August 2022 arXiv papers — page 134

Zijiang Yan, Hina Tabassum

Vehicle-to-Infrastructure (V2I) communication is becoming critical for the enhanced reliability of autonomous vehicles (AVs). However, the uncertainties in the road-traffic and AVs' wireless connections can severely impair timely decision-making. It is thus critical to simultaneously optimize the AVs' network selection and driving policies in order to minimi

Chenjie Cao, Qiaole Dong, Yanwei Fu

Many recent inpainting works have achieved impressive results by leveraging Deep Neural Networks (DNNs) to model various prior information for image restoration. Unfortunately, the performance of these methods is largely limited by the representation ability of vanilla Convolutional Neural Networks (CNNs) backbones.On the other hand, Vision Transformers (ViT

Xiang Yu, Zhe Geng, Xiaohua Huang, Qinglu Wang

In recent years, convolutional neural networks (CNNs) have shown great potential in synthetic aperture radar (SAR) target recognition. SAR images have a strong sense of granularity and have different scales of texture features, such as speckle noise, target dominant scatterers and target contours, which are rarely considered in the traditional CNN model. Thi

Yoshishige Suzuki, Soma Miki, Hikaru Nomura, Eiiti Tamura

An analytical expression is obtained for the mass of an isolated magnetic skyrmion and its linearized equation of motion. The magnetic skyrmion is viewed as a topologically protected spin-wave soliton in the magnetic ultrathin films stabilized by the interfacial-Dzyaloshinskii-Moriya interaction. The equations of motion are derived from the Landau-Lifshitz-G

Xingchen Li, Long Chen, Wenbo Ma, Yi Yang

Recently, increasing efforts have been focused on Weakly Supervised Scene Graph Generation (WSSGG). The mainstream solution for WSSGG typically follows the same pipeline: they first align text entities in the weak image-level supervisions (e.g., unlocalized relation triplets or captions) with image regions, and then train SGG models in a fully-supervised man

J. Takata, X. F. Wang, A. K. H. Kong, J. Mao

We carry out a photometric search for new cataclysmic variable stars (CVs), with the goal of identification for candidates of AR~Scorpii-type binary systems. We select GAIA sources that are likely associated with unidentified X-ray sources, and analyze the light curves taken by the Zwicky Transient Facility, Transiting Exoplanet Survey Satellite, and Lulin O

Vadim Pliner

Estimating customer lifetime value (CLV or LTV) is extremely important for making better business decisions. The proposed flexible proportional hazards model allows an estimation of lifetime value in contractual settings. This approach takes advantage of a churn model, which is assumed to be available.

Zefeng Lin, Sijia Tu, Juan Xu, Yujun Shi

Fe$_y$Te$_{1-x}$Se$_x$, an archetypical iron-based high-temperature superconductor with a simple structure but rich physical properties, has attracted lots of attention because the two end compositions, Se content $x = 0$ and 1, exhibit antiferromagnetism and nematicity, respectively, making it an ideal candidate for studying their interactions with supercon

Bo Chen, Qiyu Zeng, Xiaoxiang Yu, Jiahao Chen

The accumulation and circulation of carbon-hydrogen dictate the chemical evolution of ice giant planets. Species separation and diamond precipitation have been reported in carbon-hydrogen systems, verified by static and shock-compression experiments. Nevertheless, the dynamic formation processes for the above-mentioned phenomena are still insufficiently unde

Hadyan Luthfan Prihadi, Freddy Permana Zen, Seramika Ariwahjoedi, Donny Dwiputra

We calculate the entanglement entropy between two (maximally-extended) spacetime regions of static black hole, seperated by horizon. As a first case, we consider the Schwarzschild black hole, and then we extend the calculations to the charged Reissner- Nordstrom and Schwarzschild-de Sitter black holes with more than one horizon. The case for static and spher

Boxiao Shen, Yongpeng Wu, Wenjun Zhang, Geoffrey Ye Li

This paper investigates joint channel estimation and device activity detection in the LEO satellite-enabled grant-free random access systems with large differential delay and Doppler shift. In addition, the multiple-input multiple-output (MIMO) with orthogonal time-frequency space modulation (OTFS) is utilized to combat the dynamics of the terrestrial-satell

Wenxue Cui, Shaohui Liu, Debin Zhao

By integrating certain optimization solvers with deep neural network, deep unfolding network (DUN) has attracted much attention in recent years for image compressed sensing (CS). However, there still exist several issues in existing DUNs: 1) For each iteration, a simple stacked convolutional network is usually adopted, which apparently limits the expressiven

