of quantum walks, the parameters themselves may not be directly accessible, thus it is necessary to find alternative estimation strategi

Chen-Kuan Lee

We derive the equation of self-similar solutions to mean curvature flow based on the generalized Lawson-Osserman cone and prove the existence of self-expanders by modifying the theory of equilibria in the autonomous system. In particular, those self-expanders are unique if a local assumption is given.

Bhumika Mistry, Katayoun Farrahi, Jonathon Hare

Multilayer Perceptrons struggle to learn certain simple arithmetic tasks. Specialist neural modules for arithmetic can outperform classical architectures with gains in extrapolation, interpretability and convergence speeds, but are highly sensitive to the training range. In this paper, we show that Neural Multiplication Units (NMUs) are unable to reliably le

Xiaosheng Li, Wei Wang

In this work, we develop an efficient high order discontinuous Galerkin (DG) method for solving the Electrical Impedance Tomography (EIT). EIT is a highly nonlinear ill-posed inverse problem where the interior conductivity of an object is recovered from the surface measurements of voltage and current flux. We first propose a new optimization problem based on

Ziyi He, Albert C. S. Chung

Template generation is a critical step in groupwise image registration, which involves aligning a group of subjects into a common space. While existing methods can generate high-quality template images, they often incur substantial time costs or are limited by fixed group scales. In this paper, we present InstantGroup, an efficient groupwise template generat

Rodolfo Gambini, Javier Olmedo, Jorge Pullin

We summarize our work on spherically symmetric midi-superspaces in loop quantum gravity. Our approach is based on using inhomogeneous slicings that may penetrate the horizon in case there is one and on a redefinition of the constraints so the Hamiltonian has an Abelian algebra with itself. We discuss basic and improved quantizations as is done in loop quantu

Gastón Briozzo, Emanuel Gallo, Thomas Mädler

The shadows of black holes encode significant information about the properties of black holes and the spacetime surrounding them. So far, the effects of dispersive media, such as plasma, and relativistic aberration on the propagation of light around compact objects have been treated separately in the literature. In this paper, we will employ the Konoplya, St

Jing Wang, Zuozheng Zhang, Yuanqiu Huang

The generalized $k$-connectivity of a graph $G$, denoted by $\kappa_k(G)$, is the minimum number of internally edge disjoint $S$-trees for any $S\subseteq V(G)$ and $|S|=k$. The generalized $k$-connectivity is a natural extension of the classical connectivity and plays a key role in applications related to the modern interconnection networks. The burnt panca

Otávio Parraga, Martin D. More, Christian M. Oliveira, Nathan S. Gavenski

Despite being responsible for state-of-the-art results in several computer vision and natural language processing tasks, neural networks have faced harsh criticism due to some of their current shortcomings. One of them is that neural networks are correlation machines prone to model biases within the data instead of focusing on actual useful causal relationsh

Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, Rami Khushaba, Frank Kulwa

Surface electromyogram (sEMG) is arguably the most sought-after physiological signal with a broad spectrum of biomedical applications, especially in miniaturized rehabilitation robots such as multifunctional prostheses. The widespread use of sEMG to drive pattern recognition (PR)-based control schemes is primarily due to its rich motor information content an

Jiarul Midya, Thorsten Auth, Gerhard Gompper

The transport of particles across lipid-bilayer membranes is important for biological cells to exchange information and material with their environment. Large particles often get wrapped by membranes, a process which has been intensively investigated in the case of hard particles. However, many particles in vivo and in vitro are deformable, e.g., vesicles, f

Ye-Won Luke Cho

The main purpose of this article is to present a generalization of Forelli's theorem for functions holomorphic along a suspension of integral curves of a diagonalizable vector field of aligned type. For this purpose, we develop a new capacity theory that generalizes the theory of projective capacity introduced by Siciak \cite{Siciak82}. Our main theorem impr

