August 2022 arXiv papers — page 115

Yurii Averboukh

The paper is concerned with a variant of the continuous-time finite state Markov game of control and stopping where both players can affect transition rates, while only one player can choose a stopping time. We use the dynamic programming principle and reduce this problem to a system of ODEs with unilateral constraints. This system plays the role of the Bell

Yu Yang, Xiaohong Guan, Qing-Shan Jia, Liang Yu

By coordinating terminal smart devices or microprocessors to engage in cooperative computation to achieve systemlevel targets, distributed optimization is incrementally favored by both engineering and computer science. The well-known alternating direction method of multipliers (ADMM) has turned out to be one of the most popular tools for distributed optimiza

Elizabeth Polgreen, Kevin Cheang, Pranav Gaddamadugu, Adwait Godbole

UCLID5 is a tool for the multi-modal formal modeling, verification, and synthesis of systems. It enables one to tackle verification problems for heterogeneous systems such as combinations of hardware and software, or those that have multiple, varied specifications, or systems that require hybrid modes of modeling. A novel aspect of \uclid is an emphasis on t

Hongwei Li, Tao Dai, Yiming Li, Xueyi Zou

Image representation is critical for many visual tasks. Instead of representing images discretely with 2D arrays of pixels, a recent study, namely local implicit image function (LIIF), denotes images as a continuous function where pixel values are expansion by using the corresponding coordinates as inputs. Due to its continuous nature, LIIF can be adopted fo

Leif Holmlid, Bernhard Kotzias

In this invited response we answer all comments by Engelen and Hansen [arXiv:2207.07844]. We point out that the superfluid and superconductive properties of H(0) have been published previously. We explain some differences between covalently bonded molecules and the molecules in the ultradense matter H(0) form, and explain some aspects of the energetics of H(

N. Ikeno, M. Bayar, E. Oset

We study the interaction of two $ D^* $ and a $\bar{K}^{*}$ by using the Fixed Center Approximation to the Faddeev equations to search for bound states of the three body system. Since the $ D^* D^* $ interaction is attractive and gives a bound state, and so is the case of the $D^* \bar{K}^{*}$ interaction, where the $J^{P}=0^{+}$ bound state is identified wi

Leonard Henckel, Martin Buttenschön, Marloes H. Maathuis

We consider the efficient estimation of total causal effects in the presence of unmeasured confounding using conditional instrumental sets. Specifically, we consider the two-stage least squares estimator in the setting of a linear structural equation model with correlated errors that is compatible with a known acyclic directed mixed graph. To set the stage f

Boris Ivetic

A geometrical interpretation of Schr\"odinger's kinetic and potential energy operators is proposed, allowing for a covariant momentum space formulation of the dynamics that is relevant for the theories with the deformation of the momentum space structure. Some specific examples are discussed in the context of flat space deformations and the Euclidean Snyder

Sami Ortakaya

We present an oscillator modeling of the relativistic spin-0 charges moving in the quantum states with minimum coupling of electromagnetic fields. Rather than perturbative approach to spinless regime, we put into operation directly under integer dependent levels for anharmonicity. In this way, the charged particle of rest mass energy kept as 280 MeV. Within

Charis Anastopoulos, Bei-Lok Hu, Konstantina Savvidou

This is the first in a series of papers aiming to develop a relativistic quantum information theory in terms of unequal-time correlation functions in quantum field theory. In this work, we highlight two formalisms which together can provide a useful theoretical platform suitable for further developments: 1) Quantum field measurements using the Quantum Tempor

Leonard Münchenbach, Leo Neff

Paper strips, e.g. confetti, descending to the floor begin to rotate around the horizontal axis after a short time. This slows down the vertical velocity compared to free fall and adds a horizontal velocity component. The frequency of rotation, the angle of fall and the speed of fall seem to depend on the dimensions and mass of the paper strips. The physics

Zezhong Zhang, Guangxu Zhu, Shuguang Cui

In recent years, the exponential increase in the demand of wireless data transmission rises the urgency for accurate spectrum sensing approaches to improve spectrum efficiency. The unreliability of conventional spectrum sensing methods by using measurements from a single secondary user (SU) has motivated research on cooperative spectrum sensing (CSS). In thi

Yao Ou, Qi Zhang, Guoxiang Huang

We propose and analyze a scheme for realizing the quantum reflection of single photons in a cold Rydberg atomic gas via electromagnetically induced transparency, by which a deep and tunable attractive potential well can be prepared by using stored gate photons. Such a scheme is promising for designing dispersion-type single-photon switches, and may be taken