Xiang Ma, Haijian Sun, Rose Qingyang Hu, Yi Qian

Motivated by the ever-increasing concerns on personal data privacy and the rapidly growing data volume at local clients, federated learning (FL) has emerged as a new machine learning setting. An FL system is comprised of a central parameter server and multiple local clients. It keeps data at local clients and learns a centralized model by sharing the model p

Samaneh Abbasi, Meysam Tavakoli, Hamid Reza Boveiri, Mohammad Amin Mosleh Shirazi

In medicine, image registration is vital in image-guided interventions and other clinical applications. However, it is a difficult subject to be addressed which by the advent of machine learning, there have been considerable progress in algorithmic performance has recently been achieved for medical image registration in this area. The implementation of deep

Aohan Li, Ikumi Urabe, Minoru Fujisawa, So Hasegawa

The number of IoT devices is predicted to reach 125 billion by 2023. The growth of IoT devices will intensify the collisions between devices, degrading communication performance. Selecting appropriate transmission parameters, such as channel and spreading factor (SF), can effectively reduce the collisions between long-range (LoRa) devices. However, most of t

Yijing Yang, Vasileios Magoulianitis, Xinyu Wang, C. -C. Jay Kuo

A statistical attention localization (SAL) method is proposed to facilitate the object classification task in this work. SAL consists of three steps: 1) preliminary attention window selection via decision statistics, 2) attention map refinement, and 3) rectangular attention region finalization. SAL computes soft-decision scores of local squared windows and u

Bing Zhou, Xiucai Huang, Yongduan Song

For uncertain multiple inputs multi-outputs (MIMO) nonlinear systems, it is nontrivial to achieve asymptotic tracking, and most existing methods normally demand certain controllability conditions that are rather restrictive or even impractical if unexpected actuator faults are involved. In this note, we present a method capable of achieving zero-error steady

Jason Olsthoorn, Alexis K. Kaminski, Daniel M. Robb

Most idealized studies of stratified shear instabilities assume that the shear interface and the buoyancy interface are coincident. We discuss the role of asymmetry on the evolution of shear instabilities. Using linear stability theory and direct numerical simulations, we show that asymmetric shear instabilities exhibit features of both Holmboe and Kelvin-He

Shijie Zhou, Zhimeng Guo, Charu Aggarwal, Xiang Zhang

Link prediction is an important task that has wide applications in various domains. However, the majority of existing link prediction approaches assume the given graph follows homophily assumption, and designs similarity-based heuristics or representation learning approaches to predict links. However, many real-world graphs are heterophilic graphs, where the

Shuchang Tao, Qi Cao, Huawei Shen, Yunfan Wu

Node injection attacks on Graph Neural Networks (GNNs) have received increasing attention recently, due to their ability to degrade GNN performance with high attack success rates. However, our study indicates that these attacks often fail in practical scenarios, since defense/detection methods can easily identify and remove the injected nodes. To address thi

Jiatong Shi, George Saon, David Haws, Shinji Watanabe

Beam search, which is the dominant ASR decoding algorithm for end-to-end models, generates tree-structured hypotheses. However, recent studies have shown that decoding with hypothesis merging can achieve a more efficient search with comparable or better performance. But, the full context in recurrent networks is not compatible with hypothesis merging. We pro

Zhijie Shen, Chunyu Lin, Lang Nie, Kang Liao

For a monocular 360 image, depth estimation is a challenging because the distortion increases along the latitude. To perceive the distortion, existing methods devote to designing a deep and complex network architecture. In this paper, we provide a new perspective that constructs an interpretable and sparse representation for a 360 image. Considering the impo

Jorge A. Zavala, Veronique Buat, Caitlin M. Casey, Denis Burgarella

Lyman Break Galaxy (LBG) candidates at z>10 are rapidly being identified in JWST/NIRCam observations. Due to the (redshifted) break produced by neutral hydrogen absorption of rest-frame UV photons, these sources are expected to drop out in the bluer filters while being well detected in redder filters. However, here we show that dust-enshrouded star-forming g

Shuming Shi, Enbo Zhao, Duyu Tang, Yan Wang

In this technical report, we introduce Effidit (Efficient and Intelligent Editing), a digital writing assistant that facilitates users to write higher-quality text more efficiently by using artificial intelligence (AI) technologies. Previous writing assistants typically provide the function of error checking (to detect and correct spelling and grammatical er

Angelina Aquino, Franz de Leon

The grammatical analysis of texts in any written language typically involves a number of basic processing tasks, such as tokenization, morphological tagging, and dependency parsing. State-of-the-art systems can achieve high accuracy on these tasks for languages with large datasets, but yield poor results for languages which have little to no annotated data.

