May 2022 arXiv papers — page 143

Ildikó Schlotter, Ágnes Cseh

In a graph where vertices have preferences over their neighbors, a matching is called popular if it does not lose a head-to-head election against any other matching when the vertices vote between the matchings. Popular matchings can be seen as an intermediate category between stable matchings and maximum-size matchings. In this paper, we aim to maximize the

Ming-Ting Wu, Cheng-Hsien Yang, Yun-Fang Chung, Kuan-Ting Chen

A simple band model using higher order non-parabolic effect was adopted for single layer molybdenum tungsten alloy disulfide (i.e., $\mathrm{Mo}_{1-x}\mathrm{W}_x\mathrm{S}_2$). The first-principles method considering $2\times2$ supercell was used to study band structure of single layer alloy $\mathrm{Mo}_{1-x}\mathrm{W}_x\mathrm{S}_2$ and a simple band (i.e

Meera Ramaswamy, Itay Griniasty, James P Sethna, Bulbul Chakraborty

Recently, we proposed a universal scaling framework that shows shear thickening in dense suspensions is governed by the crossover between two critical points: one associated with frictionless isotropic jamming and a second corresponding to frictional shear jamming. Here, we show that orthogonal perturbations to the flows, an effective method for tuning shear

Mihai D. Staic

Using the $det^{S^2}$ map from [5], we introduce the notion of $S^2$-rank of a matrix of type $d\times \frac{s(s-1)}{2}$. As an application, we show that the conditional probability matrix associated to two random variables has the $S^2$-rank equal to $1$. Under suitable conditions we prove that the converse of this result also holds.

Jannatul Ferdous, Cem Yuce, Andrea Alù, Hamidreza Ramezani

Topological edge states arise at the interface of two topologically-distinct structures and have two distinct features: they are localized and robust against symmetry protecting disorder. On the other hand, conventional transport in one dimension is associated with extended states, which typically do not have topological robustness. In this paper, using loss

Christiana Erba, Richard Ignace

The mass-loss rates from single massive stars are high enough to form radio photospheres at large distances from the stellar surface where the wind is optically thick to (thermal) free-free opacity. Here we calculate the far-infrared, millimeter, and radio band spectral energy distributions (SEDs) that can result from the combination of free-free processes a

Diego Vaca, Matthew Barry, Luke Yates, Neeraj Nepal

We report a method to obtain insights into lower thermal conductivity of β-Ga2O3 thin films grown by molecular beam epitaxy (MBE) on c-plane sapphire and 4H-SiC substrates. We compare experimental values against the numerical predictions to decipher the effect of boundary scattering and defects in thin-films. We used time domain thermoreflectance (TDTR) to p

Mihai D. Staic

In this paper we show that for a vector space $V_d$ of dimension $d$ there exists a linear map $det^{S^2}:V_d^{\otimes d(2d-1)}\to k$ with the property that $det^{S^2}(\otimes_{1\leq i<j\leq 2d}(v_{i,j}))=0$ if there exists $1\leq x<y<z\leq 2d$ such that $v_{x,y}=v_{x,z}=v_{y,z}$. The existence of such a map was conjectured in [4]. We present two application

Cheng-Hsien Yang, Yun-Fang Chung, Yen-Shuo Su, Kuan-Ting Chen

A simple band model such as the effective mass approximation (EMA) can be used to quickly obtain the lower-energy region for the band structure of monolayer molybdenum disulfide. But the EMA band model cannot give the correct description for the band structure in the higher-energy region. To address this major issue, we propose an analytical band calculation

George Georgescu

It is known that by using the commutator operation, for each congruence modular algebra $A$ one can define a notion of prime congruence. The set $Spec(A)$ of prime congruences of $A$ is endowed with a Zariski style topology. The reticulation of the algebra $A$ is a bounded distributive lattice $L(A)$ whose prime spectrum $Spec(L(A))$ (with the Stone topology

Yang He, Na Li, Ivano E. Castelli, Ruoning Li

Investigation of intermolecular electron spin interaction is of fundamental importance in both science and technology.Here, radical pairs of all-trans retinoic acid molecules on Au(111) are created using an ultra-low temperature scanning tunneling microscope. Antiferromagnetic coupling between two radicals is identified by magnetic-field dependent spectrosco

Jorge A. V. Tohalino, Thiago C. Silva, Diego R. Amancio

Detecting keywords in texts is important for many text mining applications. Graph-based methods have been commonly used to automatically find the key concepts in texts, however, relevant information provided by embeddings has not been widely used to enrich the graph structure. Here we modeled texts co-occurrence networks, where nodes are words and edges are