Andreas Papadimitriou, Hedyeh Jafari, Sina Sharif Mansouri, George Nikolakopoulos

Time delays in communication networks are one of the main concerns in deploying robots with computation boards on the edge. This article proposes a multi-stage Nonlinear Model Predictive Control (NMPC) that is capable of handling varying network-induced time delays for establishing a control framework being able to guarantee collision-free Micro Aerial Vehic

Bin-Lei Wang, Fan Gao, Long-Jun Wang, Yang Sun

The Wigner rotation matrix ($d$-function), which appears as a part of the angular-momentum-projection operator, plays a crucial role in modern nuclear-structure models. However, it is a long-standing problem that its numerical evaluation suffers from serious errors and instability, which hinders precise calculations for nuclear high-spin states. Recently, Ta

S. Meljanac, S. Mignemi

We investigate a quantum mechanical harmonic oscillator based on the extended Snyder model. This realization of the Snyder model is constructed as a quantum phase space generated by $D$ spatial coordinates and $D(D-1)/2$ tensorial degrees of freedom, together with their conjugate momenta. The \coo obey nontrivial \cor and generate a noncommutative geometry,

Andrea Galasso, Chin-Yu Hsiao

In this paper we study the microlocal properties of the Szeg\H{o} kernel of a given compact connected orientable CR orbifold whose Kohn Laplacian has closed range. This last assumption is satisfied if certain geometric conditions hold true, as in the smooth case. As applications, we give a pure analytic proof of Kodaira-Bailey theorem and explain how to gene

Vaclav Skala

This paper describes novel and fast, simple and robust algorithm with O(N) expected complexity which enables to decrease run-time needed to find an exact maximum distance of two points in E2. The proposed algorithm has been evaluated experimentally on larger different datasets. The proposed algorithm gives a significant speed-up to applications, when medium

B. Lefloch, C. Vastel, E. Bianchi, R. Bachiller

The Large Program "Astrochemical Surveys At IRAM" (ASAI) investigates the emergence of molecular complexity along the different stages of the solar-type star formation process, by carrying out unbiased line surveys of a sample of ten template sources in the range 80-272 GHz with the IRAM 30m telescope. We present here an overview of the main results of the L

Shubham Kumar Gupta, Azeem Ahmad, Prakhar Kumar, Frank Melandso

Scanning acoustic microscopy (SAM) has been employed since microscopic images are widely used for biomedical or materials research. Acoustic imaging is an important and well-established method used in nondestructive testing (NDT), bio-medical imaging, and structural health monitoring.The imaging is frequently carried out with signals of low amplitude, which

Vaclav Skala

This paper presents a new approach to computation of geometric continuity for parametric bi-cubic patches, based on a simple mathematical reformulation which leads to simple additional conditions to be applied in the patching computation. The paper presents an Hermite formulation of a bicubic parametric patch, but reformulations can be made also for B\'ezier

Nico Goldammer, Volker H. Schulz, Kathrin Welker

Shape optimization problems constrained by variational inequalities (VI) are non-smooth and non-convex optimization problems. The non-smoothness arises due to the variational inequality constraint, which makes it challenging to derive optimality conditions. Besides the non-smoothness there are complementary aspects due to the VIs as well as distributed, non-

H. S. Abdel-Aziz, M. Khalifa Saad, Haytham. A. Ali

In the theory of differential geometry curves, a curve is said to be of constant-ratio if the ratio of the length of the tangential and normal components of its position vector function is constant. In this paper, we study and characterize a spacelike admissible curve of constant-ratio in terms of its curvature functions in pseudo-Galilean space. Some specia

Vaclav Skala

Line intersection with convex and un-convex polygons or polyhedron algorithms are well known as line clipping algorithms and very often used in computer graphics. Rendering of geometrical problems often leads to ray tracing techniques, when an intersection of many lines with spheres or quadrics is a critical issue due to ray-tracing algorithm complexity. A n

Kaifeng Yang, Guozhi Dong, Michael Affenzeller

Bayesian global optimization (BGO) is an efficient surrogate-assisted technique for problems involving expensive evaluations. A parallel technique can be used to parallelly evaluate the true-expensive objective functions in one iteration to boost the execution time. An effective and straightforward approach is to design an acquisition function that can evalu

Raphael Baena, Lucas Drumetz, Vincent Gripon

Labeling a classification dataset implies to define classes and associated coarse labels, that may approximate a smoother and more complicated ground truth. For example, natural images may contain multiple objects, only one of which is labeled in many vision datasets, or classes may result from the discretization of a regression problem. Using cross-entropy

