April 2023 arXiv papers — page 148

Yuxin Xue, Yige Peng, Lei Bi, Dagan Feng

Positron emission tomography (PET) is the most sensitive molecular imaging modality routinely applied in our modern healthcare. High radioactivity caused by the injected tracer dose is a major concern in PET imaging and limits its clinical applications. However, reducing the dose leads to inadequate image quality for diagnostic practice. Motivated by the nee

Sioree Ansar, Sandeep Kumar Kataria, Mousumi Das

Dark matter (DM) halo properties are extensively studied in cosmological simulations but are very challenging to estimate from observations. The DM halo density profile of observed galaxies is modelled using multiple probes that trace the dark matter potential. However, the angular momentum distribution of DM halos is still a subject of debate. In this study

Yi Chen, Rui Wang, Haiyun Jiang, Shuming Shi

Evaluating the quality of generated text is a challenging task in NLP, due to the inherent complexity and diversity of text. Recently, large language models (LLMs) have garnered significant attention due to their impressive performance in various tasks. Therefore, we present this paper to investigate the effectiveness of LLMs, especially ChatGPT, and explore

Yu-Xiang Zhang

To build up a collective emission, the atoms in an ensemble must coordinate their behavior by exchanging virtual photons. We study this non-Markovian process in a subwavelength atom chain coupled to a one-dimensional (1D) waveguide and find that retardation is not the only cause of non-Markovianity. The other factor is the memory of the photonic environment,

Chengxi Li, Gang Li, Zhuoyue Wang, Xueqian Wang

In this paper, we consider the problem of change detection (CD) with two heterogeneous remote sensing (RS) images. For this problem, an unsupervised change detection method has been proposed recently based on the image translation technique of Cycle-Consistent Adversarial Networks (CycleGANs), where one image is translated from its original modality to the m

Nikhil Potu Surya Prakash, Joohwan Seo, Alexander Rose, Roberto Horowitz

In this paper, we present a frequency domain data-driven feedback control design methodology for the design of tracking controllers for hard disk drives with two-stage actuator as a part of the open invited track 'Benchmark Problem on Control System Design of Hard Disk Drive with a Dual-Stage Actuator' in the IFAC World Congress 2023 (Yokohoma, Japan). The b

Jaeyoo Park, Bohyung Han

We propose a visual-linguistic representation learning approach within a self-supervised learning framework by introducing a new operation, loss, and data augmentation strategy. First, we generate diverse features for the image-text matching (ITM) task via soft-masking the regions in an image, which are most relevant to a certain word in the corresponding ca

Ross J. Turner, Jared C. Magyar, Sue Cook, Anya M. Reading

The field of ice sheet, ice shelf and glacier-related seismology, cryoseismology, has seen rapid development in recent years. As concern grows for the implications of change in the great ice sheets of Greenland and Antarctica, so instrument advances and international field programs have expanded the availability of passive seismic datasets that contain recor

Xin Yao, Ziqing Yang, Yiming Cui, Shijin Wang

In natural language processing, pre-trained language models have become essential infrastructures. However, these models often suffer from issues such as large size, long inference time, and challenging deployment. Moreover, most mainstream pre-trained models focus on English, and there are insufficient studies on small Chinese pre-trained models. In this pa

Yongtao Li, Lihua Feng, Yuejian Peng

A theorem of Nosal and Nikiforov states that if $G$ is a triangle-free graph with $m$ edges, then $\lambda (G)\le \sqrt{m}$, where the equality holds if and only if $G$ is a complete bipartite graph. A well-known spectral conjecture of Bollob\'{a}s and Nikiforov [J. Combin. Theory Ser. B 97 (2007)] asserts that if $G$ is a $K_{r+1}$-free graph with $m$ edges

Kyoungmin Kim, Jaehyun Ha, George Fletcher, Wook-Shin Han

We propose a new method for estimating the number of answers OUT of a small join query Q in a large database D, and for uniform sampling over joins. Our method is the first to satisfy all the following statements. - Support arbitrary Q, which can be either acyclic or cyclic, and contain binary and non-binary relations. - Guarantee an arbitrary small error wi

Tian Huey Teh, Vivian Hu, Devang S Ram Mohan, Zack Hodari

Generating expressive speech with rich and varied prosody continues to be a challenge for Text-to-Speech. Most efforts have focused on sophisticated neural architectures intended to better model the data distribution. Yet, in evaluations it is generally found that no single model is preferred for all input texts. This suggests an approach that has rarely bee

