December 2020 arXiv papers — page 42

Nils Wandel, Michael Weinmann, Reinhard Klein

Physically plausible fluid simulations play an important role in modern computer graphics and engineering. However, in order to achieve real-time performance, computational speed needs to be traded-off with physical accuracy. Surrogate fluid models based on neural networks have the potential to achieve both, fast fluid simulations and high physical accuracy.

Xilin Yang, Luzhe Huang, Yilin Luo, Yichen Wu

We present a virtual image refocusing method over an extended depth of field (DOF) enabled by cascaded neural networks and a double-helix point-spread function (DH-PSF). This network model, referred to as W-Net, is composed of two cascaded generator and discriminator network pairs. The first generator network learns to virtually refocus an input image onto a

Vincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard, Christian Sohler

$k$-means++ \cite{arthur2007k} is a widely used clustering algorithm that is easy to implement, has nice theoretical guarantees and strong empirical performance. Despite its wide adoption, $k$-means++ sometimes suffers from being slow on large data-sets so a natural question has been to obtain more efficient algorithms with similar guarantees. In this paper,

Nastaran Hajinazar, Geraldo F. Oliveira, Sven Gregorio, João Dinis Ferreira

Processing-using-DRAM has been proposed for a limited set of basic operations (i.e., logic operations, addition). However, in order to enable the full adoption of processing-using-DRAM, it is necessary to provide support for more complex operations. In this paper, we propose SIMDRAM, a flexible general-purpose processing-using-DRAM framework that enables mas

Dongyang Xing, Suyan Tian, Yukun Chen, Jinmei Wang

Background: Coronavirus disease 2019 (COVID-19) and Influenza A are common disease caused by viral infection. The clinical symptoms and transmission routes of the two diseases are similar. However, there are no relevant studies on laboratory diagnostic models to discriminate COVID-19 and influenza A. This study aims at establishing a signature of laboratory

Oylum Şeker, Neda Tanoumand, Merve Bodur

Digital Annealer (DA) is a computer architecture designed for tackling combinatorial optimization problems formulated as quadratic unconstrained binary optimization (QUBO) models. In this paper, we present the results of an extensive computational study to evaluate the performance of DA in a systematic way in comparison to multiple state-of-the-art solvers f

V. P. Berezovoj, M. I. Konchatnij, A. J. Nurmagambetov

We study features of tunneling dynamics in an exactly-solvable model of N=4 supersymmetric quantum mechanics with a multi-well potential and with broken reflective symmetry. Quantum systems with a phenomenological potential of this type demonstrate the phenomenon of partial localization of under-barrier states, possibly resulting in the appearance of the so-

Shuyan Hu, Wei Ni, Xin Wang, Abbas Jamalipour

Autonomous tracking of suspicious unmanned aerial vehicles (UAVs) by legitimate monitoring UAVs (or monitors) can be crucial to public safety and security. It is non-trivial to optimize the trajectory of a monitor while conceiving its monitoring intention, due to typically non-convex propulsion and thrust power functions. This paper presents a novel framewor

Pavel Yu. Moshin, Alexander A. Reshetnyak, Ricardo A. Castro

Non-Abelian gauge theories with composite fields are examined in the background field method. Generating functionals of Green's functions for a Yang--Mills theory with composite and background fields are introduced, including the generating functional of vertex Green's functions (effective action). The corresponding Ward identities are obtained, and the issu

Chao-Yang Tan, Chang-Xu Yan, Yong-Hong Zhao, Hong Guo

1T$^\prime$-MoS$_2$ exhibits valley-spin-polarized tilted Dirac bands in the presence of external vertical electric field and undergoes a topological phase transition between the topological insulator and band insulator around the critical value of the electric field. Within the linear response theory, we theoretically investigate the anisotropic longitudina

Luca Chirolli, Joel E. Moore

In superconducting circuits interrupted by Josephson junctions, the dependence of the energy spectrum on offset charges on different islands is $2e$ periodic through the Aharonov-Casher effect and resembles a crystal band structure that reflects the symmetries of the Josephson potential. We show that higher-harmonic Josephson elements described by a $\cos(2\

Zhangquan Xie, Jun Cao, Yayun Ding, Mengchao Liu

A liquid scintillator (LS) is developed for the Taishan Antineutrino Observatory (TAO), a ton-level neutrino detector to measure the reactor antineutrino spectrum with sub-percent energy resolution by adopting Silicon Photomultipliers (SiPMs) as photosensor. To reduce the dark noise of SiPMs to an acceptable level, the LS has to work at -50 degree or lower.