Vaclav Skala

There are many practical applications based on the Least Square Error (LSE) or Total Least Square Error (TLSE) methods. Usually the standard least square error is used due to its simplicity, but it is not an optimal solution, as it does not optimize distance, but square of a distance. The TLSE method, respecting the orthogonality of a distance measurement, i

Ahmet M. Elbir, Wei Shi, Anastasios K. Papazafeiropoulos, Pandelis Kourtessis

For the demonstration of ultra-wideband bandwidth and pencil-beamforming, the terahertz (THz)-band has been envisioned as one of the key enabling technologies for the sixth generation networks. However, the acquisition of the THz channel entails several unique challenges such as severe path loss and beam-split. Prior works usually employ ultra-massive arrays

Vaclav Skala

There are many space subdivision and space partitioning techniques used in many algorithms to speed up computations. They mostly rely on orthogonal space subdivision, resp. using hierarchical data structures, e.g. BSP trees, quadtrees, octrees, kd-trees, bounding volume hierarchies, etc. However in some applications a non-orthogonal space subdivision can off

Paramita Deka, Jaydip Singh, Kalpana Bora

Long baseline (LBL) neutrino experiments aim to measure the neutrino oscillation parameters to high precision. These experiments use nuclear targets for neutrino scattering and hence are inflicted with complexities of nuclear effects. Nuclear effects and their percolation into sensitivity measurement of neutrino oscillations parameters are not yet fully unde

Zhongzhan Huang, Senwei Liang, Hong Zhang, Haizhao Yang

The large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines. However, traditional numerical solvers are limited by the choice of step sizes when estimating integration, resulting in a trade-off between accuracy and computational efficiency. To address this challenge, we introduce a deep learning-based correc

Ainesh Sewak, Torsten Hothorn

Receiver operating characteristic (ROC) analysis is one of the most popular approaches for evaluating and comparing the accuracy of medical diagnostic tests. Although various methodologies have been developed for estimating ROC curves and its associated summary indices, there is no consensus on a single framework that can provide consistent statistical infer

Xi Zhang, Le Wang, Huimin Su, Xiuquan Xia

Layered ferromagnets with high coercivity have special applications in nanoscale memory elements in electronic circuits, such as data storage. Therefore, searching for new hard ferromagnets and effectively tuning or enhancing the coercivity are the hottest topics in layered magnets today. Here, we report a strain tunability of perpendicular magnetic anisotro

Vaclav Skala

There are many applications in which a bounding sphere containing the given triangle E3 is needed, e.g. fast collision detection, ray-triangle intersecting in raytracing etc. This is a typical geometrical problem in E3 and it has also applications in computational problems in general. In this paper a new fast and robust algorithm of circumscribed sphere comp

Hyoungjun Kim, Sungjong No, Hyungkee Yoo

The ribbonlength Rib$(K)$ of a knot $K$ is the infimum of the ratio of the length of any flat knotted ribbon with core $K$ to its width. A twisted torus knot $T_{p,q;r,s}$ is obtained from the torus knot $T_{p,q}$ by twisting $r$ adjacent strands $s$ full twists. In this paper, we show that the ribbonlength of $T_{p,q;r,s}$ is less then or equal to $2(\max \

Marcos Matabuena, J. C Vidal, Oscar Hernan Madrid Padilla, Dino Sejdinovic

Biclustering algorithms partition data and covariates simultaneously, providing new insights in several domains, such as analyzing gene expression to discover new biological functions. This paper develops a new model-free biclustering algorithm in abstract spaces using the notions of energy distance (ED) and the maximum mean discrepancy (MMD) -- two distance

Vaclav Skala

Many algorithms used are based on geometrical computation. There are several criteria in selecting appropriate algorithm from already known. Recently, the fastest algorithms have been preferred. Nowadays, algorithms with a high stability are preferred. Also technology and computer architecture, like GPU etc., plays a significant role for large data processin

Thuong D. Hoang, Tomotake Matsumura, Ryota Takaku, Takashi Hasebe

LiteBIRD is the Cosmic Microwave Background (CMB) radiation polarization satellite mission led by ISAS/JAXA. The main scientific goal is to search for primordial gravitational wave signals generated from the inflation epoch of the Universe. LiteBIRD telescopes employ polarization modulation units (PMU) using continuously rotating half-wave plates (HWP). The