Jun Wang, Mingfei Gao, Yuqian Hu, Ramprasaath R. Selvaraju

Text-VQA aims at answering questions that require understanding the textual cues in an image. Despite the great progress of existing Text-VQA methods, their performance suffers from insufficient human-labeled question-answer (QA) pairs. However, we observe that, in general, the scene text is not fully exploited in the existing datasets -- only a small portio

Rusheng Wang, Bo Chen, Zhongyao Hu, Li Yu

This paper studies the event-triggered distributed fusion estimation problems for a class of nonlinear networked multisensor fusion systems without noise statistical characteristics. When considering the limited resource problems of two kinds of communication channels (i.e., sensor-to-remote estimator channel and smart sensor-to-fusion center channel), an ev

David I. Warton

Residual plots are often used to interrogate regression model assumptions, but interpreting them requires an understanding of how much sampling variation to expect when assumptions are satisfied. In this paper, we propose constructing global envelopes around data (or around trends fitted to data) on residual plots, exploiting recent advances that enable cons

Meysam Tavakoli, Patrick Kelley

Diabetes Mellitus (DM) can lead to significant microvasculature disruptions that eventually causes diabetic retinopathy (DR), or complications in the eye due to diabetes. If left unchecked, this disease can increase over time and eventually cause complete vision loss. The general method to detect such optical developments is through examining the vessels, op

Olivier Guyon, Kyohoon Ahn, Masayuki Akiyama, Thayne Currie

Adaptive Optics projects at Subaru Telescope span a wide field of capabilities ranging from ground-layer adaptive optics (GLAO) providing partial correction over a 20 arcmin FOV to extreme adaptive optics (ExAO) for exoplanet imaging. We describe in this paper current and upcoming narrow field-of-view capabilities provided by the Subaru Extreme Adaptive Opti

Jae-Cheon Joo, Kang-Hyurk Lee

In this paper, we deal with a strongly pseudoconvex almost CR manifold with a CR contraction. We will prove that the stable manifold of the CR contaction is CR equivalent to the Heisenberg group model.

Ian Wagner

We define Jacobi forms with complex multiplication. Analogous to modular forms with complex multiplication, they are constructed from Hecke characters of the associated imaginary quadratic field. From this construction we obtain a Jacobi form which specializes to $\eta(\tau)^{26}$ which we present to highlight an open question of Dyson and Serre. We give oth

Olivier Guyon, Barnaby Norris, Marc-Antoine Martinod, Kyohoon Ahn

Speckle Noise is the dominant source of error in high contrast imaging with adaptive optics system. We discuss the potential for wavefront sensing telemetry to calibrate speckle noise with sufficient precision and accuracy so that it can be removed in post-processing of science images acquired by high contrast imaging instruments. In such a self-calibrating

Chengyuan Li, Meifu Li, Zhifang Qiu

During applying data-oriented diagnosis systems to distinguishing the type of and evaluating the severity of nuclear power plant initial events, it is of vital importance to decide which parameters to be used as the system input. However, although several diagnosis systems have already achieved acceptable performance in diagnosis precision and speed, hardly

Michael R. Geller

Any state r = (x,y,z) of a qubit, written in the Pauli basis and initialized in the pure state r = (0,0,1), can be prepared by composing three quantum operations: two unitary rotation gates to reach a pure state on the Bloch sphere, followed by a depolarization gate to decrease |r|. Here we discuss the complementary state-preparation protocol for qubits init

Ryogo Yamamoto, Kanji Tanaka

The use of relative attribute (e.g., beautiful, safe, convenient) -based image embeddings in visual place recognition, as a domain-adaptive compact image descriptor that is orthogonal to the typical approach of absolute attribute (e.g., color, shape, texture) -based image embeddings, is explored in this paper.