Xiang Liu, Deborah Cohen, Tianyao Huang, Yimin Liu

Pulse Doppler radars suffer from range-Doppler ambiguity that translates into a trade-off between maximal unambiguous range and velocity. Several techniques, like the multiple PRFs (MPRF) method, have been proposed to mitigate this problem. The drawback of the MPRF method is that the received samples are not processed jointly, decreasing signal to noise rati

Sharath Nittur Sridhar, Anthony Sarah

In recent times, BERT-based models have been extremely successful in solving a variety of natural language processing (NLP) tasks such as reading comprehension, natural language inference, sentiment analysis, etc. All BERT-based architectures have a self-attention block followed by a block of intermediate layers as the basic building component. However, a st

Anvar Imomkulov

In this paper we construct some families of three-dimensional evolution algebras which satisfies Chapman-Kolmogorov equation. For all of these chains we study the behavior of the baric property, the behavior of the set of absolute nilpotent elements and dynamics of the set of idempotent elements depending on the time.

Tomohiro Ikkai, Hiromichi Ohno, Yusuke Sawada

A pointed graph $(\Gamma,v_0)$ induces a family of transition matrices in Wildberger's construction of a hermitian hypergroup via a random walk on $\Gamma$ starting from $v_0$. We will give a necessary condition for producing a hermitian hypergroup as we assume a weaker condition than the distance-regularity for $(\Gamma,v_0)$. The condition obtained in this

Zequn Qin, Pengyi Zhang, Fei Wu, Xi Li

Attention mechanism, especially channel attention, has gained great success in the computer vision field. Many works focus on how to design efficient channel attention mechanisms while ignoring a fundamental problem, i.e., channel attention mechanism uses scalar to represent channel, which is difficult due to massive information loss. In this work, we start

Leonard Yoon, Dongseok Yang, Jaehyun Kim, Choongho Chung

Rapidly developing technologies are realizing a 3D telepresence, in which geographically separated users can interact with each other through their virtual avatars. In this paper, we present novel methods to determine the avatar's position in an indoor space to preserve the semantics of the user's position in a dissimilar indoor space with different space co

Connor Paul Wilson

We note an interesting and under-expressed fact from Chebyshev's initial bounding for the prime counting function, $\pi(x) := \# \{p \leq x : p \text{ prime}\},$ based upon a selection of fixed coefficients $d\in D$ to show $\psi(x) \asymp x$, and thus the goal of choosing some $a(d)$ approximately the same as $\mu(d)$ such that: $$ \sum_{d}\frac{a(d)}{d} =

Aria Rezaei, Jie Gao, Anand D. Sarwate

The presence of correlation is known to make privacy protection more difficult. We investigate the privacy of socially contagious attributes on a network of individuals, where each individual possessing that attribute may influence a number of others into adopting it. We show that for contagions following the Independent Cascade model there exists a giant co

Salman Mousaeirad

Customer Segmentation is the process of dividing customers into groups based on common characteristics. An intelligent Customer Segmentation will not only enable an organization to effectively allocate marketing resources (e.g., Recommender Systems in the Banking sector) but also it will enable identifying the customer cohorts that are most likely to benefit

Dongfen Bian, Shouyi Dai, Jingjing Mao

In this paper, we consider the Boussinesq equations with magnetohydrodynamics convection in the domain $\mathbb{T} \times \mathbb{R}$ and establishes the nonlinear stability of the Couette flow $(\mathbf{u}_{sh} = (y,0), \mathbf{b}_{sh} = (1,0), p_{sh} = 0, \theta_{sh} = 0$). The novelty in this paper is that we design a new Fourier multiplier operator by us

You-Lin Chen, Yu-Chin Lu, Zhong-Xuan Lin, Tzonelih Hwang

This study points out a semi-quantum protocol for private comparison using Bell states (SQPC) suffering from the double C-NOT attack and the malicious agent attack. The attacker can easily obtain information through these attacks. An improved protocol is proposed, which can effectively resist both of these attacks.