Jonathan Cook, Sabih ur Rehman, M. Arif Khan

The growth in the use of small sensor devices, commonly known as the Internet of Things (IoT), has resulted in unprecedented amounts of data being generated and captured. With the rapidly growing popularity of personal IoT devices, the collection of personal data through such devices has also increased exponentially. To accommodate the anticipated growth in

Aldo Conca, Simone Naldi, Giorgio Ottaviani, Bernd Sturmfels

A Taylor variety consists of all fixed order Taylor polynomials of rational functions, where the number of variables and degrees of numerators and denominators are fixed. In one variable, Taylor varieties are given by rank constraints on Hankel matrices. Inversion of the natural parametrization is known as Pad\'e approximation. We study the dimension and def

Tapaswini Patro, Kaushiki Mukherjee, Nirman Ganguly

Environmental interactions are ubiquitous in any real-world application of a quantum information processing protocol. Such interactions result in depletion of quantum resources. Two important figure of merits in the context of quantum information are the fully entangled fraction (FEF) and conditional entropy of a composite quantum system. FEF has a key role

David Lovitz

The Yang-Baxter equation and it's various forms have applications in many fields, including statistical mechanics, knot theory, and quantum information. Unitary solutions of the braided Yang-Baxter equation are of particular interest as quantum gates for topological quantum computers. We demonstrate a simple construction for solutions in any dimension, which

Xu Tan, Jiawei Yang, Junqi Chen, Sylwan Rahardja

AutoEncoders (AEs) are commonly used for machine learning tasks due to their intrinsic learning ability. This unique characteristic can be capitalized for Outlier Detection (OD). However conventional AE-based methods face the issue of overconfident decisions and unexpected reconstruction results of outliers, limiting their performance in OD. To mitigate thes

Jingkai Yang, Qiwen Ran, Hongyu Wu, Jing Ma

With the development of the massive satellite constellation and the on-orbit laser-based communication equipment, the wavelength routing optical satellite network (WROSN) becomes a potential solution for on-orbit, high-capacity, and high-speed communication. Since the inter-satellite links (ISLs) are time-varying, one of the fundamental considerations in the

Krishnakumar Balasubramanian, Promit Ghosal, Ye He

We derive high-dimensional scaling limits and fluctuations for the online least-squares Stochastic Gradient Descent (SGD) algorithm by taking the properties of the data generating model explicitly into consideration. Our approach treats the SGD iterates as an interacting particle system, where the expected interaction is characterized by the covariance struc

Ping Cheng, Rong Wei, Tusheng Zhang

In this paper, we prove a large deviation principle for the empirical measures of a system of weakly interacting diffusion with reflection. We adopt the weak convergence approach. To make this approach work, we show that the sequence of empirical measures of the controlled reflected system will converge to the weak solution of an associated reflected McKean-

Zhibin Zhou, Junnan Yu

Through systematically analyzing the literature on designing AI-based technologies, we extracted design implications and synthesized them into a generic human-centered design framework for AI technologies to better support human needs and mitigate their concerns. When adapting the framework to children's context, understanding their specific needs, behaviors

Sunao Sugiyama, Hironao Miyatake, Surhud More, Xiangchong Li

We present cosmological parameter constraints from a blind joint analysis of three two-point correlation functions measured from the Year 3 Hyper Suprime-Cam (HSC-Y3) imaging data, covering 416 deg$^2$, and the SDSS DR11 spectroscopic galaxies spanning the redshift range $[0.15, 0.70]$. We subdivide the SDSS galaxies into three volume-limited samples separat

Hironao Miyatake, Sunao Sugiyama, Masahiro Takada, Takahiro Nishimichi

We present cosmology results from a blinded joint analysis of cosmic shear, $\xi_{\pm}(\vartheta)$, galaxy-galaxy weak lensing, $\Delta\!\Sigma(R)$, and projected galaxy clustering, $w_{\rm p}(R)$, measured from the Hyper Suprime-Cam three-year (HSC-Y3) shape catalog and the Sloan Digital Sky Survey (SDSS) DR11 spectroscopic galaxy catalog - a 3$\times$2pt c

Surhud More, Sunao Sugiyama, Hironao Miyatake, Markus Michael Rau

We use the Sloan Digital Sky Survey (SDSS) BOSS galaxies and their overlap with approximately 416 sq. degree of deep $grizy$-band imaging from the Subaru Hyper Suprime-Cam Survey (HSC). We measure three two-point correlations that form the basis of the cosmological inference presented in our companion papers, Miyatake et al. and Sugiyama et al. We use three