A. Agarwal, Ashwani Pandey, Aykut Özdönmez, Ergün Ege

We report the results from our study of the blazar S5 1803+784 carried out using the quasi-simultaneous $B$, $V$, $R$, and $I$ observations from May 2020 to July 2021 on 122 nights. Our observing campaign detected the historically bright optical flare during MJD 59063.5$-$MJD 59120.5. We also found the source in its brightest ($R_{mag}$= 13.617) and faintest

César A. Hidalgo

What would you do if you were asked to &#34;add&#34; knowledge? Would you say that &#34;one plus one knowledge&#34; is two &#34;knowledges&#34;? Less than that? More? Or something in between? Adding knowledge sounds strange, but it brings to the forefront questions that are as fundamental as they are eclectic. These are questions about the nature of knowledg

T. O. Puel, S. Chesi, S. Kirchner, P. Ribeiro

Bosons in one dimension display a phenomenon called quasi-condensation, where correlations decay in a powerlaw fashion. We study the fate of quasi-condensation in the non-equilibrium steady-state of a chain of hard-core bosons coupled to macroscopic leads which are held at different chemical potentials. It is found that a finite bias destroys the quasi-conde

Andrés E. Piatti

We study the outer regions of the Milky Way globular cluster NGC 7089 based on new Dark Energy Camera (DECam) observations. The resulting background cleaned stellar density profile reveals the existence of an extended envelope. We confirm previous results that cluster stars are found out to ~ 1deg from the cluster&#39;s centre, which is nearly three times th

Elizabeth Campolongo, Krystal Taylor

We study a lattice point counting problem for spheres arising from the Heisenberg groups. In particular, we prove an upper bound on the number of points on and near large dilates of the unit spheres generated by the anisotropic norms $\|(z,t)\|_α= ( |z|^α+ |t|^{α/2})^{1/α}$ for $α\geq 2$. As a first step, we reduce our counting problem to one of bounding an

R. D. Strauss, Nigussie M. Giday, Ephrem B. Seba, Daniel A. Chekole

We discuss a newly established neutron monitor station installed at the ENTOTO Observatory Research Center outside of Addis Ababa, Ethiopia. This is a version of a mini-neutron monitor, recently upgraded to detect individual neutrons and able to calculate the waiting time distribution between neutron pulses down to $\sim 1 $ $μ$s. From the waiting time distr

Haowei Zhu, Wenjing Ke, Dong Li, Ji Liu

Recently, self-attention mechanisms have shown impressive performance in various NLP and CV tasks, which can help capture sequential characteristics and derive global information. In this work, we explore how to extend self-attention modules to better learn subtle feature embeddings for recognizing fine-grained objects, e.g., different bird species or person

Niket Thakkar, Mike Famulare

In this paper we create a compartmental, stochastic process model of SARS-CoV-2 transmission, where the process&#39;s mean and variance have distinct dynamics. The model is fit to time series data from Washington from January 2020 to March 2021 using a deterministic, biologically-motivated signal processing approach, and we show that the model&#39;s hidden s

Francesca Bisconti, Andrea Chiavassa

In the framework of the development of the SWGO experiment we have performed a detailed study of the single unit of an extensive air shower observatory based on an array of water Cherenkov detectors. Indeed, one of the possible water Cherenkov detector unit configurations for SWGO consists of tanks, and to reach a high detection efficiency and discrimination

N Mont-Geli, A Tarifeño-Saldivia, F Calviño, M Pallàs

In this work, we present the design of a new modular and transportable neutron detector for (α,n) reactions. The detector is based on the use of several 3He-filled proportional counters embedded in high density polyethylene. In order to provide the detector with a response independent of the neutron energy, a flat response, an innovative design methodology h

Coloma Ballester, Aurelie Bugeau, Samuel Hurault, Simone Parisotto

Image inpainting refers to the restoration of an image with missing regions in a way that is not detectable by the observer. The inpainting regions can be of any size and shape. This is an ill-posed inverse problem that does not have a unique solution. In this work, we focus on learning-based image completion methods for multiple and diverse inpainting which

Benjamin Lynch, Nada Al-Haddad, Wenyuan Yu, Erika Palmerio

We present a comprehensive analysis of the three-dimensional magnetic flux rope structure generated during the Lynch et al. (2019) magnetohydrodynamic (MHD) simulation of a global-scale, 360 degree-wide streamer blowout coronal mass ejection (CME) eruption. We create both fixed and moving synthetic spacecraft to generate time series of the MHD variables thro