Vincent Boudry

An extended version of the CALICE silicon-tungsten ECAL was tested in November 2021 at the DESY beam test facility. With 15 active layers, it featured some with a thin PCB design, and a new compact DAQ system handling all layers in a common set. The noise, self-trigger performances and response to punch-though electrons, without tungsten absorbers, have been

Kristian Løvland, Bjarne Grimstad, Lars Struen Imsland

Steady-state models which have been learned from historical operational data may be unfit for model-based optimization unless correlations in the training data which are introduced by control are accounted for. Using recent results from work on structural dynamical causal models, we derive a formula for adjusting for this control confounding, enabling the es

Matthias Dorfer, Anton R. Fuxjäger, Kristian Kozak, Patrick M. Blies

The energy sector is facing rapid changes in the transition towards clean renewable sources. However, the growing share of volatile, fluctuating renewable generation such as wind or solar energy has already led to an increase in power grid congestion and network security concerns. Grid operators mitigate these by modifying either generation or demand (redisp

Fabien Cléry, Gerard van der Geer

We discuss two simple but useful observations that allow the construction of modular forms from given ones using invariant theory. The first one deals with elliptic modular forms and their derivatives, and generalizes the Rankin-Cohen bracket, while the second one deals with vector-valued modular forms of genus greater than one.

Mohsen Fayyaz, Ehsan Aghazadeh, Ali Modarressi, Mohammad Taher Pilehvar

Current pre-trained language models rely on large datasets for achieving state-of-the-art performance. However, past research has shown that not all examples in a dataset are equally important during training. In fact, it is sometimes possible to prune a considerable fraction of the training set while maintaining the test performance. Established on standard

Youjun Deng, Yueguang Hu, Hongyu Liu, Wanjing Tang

We are concerned with the field concentration between two nearly-touching inclusions with high-contrast material parameters, which is a central topic in the theory of composite materials. The degree of concentration is characterised by the blowup rate of the gradient of the underlying field. In this paper, we derive optimal gradient estimates for the wave fi

Rémy Cerda, Lionel Vaux Auclair

Originating in Girard's Linear logic, Ehrhard and Regnier's Taylor expansion of $\lambda$-terms has been broadly used as a tool to approximate the terms of several variants of the $\lambda$-calculus. Many results arise from a Commutation theorem relating the normal form of the Taylor expansion of a term to its B\"ohm tree. This led us to consider extending t

Erik J. Gustafson

Smearing of gauge-field configurations in lattice field theory improves the results of lattice simulations by suppressing high energy modes from correlation functions. In quantum simulations, high kinetic energy eigenstates are introduced when the time evolution operator is approximated such as Trotterization. While improved Trotter product formulae exist to

Arnau Bas i Beneito, Gianluca Calcagni, Lesław Rachwał

This chapter of the Handbook of Quantum Gravity aims to illustrate how nonlocality can be implemented in field theories, as well as the manner it solves fundamental difficulties of gravitational theories. We review Stelle's quadratic gravity, which achieves multiplicative renormalizability successfully to remove quantum divergences by modifying the Einstein'

Marco Garofalo, Maxim Mai, Fernando Romero-López, Akaki Rusetsky

We study the properties of three-body resonances using a lattice complex scalar $\varphi^4$ theory with two scalars, with parameters chosen such that one heavy particle can decay into three light ones. We determine the two- and three-body spectra for several lattice volumes using variational techniques, and then analyze them with two versions of the three-pa

Ilia Kuznetsov, Iryna Gurevych

Natural language processing (NLP) researchers develop models of grammar, meaning and communication based on written text. Due to task and data differences, what is considered text can vary substantially across studies. A conceptual framework for systematically capturing these differences is lacking. We argue that clarity on the notion of text is crucial for