Xiangchong Li, Tianqing Zhang, Sunao Sugiyama, Roohi Dalal

We perform a blinded cosmology analysis with cosmic shear two-point correlation functions (2PCFs) measured from more than 25 million galaxies in the Hyper Suprime-Cam three-year shear catalog in four tomographic redshift bins ranging from 0.3 to 1.5. After conservative masking and galaxy selection, the survey covers 416 deg$^2$ of the northern sky with an ef

Roohi Dalal, Xiangchong Li, Andrina Nicola, Joe Zuntz

We measure weak lensing cosmic shear power spectra from the three-year galaxy shear catalog of the Hyper Suprime-Cam (HSC) Subaru Strategic Program imaging survey. The shear catalog covers $416 \ \mathrm{deg}^2$ of the northern sky, with a mean $i$-band seeing of 0.59 arcsec and an effective galaxy number density of 15 $\mathrm{arcmin}^{-2}$ within our adopt

Ankang Liu, Alexander M. Finkel'stein

We develop a description of spin waves in a $3D$ quantum $XY$ antiferromagnet (AFM) in terms of macroscopic variables, magnetization and N\'eel vector densities. We consider a layered AFM with spins located on the honeycomb lattice. In the discussed system, the spectrum of spin waves consists of four modes, all well captured by our macroscopic description. T

Sergei Gukov, Ludmil Katzarkov, Josef Svoboda

We study quantum $q$-series invariants of 3-manifolds $\widehat{Z}_\sigma$ of Gukov-Pei-Putrov-Vafa, using techniques from the theory of normal surface singularities such as splice diagrams. We show that the (suitably normalized) sum of all $\widehat{Z}_\sigma$ depends only on the splice diagram, and in particular, it agrees for manifolds with the same unive

Cheng Yang, Xumeng Gong, Chuan Shi, Philip S. Yu

Recent years have witnessed the success of heterogeneous graph neural networks (HGNNs) in modeling heterogeneous information networks (HINs). In this paper, we focus on the benchmark task of HGNNs, i.e., node classification, and empirically find that typical HGNNs are not good at predicting the label of a test node whose receptive field (1) has few training

Xin Zhang, Yuqi Song, Xiaofeng Wang, Fei Zuo

Convolutional neural networks (CNNs) have been widely applied in many safety-critical domains, such as autonomous driving and medical diagnosis. However, concerns have been raised with respect to the trustworthiness of these models: The standard testing method evaluates the performance of a model on a test set, while low-quality and insufficient test sets ca

Aniket Dashpute, Vishwanath Saragadam, Emma Alexander, Florian Willomitzer

Robust and non-destructive material classification is a challenging but crucial first-step in numerous vision applications. We propose a physics-guided material classification framework that relies on thermal properties of the object. Our key observation is that the rate of heating and cooling of an object depends on the unique intrinsic properties of the ma

Jiawang Nie, Jane J. Ye, Suhan Zhong

This paper studies bilevel polynomial optimization in which lower-level constraint functions depend linearly on lower-level variables. We show that such bilevel program can be reformulated as a disjunctive program by using Karush-Kuhn-Tucker (KKT) conditions with a sparse type of Lagrange multipliers. This kind of Lagrange multipliers can be conveniently rep

Kanghong Shi, Ian R. Petersen, Igor G. Vladimirov

In this paper, we extend nonlinear negative imaginary (NI) systems theory to switched systems. Switched nonlinear NI systems and switched nonlinear output strictly negative imaginary (OSNI) systems are defined. We show that the interconnection of two switched nonlinear NI systems is still switched nonlinear NI. The interconnection of a switched nonlinear NI

Pedram Rabiee, Jesse B. Hoagg

This paper presents a new control approach for guaranteed safety (remaining in a safe set) subject to actuator constraints (the control is in a convex polytope). The control signals are computed using real-time optimization, including linear and quadratic programs subject to affine constraints, which are shown to be feasible. The control method relies on a n

Sheng Zhang, Yongwei Cui, Shunjia Wang, Haoran Chen

Precise and ultrafast control over photo-induced charge currents across nanoscale interfaces could lead to important applications in energy harvesting, ultrafast electronics, and coherent terahertz sources. Recent studies have shown that several relativistic mechanisms, including inverse spin-Hall effect, inverse Rashba-Edelstein effect and inverse spin-orbi

Kate Qi Zhou, Yan Qin, Chau Yuen

Lithium-ion batteries (LiBs) degrade slightly until the knee onset, after which the deterioration accelerates to end of life (EOL). The knee onset, which marks the initiation of the accelerated degradation rate, is crucial in providing an early warning of the battery's performance changes. However, there is only limited literature on online knee onset identi