Takumi Sanno, Masahiko G. Yamada, Takeshi Mizushima, Satoshi Fujimoto

We propose the platform of a Yang-Lee anyon system which is constructed from Majorana bound states in topological superconductors. Yang-Lee anyons, described by the non-unitary conformal field theory with the central charge $c=-22/5$, are non-unitary counterparts of Fibonacci anyons, obeying the same fusion rule, but exhibiting non-unitary non-Abelian braidi

Pranav Sankhe, Seventy F. Hall, Melanie Sage, Maria Y. Rodriquez

Youth in the American foster care system are significantly more likely than their peers to face a number of negative life outcomes, from homelessness to incarceration. Administrative data on these youth have the potential to provide insights that can help identify ways to improve their path towards a better life. However, such data also suffer from a variety

Takayuki Myo, Kiyoshi Kato

We investigate the multineutron excitations of neutron-rich $^8$He in the electric dipole strength using a $^4$He+$n$+$n$+$n$+$n$ five-body model. Many-body unbound states of $^8$He are obtained in the complex scaling method. We found that the different excitation modes coexist in the dipole strength below the excitation energy of 20 MeV. The strength below

Worasait Suwannik

CycleGAN can be used to transfer an artistic style to an image. It does not require pairs of source and stylized images to train a model. Taking this advantage, we propose using randomly generated data to train a machine learning model that can transfer traditional art style to a black and white silhouette image. The result is noticeably better than the prev

Kensuke Nakamura, María Santos, Naomi Ehrich Leonard

This paper presents an algorithm for a team of mobile robots to simultaneously learn a spatial field over a domain and spatially distribute themselves to optimally cover it. Drawing from previous approaches that estimate the spatial field through a centralized Gaussian process, this work leverages the spatial structure of the coverage problem and presents a

Zongtang Wan, Yuqian Zhao, Jiabin Liu, Yuesheng Li

We report the first investigation of the electrical and magnetic properties of the triangular-lattice compound Zr$_2$NiP$_2$ (space group $P$6$_3$/$mmc$). The temperature evolution of electrical resistivity follows the Bloch-Gr\"uneisen-Mott law, and exhibits a typically metallic behavior. No transition is visible by both electrical and magnetic property mea

Shoichi Sato, Masaaki Tanaka, Ryosho Nakane

Department of Electrical Engineering and Information Systems, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan Center for Spintronics Research Network (CSRN), The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Ruancun Li, Luis C. Ho, Claudio Ricci, Benny Trakhtenbrot

Changing-look active galactic nuclei (AGNs) present an important laboratory to understand the origin and physical properties of the broad-line region (BLR). We investigate follow-up optical spectroscopy spanning $\sim 500$ days after the outburst of the changing-look AGN 1ES\,1927+654. The emission lines displayed dramatic, systematic variations in intensity

Carlos V. G. C. Lima, Vinicius F. dos Santos, João H. G. Sousa, Sebastián A. Urrutia

A strong geodetic set of a graph~$G=(V,E)$ is a vertex set~$S \subseteq V(G)$ in which it is possible to cover all the remaining vertices of~$V(G) \setminus S$ by assigning a unique shortest path between each vertex pair of~$S$. In the Strong Geodetic problem (SG) a graph~$G$ and a positive integer~$k$ are given as input and one has to decide whether~$G$ has

Frederico Fernandes Afonso Silva, Bruno Vilhena Adorno

When modeling complex robot systems such as branched robots, whose kinematic structures are a tree, current techniques often require modeling the whole structure from scratch, even when partial models for the branches are available. This paper proposes a systematic modular procedure for the dynamic modeling of branched robots comprising several subsystems, e

Elliot J. Carr, Luke P. Filippini

Calculating the thermal diffusivity of solid materials is commonly carried out using the laser flash experiment. This classical experiment considers a small (usually thin disc-shaped) sample of the material with parallel front and rear surfaces, applying a heat pulse to the front surface and recording the resulting rise in temperature over time on the rear s

Yoga Suhas Kuruba Manjunath, Sihao Zhao, Hatem Abou-zeid, Akram Bin Sediq

Class-of-service (CoS) network traffic classification (NTC) classifies a group of similar traffic applications. The CoS classification is advantageous in resource scheduling for Internet service providers and avoids the necessity of remodelling. Our goal is to find a robust, lightweight, and fast-converging CoS classifier that uses fewer data in modelling an

Matt Jacobs

In this paper, we construct global-in-time forward and backward Lagrangian flow maps along the pressure gradient generated by weak solutions of the Porous Media Equation. The main difficulty is that when the initial data has compact support, it is well-known that the pressure gradient is not a BV function. Thus, the theory of regular Lagrangian flows cannot