Jianfa Chen, Yue Yin, Yifan Xu

In this paper we want to address the problem of automation for recognition of photographed cooking dishes and generating the corresponding food recipes. Current image-to-recipe models are computation expensive and require powerful GPUs for model training and implementation. High computational cost prevents those existing models from being deployed on portabl

Gauthier Durieux, Abel Gutiérrez Camacho, Luca Mantani, Víctor Miralles

In this contribution to the 2021 Snowmass community planning exercise that informs the American strategy for particle physics, we present the prospects for measurements of the top-quark couplings at future colliders. Projections are presented for the high luminosity phase of the Large Hadron Collider and a future Higgs/electroweak/top factory electron-positr

Kymani Armstrong-Williams, Chris D. White, Sam Wikeley

The double copy is by now a firmly-established correspondence between amplitudes and classical solutions in biadjoint scalar, gauge and gravity theories. To date, no strongly coupled examples of the double copy in four dimensions have been found, and previous attempts based on exact non-linear solutions of biadjoint theory in Lorentzian signature have failed

Mitchell Black, Amir Nayyeri

We describe a nearly-linear time algorithm to solve the linear system $L_1x = b$ parameterized by the first Betti number of the complex, where $L_1$ is the 1-Laplacian of a simplicial complex $K$ that is a subcomplex of a collapsible complex $X$ linearly embedded in $\mathbb{R}^{3}$. Our algorithm generalizes the work of Black et al.~[SODA2022] that solved t

Yang Xiao, Jinlan Fu, See-Kiong Ng, Pengfei Liu

In this paper, we ask the research question of whether all the datasets in the benchmark are necessary. We approach this by first characterizing the distinguishability of datasets when comparing different systems. Experiments on 9 datasets and 36 systems show that several existing benchmark datasets contribute little to discriminating top-scoring systems, wh

Étienne Martel, Geoffroy Lesur

Protoplanetary discs (PPDs) are cold, dense and weakly ionised environments that witness the planetary formation. Among these discs, transition discs (TDs) are characterised by a wide cavity in the dust and gas distribution. Despite this lack of material, many TDs strongly accrete onto their central star, possibly indicating that a mechanism is driving fast

Iman Peivaste, Nima H. Siboni, Ghasem Alahyarizadeh, Reza Ghaderi

Phase-field-based models have become common in material science, mechanics, physics, biology, chemistry, and engineering for the simulation of microstructure evolution. Yet, they suffer from the drawback of being computationally very costly when applied to large, complex systems. To reduce such computational costs, a Unet-based artificial neural network is d

Jack S. Keeler, Terence D. Blake, Duncan A. Lockerby, James E. Sprittles

We report a molecularly-augmented continuum-based computational model of dynamic wetting and apply it to the displacement of an externally-driven liquid plug between two partially-wetted parallel plates. The results closely follow those obtained in a recent molecular-dynamics (MD) study of the same problem Toledano (2021) which we use as a benchmark. We are

Muhammad Usman Awais

Deep Reinforcement Learning (DRL) is being used in many domains. One of the biggest advantages of DRL is that it enables the continuous improvement of a learning agent. Secondly, the DRL framework is robust and flexible enough to be applicable to problems of varying nature and domain. Presented work is evidence of using the DRL technique to solve an Optimal

Matthieu Ospici, Klaas Sys, Sophie Guegan-Marat

This paper combines fisheries dependent data and environmental data to be used in a machine learning pipeline to predict the spatio-temporal abundance of two species (plaice and sole) commonly caught by the Belgian fishery in the North Sea. By combining fisheries related features with environmental data, sea bottom temperature derived from remote sensing, a

Pedro Fouto, Pedro Ákos Costa, Nuno Preguiça, João Leitão

Prototyping and implementing distributed algorithms, particularly those that address challenges related with fault-tolerance and dependability, is a time consuming task. This is, in part, due to the need of addressing low level aspects such as management of communication channels, controlling timeouts or periodic tasks, and dealing with concurrency issues. T

Qinghang Hong, Fengming Liu, Dong Li, Ji Liu

Sparse R-CNN is a recent strong object detection baseline by set prediction on sparse, learnable proposal boxes and proposal features. In this work, we propose to improve Sparse R-CNN with two dynamic designs. First, Sparse R-CNN adopts a one-to-one label assignment scheme, where the Hungarian algorithm is applied to match only one positive sample for each g

Yiwei Fu, Feng Xue

In this paper, we introduce Masked Anomaly Detection (MAD), a general self-supervised learning task for multivariate time series anomaly detection. With the increasing availability of sensor data from industrial systems, being able to detecting anomalies from streams of multivariate time series data is of significant importance. Given the scarcity of anomali