Aoran Xiao, Jiaxing Huang, Weihao Xuan, Ruijie Ren

Robust point cloud parsing under all-weather conditions is crucial to level-5 autonomy in autonomous driving. However, how to learn a universal 3D semantic segmentation (3DSS) model is largely neglected as most existing benchmarks are dominated by point clouds captured under normal weather. We introduce SemanticSTF, an adverse-weather point cloud dataset tha

Takahiro Shindo, Taiju Watanabe, Kein Yamada, Hiroshi Watanabe

With advances in image recognition technology based on deep learning, automatic video analysis by Artificial Intelligence is becoming more widespread. As the amount of video used for image recognition increases, efficient compression methods for such video data are necessary. In general, when the image quality deteriorates due to image encoding, the image re

William M. Campbell, Michael E. Tobar, Serge Galliou, Maxim Goryachev

Many theories that attempt to formulate a quantum description of gravity suggest the existence of a fundamental minimum length scale. A popular method for incorporating this minimum length is through a modification of the Heisenberg uncertainty principle known as the generalised uncertainty principle (GUP). Experimental tests of the GUP applied to composite

Jeffrey Lu

We revisit the original hawk-dove game with slight modifications to payoff values while maintaining the fundamental principles of interaction. The practical robustness of the theoretical tools of game theory is tested on a simulated population of hawks and doves with varying initial population distributions and peak growth rates. Additionally, we aim to find

Zihao Li, Aixin Sun, Chenliang Li

Mainstream solutions to Sequential Recommendation (SR) represent items with fixed vectors. These vectors have limited capability in capturing items' latent aspects and users' diverse preferences. As a new generative paradigm, Diffusion models have achieved excellent performance in areas like computer vision and natural language processing. To our understandi

Jingyi Zhang, Jiaxing Huang, Sheng Jin, Shijian Lu

Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition paradigm. To address the two challenges, Vision-Language Models (VLMs) have been intensively investigated recently, whic

Ciro M. Diniz, Rogerio J. de Assis, Norton G. de Almeida, Celso J. Villas-Boas

Many quantum algorithms demand a large number of repetitions to obtain reliable statistical results. Thus, at each repetition it is necessary to reset the qubits efficiently and precisely in the shortest possible time, so that quantum computers actually have advantages over classical ones. In this work, we perform a detailed analysis on three different model

Lijun Zhu

Magnetic materials with strong perpendicular magnetic anisotropy are of great interest for the development of nonvolatile magnetic memory and computing technologies due to their high stabilities at the nanoscale. However, electrical switching of such perpendicular magnetization in an energy-efficient, deterministic, scalable manner has remained a big challen

Efstratia Kalfagianni, Joseph M. Melby

We use Dehn surgery methods to construct infinite families of hyperbolic knots in the 3-sphere satisfying a weak form of the Turaev--Viro invariants volume conjecture. The results have applications to a conjecture of Andersen, Masbaum, and Ueno about quantum representations of surface mapping class groups. We obtain an explicit family of pseudo-Anosov mappin

Satoru Hayami, Kazumasa Hattori

We investigate a mechanism of multiple-$q$ states consisting of magnetic dipole and electric quadrupole degrees of freedom in spin-1 triangular-lattice systems. By systematically analyzing a minimal effective multipole model with bilinear multipole-multipole interactions in momentum space on a triangular lattice, we find minimum conditions of multipole inter

Qingtian Miao, G. S. Agarwal

The ultrastrong coupling between the elementary excitations of matter and microcavity modes is studied in a fully analytical quantum-mechanical theoretical framework. The elementary excitation could be phonons, excitons, plasmons, etc. From the diagonalization of the Hamiltonian, we obtain the ground state of the polariton Hamiltonian. The ground state belon

Josh Kirklin

I discuss some general information-theoretic properties of quantum mechanical probes in semiclassical gravity: their purview, i.e. what they can see and act on (in terms of a generalised entanglement wedge), their spontaneous evaporation into a cloud of highly entropic particles when one tries to make them see too much (perhaps a parable on the dangers of st

Rui Wang

This paper studies semiparametric identification of substitution and complementarity patterns between two goods using a panel multinomial choice model with bundles. The model allows the two goods to be either substitutes or complements and admits heterogeneous complementarity through observed characteristics. I first provide testable implications for the com

Minh Nguyen, Jacob Gately, Swati Kar, Soumyabrata Dey

In order to satisfy diverse quality-of-service (QoS) requirements of complex real-time video applications, civilian and tactical use cases are employing software-defined hybrid edge-cloud systems. One of the primary QoS requirements of such applications is ultra-low end-to-end latency for video applications that necessitates rapid frame transfer between end-