Gabriele Borg, Diego Gentile Passaro, Santiago Hermo

The recent rise of sub-national minimum wage (MW) policies in the US has resulted in significant dispersion of MW levels within urban areas. In this paper, we study the spillover effects of these policies on local rental markets through commuting. To do so, for each USPS ZIP code we construct a "workplace" MW measure based on the location of its resident's j

Iosif Pinelis

A necessary and suffcient condition for Pitman's asymptotic relative effciency (ARE) of the Kendall and Spearman correlation statistics for the independence test to be 1 is given, in terms of certain smoothness and nondegeneracy properties of the model. Corresponding easy to use and broadly applicable sufficient conditions are obtained, which are then illust

Keshav Kapoor, Si Xie, Joaquin Chung, Raju Valivarthi

We demonstrate a three-node quantum network for C-band photon pairs using 2 pairs of 59 km of deployed fiber between Fermi and Argonne National Laboratories. The C-band pairs are directed to nodes using a standard telecommunication switch and synchronized to picosecond-scale timing resolution using a coexisting O- or L-band optical clock distribution system.

S. Hubmann, G. Di Battista, I. A. Dmitriev, K. Watanabe

We report on observation of the infrared photoresistance of twisted bilayer graphene under continuous quantum cascade laser illumination at a frequency of 57.1 THz. The photoresistance shows an intricate sign-alternating behavior under variations of temperature and back gate voltage, and exhibits giant resonance-like enhancements at certain gate voltages. Th

Haruki Ide, Taka-aki Tanaka

We construct a complex entire function with arbitrary number of variables which has the following property: The infinite set consisting of all the values of all its partial derivatives of any orders at all algebraic points, including zero components, is algebraically independent. In Section 2 of this paper, we develop a new technique involving linear isomorp

Kamak Ebadi, Lukas Bernreiter, Harel Biggie, Gavin Catt

This paper reports on the state of the art in underground SLAM by discussing different SLAM strategies and results across six teams that participated in the three-year-long SubT competition. In particular, the paper has four main goals. First, we review the algorithms, architectures, and systems adopted by the teams; particular emphasis is put on lidar-centr

Victor Paredes, Ayonga Hereid

We present a framework to generate periodic trajectory references for a 3D under-actuated bipedal robot, using a linear inverted pendulum (LIP) based controller with adaptive neural regulation. We use the LIP template model to estimate the robot's center of mass (CoM) position and velocity at the end of the current step, and formulate a discrete controller t

Longfei Ma, Nan Cheng, Xiucheng Wang, Ruijin Sun

On-demand service provisioning is a critical yet challenging issue in 6G wireless communication networks, since emerging services have significantly diverse requirements and the network resources become increasingly heterogeneous and dynamic. In this paper, we study the on-demand wireless resource orchestration problem with the focus on the computing delay i

Kisun Lee

The package \texttt{NumericalCertification} implements methods for certifying numerical approximations of solutions for a given system of polynomial equations. For certifying regular solutions, the package implements Smale's $\alpha$-theory and Krawczyk method. For a singular solution, we implement soft verification using the iterative deflation method. We d

Brian Conrey, Brad Rodgers

We investigate averages of long Dirichlet polynomials twisted by Kronecker symbols and we compare our result with the recipe of [CFKRS]. We are able to compute these averages in the case that the length of the polynomial is a power less than 2 of the basic scaling parameter on the assumption of the Lindel\"of Hypothesis for $L$-functions of quadratic charact

S. Hernández-Gómez, S. Gherardini, A. Belenchia, A. Trombettoni

We report the experimental quantification of the contribution to non-equilibrium entropy production that stems from the quantum coherence content in the initial state of a qubit exposed to both coherent driving and dissipation. Our experimental demonstration builds on the exquisite experimental control of the spin state of a nitrogen-vacancy defect in diamon

Xiucheng Wang, Longfei Ma, Haocheng Li, Zhisheng Yin

Task scheduling is a critical problem when one user offloads multiple different tasks to the edge server. When a user has multiple tasks to offload and only one task can be transmitted to server at a time, while server processes tasks according to the transmission order, the problem is NP-hard. However, it is difficult for traditional optimization methods to

Chase Stokes, Vidya Setlur, Bridget Cogley, Arvind Satyanarayan

While visualizations are an effective way to represent insights about information, they rarely stand alone. When designing a visualization, text is often added to provide additional context and guidance for the reader. However, there is little experimental evidence to guide designers as to what is the right amount of text to show within a chart, what its qua