Kush Kinra, Renhai Wang, Manil T. Mohan

This article concerns the long-term random dynamics in regular spaces for a non-autonomous Navier-Stokes equation defined on a bounded smooth domain $\mathcal{O}$ driven by multiplicative and additive noise. For the two kinds of noise driven equations, we demonstrate the existence of a unique pullback attractor which is backward compact and asymptotically au

C. Muñoz-Cabello, J. J. Nuño-Ballesteros, R. Oset Sinha

We consider singularities of frontal surfaces of corank one and finite frontal codimension. We look at the classification under left-right-equivalence and introduce the notion of frontalisation for singularities of fold type. We define the cuspidal and the transverse double point curves and prove that the frontal has finite codimension if and only if both cu

Darwin Quezada-Gaibor, Lucie Klus, Joaquín Torres-Sospedra, Elena Simona Lohan

Wearable and IoT devices requiring positioning and localisation services grow in number exponentially every year. This rapid growth also produces millions of data entries that need to be pre-processed prior to being used in any indoor positioning system to ensure the data quality and provide a high Quality of Service (QoS) to the end-user. In this paper, we

Steven James, Benjamin Rosman, George Konidaris

We are concerned with the question of how an agent can acquire its own representations from sensory data. We restrict our focus to learning representations for long-term planning, a class of problems that state-of-the-art learning methods are unable to solve. We propose a framework for autonomously learning state abstractions of an agent&#39;s environment, g

Yifei Zhou, Yansong Feng

Recent works show that discourse analysis benefits from modeling intra- and inter-sentential levels separately, where proper representations for text units of different granularities are desired to capture both the meaning of text units and their relations to the context. In this paper, we propose to take advantage of transformers to encode contextualized re

Eleonora Grassucci, Luigi Sigillo, Aurelio Uncini, Danilo Comminiello

Image-to-image translation (I2I) aims at transferring the content representation from an input domain to an output one, bouncing along different target domains. Recent I2I generative models, which gain outstanding results in this task, comprise a set of diverse deep networks each with tens of million parameters. Moreover, images are usually three-dimensional

Leonard Bruns, Fereidoon Zangeneh, Patric Jensfelt

We consider the problem of tracking the 6D pose of a moving RGB-D camera in a neural scene representation. Different such representations have recently emerged, and we investigate the suitability of them for the task of camera tracking. In particular, we propose to track an RGB-D camera using a signed distance field-based representation and show that compare

Denis Bernard, Tanmoy Chattopadhyay, Fabian Kislat, Nicolas Produit

While the scientific potential of high-energy X-ray and gamma-ray polarimetry has long been recognized, measuring the polarization of high-energy photons is challenging. To date, there has been very few significant detections from an astrophysical source. However, recent technological developments raise the possibility that this may change in the not-too-dis

Yuan Zhou, Keran Chen, Xiaofeng Li

Sea fog significantly threatens the safety of maritime activities. This paper develops a sea fog dataset (SFDD) and a dual branch sea fog detection network (DB-SFNet). We investigate all the observed sea fog events in the Yellow Sea and the Bohai Sea (118.1°E-128.1°E, 29.5°N-43.8°N) from 2010 to 2020, and collect the sea fog images for each event from the Ge

Wenting Zhao, Konstantine Arkoudas, Weiqi Sun, Claire Cardie

Task-oriented parsing (TOP) aims to convert natural language into machine-readable representations of specific tasks, such as setting an alarm. A popular approach to TOP is to apply seq2seq models to generate linearized parse trees. A more recent line of work argues that pretrained seq2seq models are better at generating outputs that are themselves natural l

O. G. Styrt

The article is devoted to the question whether the orbit space of a compact linear group is a topological manifold and a homological manifold. In the paper, the case of a simple three-dimensional group is considered. An upper bound is obtained for the sum of the half-dimension integral parts of the irreducible components of a representation whose quotient sp

Zhiming Cui, Jaehyung Ju

Mechanical couplings such as axial-shear and axial-bending have great potential in the design of active mechanical metamaterials with directional control of input and output loads in sensors and actuators. However, the current ad hoc design of mechanical coupling without theoretical support of elasticity cannot provide design guidelines for mechanical coupli

T. Wareham

Teams of interacting and co-operating agents have been proposed as an efficient and robust alternative to monolithic centralized control for carrying out specified tasks in a variety of applications. A number of different team and agent architectures have been investigated, e.g., teams based on single vs multiple behaviorally-distinct types of agents (homoge

Yeshwanth Cherapanamjeri, Constantinos Daskalakis, Andrew Ilyas, Manolis Zampetakis