Zilin Huang, Sikai Chen, Yuzhuang Pian, Zihao Sheng

An accurate and robust localization system is crucial for autonomous vehicles (AVs) to enable safe driving in urban scenes. While existing global navigation satellite system (GNSS)-based methods are effective at locating vehicles in open-sky regions, achieving high-accuracy positioning in urban canyons such as lower layers of multi-layer bridges, streets bes

Haoyue Zhang, Peng Xu, Zongqi Ye, Dong Ye

High-precision inertial sensors or accelerometers can provide us references of free-falling motions in gravitational field in space. They serve as the key payloads for gravity recovery missions such as the CHAMP, the GRACE-type missions, and the planned Next Generation Gravity Missions. In this work, a systematic method of electrostatic inertial sensor calib

F. D. Moyano, P. Eggenberger, S. J. A. J. Salmon, J. S. G. Mombarg

Context. Asteroseismic studies showed that cores of post main-sequence stars rotate slower than theoretically predicted by stellar models with purely hydrodynamical transport processes. Recent studies on main sequence stars, particularly Gamma Doradus ($\gamma$ Dor) stars, revealed their internal rotation rate for hundreds of stars, offering a counterpart on

Saumya Y. Sahai, Jing Liu, Thejaswi Muniyappa, Kanthashree M. Sathyendra

We present dual-attention neural biasing, an architecture designed to boost Wake Words (WW) recognition and improve inference time latency on speech recognition tasks. This architecture enables a dynamic switch for its runtime compute paths by exploiting WW spotting to select which branch of its attention networks to execute for an input audio frame. With th

Fan-Yun Sun, Jonathan Tremblay, Valts Blukis, Kevin Lin

We propose Filtering Inversion (FINV), a learning framework and optimization process that predicts a renderable 3D object representation from one or few partial views. FINV addresses the challenge of synthesizing novel views of objects from partial observations, spanning cases where the object is not entirely in view, is partially occluded, or is only observ

Osamu Fujino, Taro Fujisawa

We discuss variations of mixed Hodge structure arising from projective morphisms of complex analytic spaces. Then we treat generalizations of Koll\'ar's torsion-free theorem, vanishing theorem, and so on, for reducible complex analytic spaces as an application. The results will play a crucial role in the theory of minimal models for projective morphisms betw

Wenhui Du, Kaiying Dou, Ying Dai, Baibiao Huang

Magnetic skyrmions in two-dimensional lattice are a prominent topic of condensed matter physics and material science. Current research efforts in this field are exclusively constrained to Neel-type and antiskyrmion, while Bloch-type magnetic skyrmions are rarely explored. Here, we report the discovery of Bloch-type magnetic skyrmions in two-dimensional latti

Youngseok Kim, Juyeb Shin, Sanmin Kim, In-Jae Lee

Autonomous driving requires an accurate and fast 3D perception system that includes 3D object detection, tracking, and segmentation. Although recent low-cost camera-based approaches have shown promising results, they are susceptible to poor illumination or bad weather conditions and have a large localization error. Hence, fusing camera with low-cost radar, w

Sina Baghali, Julio Deride, Yueyue Fan, Zhaomiao Guo

This paper presents a network-based multi-agent optimization model for the strategic planning of service facilities in a stochastic and competitive market. We focus on the type of service facilities that are of intermediate nature, i.e., users may need to deviate from the shortest path to receive/provide services in between the users' planned origins and des

Weijie Li, Wei Yang, Li Liu, Wenpeng Zhang

In recent years, deep learning has been widely used in SAR ATR and achieved excellent performance on the MSTAR dataset. However, due to constrained imaging conditions, MSTAR has data biases such as background correlation, i.e., background clutter properties have a spurious correlation with target classes. Deep learning can overfit clutter to reduce training

Shi Jin, Nana Liu, Xiantao Li, Yue Yu

Quantum dynamics, typically expressed in the form of a time-dependent Schr\"odinger equation with a Hermitian Hamiltonian, is a natural application for quantum computing. However, when simulating quantum dynamics that involves the emission of electrons, it is necessary to use artificial boundary conditions (ABC) to confine the computation within a fixed doma

Bruno Alexandre, Raymond Isichei, João Magueijo

It is remarkably difficult to reconcile unitary and Vilenkin's wave function. For example, the natural conserved inner product found in quantum unimodular gravity applies to the Hartle-Hawking wave function, but fails for its Vilenkin counterpart. We diagnose this failure from different angles (Laplace transform instead of Fourier transform, non-Hermiticity