James Noeckel, Benjamin T. Jones, Karl Willis, Brian Curless

We describe our work on inferring the degrees of freedom between mated parts in mechanical assemblies using deep learning on CAD representations. We train our model using a large dataset of real-world mechanical assemblies consisting of CAD parts and mates joining them together. We present methods for re-defining these mates to make them better reflect the m

Uriya A. First, Tali Kaufman

We expose a strong connection between good $2$-query locally testable codes (LTCs) and high dimensional expanders. Here, an LTC is called good if it has constant rate and linear distance. Our emphasis in this work is on LTCs testable with only $2$ queries, which are of particular interest to theoretical computer science. This is done by introducing a new obj

Seyyed Shaho Alaviani, Atul Gajanan Kelkar, Umesh Vaidya

This paper aims at proposing a procedure to derive distributed algorithms for distributed consensus-based optimization by using distributed algorithms for network resource allocation and vice versa over switching networks with/without synchronous protocol. It is shown that first-order gradient distributed consensus-based optimization algorithms can be used f

Uriya A. First, Tali Kaufman

The Cheeger constant of a graph, or equivalently its coboundary expansion, quantifies the expansion of the graph. This notion assumes an implicit choice of a coefficient group, namely, $\mathbb{F}_2$. In this paper, we study Cheeger-type inequalities for graphs endowed with a generalized coefficient group, called a sheaf; this is motivated by applications to

Kazuhiro Horihata

This paper presents a new partial differential equation to build Brakke's motion, which is a weak notion of mean curvature flow. We call the equation a modified Allen-Cahn equation abbreviated to MAC. After that we introduce its benefit: An improved estimate on the discrepant energy that means the equipartition of the first energy. This equation is obtained

Qijin Chen, Zhiqiang Wang, Rufus Boyack, Shuolong Yang

New developments in superconductivity, particularly through unexpected and often astonishing forms of superconducting materials, continue to excite the community and stimulate theory. It is now becoming clear that there are two distinct platforms for superconductivity: natural and synthetic materials. The study of these artificial materials has greatly expan

Yotto Koga, Heather Kerrick, Sachin Chitta

We introduce a robotic assembly system that streamlines the design-to-make workflow for going from a CAD model of a product assembly to a fully programmed and adaptive assembly process. Our system captures (in the CAD tool) the intent of the assembly process for a specific robotic workcell and generates a recipe of task-level instructions. By integrating vis

Georgia Shay, Justin Solomon, Oded Stein

UV parameterization is a core task in computer graphics, with applications in mesh texturing, remeshing, mesh repair, mesh editing, and more. It is thus an active area of research, which has led to a wide variety of parameterization methods that excel according to different measures of quality. There is no single metric capturing parameterization quality in

Chen-Kai Qiao

In a recent work PRD 106, L021501 (2022), a new geometric approach is proposed to obtain the photon sphere (circular photon orbit) and the black hole shadow radius. In this approach, photon spheres and the black hole shadow radius are determined using geodesic curvature and Gaussian curvature in the optical geometry of black hole spacetimes. However, the cal

Waixiang Cao, Chunmei Wang, Junping Wang

This paper presents a new $L^p$-primal-dual weak Galerkin (PDWG) finite element method for the div-curl system with the normal boundary condition for $p>1$. Two crucial features for the proposed $L^p$-PDWG finite element scheme are as follows: (1) it offers an accurate and reliable numerical solution to the div-curl system under the low $W^{\alpha, p}$-regul

Ibrahim H. Ahmed, Cillian Brewitt, Ignacio Carlucho, Filippos Christianos

The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Towards this goal, the Autonomous Agents Research Group develops novel machine learning algorithms for autonomous systems control, with a specific focus on deep reinforcement learning

S. A. Osorio, A. Athanasopoulos, V. Laliena, J. Campo

Spin polarized currents originate a spin-transfer torque that enables the manipulation of magnetic textures. Here we theoretically study the effect of a spin-polarized current on the magnetic texture corresponding to a chiral soliton lattice in a monoaxial helimagnet under a transverse magnetic field. At sufficiently small current density the chiral soliton

Stanley Rabinowitz, Ercole Suppa

Let P be a point inside a convex quadrilateral ABCD. The lines from P to the vertices of the quadrilateral divide the quadrilateral into four triangles. If we locate a triangle center in each of these triangles, the four triangle centers form another quadrilateral called a central quadrilateral. For each of various shaped quadrilaterals, and each of 1000 dif