We provide efficient estimation methods for first- and second-price auctions under independent (asymmetric) private values and partial observability. Given a finite set of observations, each comprising the identity of the winner and the price they paid in a sequence of identical auctions, we provide algorithms for non-parametrically estimating the bid distri

Lei Deng, Danzhou Wu, Zilong Liu, Yijin Zhang

In this paper, we for the first time investigate the random access problem for a delay-constrained heterogeneous wireless network. We begin with a simple two-device problem where two devices deliver delay-constrained traffic to an access point (AP) via a common unreliable collision channel. By assuming that one device (called Device 1) adopts ALOHA, we aim t

Umberto Grandi, Grzegorz Lisowski, M. S. Ramanujan, Paolo Turrini

Majority illusion occurs in a social network when the majority of the network nodes belong to a certain type but each node&#39;s neighbours mostly belong to a different type, therefore creating the wrong perception, i.e., the illusion, that the majority type is different from the actual one. From a system engineering point of view, we want to devise algorith

Abdulhalim Fayad, Manish Jha, Tibor Cinkler, Jacek Rak

With the rapid growth in the telecommunications industry moving towards 5G and beyond (5GB) and the emergence of data-hungry and time-sensitive applications, Mobile Network Operators (MNOs) are faced with a considerable challenge to keep up with these new demands. Cloud radio access network (CRAN) has emerged as a cost-effective architecture that improves 5G

Yujian Gan, Xinyun Chen, Qiuping Huang, Matthew Purver

In text-to-SQL tasks -- as in much of NLP -- compositional generalization is a major challenge: neural networks struggle with compositional generalization where training and test distributions differ. However, most recent attempts to improve this are based on word-level synthetic data or specific dataset splits to generate compositional biases. In this work,

Caterina Braggio, Giulio Cappelli, Giovanni Carugno, Nicolò Crescini

In this paper we will describe the characterisation of a rf detection chain based on a travelling wave parametric amplifier (TWPA). The detection chain is meant to be used for dark matter axion searches and thus it is mounted coupled to a high Q microwave resonant cavity. A system noise temperature $T_{\rm sys} = (3.3 \pm 0.1$) K has been measured at a frequ

Stanley Simoes, Deepak P, Muiris MacCarthaigh

We conduct an exploratory study that looks at incorporating John Rawls&#39; ideas on fairness into existing unsupervised machine learning algorithms. Our focus is on the task of clustering, specifically the k-means clustering algorithm. To the best of our knowledge, this is the first work that uses Rawlsian ideas in clustering. Towards this, we attempt to de

Alex Samorodnitsky

For $0 < λ< 1$ and $n \rightarrow \infty$ pick uniformly at random $λn$ vectors in $\{0,1\}^n$ and let $C$ be the orthogonal complement of their span. Given $0 < γ< \frac12$ with $0 < λ< h(γ)$, let $X$ be the random variable that counts the number of words in $C$ of Hamming weight $i = γn$ (where $i$ is assumed to be an even integer). Linial and Mosheiff det

Fazal Hameed, Asif Ali Khan, Sebastien Ollivier, Alex K. Jones

Recent DNA pre-alignment filter designs employ DRAM for storing the reference genome and its associated meta-data. However, DRAM incurs increasingly high energy consumption background and refresh energy as devices scale. To overcome this problem, this paper explores a design with racetrack memory (RTM)--an emerging non-volatile memory that promises higher st

Teemu Pennanen, Ari-Pekka Perkkiö

This paper studies duality and optimality conditions in general convex stochastic optimization problems introduced by Rockafellar and Wets in 1976. We derive an explicit dual problem in terms of two dual variables, one of which is the shadow price of information while the other one gives the marginal cost of a perturbation much like in classical Lagrangian d

A. Dutta, Bharat Kumar, Deepmala, A. K. Das

The paper aims to propose a suitable method in finding the solution of tensor complementarity problem. The tensor complementarity problem is a subclass of nonlinear complementarity problems for which the involved function is defined by a tensor. We propose a new homotopy function with smooth and bounded homotopy path to obtain solution of the tensor compleme

Hwanhee Lee, Kang Min Yoo, Joonsuk Park, Hwaran Lee

Despite the recent advances in abstractive summarization systems, it is still difficult to determine whether a generated summary is factual consistent with the source text. To this end, the latest approach is to train a factual consistency classifier on factually consistent and inconsistent summaries. Luckily, the former is readily available as reference sum

Chifumi Nishioka, Michael Färber, Tarek Saier

Citing is an important aspect of scientific discourse and important for quantifying the scientific impact quantification of researchers. Previous works observed that citations are made not only based on the pure scholarly contributions but also based on non-scholarly attributes, such as the affiliation or gender of authors. In this way, citation bias is prod