Xin-Wei Liu, Yu-Hong Dai, Ya-Kui Huang

We present a primal-dual majorization-minimization method for solving large-scale linear programs. A smooth barrier augmented Lagrangian (SBAL) function with strict convexity for the dual linear program is derived. The majorization-minimization approach is naturally introduced to develop the smoothness and convexity of the SBAL function. Our method only depe

Rui Wang, Fan Liu, Min-Li Li, Wei-Zhong Zhao

We construct the supersymmetric $\beta$ and $(q,t)$-deformed Hurwitz-Kontsevich partition functions through $W$-representations and present the corresponding character expansions with respect to the Jack and Macdonald superpolynomials, respectively. Based on the constructed $\beta$ and $(q,t)$-deformed superoperators, we further give the supersymmetric $\bet

Lucio Galeati, Chengcheng Ling

We consider multidimensional SDEs with singular drift $b$ and Sobolev diffusion coefficients $\sigma$, satisfying Krylov--R\"ockner type assumptions. We prove several stability estimates, comparing solutions driven by different $(b^i,\sigma^i)$, both for It\^o and Stratonovich SDEs, possibly depending on negative Sobolev norms of the difference $b^1-b^2$. We

Hyoungjun Kim, Sungjong No, Hyungkee Yoo

A ribbon is a two-dimensional object with one-dimensional properties which is related with geometry, robotics and molecular biology. A folded ribbon structure provides a complex structure through a series of folds. We focus on a folded ribbon with knotted core. The folded ribbonlength $Rib(K)$ of a knot $K$ is the infimum of the quotient of length by width a

R. Y. Guan, M. X. Lan

Aims. With the accumulation of polarization data in the gamma-ray burst (GRB) prompt phase, polarization models can be tested. Methods. We predicted the time-integrated polarizations of 37 GRBs with polarization observation. We used their observed spectral parameters to do this. In the model, the emission mechanism is synchrotron radiation, and the magnetic

Rui Guo, Juntai Shen, Zhao-yu Li, Chao Liu

The Galaxy is found to be in disequilibrium based on recent findings of the North/South (N/S) asymmetry and the phase mixing signatures, such as a phase spiral (snail) structure in the vertical phase space ($z-V_{z}$). We show that the N/S asymmetry in a tracer population of dwarfs may be quantitatively modeled with a simple phase snail model superimposed on

Zesheng Ye, Lina Yao, Yu Zhang, Sylvia Gustin

Recent studies demonstrate the use of a two-stage supervised framework to generate images that depict human perception to visual stimuli from EEG, referring to EEG-visual reconstruction. They are, however, unable to reproduce the exact visual stimulus, since it is the human-specified annotation of images, not their data, that determines what the synthesized

Yong Song, Yiting Cen, Leilei Tang, Jiabao Hu

In this work, inspired by the definition of the photon surface given by Claudel, Virbhadra, and Ellis, we give an alternative quasi-local definition to study the circular orbits of single-pole particles. This definition does not only apply to photons but also to massive point particles. For the case of photons in spherically symmetric spacetime, it will give

Lakshmi Jayalal, Shashank Shekhar, Athira Subhash, Sheetal Kalyani

In this work, we characterize the outage probability (OP) of an intelligent reflecting surface (IRS) assisted multi-user multiple-input-single-output (MU-MISO) communication system. Using a two-step approximation method, we approximate the signal-to-interference-plus-noise ratio (SINR) for any downlink user by a Log-Normal random variable. The impact of vari

Kai Liu, Tianxian Zhang, Lingjiang Kong

We explore value decomposition solutions for multi-agent deep reinforcement learning in the popular paradigm of centralized training with decentralized execution(CTDE). As the recognized best solution to CTDE, Weighted QMIX is cutting-edge on StarCraft Multi-agent Challenge (SMAC), with a weighting scheme implemented on QMIX to place more emphasis on the opt

Arvind Subramaniam, Avinash Sharma

The over-parametrized nature of Deep Neural Networks leads to considerable hindrances during deployment on low-end devices with time and space constraints. Network pruning strategies that sparsify DNNs using iterative prune-train schemes are often computationally expensive. As a result, techniques that prune at initialization, prior to training, have become

Yong Song, Chuanyu Zhang

In this paper, enlightened by the definition of the photon surface given by Claudel, Virbhadra and Ellis, we give a quasi-local definition of the particle surface. From this definition, one can study the evolution of the circular orbits in general spacetime. Especially, we pointed out that this definition can be used to get the spherical circular orbits in s