Gao Jun Wu, Sanjiva K. Lele, Jinah Jeun

Screech resonance is studied with experimentally validated large-eddy simulation data for a 4:1 rectangular under-expanded jet at three nozzle pressure ratios. The analysis uses spectral proper orthogonal decomposition (SPOD) and spatial cross correlation to characterize the oppositely-traveling waves in the jet at the screech fundamental frequency. The resu

Hadi Eskandari, Michael Bewong, Sabih ur Rehman

An ever-growing number of vulnerabilities are reported every day. Yet these vulnerabilities are not all the same; Some are more targeted than others. Correctly estimating the likelihood of a vulnerability being exploited is a critical task for system administrators. This aids the system administrators in prioritizing and patching the right vulnerabilities. O

Sijie Zhuo, Robert Biddle, Lucas Betts, Nalin Asanka Gamagedara Arachchilage

Phishing is one of the most prevalent social engineering attacks that targets both organizations and individuals. It is crucial to understand how email presentation impacts users' reactions to phishing attacks. We speculated that the device and email presentation may play a role, and, in particular, that how links are shown might influence susceptibility. Co

Ramón Bécar, P. A. González, Felipe Moncada, Yerko Vásquez

In this work we consider the propagation of massive scalar fields in the background of Weyl black holes and we mainly study the effect of the scalar field mass in the spectrum of the quasinormal frequencies (QNFs) via the Wentzel-Kramers-Brillouin (WKB) method, and the pseudospectral Chebyshev method. The spectrum of QNFs is described by two families of mode

Ismail Laraiedh, Sergei Silvestrov

The aim of this paper is to give some constructions results of averaging operators on Hom-Lie algebras. The homogeneous averaging operators on $q$-deformed Witt and $q$-deformed $W(2,2)$ Hom-algebras are classified. As applications, the induced Hom-Leibniz algebra structures are obtained and their multiplicativity conditions are also given.

Xuan Kien Phung

We establish several extensions of the well-known Garden of Eden theorem for non-uniform cellular automata over the full shifts and over amenable group universes. In particular, our results describe quantitatively the relations between the partial pre-injectivity and the size of the image of a non-uniform cellular automata. A strengthened surjunctivity resul

Mohammad Ghomi

We devise some differential forms after Chern to compute a family of formulas for comparing total mean curvatures of nested hypersurfaces in Riemannian manifolds. This yields a quicker proof of a recent result of the author with Joel Spruck, which had been obtained via Reilly's identities.

Hoon Yeub Jeong, Yeonsoo Lim, Jungho Han, Soo-Chan An

Exceptional points (EPs) are degenerate singularities in a non-Hermitian system that can be induced by controlling the interaction between resonant photonic modes. EPs can enable unusual optical phenomena and significantly enhance the optical sensitivity under small perturbations. However, most studies thus far have been limited to static photonic structures

Carlos Maciel-Escudero, Andrew B. Yankovich, Battulga Munkhbat, Denis G. Baranov

Optical anapoles are intriguing charge-current distributions characterized by a strong suppression of electromagnetic radiation. They originate from the destructive interference of the radiation produced by electric and toroidal multipoles. Although anapoles in dielectric structures have been probed and mapped with a combination of near- and far-field optica

Ethan Q. Simmons, Roshan Sajjad, Kimberlee Keithley, Hector Mas

Can quantum mechanical thermodynamic engines outperform their classical counterparts? To address one aspect of this question, we experimentally realize and characterize an isentropic thermodynamic engine that uses a Bose-condensed working fluid. In this engine, an interacting quantum degenerate gas of bosonic lithium is subjected to trap compression and rela

Szu-Wei Fu, Yaran Fan, Yasaman Hosseinkashi, Jayant Gupchup

Meetings are a pervasive method of communication within all types of companies and organizations, and using remote collaboration systems to conduct meetings has increased dramatically since the COVID-19 pandemic. However, not all meetings are inclusive, especially in terms of the participation rates among attendees. In a recent large-scale survey conducted a

Greta Marino, Sunra Mosconi

We prove local Lipschitz regularity for local minimiser of \[ W^{1,1}(\Omega)\ni v\mapsto \int_\Omega F(Dv)\, dx \] where $\Omega\subseteq {\mathbb R}^N$, $N\ge 2$ and $F:{\mathbb R}^N\to {\mathbb R}$ is a quasiuniformly convex integrand in the sense of Kovalev and Maldonado, i.e. a convex $C^1$-function such that the ratio between the maximum and minimum ei