Ngoc Long Nguyen, Jérémy Anger, Axel Davy, Pablo Arias

Modern Earth observation satellites capture multi-exposure bursts of push-frame images that can be super-resolved via computational means. In this work, we propose a super-resolution method for such multi-exposure sequences, a problem that has received very little attention in the literature. The proposed method can handle the signal-dependent noise in the i

Xin Wang, Yasheng Wang, Yao Wan, Jiawei Wang

Recent years have witnessed increasing interest in code representation learning, which aims to represent the semantics of source code into distributed vectors. Currently, various works have been proposed to represent the complex semantics of source code from different views, including plain text, Abstract Syntax Tree (AST), and several kinds of code graphs (

Haodong Duan, Nanxuan Zhao, Kai Chen, Dahua Lin

Recognizing transformation types applied to a video clip (RecogTrans) is a long-established paradigm for self-supervised video representation learning, which achieves much inferior performance compared to instance discrimination approaches (InstDisc) in recent works. However, based on a thorough comparison of representative RecogTrans and InstDisc methods, w

Beibei Liu, Sean N. Raymond, Seth A. Jacobson

The Solar System&#39;s orbital structure is thought to have been sculpted by an episode of dynamical instability among the giant planets. However, the instability trigger and timing have not been clearly established. Hydrodynamical modeling has shown that while the Sun&#39;s gaseous protoplanetary disk was present the giant planets migrated into a compact or

R. M. Khakimov, M. T. Makhammadaliev, U. A. Rozikov

In this paper, we study the HC-model with a countable set $\mathbb Z$ of spin values on a Cayley tree of order $k\geq 2$. This model is defined by a countable set of parameters (that is, the activity function $λ_i>0$, $i\in \mathbb Z$). A functional equation is obtained that provides the consistency condition for finite-dimensional Gibbs distributions. Analy

Khaled Janada, Hassan Soltan, Mohamed-Sobeih Hussein, Ahmad Abdel-Shafi

Control charts, as had been used traditionally for quality monitoring, were applied alternatively to monitor systems&#39; reliability. In other words, they can be applied to detect changes in the failure behavior of systems. Such purpose imposed modifying traditional control charts in addition to developing charts that are more compatible with reliability mo

Vishwanath R. Singireddy, Manjanna Basappa

In this paper, we consider the following $k$-dispersion problem. Given a set $S$ of $n$ points placed in the plane in a convex position, and an integer $k$ ($0<k<n$), the objective is to compute a subset $S&#39;\subset S$ such that $|S&#39;|=k$ and the minimum distance between a pair of points in $S&#39;$ is maximized. Based on the bounded search tree method

O. V. Borovkova, S. V. Lutsenko, D. A. Sylgacheva, A. N. Kalish

The magneto-optical Faraday effect in the magnetoplasmonic nanostructures with nonuniform, periodically modulated spatial distribution of the magnetization is considered. It is shown that in such nanostructures the Faraday effect can experience the resonant enhancement in the spectral range of the plasmonic and waveguide optical modes excitation. It happens

Marie-France Vignéras

Motivated by the Langlands program in representation theory, number theory and geometry, the theory of representations of a reductive $p$-adic group over a coefficient ring different from the field of complex numbers has been widely developped during the last two decades. This article provides a survey of basic results obtained in the 21st century.

Bill Yuchen Lin, Sida Wang, Xi Victoria Lin, Robin Jia

Real-world natural language processing (NLP) models need to be continually updated to fix the prediction errors in out-of-distribution (OOD) data streams while overcoming catastrophic forgetting. However, existing continual learning (CL) problem setups cannot cover such a realistic and complex scenario. In response to this, we propose a new CL problem formul

Peter Hansbo, Mats G. Larson

In this paper we apply a nonconforming rotated bilinear tetrahedral element to the Stokes problem in $\mathbb{R}^3$. We show that the element is stable in combination with a piecewise linear, continuous, approximation of the pressure. This gives an approximation similar to the well known continuous $P^2-P^1$ Taylor$-$Hood element, but with fewer degrees of f

Georg Bergner, Marios Costa, Haralambos Panagopoulos, Ivan Soler

In this work we perform a perturbative study of the Noether supercurrent operator in the context of Supersymmetric ${\cal N}{=}1$ Yang-Mills (SYM) theory on the lattice. The supercurrent mixes with several other operators, some of which are not gauge invariant, having the same quantum numbers. We determine, to one loop order, the renormalization and all corr