Yujiao Shi, Xin Yu, Shan Wang, Hongdong Li

This paper tackles the problem of Cross-view Video-based camera Localization (CVL). The task is to localize a query camera by leveraging information from its past observations, i.e., a continuous sequence of images observed at previous time stamps, and matching them to a large overhead-view satellite image. The critical challenge of this task is to learn a p

Mohammad Hossein Nasseri, Mohammadreza Babaee, Hadi Moradi, Reshad Hosseini

To overcome challenges in multiple object tracking task, recent algorithms use interaction cues alongside motion and appearance features. These algorithms use graph neural networks or transformers to extract interaction features that lead to high computation costs. In this paper, a novel interaction cue based on geometric features is presented aiming to dete

Subhash Chand Bhoria, Pramod Eyyunni, Bibekananda Maji

Euler's classical identity states that the number of partitions of an integer into odd parts and distinct parts are equinumerous. Franklin gave a generalization by considering partitions with exactly $j$ different multiples of $r$, for a positive integer $r$. We prove an analogue of Franklin's identity by studying the number of partitions with $j$ multiples

Salah G. Elgendi

In this paper, we introduce a new look at Finsler surfaces. Landsberg surfaces are Finsler surfaces that are solutions of a system of non-linear partial differential equations. Considering the unicorn's Landsberg problem, we reduce this system to a single non-linear PDE which we call the Landsberg's PDE. By making use of the new look of Finsler surfaces, we

Paritosh Verma

This article presents a theoretical limit on the Brans-Dicke (BD) parameter using a neutron star (NS) revolving around a galactic central engine.The assumption that the orbital radius is large enough allows to ignore strong curvature due to the central supermassive black hole (SMBH) and treat the problem with Newtonian dynamics. First, gravitational radiatio

Gal Shavit, Kryštof Kolář, Christophe Mora, Felix von Oppen

Correlated insulators are frequently observed in magic angle twisted bilayer graphene at even fillings of electrons or holes per moir\'e unit-cell. Whereas theory predicts these insulators to be intervalley coherent excitonic phases, the measured gaps are routinely much smaller than theoretical estimates. We explore the effects of random strain variations on

Zihan Liu, Yun Luo, Lirong Wu, Siyuan Li

Graph edge perturbations are dedicated to damaging the prediction of graph neural networks by modifying the graph structure. Previous gray-box attackers employ gradients from the surrogate model to locate the vulnerable edges to perturb the graph structure. However, unreliability exists in gradients on graph structures, which is rarely studied by previous wo

Yixin Guo, Hiroyuki Tajima

We theoretically investigate in-medium two- and three-body correlations in one-dimensional spinless fermions with attractive two-body p-wave interaction. By investigating the variational problem of two- and three-body states above the Fermi sea, we elucidate the fate of the in-medium two- and three-body cluster states. The one-dimensional system with the str

Etienne Moullet, Agnès Roby-Brami, Emmanuel Guigon

When human participants repeatedly encounter a velocity-dependent force field that distorts their movement trajectories, they adapt their motor behavior to recover straight trajectories. Computational models suggest that adaptation to a force field occurs at the action selection level through changes in the mapping between goals and actions. The quantitative

Yinan Dong, Roya Zandi, Alex Travesset

The problem of characterizing the structure of an elastic network constrained to lie on a frozen curved surface appears in many areas of science and has been addressed by many different approaches, most notably, extending linear elasticity or through effective defect interaction models. In this paper, we show that the problem can be solved by considering non

Adam S. Jermyn, Evan B. Bauer, Josiah Schwab, R. Farmer

We update the capabilities of the open-knowledge software instrument Modules for Experiments in Stellar Astrophysics (MESA). The new auto_diff module implements automatic differentiation in MESA, an enabling capability that alleviates the need for hard-coded analytic expressions or finite difference approximations. We significantly enhance the treatment of t

Chang Yang, Ruiyu Wang, Xinrun Wang, Zhen Wang

Generalization in reinforcement learning (RL) is of importance for real deployment of RL algorithms. Various schemes are proposed to address the generalization issues, including transfer learning, multi-task learning and meta learning, as well as the robust and adversarial reinforcement learning. However, there is not a unified formulation of the various sch

Yujie Qin, Mustafa A. Kishk, Mohamed-Slim Alouini

This paper analyzes the energy efficiency of a novel system model where unmanned aerial vehicles (UAVs) are used to provide coverage for user hotspots (user clusters) and are deployed on charging pads to enhance the flight time. We introduce a new notion of "cluster pairs" to capture the dynamic nature of the users' spatial distribution in order to exploit o