Guangxiong Zhang, Peng Huang, Bao-Feng Feng, Chengfa Wu

In this paper, we study the general rogue wave solutions and their patterns in the vector (or $M$-component) nonlinear Schr\"{o}dinger (NLS) equation. By applying the Kadomtsev-Petviashvili hierarchy reduction method, we derived an explicit solution for the rogue wave expressed by $\tau$ functions that are determinants of $K\times K$ block matrices ($K=1,2,\

Vladimir Sosnilo

Weibel proved that $p$-inverted K-theory is $\mathbb{A}^1$-invariant on $\mathbb{F}_p$-schemes and K-theory with $\mathbb{Z}/p$-coefficients is $\mathbb{A}^1$-invariant on $\mathbb{Z}[\frac{1}{p}]$-schemes. We extend this result to all finitary localizing invariants of small stable $\infty$-categories. Along the way we study the Frobenius and Verschiebung en

Ignacio Torroba, Marco Chella, Aldo Teran, Niklas Rolleberg

Autonomous underwater vehicles (AUVs) are becoming standard tools for underwater exploration and seabed mapping in both scientific and industrial applications \cite{graham2022rapid, stenius2022system}. Their capacity to dive untethered allows them to reach areas inaccessible to surface vessels and to collect data more closely to the seafloor, regardless of t

Fangyao Zhu, Juntao Huang, Yang Yang

In this paper, we develop bound-preserving discontinuous Galerkin (DG) methods for chemical reactive flows. There are several difficulties in constructing suitable numerical schemes. First of all, the density and internal energy are positive, and the mass fraction of each species is between 0 and 1. Secondly, due to the rapid reaction rate, the system may co

Sandeep Ramachandra, Gilles Vandewiele, David Vander Mijnsbrugge, Femke Ongenae

A paper of Alsinglawi et al was recently accepted and published in Scientific Reports. In this paper, the authors aim to predict length of stay (LOS), discretized into either long (> 7 days) or short stays (< 7 days), of lung cancer patients in an ICU department using various machine learning techniques. The authors claim to achieve perfect results with an A

Makesh Narsimhan Sreedhar, Christopher Parisien

Conversation designers continue to face significant obstacles when creating production quality task-oriented dialogue systems. The complexity and cost involved in schema development and data collection is often a major barrier for such designers, limiting their ability to create natural, user-friendly experiences. We frame the classification of user intent a

Arturo de Giorgi, Gioacchino Piazza

Within the assumption of Left-Handed (LH) New Physics (NP), we review the relations between $\mathcal{B}(B\to K^{(\ast)} \tau^+\tau^-)$ and $\mathcal{B}(B\to K^{(\ast)} \nu\bar \nu)$ for several Beyond the Standard Model (BSM) scenarios, commonly considered to explain the Lepton flavor Universality (LFU) violation observed in charged and neutral-current semi

Philipp Diercks, Dennis Gläser, Ontje Lünsdorf, Michael Selzer

In the field of computational science and engineering, workflows often entail the application of various software, for instance, for simulation or pre- and postprocessing. Typically, these components have to be combined in arbitrarily complex workflows to address a specific research question. In order for peer researchers to understand, reproduce and (re)use

Changzheng Qu, Zhiwei Wu

The Miura transformation plays a crucial role in the study of integrable systems. There have been various extensions of the Miura transformation, which have been used to relate different kinds of integrable equations and to classify the bi-Hamiltonian structures. In this paper, we are mainly concerned with the geometric aspects of the Miura transformation. T

Jue Xu, Qi Zhao

Detection of entanglement is an indispensable step to practical quantum computation and communication. Compared with the conventional entanglement witness method based on fidelity, we propose a flexible, machine learning assisted entanglement detection protocol that is robust to different types of noises and sample efficient. In this protocol, an entanglemen

Fernanda Pérez-Verdugo, Shiladitya Banerjee

Cell neighbor exchanges play a critical role in regulating tissue fluidity during epithelial morphogenesis and repair. In vivo, these neighbor exchanges are often hindered by the formation of transiently stable four-fold vertices, which can develop into complex multicellular rosettes where five or more cell junctions meet. Despite their importance, the mecha