Adrià Canós Valero, Dmitrii Borovkov, Mikhail Sidorenko, Pavel Dergachev

Multipoles are paramount for describing electromagnetic fields in many areas of nanoscale optics, playing an essential role for the design of devices in plasmonics and all-dielectric nanophotonics. Challenging the traditional division into electric and magnetic moments, toroidal moments have been proposed as a physically distinct family of multipoles with si

Michael Hutchings

In a previous paper, we defined an "elementary" alternative to the ECH capacities of symplectic four-manifolds, using max-min energy of holomorphic curves subject to point constraints, and avoiding the use of Seiberg-Witten theory. In the present paper we use a variant of this construction to define an alternative to the ECH spectrum of a contact three-manif

H. L. Iglesias, J. Lange, I. Bartos, S. Bhaumik

The detection of orbital eccentricity for a binary black hole system via gravitational waves is a key signature to distinguish between the possible binary origins. The identification of eccentricity has been difficult so far due to the limited availability of eccentric gravitational waveforms over the full range of black hole masses and eccentricities. Here

Samuel R. Hedemann

We prove that all states (mixed or pure) of qubit-qutrit ($2\times 3$) systems have entanglement-preserving unitary (EPU) equivalence to a compact subset of true-generalized X (TGX) states called EPU-minimal TGX states which we give explicitly. Thus, for any spectrum-entanglement combination achievable by general states, there exists an EPU-minimal TGX state

Jennifer Head, Dianne P. O'Leary

In June 1965, Sister Mary Kenneth Keller, BVM, received the first US PhD in Computer Science, and this paper outlines her life and accomplishments. As a scholar, she has the distinction of being an early advocate of learning-by-example in artificial intelligence. Her main scholarly contribution was in shaping computer science education in high schools and sm

Matthew Farkas, Bernard Deconinck

We consider the heat equation with spatially variable thermal conductivity and homogeneous Dirichlet boundary conditions. Using the Method of Fokas or Unified Transform Method, we derive solution representations as the limit of solutions of constant-coefficient interface problems where the number of subdomains and interfaces becomes unbounded. This produces

Maryam Akhavin, Abbas Nasrollah Nejad

In this paper, we introduce the notion of relation type of analytic and formal algebras and prove that it is well-defined and invariant by describing this notion in terms of the Andr\'e-Quillen homology and using the Jacobi-Zariski long exact sequence of homology. In particular, the relation type is an invariant of schemes of finite type over a field, analyt

Zongwei Wu, Shriarulmozhivarman Gobichettipalayam, Brahim Tamadazte, Guillaume Allibert

Efficiently exploiting multi-modal inputs for accurate RGB-D saliency detection is a topic of high interest. Most existing works leverage cross-modal interactions to fuse the two streams of RGB-D for intermediate features' enhancement. In this process, a practical aspect of the low quality of the available depths has not been fully considered yet. In this wo

Etinosa Ekomwenrenren, John Simpson-Porco, Evangelos Farantatos, Mahendra Patel

We develop and test a data-driven and area-based fast frequency control scheme, which rapidly redispatches inverter-based resources to compensate for local power imbalances within the bulk power system. The approach requires no explicit system model information, relying only on historical measurement sequences for the computation of control actions. Our tech

C. Augier, G. Baulieu, V. Belov, L. Berge

The future Ricochet experiment aims at searching for new physics in the electroweak sector by providing a high precision measurement of the Coherent Elastic Neutrino-Nucleus Scattering (CENNS) process down to the sub-100 eV nuclear recoil energy range. The experiment will deploy a kg-scale low-energy-threshold detector array combining Ge and Zn target crysta

Roberto Bramati, Angela Pasquale, Tomasz Przebinda

Let $(G,G')$ be a reductive dual pair in $Sp(W)$ with rank $G\leq$ rank $G'$ and $G'$ semisimple. The image of the Casimir element of the universal enveloping algebra of $G'$ under the Weil representation $\omega$ is a Capelli operator. It is a hermitian operator acting on the smooth vectors of the representation space of $\omega$. We compute the resonances

Yuan-Hang Zhang, Massimiliano Di Ventra

Inspired by the advancements in large language models based on transformers, we introduce the transformer quantum state (TQS): a versatile machine learning model for quantum many-body problems. In sharp contrast to Hamiltonian/task specific models, TQS can generate the entire phase diagram, predict field strengths with experimental measurements, and transfer