Tongyi Luo, Jia Xiao, Chuncao Zhang, Siheng Chen

To make the earlier medical intervention of infants' cerebral palsy (CP), early diagnosis of brain damage is critical. Although general movements assessment(GMA) has shown promising results in early CP detection, it is laborious. Most existing works take videos as input to make fidgety movements(FMs) classification for the GMA automation. Those methods requi

Yifan Hu, Yu Wang

The development of IoT technology enables a variety of sensors can be integrated into mobile devices. Human Activity Recognition (HAR) based on sensor data has become an active research topic in the field of machine learning and ubiquitous computing. However, due to the inconsistent frequency of human activities, the amount of data for each activity in the h

Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li

Transformers are considered one of the most important deep learning models since 2018, in part because it establishes state-of-the-art (SOTA) records and could potentially replace existing Deep Neural Networks (DNNs). Despite the remarkable triumphs, the prolonged turnaround time of Transformer models is a widely recognized roadblock. The variety of sequence

Yongjun Chen, Jia Li, Zhiwei Liu, Nitish Shirish Keskar

To make Sequential Recommendation (SR) successful, recent works focus on designing effective sequential encoders, fusing side information, and mining extra positive self-supervision signals. The strategy of sampling negative items at each time step is less explored. Due to the dynamics of users' interests and model updates during training, considering random

Junkun Yuan, Xu Ma, Defang Chen, Kun Kuang

Considerable progress has been made in domain generalization (DG) which aims to learn a generalizable model from multiple well-annotated source domains to unknown target domains. However, it can be prohibitively expensive to obtain sufficient annotation for source datasets in many real scenarios. To escape from the dilemma between domain generalization and a

Xu Xu, Chao Zheng

In this paper, we investigate the deformation of generalized circle packings on ideally triangulated surfaces with boundary, which is the $(-1,-1,-1)$ type generalized circle packing metric introduced by Guo-Luo \cite{GL2}. To find hyperbolic metrics on surfaces with totally geodesic boundaries of prescribed lengths, we introduce combinatorial Ricci flow and

Natsuki Tsutsumi, Kengo Nakai, Yoshitaka Saiki

We propose a simple method of constructing a system of differential equations of chaotic behavior based on the regression only from a scalar observable time-series data. The estimated system enables us to reconstruct invariant sets and statistical properties as well as to infer short time-series. Our successful modeling relies on the introduction of a set of

Jonathan Husson, Justin Ko

We consider the asymptotics of $k$-dimensional spherical integrals when $k = o(N)$. We prove that the $o(N)$-dimensional spherical integrals are approximately the products of $1$-dimensional spherical integrals. Our formulas extend the results for $k$-dimensional spherical integrals proved by Guionnet and Ma\"ida in [29] and Husson and Guionnet in [34] which

Raja Sunkara, Tie Luo

Convolutional neural networks (CNNs) have made resounding success in many computer vision tasks such as image classification and object detection. However, their performance degrades rapidly on tougher tasks where images are of low resolution or objects are small. In this paper, we point out that this roots in a defective yet common design in existing CNN ar

Arvind Subramaniam

Neuromorphic engineering is essentially the development of artificial systems, such as electronic analog circuits that employ information representations found in biological nervous systems. Despite being faster and more accurate than the human brain, computers lag behind in recognition capability. However, it is envisioned that the advancement in neuromorph

Li-Na Zong, Ren-Shu Wang, Di Peng, Xiao-Jia Chen

To establish the doping-dependent phase diagram in alkali-metal doped C$_{60}$, we synthesize Rb-doped C$_{60}$ samples with different stoichiometries by using the improved wet-chemistry technique. The doping levels determined from the Raman scattering spectra often show the appearance of three electrons corresponding to the band filling of three for the syn

Yue-Xin Huang, Xiaolong Feng, Hui Wang, Cong Xiao

We propose an intrinsic nonlinear planar Hall effect, which is of band geometric origin, independent of scattering, and scales with the second order of electric field and first order of magnetic field. We show that this effect is less symmetry constrained compared to other nonlinear transport effects and is supported in a large class of nonmagnetic polar and