Raphael Joud, Pierre-Alain Moellic, Simon Pontie, Jean-Baptiste Rigaud

Model extraction is a major threat for embedded deep neural network models that leverages an extended attack surface. Indeed, by physically accessing a device, an adversary may exploit side-channel leakages to extract critical information of a model (i.e., its architecture or internal parameters). Different adversarial objectives are possible including a fid

Grigory Garkusha

A general method of producing correspondences and spectral categories out of symmetric ring objects in general categories is given. As an application, stable homotopy theory of spectra $SH$ is recovered from modules over a commutative symmetric ring spectrum defined in terms of framed correspondences over an algebraically closed field. Another application re

Soumya Jahagirdar, Minesh Mathew, Dimosthenis Karatzas, C. V. Jawahar

Video Question Answering methods focus on commonsense reasoning and visual cognition of objects or persons and their interactions over time. Current VideoQA approaches ignore the textual information present in the video. Instead, we argue that textual information is complementary to the action and provides essential contextualisation cues to the reasoning pr

Aritra Laha, Santosh Kumar

One of the key issues in quantum information theory related problems concerns with that of distinguishability of quantum states. In this context, Bures distance serves as one of the foremost choices among various distance measures. It also relates to fidelity, which is another quantity of immense importance in quantum information theory. In this work, we der

Henrik Eklund, Mikolaj Szydlarski, Sven Wedemeyer

The intensity of radiation at millimeter wavelengths from the solar atmosphere is closely related to the plasma temperature and the height of formation of the radiation is wavelength dependent. From that follows that the slope of the brightness temperature (T$_\mathrm{b}$) continuum, samples the local gradient of the gas temperature of the sampled layers in

Sumit Nandi

A novel criterion of extracting thermodynamical work from a bipartite pure qudit-entangled state by means of local operation and classical communication (LOCC) has been presented. We have shown that non-vanishing $G$-concurrence is a necessary condition to extract work from an higher dimensional entangled state in LOCC paradigm.

Leonardo Rydin Gorjão, Jacques Maritz

In this work, we explore two mechanisms that explain non-Gaussian behaviour of power-grid frequency recordings in the South African grid. We make use of a Fokker-Planck approach to power-grid frequency that yields a direct relation between common model parameters such as inertia, damping, and noise amplitude and non-parametric estimations of the same directl

Jigang Tong, Fanhang Yang, Sen Yang, Enzeng Dong

Recently, Transformer has achieved great success in computer vision. However, it is constrained because the spatial and temporal complexity grows quadratically with the number of large points in 3D object detection applications. Previous point-wise methods are suffering from time consumption and limited receptive fields to capture information among points. I

Xiao-Qiong Wang, Guang-Quan Luo, Jin-Yu Liu, Guan-Hua Huang

Understanding strongly correlated quantum materials, such as high $T_\textrm{c}$ superconductors, iron-based superconductors, and twisted bilayer graphene systems, remains to be one of the outstanding challenges in condensed matter physics. Quantum simulation with ultra-cold atoms in particular optical lattices, which provide orbital degrees of freedom, is a

Sugumi Kanno, Ann Mukuno, Jiro Soda, Kazushige Ueda

There exist observational evidence to believe the existence of primordial magnetic fields generated during inflation. We study primordial gravitational waves (PGWs) during inflation in the presence of magnetic fields sustained by a gauge kinetic coupling. In the model, not only gravitons as excitations of PGWs, but also photons as excitations of electromagne

Ángel Javier Alonso, Michael Kerber, Siddharth Pritam

Bifiltered graphs are a versatile tool for modelling relations between data points across multiple grades of a two-dimensional scale. They are especially popular in topological data analysis, where the homological properties of the induced clique complexes are studied. To reduce the large size of these clique complexes, we identify filtration-dominated edges