S. Majumder, S. Chowdhury, B. K. De, V. Dwij

Exchange bias (EB) shifts are commonly reported for the ferromagnetic (FM)/antiferromagnetic (AFM) bilayer systems. While stoichiometric ordered Sm$_{2}$NiMnO$_{6}$ (SNMO) and BaTiO$_{3}$ (BTO) are known to possesses FM and diamagnetic orderings respectively, here we have demonstrated the cooling field dependent EB and training effects in epitaxial SNMO/BTO/

H. Viswanathan

The influence of drop formation due to micro rib-like structures, viz., the Junction Gutters (JGs) within a standard microfluidic T-junction, is numerically investigated. Hydrodynamic conditions that lead to various flow regimes are identified characterized by the Capillary number (Ca) and velocity ratios of the dispersed and continuous phases (q) within a s

Ankan Mullick, Sukannya Purkayastha, Pawan Goyal, Niloy Ganguly

Systems like Voice-command based conversational agents are characterized by a pre-defined set of skills or intents to perform user specified tasks. In the course of time, newer intents may emerge requiring retraining. However, the newer intents may not be explicitly announced and need to be inferred dynamically. Thus, there are two important tasks at hand (a

Minjong Cheon, Minseon Kim, Hanseon Joo

The Korean wave, which denotes the global popularity of South Korea&#39;s cultural economy, contributes to the increasing demand for the Korean language. However, as there does not exist any application for foreigners to learn Korean, this paper suggested a design of a novel Korean learning application. Speech recognition, speech-to-text, and speech-to-wavef

Hong Wang

In order to describe the impact of nonholonomic constraints for the dynamics of a regular controlled Hamiltonian (RCH) system, in this paper, for an RCH system with nonholonomic constraint, we first derive its distributional RCH system, by analyzing carefully the structure of dynamical vector field of the nonholonomic RCH system. Secondly, we derive precisel

Sven Buechel, Udo Hahn

We describe EmoBank, a corpus of 10k English sentences balancing multiple genres, which we annotated with dimensional emotion metadata in the Valence-Arousal-Dominance (VAD) representation format. EmoBank excels with a bi-perspectival and bi-representational design. On the one hand, we distinguish between writer&#39;s and reader&#39;s emotions, on the other

Eloisa Detomi, Marta Morigi, Pavel Shumyatsky

Let $G$ be a finite group. A coprime commutator in $G$ is any element that can be written as a commutator $[x,y]$ for suitable $x,y\in G$ such that $π(x)\capπ(y)=\emptyset$. Here $π(g)$ denotes the set of prime divisors of the order of the element $g\in G$. An anti-coprime commutator is an element that can be written as a commutator $[x,y]$, where $π(x)=π(y)

Lei Wang, Yi Jiang, Jiaxi Liu, Shuai Zhang

According to topological quantum chemistry, a class of electronic materials have been called obstructed atomic insulators (OAIs), in which a portion of valence electrons necessarily have their centers located on some empty $\textit{Wyckoff}$ positions without atoms occupation in the lattice. The obstruction of centering these electrons coinciding with their

Duilio De Santis, Claudio Guarcello, Bernardo Spagnolo, Angelo Carollo

The emergence of travelling sine-Gordon breathers due to the nonlinear supratransmission effect is theoretically studied in a long Josephson junction driven by suitable magnetic pulses, taking into account the presence of dissipation, a current bias, and a thermal noise source. The simulations clearly indicate that, depending on the pulse&#39;s shape and the

Gullal S. Cheema, Sherzod Hakimov, Abdul Sittar, Eric Müller-Budack

In recent years, the problem of misinformation on the web has become widespread across languages, countries, and various social media platforms. Although there has been much work on automated fake news detection, the role of images and their variety are not well explored. In this paper, we investigate the roles of image and text at an earlier stage of the fa

Marcely Zanon Boito, John Ortega, Hugo Riguidel, Antoine Laurent

This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2022: low-resource and dialect speech translation. For the Tunisian Arabic-English dataset (low-resource and dialect tracks), we build an end-to-end model as our joint primary submission, and compare it against casca

Vladimir Klinshov, Sergey Kirillov

Recently, the so-called next-generation neural mass models have received a lot of attention of the researchers in the field of mathematical neuroscience. The ability of these models to account for the degree of synchrony in neural populations proved useful in many contexts such as the modeling of brain rhythms, working memory and spatio-temporal patterns of

Zarathustra A. Goertzel, Jan Jakubův, Cezary Kaliszyk, Miroslav Olšák

We significantly improve the performance of the E automated theorem prover on the Isabelle Sledgehammer problems by combining learning and theorem proving in several ways. In particular, we develop targeted versions of the ENIGMA guidance for the Isabelle problems, targeted versions of neural premise selection, and targeted strategies for E. The methods are