Masaaki Mizukami, Yuya Tanaka, Tomomi Yokota

This paper deals with the two-species chemotaxis-competition models \begin{align*} \begin{cases} u_t = d_1 \Delta u - \chi_1 \nabla \cdot (u \nabla w) + \mu_1 u (1- u^{\kappa_1-1} - a_1 v^{\lambda_1-1}), &\quad x \in \Omega,\ t>0,\\ % v_t = d_2 \Delta v - \chi_2 \nabla \cdot (v \nabla w) + \mu_2 v (1- a_2 u^{\lambda_2-1} - v^{\kappa_2-1}), &\quad x \in \Omeg

Pavan Kumar Reddy Boppidi, Victor Jeffry Louis, Arvind Subramaniam, Rajesh K. Tripathy

Independent component analysis is an unsupervised learning approach for computing the independent components (ICs) from the multivariate signals or data matrix. The ICs are evaluated based on the multiplication of the weight matrix with the multivariate data matrix. This study proposes a novel memristor crossbar array for the implementation of both ACY ICA a

Wenxin Ding, Chuanru Dai, Zhengfei Hu

Recently, an {\it algebraic-dynamical theory} (ADT) for strongly interacting many-body quantum Hamiltonians in W. Ding, arXiv: 2202.12082 (2022). By introducing the complete operator basis set, ADT proposes a generic framework for systematically constructing dynamical theories for interacting quantum Hamiltonians, using quantum entanglement as the organizing

K. Y. Zhang, C. Pan, S. Q. Zhang

The Woods-Saxon basis has achieved great success in both nonrelativistic and covariant density functional theories in recent years. Due to its nonanalytical nature, however, applications of the Woods-Saxon basis are numerically complicated and computationally time consuming. In this paper, based on the deformed relativistic Hartree-Bogoliubov theory in conti

Amanda Gatto Lamas, Eric Chitambar

We adopt a resource-theoretic framework to classify different types of quantum network nonlocality in terms of operational constraints placed on the network. One type of constraint limits the parties to perform local Clifford gates on pure stabilizer states, and we show that quantum network nonlocality cannot emerge in this setting. Yet, if the constraint is

Xiaoxiao Li, Zhao Song, Jiaming Yang

Federated learning (FL) is a trending training paradigm to utilize decentralized training data. FL allows clients to update model parameters locally for several epochs, then share them to a global model for aggregation. This training paradigm with multi-local step updating before aggregation exposes unique vulnerabilities to adversarial attacks. Adversarial

Yunfei Song

In this paper, we propose a PDE-based optimization motivated by the problem of microfluidic heat transfer to finding the optimal incompressible velocity fields in 2D domain. To solve this optimization model, we use spectral method to discretize the model to obtain an ODE based optimization. This way significantly reduces the complexity of the discretization

Jinng Yi, Zhenzhong Chen

Micro-video background music recommendation is a complicated task where the matching degree between videos and uploader-selected background music is a major issue. However, the selection of the user-generated content (UGC) is biased caused by knowledge limitations and historical preferences among music of each uploader. In this paper, we propose a Debiased C

Ruofan Xu, Jiti Gao, Tatsushi Oka, Yoon-Jae Whang

We propose a quantile random-coefficient regression with interactive fixed effects to study the effects of group-level policies that are heterogeneous across individuals. Our approach is the first to use a latent factor structure to handle the unobservable heterogeneities in the random coefficient. The asymptotic properties and an inferential method for the

Marco Simonetti, Damiano Perri, Osvaldo Gervasi

This paper introduces a deep learning system based on a quantum neural network for the binary classification of points of a specific geometric pattern (Two-Moons Classification problem) on a plane. We believe that the use of hybrid deep learning systems (classical + quantum) can reasonably bring benefits, not only in terms of computational acceleration but i

Xuanle Ren, Xiaoxia Cui

Secure Element (SE) in SoC sees an increasing adoption in industry. Many applications in IoT devices are bound to the SE because it provides strong cryptographic functions and physical protection. Though SE-in-SoC provides strong proven isolation for software programs, it also brings more design complexity and higher cost to PCB board building. More, SE-in-S

Paul W. Vos

Point estimators may not exist, need not be unique, and their distributions are not parameter invariant. Generalized estimators provide distributions that are parameter invariant, unique, and exist when point estimates do not. Comparing point estimators using variance is less useful when estimators are biased. A squared slope $\Lambda$ is defined that can be

Xue-Zheng Zhu, Yang Yu, Xian Gao

We investigate the scalar perturbations in a class of spatially covariant gravity theory with a dynamical lapse function. Generally, there are two scalar degrees of freedom due to the presence of the velocity of the lapse function. We treat the scalar perturbations as analogues of those in a two-field inflationary mode, in which one is light mode and the oth