D. Elia, S. Molinari, E. Schisano, J. D. Soler

We present a new derivation of the Milky Way's current star formation rate (SFR) based on the data of the Hi-GAL Galactic plane survey. We estimate the distribution of the SFR across the Galactic plane from the star-forming clumps identified in the Hi-GAL survey and calculate the total SFR from the sum of their contributions. The estimate of the global SFR a

Thorben Petersen, Ulrich K. Rößler, Liviu Hozoi

The notion of strong electronic correlations arose in the context of $d$-metal oxides such as NiO but can be exemplified on systems as simple as the H$_2$ molecule. Here we shed light on correlation effects on B$_6^{2-}$ clusters as found in $M$B$_6$ hexaborides and show that the B 2$p$ valence electrons are fairly correlated. B$_6$-octahedron excitation ene

Alexandre Jannaud

Using the technology of barcodes and previously proven continuity results, we extend to $C^0$ symplectic topology a beautiful result from Keating. Given two Lagrangian spheres in a Liouville domain, with good conditions, we prove that the Dehn twists about these spheres generate a free subgroup of the $C^0$ symplectic mapping class group.

Richard D. Gill

In this short note, I derive the Bell-CHSH inequalities as an elementary result in the present-day theory of statistical causality based on graphical models or Bayes' nets, defined in terms of DAGs (Directed Acyclic Graphs) representing direct statistical causal influences between a number of observed and unobserved random variables. I show how spatio-tempor

Carlo Alberto Barbano, Benoit Dufumier, Enzo Tartaglione, Marco Grangetto

Many datasets are biased, namely they contain easy-to-learn features that are highly correlated with the target class only in the dataset but not in the true underlying distribution of the data. For this reason, learning unbiased models from biased data has become a very relevant research topic in the last years. In this work, we tackle the problem of learni

Zishuo Li, Muhammad Umar B. Niazi, Changxin Liu, Yilin Mo

This paper studies the problem of secure state estimation of a linear time-invariant (LTI) system with bounded noise in the presence of sparse attacks on an unknown, time-varying set of sensors. In other words, at each time, the attacker has the freedom to choose an arbitrary set of no more that $p$ sensors and manipulate their measurements without restraint

Mehdi Rafiei, Jenni Raitoharju, Alexandros Iosifidis

X-ray imaging technology has been used for decades in clinical tasks to reveal the internal condition of different organs, and in recent years, it has become more common in other areas such as industry, security, and geography. The recent development of computer vision and machine learning techniques has also made it easier to automatically process X-ray ima

Zili Huang, Zhuo Chen, Naoyuki Kanda, Jian Wu

Self-supervised learning (SSL), which utilizes the input data itself for representation learning, has achieved state-of-the-art results for various downstream speech tasks. However, most of the previous studies focused on offline single-talker applications, with limited investigations in multi-talker cases, especially for streaming scenarios. In this paper,

Xin-Yu Xu, Qing Zhou, Shuai Zhao, Shu-Ming Hu

Design of detection strategies for multipartite entanglement stands as a central importance on our understanding of fundamental quantum mechanics and has had substantial impact on quantum information applications. However, accurate and robust detection approaches are severely hindered, particularly when the number of nodes grows rapidly like in a quantum net

Wanming Hao, Junjie Li, Gangcan Sun, Chongwen Huang

In this paper, we investigate the energy efficiency (EE) problem under reconfigurable intelligent surface (RIS)-aided secure cell-free networks, where multiple legitimate users and eavesdroppers (Eves) exist. We formulate a max-min secure EE optimization problem by jointly designing the distributed active beamforming and artificial noise at base stations as

Hao Lang, Yinhe Zheng, Jian Sun, Fei Huang

Out-of-Domain (OOD) intent detection is important for practical dialog systems. To alleviate the issue of lacking OOD training samples, some works propose synthesizing pseudo OOD samples and directly assigning one-hot OOD labels to these pseudo samples. However, these one-hot labels introduce noises to the training process because some hard pseudo OOD sample