Emine Altuntas, Ian B. Spielman

A majority of ultracold atom experiments utilize resonant absorption imaging techniques to obtain the atomic density. To make well-controlled quantitative measurements, the optical intensity of the probe beam must be precisely calibrated in units of the atomic saturation intensity ${I_{\rm sat}}$. In quantum gas experiments, the atomic sample is enclosed in

Ken-ichiro Arita

Background: Ground-state octupole deformations are suggested in nuclei located in the north-east neighbor of the doubly magic nuclei on the nuclear chart (N,Z), such as those in Ba and Ra-Th regions. This systematics has been attributed to the parity mixing of the approximately degenerate Delta l=3 pair of single-particle levels near the Fermi surface. Purpo

Martina Boschi, Rūta Juozaitienė, Ernst-Jan Camiel Wit

Alien species refer to non-native species introduced by humans into an ecosystem, which can cause harm to the environment, economy, or human health. Although there is considerable literature on the subject, the presence of confounding factors has so far prevented a comprehensive picture of the relative importance of various drivers of such invasions. In this

Sudath Rohitha Heiyanthuduwage, Md Anisur Rahman, Md Zahidul Islam

Ontology-based clustering has gained attention in recent years due to the potential benefits of ontology. Current ontology-based clustering approaches have mainly been applied to reduce the dimensionality of attributes in text document clustering. Reduction in dimensionality of attributes using ontology helps to produce high quality clusters for a dataset. H

Yasaman Hosseinkashi, Lev Tankelevitch, Jamie Pool, Ross Cutler

Workplace meetings are vital to organizational collaboration, yet relatively little progress has been made toward measuring meeting effectiveness and inclusiveness at scale. The recent rise in remote and hybrid meetings represents an opportunity to do so via computer-mediated communication (CMC) systems. Here, we share the results of an effective and inclusi

Syngjoo Choi, Kyu Sup Hahn, Byung-Yeon Kim, Eungik Lee

This paper investigates whether ideological indoctrination by living in a communist regime relates to low economic performance in a market economy. We recruit North Korean refugees and measure their implicit bias against South Korea by using the Implicit Association Test. Conducting double auction and bilateral bargaining market experiments, we find that Nor

Shammur Absar Chowdhury, Ahmed Ali

The success of the multilingual automatic speech recognition systems empowered many voice-driven applications. However, measuring the performance of such systems remains a major challenge, due to its dependency on manually transcribed speech data in both mono- and multilingual scenarios. In this paper, we propose a novel multilingual framework -- eWER3 -- jo

Mohamed k. Fadul, Donald R. Reising, Lakmali P. Weerasena, T. Daniel Loveless

The number of Internet of Things (IoT) deployments is expected to reach 75.4 billion by 2025. Roughly 70% of all IoT devices employ weak or no encryption; thus, putting them and their connected infrastructure at risk of attack by devices that are wrongly authenticated or not authenticated at all. A physical layer security approach -- known as Specific Emitte

Abdelkrim Moussaoui, Kamel Saoudi

Existence of nodal (i.e., sign changing) solutions and constant sign solutions for quasilinear elliptic equations involving convection-absorption terms are presented. A location principle for nodal solutions is obtained by means of constant sign solutions whose existence is also derived. The proof is chiefly based on sub-supersolutions technique together wit

Michael V. Klibanov, Jingzhi Li, Hongyu Liu

We are concerned with the mathematical study of the Mean Field Games system (MFGS). In the conventional setup, the MFGS is a system of two coupled nonlinear parabolic PDEs of the second order in a backward-forward manner, namely one terminal and one initial conditions are prescribed respectively for the value function and the population density. In this pape

Muhammad Fadhil Ginting, Sung-Kyun Kim, Oriana Peltzer, Joshua Ott

To achieve autonomy in unknown and unstructured environments, we propose a method for semantic-based planning under perceptual uncertainty. This capability is crucial for safe and efficient robot navigation in environment with mobility-stressing elements that require terrain-specific locomotion policies. We propose the Semantic Belief Graph (SBG), a geometri

Licio Romao, Ashish R. Hota, Alessandro Abate

We present a novel distributionally robust framework for dynamic programming that uses kernel methods to design feedback control policies. Specifically, we leverage kernel mean embedding to map the transition probabilities governing the state evolution into an associated repreducing kernel Hilbert space. Our key idea lies in combining conditional mean embedd

Eric R. Anschuetz, David Gamarnik, Bobak Kiani

In an important recent development, Anshu, Breuckmann, and Nirkhe [ABN22] resolved positively the so-called No Low-Energy Trivial State (NLTS) conjecture by Freedman and Hastings. The conjecture postulated the existence of linear-size local Hamiltonians on n qubit systems for which no near-ground state can be prepared by a shallow (sublogarithmic depth) circ