Ren-Shu Wang, Di Peng, Li-Na Zong, Zeng-Wei Zhu

The superconducting parameters are the key for building or identifying the theory responsible for the mechanism of superconductivity. Such parameters for fulleride superconductors have not been well established despite the tremendous efforts over the past 30 years. Here we provide a full set of parameters through a systematic study on a well-characterized K$

Mingying Zhong

The pointwise space-time behaviors of the Green's function and the global solution to the Vlasov-Poisson-Fokker-Planck (VPFP) system in spatial three dimension are studied in this paper. It is shown that the Green's function consists of the diffusion waves decaying exponentially in time but algebraically in space, and the singular kinetic waves which become

Zhou Huang, Chencheng Han, Abdusalam Abdukerim, Zihao Bo

We present the constraints on the axial-vector and pseudo-scalar mediated WIMP-nucleus interactions from the PandaX-4T experiment, using the data set corresponding to a total exposure of 0.63~tonne$\cdot$year. No significant signal excess is observed, and the most stringent upper limits to date on the spin-dependent WIMP-neutron scattering cross section are

Ramtin Madani, Mersedeh Ashraphijuo, Mohsen Kheirandishfard, Alper Atamturk

In the first part of this work [32], we introduce a convex parabolic relaxation for quadratically-constrained quadratic programs, along with a sequential penalized parabolic relaxation algorithm to recover near-optimal feasible solutions. In this second part, we show that starting from a feasible solution or a near-feasible solution satisfying certain regula

Honghui Yang, Zili Liu, Xiaopei Wu, Wenxiao Wang

Two-stage detectors have gained much popularity in 3D object detection. Most two-stage 3D detectors utilize grid points, voxel grids, or sampled keypoints for RoI feature extraction in the second stage. Such methods, however, are inefficient in handling unevenly distributed and sparse outdoor points. This paper solves this problem in three aspects. 1) Dynami

Yusuke Sakai, Yousuke Itoh, Piljong Jung, Keiko Kokeyama

Transient noise appearing in the data from gravitational-wave detectors frequently causes problems, such as instability of the detectors and overlapping or mimicking gravitational-wave signals. Because transient noise is considered to be associated with the environment and instrument, its classification would help to understand its origin and improve the det

Ramtin Madani, Mersedeh Ashraphijuo, Mohsen Kheirandishfard, Alper Atamturk

For general quadratically-constrained quadratic programming (QCQP), we propose a parabolic relaxation described with convex quadratic constraints. An interesting property of the parabolic relaxation is that the original non-convex feasible set is contained on the boundary of the parabolic relaxation. Under certain assumptions, this property enables one to re

Khadija Zanna, Kusha Sridhar, Han Yu, Akane Sano

There has been an increase in research in developing machine learning models for mental health detection or prediction in recent years due to increased mental health issues in society. Effective use of mental health prediction or detection models can help mental health practitioners re-define mental illnesses more objectively than currently done, and identif

Keshav Bhandari, Bin Duan, Gaowen Liu, Hugo Latapie

Optical flow estimation in omnidirectional videos faces two significant issues: the lack of benchmark datasets and the challenge of adapting perspective video-based methods to accommodate the omnidirectional nature. This paper proposes the first perceptually natural-synthetic omnidirectional benchmark dataset with a 360-degree field of view, FLOW360, with 40

Junyan Zhao

Let $X$ be the blow-up of $\mathbb{P}^2$ along $m$ general points, and $A=H-\sum \varepsilon_iE_i$ be a generic polarization with $0<\varepsilon_i\ll1$. We classify the Chern characters which satisfy the weak Brill-Noether property, i.e. a general sheaf in $M_A({\bf{v}})$, the moduli space of slope stable sheaves with Chern character ${\bf{v}}$, has at most

Akram Shafie, Chunhui Li, Nan Yang, Xiangyun Zhou

We propose a new spectrum allocation strategy, aided by unsupervised learning, for multiuser terahertz communication systems. In this strategy, adaptive sub-band bandwidth is considered such that the spectrum of interest can be divided into sub-bands with unequal bandwidths. This strategy reduces the variation in molecular absorption loss among the users, le

Zaifa Xue, Huibin Lu, Tao Zhang, Max A. Little

Dysphonia is one of the early symptoms of Parkinson's disease (PD). Most existing methods use feature selection methods to find the optimal subset of voice features for all PD patients. Few have considered the heterogeneity between patients, which implies the need to provide specific prediction models for different patients. However, building the specific mo