Victorita Dolean, Alexander Heinlein, Siddhartha Mishra, Ben Moseley

Physics-informed neural networks (PINNs) [4, 10] are an approach for solving boundary value problems based on differential equations (PDEs). The key idea of PINNs is to use a neural network to approximate the solution to the PDE and to incorporate the residual of the PDE as well as boundary conditions into its loss function when training it. This provides a

Fateme Movahedi

Let $G=(V, E)$ be a simple graph with vertex set $V$ and edge set $E$. The Sombor index of the graph $G$ is a degree-based topological index, defined as $$SO(G)=\sum_{uv \in E}\sqrt{d(u)^2+d(v)^2},$$ in which $d(x)$ is the degree of the vertex $x \in V$ for $x=u, v$. In this paper, we characterize the extremal trees with a given degree sequence that maximize

Ivan Damnjanović, Dragan Stevanović

Recently, Gutman [MATCH Commun. Math. Comput. Chem. 86 (2021) 11-16] defined a new graph invariant which is named the Sombor index $\mathrm{SO}(G)$ of a graph $G$ and is computed via the expression \[ \mathrm{SO}(G) = \sum_{u \sim v} \sqrt{\mathrm{deg}(u)^2 + \mathrm{deg}(v)^2} , \] where $\mathrm{deg}(u)$ represents the degree of the vertex $u$ in $G$ and t

Kan Chen, Zi-Yang Lin, Shi-Lin Zhu

We construct the effective potentials of the $P_c$ and $P_{cs}$ states based on the SU(3)$_{\text{f}}$ symmetry and heavy quark symmetry. Then we perform the coupled-channel analysis of the lowest isospin $P_c$ and $P_{cs}$ systems. The coupled-channel effects play different roles in the $P_c$ and $P_{cs}$ systems. In the $P_c$ systems, this effect gives min

Rohit Misra, Sapna S Mishra, Tapan K. Gandhi

Damage to the inferior frontal gyrus (Broca's area) can cause agrammatic aphasia wherein patients, although able to comprehend, lack the ability to form complete sentences. This inability leads to communication gaps which cause difficulties in their daily lives. The usage of assistive devices can help in mitigating these issues and enable the patients to com

Lars Doorenbos, Stefano Cavuoti, Giuseppe Longo, Massimo Brescia

A trade-off between speed and information controls our understanding of astronomical objects. Fast-to-acquire photometric observations provide global properties, while costly and time-consuming spectroscopic measurements enable a better understanding of the physics governing their evolution. Here, we tackle this problem by generating spectra directly from ph

Yueqi Xie, Weizhong Zhang, Renjie Pi, Fangzhao Wu

Non-IID data distribution across clients and poisoning attacks are two main challenges in real-world federated learning (FL) systems. While both of them have attracted great research interest with specific strategies developed, no known solution manages to address them in a unified framework. To universally overcome both challenges, we propose SmartFL, a gen

G. Dallabona, O. A. Battistel

An explicit investigation about the equal-mass two-loop sunrise Feynman graph is performed. Such perturbative amplitude is related with many important physical process treated in the standard model context. The background of this investigation is an alternative strategy to handle with the divergences typical of perturbative solutions of quantum field theory.

Ilan Shomorony, Reinhard Heckel

Due to its longevity and enormous information density, DNA is an attractive medium for archival data storage. Thanks to rapid technological advances, DNA storage is becoming practically feasible, as demonstrated by a number of experimental storage systems, making it a promising solution for our society's increasing need of data storage. While in living thing

D. D. Pawar, G. G. Bhuttampalle, S. B. Chavhan, Wagdi F. S. Ahmed

In this current article, we introduce the quadruple Shehu transform and its inverse. We also introduce some properties of quadruple Shehu transform. The Convolution theorem and its proof are also discussed. Further, to solve homogeneous and nonhomogeneous partial differential equation we use this transform.