Ruibo Wang, Anna Talgat, Mustafa A. Kishk, Mohamed-Slim Alouini

This letter characterizes the contact angle distribution based on the condition that the relay low earth orbit (LEO) satellite is in the communication range of both the ground transmitter and the ground receiver. As one of the core distributions in stochastic geometry-based routing analysis, the analytical expression of the \ac{CDF} of the conditional contac

James M. Goff, Charles Sievers, Mitchell A. Wood, Aidan P. Thompson

Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These

Dhanasekar Sundararaman, Vivek Subramanian

Biases in culture, gender, ethnicity, etc. have existed for decades and have affected many areas of human social interaction. These biases have been shown to impact machine learning (ML) models, and for natural language processing (NLP), this can have severe consequences for downstream tasks. Mitigating gender bias in information retrieval (IR) is important

Satoru Hayami, Hiroaki Kusunose

We theoretically investigate an antiferromagnetic structure in a hexagonal zigzag-chain compound Ce$_3$TiBi$_5$, which shows a linear magnetoelectric effect in metals and an unfamiliar temperature dependence of magnetic susceptibility. We find a partial magnetic order as a coexistence of a nonmagnetic zigzag chain and staggered antiferromagnetic zigzag chain

Edward Fish, Jon Weinbren, Andrew Gilbert

Pure vision transformer architectures are highly effective for short video classification and action recognition tasks. However, due to the quadratic complexity of self attention and lack of inductive bias, transformers are resource intensive and suffer from data inefficiencies. Long form video understanding tasks amplify data and memory efficiency problems

Ardeshir Shojaeinasab, Masoud Jalayer, Homayoun Najjaran

A comprehensive literature review has always been an essential first step of every meaningful research. In recent years, however, the availability of a vast amount of information in both open-access and subscription-based literature in every field has made it difficult, if not impossible, to be certain about the comprehensiveness of one's survey. This subseq

Levi C. Felix, Alexandre F. Fonseca, Douglas S. Galvao

In this work, we investigated the effect of knots in the thermal transport of graphene nanoribbons through non-equilibrium molecular dynamics simulations. We considered the cases of one, two, and three knots are present. Temperature jumps appear in the temperature profile where the knots are located, which indicates that they introduce thermal resistances in

Ali Muhammad, Mohamed Elhattab, Mohamed Amine Arfaoui, Chadi Assi

This paper investigates the benefits of integrating multiple reconfigurable intelligent surfaces (RISs) in enhancing the timeliness performance of uplink Internet-of-Things (IoT) network, where IoT devices (IoTDs) upload their time-stamped status update information to a base station (BS) using non-orthogonal multiple access (NOMA). Accounting to the potentia

Jackson Loper, Jeffrey Regier

In high-throughput screenings, it is common to estimate the effects of many treatments using a small number of independent trials of each. Because little is known about the distributional properties of the measurements from these trials, it is challenging to identify plausible assumptions that can serve as a basis for inferential statistics in this setting.

Vishrant Tripathi, Eytan Modiano

We develop a simple model for the timely monitoring of correlated sources over a wireless network. Using this model, we study how to optimize weighted-sum average Age of Information (AoI) in the presence of correlation. First, we discuss how to find optimal stationary randomized policies and show that they are at-most a factor of two away from optimal polici

Kirill Mosievich

Conditions sufficient for the transience of the process have been established for the Markov diffusion model with switching and two modes, transient and ergodic, with intensities bounded away from zero. This paper shows limitations on the conditions for exponential ergodicity with a given switching system.

Han Zhang, Hao Zhou, Melike Erol-Kantarci

Recently, open radio access network (O-RAN) has become a promising technology to provide an open environment for network vendors and operators. Coordinating the x-applications (xAPPs) is critical to increase flexibility and guarantee high overall network performance in O-RAN. Meanwhile, federated reinforcement learning has been proposed as a promising techni

A. W. Shaw, J. M. Miller, V. Grinberg, D. J. K. Buisson

We observed the Galactic black hole X-ray binary V4641 Sgr with the high resolution transmission gratings on Chandra during the source's 2020 outburst. Over two epochs of Chandra gratings observations, we see numerous highly ionized metal lines, superimposed on a hot, disc-dominated X-ray continuum. The measured inner disc temperatures and luminosities imply