Muhammad Awais Jadoon, Adriano Pastore, Monica Navarro

Grant-free random access (RA) techniques are suitable for machine-type communication (MTC) networks but they need to be adaptive to the MTC traffic, which is different from the human-type communication. Conventional RA protocols such as exponential backoff (EB) schemes for slotted-ALOHA suffer from a high number of collisions and they are not directly applic

Martin Knor, Mirko Petruševski, Riste Škrekovski

The (independent) chromatic vertex stability ($\ivs(G)$) $\vs(G)$ is the minimum size of (independent) set $S\subseteq V(G)$ such that $χ(G-S)=χ(G)-1$. In this paper we construct infinitely many graphs $G$ with $Δ(G)=4$, $χ(G)=3$, $\ivs(G)=3$ and $\vs(G)=2$, which gives a partial negative answer to a problem posed in \cite{ABKM}.

David Koisser, Patrick Jauernig, Gene Tsudik, Ahmad-Reza Sadeghi

We address the challenging problem of efficient trust establishment in constrained networks, i.e., networks that are composed of a large and dynamic set of (possibly heterogeneous) devices with limited bandwidth, connectivity, storage, and computational capabilities. Constrained networks are an integral part of many emerging application domains, from IoT mes

Felix Dellinger

This paper studies the discrete differential geometry of the checkerboard pattern inscribed in a quadrilateral net by connecting edge midpoints. It turns out to be a versatile tool which allows us to consistently define principal nets, Koenigs nets and eventually isothermic nets as a combination of both. Principal nets are based on the notions of orthogonali

Ľubomír Baňas, Martin Ondreját

We propose a fully practical numerical scheme for the simulation of the stochastic total variation flow (STFV). The approximation is based on a stable time-implicit finite element space-time approximation of a regularized STVF equation. The approximation also involves a finite dimensional discretization of the noise that makes the scheme fully implementable

Yusef Maleki, Alireza Maleki

Quantization of the gravity remains one of the most important, yet extremely illusive, challenges at the heart of modern physics. Any attempt to resolve this long-standing problem seems to be doomed, as the route to any direct empirical evidence (i.e., detecting gravitons) for shedding light on the quantum aspect of the gravity is far beyond the current capa

Jindřich Helcl, Barry Haddow, Alexandra Birch

Efficient machine translation models are commercially important as they can increase inference speeds, and reduce costs and carbon emissions. Recently, there has been much interest in non-autoregressive (NAR) models, which promise faster translation. In parallel to the research on NAR models, there have been successful attempts to create optimized autoregres

Lorenzo Steccanella, Anders Jonsson

This paper presents a novel state representation for reward-free Markov decision processes. The idea is to learn, in a self-supervised manner, an embedding space where distances between pairs of embedded states correspond to the minimum number of actions needed to transition between them. Compared to previous methods, our approach does not require any domain

Shifen Wang, Qingying Xue, Chunmei Zhang

In this paper, the object of our investigation is the following Littlewood-Paley square function $g$ associated with the Schrödinger operator $L=-Δ+V$ which is defined by: $g(f)(x)=\Big(\int_{0}^{\infty}\Big|\frac{d}{dt}e^{-tL}(f)(x)\Big|^2tdt\Big)^{1/2},$ where $Δ$ is the laplacian operator on $\mathbb{R}^n$ and $V$ is a nonnegative potential. We show that

S. A. Tyul&#39;bashev, V. S. Tyul&#39;bashev, M. A. Kitaeva, A. I. Chernyshova

Pulsars with periods more than 0.4 seconds in the declination range -9o < decj < 42o and in the right ascension range 0h < r.a.< 24h were searched in parallel with the program of interplanetary scintillations monitoring of a large number of sources with the radiotelescope LPA LPI. Four-year observations carried out at the central frequency 110.25 MHz in the

Mingsheng Ying

A first-order logic with quantum variables is needed as an assertion language for specifying and reasoning about various properties (e.g. correctness) of quantum programs. Surprisingly, such a logic is missing in the literature, and the existing first-order Birkhoff-von Neumann quantum logic deals with only classical variables and quantifications over them.

Mehrdad Ghasabehi, Ali Jabbary, Mehrzad Shams

A Proton Exchange Membrane Fuel Cell (PEMFC) provides stable, emission-free, high-efficiency power. Water management and durability of PEMFCs are directly affected by transport phenomena at the cathode side. In the present study, transport phenomena are investigated and optimized in a tapered parallel flow field. Main channels in the flow field are tapered,