Christopher Sims

Black holes are objects that have a large mass and curve space time, characterized by their event horizon and singularity. Recently, an interesting concept of analogous black holes has emerged in the field of condensed matter physics. In this work, the possibility of realizing analogous black holes in topological material is Ni$_3$In$_2$X$_2$ (X = S, Se) dis

Gabriel Fernandes, Nuno Lourenço, João Correia

The design of cable-stayed bridges requires the determination of several design variables' values. Civil engineers usually perform this task by hand as an iteration of steps that stops when the engineer is happy with both the cost and maintaining the structural constraints of the solution. The problem's difficulty arises from the fact that changing a variabl

Pedro A. Quinto-Su

In this work we demonstrate a simple setup to generate and measure arbitrary vector beams that are tightly focused. The vector beams are created with a spatial light modulator and focused with a microscope objective with an effective numerical aperture of 1.2. The transverse polarization components ($E_x$, $E_y$) of the tightly focused vector beams are measu

Mohannad Alkhraijah, Rachel Harris, Carleton Coffrin, Daniel K. Molzahn

This paper presents PowerModelsADA, an open-source framework for solving Optimal Power Flow (OPF) problems using Alternating Distributed Algorithms (ADA). PowerModelsADA provides a framework to test, verify, and benchmark both existing and new ADAs. This paper demonstrates use cases for PowerModelsADA and validates its implementation with multiple OPF formul

A. G. Nikitin

Quantum mechanical systems with position dependent masses (PDM) admitting two parametric Lie symmetry groups are classified. Namely, all PDM systems are specified which, in addition to their invariance w.r.t. a two parametric Lie group, admit at least one second order integral of motion. The presented classification is partially extended to the more generic

João Correia, Gustavo Gama, João Tiago Guerrinha, Ricardo Cadime

With the increasing demand for high-quality internet services, deploying GPON/Fiber-to-the-Home networks is one of the biggest challenges that internet providers have to deal with due to the significant investments involved. Automated network design usage becomes more critical to aid with planning the network by minimising the costs of planning and deploymen

Rabia Bounaama, Mohammed El Amine Abderrahim

The present paper is about the participation of our team "techno" on CERIST'22 shared tasks. We used an available dataset "task1.c" related to covid-19 pandemic. It comprises 4128 tweets for sentiment analysis task and 8661 tweets for fake news detection task. We used natural language processing tools with the combination of the most renowned pre-trained lan

Paul Verschueren

We study Birkhoff sums over rotations (series of the form $\sum_{r=1}^{N}\phi(r\alpha)$), in which the summed function $\phi$ may be unbounded at the origin. Estimates of these sums have been of significant interest and application in pure mathematics since the late 1890s, but in recent years they have also appeared in numerous areas of applied mathematics,

Dwip Dalal, Vivek Srivastava, Mayank Singh

Social media plays a significant role in cross-cultural communication. A vast amount of this occurs in code-mixed and multilingual form, posing a significant challenge to Natural Language Processing (NLP) tools for processing such information, like language identification, topic modeling, and named-entity recognition. To address this, we introduce a large-sc

D. Iannarelli, F. Napoli, F. Alladio, G. Apruzzese

This article presents a new method for estimating the electron temperature of the Protosphera's screw pinch. The temperature radial profile is obtained by a self-consistent modeling of a 1D MHD equilibrium along with a 0D power balance of the plasma column, given measurements and estimates of the axial pinch plasma current, of the plasma rotational frequency

Xiao Wang, Fengfeng Zhu, Navid Qureshi, Ketty Beauvois

We report a comprehensive single-crystal neutron diffraction investigation of the Kitaev quantum magnet $\alpha$-RuCl$_{3}$ under hydrostatic pressure. Utilizing a He-gas pressure cell, we successfully applied an ideal hydrostatic pressure in situ at low temperatures, which allows to effectively eliminate any possible influences from the structural transitio

Pinjun Zheng, Hui Chen, Tarig Ballal, Mikko Valkama

Reconfigurable intelligent surface (RIS)-assisted localization has attracted extensive attention as it can enable and enhance localization services in extreme scenarios. However, most existing works treat RISs as anchors with known positions and orientations, which is not realistic in applications with mobile or uncalibrated RISs. This work considers the joi

Calista Bernard

We develop a theory of operations on the twisted homology of $E_{\infty}$-algebras, generalizing a classical theory developed by J.P. May. First we describe a framework suitable for discussing twisted coefficients, which requires working with $E_{\infty}$-algebras in certain categories of functors. In this context, we define twisted versions of the classical