Wei Wang, Yi Qiao, Rong-Hua Liu, Wu-Ming Liu

The exact elementary excitations in a typical U(1) symmetry broken quantum integrable system, that is the twisted J1-J2 spin chain with nearest-neighbor, next nearest neighbor and chiral three spin interactions, are studied. The main technique is that we quantify the energy spectrum of the system by the zero roots of transfer matrix instead of the traditiona

Liansheng Wang, Jiacheng Wang, Lei Zhu, Huazhu Fu

Automated detecting lung infections from computed tomography (CT) data plays an important role for combating COVID-19. However, there are still some challenges for developing AI system. 1) Most current COVID-19 infection segmentation methods mainly relied on 2D CT images, which lack 3D sequential constraint. 2) Existing 3D CT segmentation methods focus on si

Ziye Jia, Qihui Wu, Chao Dong, Chau Yuen

Numerous communication networks are emerging to serve the various demands and improve the quality of service. Heterogeneous users have different requirements on quality metrics such as delay and service efficiency. Besides, the networks are equipped with different types and amounts of resources, and how to efficiently optimize the usage of such limited resou

Ji Oon Lee, Yiting Li

Consider the sample covariance matrix $$\Sigma^{1/2}XX^T\Sigma^{1/2}$$ where $X$ is an $M\times N$ random matrix with independent entries and $\Sigma$ is an $M\times M$ diagonal matrix. It is known that if $\Sigma$ is deterministic, then the fluctuation of $$\sum_if(\lambda_i)$$ converges in distribution to a Gaussian distribution. Here $\{\lambda_i\}$ are e

Anna Guseva, Steven M. Tobias

Taylor-Couette flow is often used as a simplified model for complex rotating flows in the interior of stars and accretion disks. The flow dynamics in these objects is influenced by magnetic fields. For example, quasi-Keplerian flows in Taylor-Couette geometry become unstable to a travelling or standing wave in an external magnetic field if the fluid is condu

Fernando Alonso-Fernandez, Josef Bigun

Periocular recognition has gained attention recently due to demands of increased robustness of face or iris in less controlled scenarios. We present a new system for eye detection based on complex symmetry filters, which has the advantage of not needing training. Also, separability of the filters allows faster detection via one-dimensional convolutions. This

Runbang Zhang, Yixiao Zhang, Kai Shao, Ying Shan

In this study, we explore the representation mapping from the domain of visual arts to the domain of music, with which we can use visual arts as an effective handle to control music generation. Unlike most studies in multimodal representation learning that are purely data-driven, we adopt an analysis-by-synthesis approach that combines deep music representat

Roman Gielerak

A renormalized version of the von Neumann quantum entropy (which is finite and continuous in general, infinite dimensional case) and which obeys several of the natural physical demands (as expected for a "good" measure of entanglement in the case of general quantum states describing bipartite and infinite-dimensional systems) is proposed. The renormalized qu

Mengxi Liu, Sizhen Bian, Paul Lukowicz

This work described a novel non-contact, wearable, real-time eye blink detection solution based on capacitive sensing technology. A low-cost and low-power consumption capacitive sensing prototype was developed and deployed on a pair of standard glasses with a copper electrode attached to the glass frame. The eye blink action will cause the capacitance variat

Bryce Kerr, Oleksiy Klurman

Tur\'an observed that logarithmic partial sums $\sum_{n\le x}\frac{f(n)}{n}$ of completely multiplicative functions (in the particular case of the Liouville function $f(n)=\lambda(n)$) tend to be positive. We develop a general approach to prove two results aiming to explain this phenomena. Firstly, we show that for every $\varepsilon>0$ there exists some $x_

Benjamin Tam

The SNO+ experiment is a large-scale, multipurpose neutrino experiment situated 2 km underground at SNOLAB in Canada. Successor to the Sudbury Neutrino Observatory, the SNO+ detector has inherited much of the original infrastructure including the 12-m diameter acrylic vessel which serves as the main detector body. Initially filled with ultrapure water, the S

Aparajita Bhattacharyya, Ahana Ghoshal, Ujjwal Sen

We show that in presence of a local and uncorrelated dephasing noise, quantum advantage can be obtained in the Fisher information-based lower bound of the minimum uncertainty in estimating parameters of the system Hamiltonian. The quantum advantage refers here to the benefit of initiating with a maximally entangled state instead of a product one. This quantu

Lidong Li, Claudio De Persis, Pietro Tesi, Nima Monshizadeh

We present a novel framework for transferring the knowledge from one system (source) to design a stabilizing controller for a second system (target). Our motivation stems from the hypothesis that abundant data can be collected from the source system, whereas the data from the target system is scarce. We consider both cases where data collected from the sourc

Yuxiang Dong, Fan Liu, Yifeng Xiong

In this letter, we investigate the joint receiver design for integrated sensing and communication (ISAC) systems, where the communication signal and the target echo signal are simultaneously received and processed to achieve a balanced performance between both functionalities. In particular, we proposed two design schemes to solve the joint sensing and commu

Takaaki Kuwahara, Gota Tanaka, Asato Tsuchiya, Kazushi Yamashiro

Motivated by the construction of the cMERA for interacting field theories, we derive a non-perturbative functional differential equation for wave functionals in scalar field theories from the exact renormalization group equation. We check the validity of the equation using the perturbation theory. We calculate the wave functional up to the first-order pertur

Panayot Panayotov, Utsav Shukla, Husrev Taha Sencar, Mohamed Nabeel

We study the problem of profiling news media on the Web with respect to their factuality of reporting and bias. This is an important but under-studied problem related to disinformation and "fake news" detection, but it addresses the issue at a coarser granularity compared to looking at an individual article or an individual claim. This is useful as it allows

Santosh Kumar Yadav, Esha Pahwa, Achleshwar Luthra, Kamlesh Tiwari

Drone-camera based human activity recognition (HAR) has received significant attention from the computer vision research community in the past few years. A robust and efficient HAR system has a pivotal role in fields like video surveillance, crowd behavior analysis, sports analysis, and human-computer interaction. What makes it challenging are the complex po

Zhanwei Yu, Yi Zhao, Tao Deng, Lei You

In sprite the state-of-the-art, significantly reducing carbon footprint (CF) in communications systems remains urgent. We address this challenge in the context of edge computing. The carbon intensity of electricity supply largely varies spatially as well as temporally. This, together with energy sharing via a battery management system (BMS), justifies the po

Shwai He, Liang Ding, Daize Dong, Boan Liu

Dynamic networks, e.g., Dynamic Convolution (DY-Conv) and the Mixture of Experts (MoE), have been extensively explored as they can considerably improve the model's representation power with acceptable computational cost. The common practice in implementing dynamic networks is to convert the given static layers into fully dynamic ones where all parameters are

Achiel Colpaert, Sibren De Bast, Andrea P. Guevara, Zhuangzhuang Cui

Channel state information (CSI) needs to be estimated for reliable and efficient communication, however, location information is hidden inside and can be further exploited. This article presents a detailed description of a Massive Multi-Input Multi-Output (MaMIMO) testbed and provides a set of experimental location-labelled CSI data. In this article, we focu

N. N. Achasov, G. N. Shestakov

We present a phenomenological description of the LHCb data for the magnitudes and phases of the $\pi^-\pi^+$ $S$-wave amplitudes in the $D^+\to\pi^-\pi^+\pi^+$ and $D^+_s\to\pi^-\pi^+\pi^+$ decays. We operate within a simple model that takes into account the known pair interactions of particles in coupled channels. The seed complex amplitudes for various int