Ondřej Pejcha

The death of massive stars is shrouded in many mysteries. One of them is the mechanism that overturns the collapse of the degenerate iron core into an explosion, a process that determines the supernova explosion energy, properties of the surviving compact remnant, and the nucleosynthetic yields. The number of core-collapse supernova observations has been gro

Li Guo, Houyi Yu, Bin Zhang

As a natural basis of the Hopf algebra of quasisymmetric functions, monomial quasisymmetric functions are formal power series defined from compositions. The same definition applies to left weak compositions, while leads to divergence for other weak compositions. We adapt the method of renormalization in quantum field theory, in the framework of Connes and Kr

Kyung Kiu Kim, Jong-Hyun Baek, Yunseok Seo

In this paper we study a black hole phase transition in a generalized JT gravity noticed in arXiv:2006.03494. We investigate the effect of the phase transition on the Euclidean geodesic and holographic two-point function in models with dilaton potential which interpolates two ordinary JT gravities with different cosmological constants. It is noted that there

Khan Md. Hasib, Md. Sadiq Iqbal, Faisal Muhammad Shah, Jubayer Al Mahmud

The problem of class imbalance is extensive for focusing on numerous applications in the real world. In such a situation, nearly all of the examples are labeled as one class called majority class, while far fewer examples are labeled as the other class usually, the more important class is called minority. Over the last few years, several types of research ha

Zhi-Gang Wang

In this article, we investigate the mass spectrum of the ground state hidden-charm tetraquark molecular states without strange, with strange and with hidden-strange via the QCD sum rules in a comprehensive way and revisit the assignments of the $X$, $Y$, $Z$ states in the scenario of tetraquark molecular states consistently based on the QCD sum rules.

Jayita Chakraborty, Nirmal Ganguli

A major impediment towards realizing technologies based on the emerging principles of antiferromagnetic spintronics is the shortage of suitable materials. In this paper, we propose a design of polar|nonpolar heterostructures of perovskite oxides, where a single unit cell of SrIrO3 is sandwiched between a thin film of LaAlO3 and a substrate of SrTiO3. Our cal

Armen Aghajanyan, Luke Zettlemoyer, Sonal Gupta

Although pretrained language models can be fine-tuned to produce state-of-the-art results for a very wide range of language understanding tasks, the dynamics of this process are not well understood, especially in the low data regime. Why can we use relatively vanilla gradient descent algorithms (e.g., without strong regularization) to tune a model with hundr

Inaam Ilahi, Muhammad Usama, Muhammad Omer Farooq, Muhammad Umar Janjua

The anticipated increase in the count of IoT devices in the coming years motivates the development of efficient algorithms that can help in their effective management while keeping the power consumption low. In this paper, we propose an intelligent multi-channel resource allocation algorithm for dense LoRa networks termed LoRaDRL and provide a detailed perfo

Xian Yang, Shuo Wang, Yuting Xing, Ling Li

The evolution of epidemiological parameters, such as instantaneous reproduction number Rt, is important for understanding the transmission dynamics of infectious diseases. Current estimates of time-varying epidemiological parameters often face problems such as lagging observations, averaging inference, and improper quantification of uncertainties. To address

Zehua Sun, Qiuhong Ke, Hossein Rahmani, Mohammed Bennamoun

Human Action Recognition (HAR) aims to understand human behavior and assign a label to each action. It has a wide range of applications, and therefore has been attracting increasing attention in the field of computer vision. Human actions can be represented using various data modalities, such as RGB, skeleton, depth, infrared, point cloud, event stream, audi

Hyun Il Seo, Sungmin Woo, Jihyun Kim, Seung Gyo Jeong

SrRuO3 (SRO) is an itinerant ferromagnet with strong coupling between the charge, spin, and lattice degrees of freedom. This strong coupling suggests that the electronic and magnetic behaviors of SRO are highly susceptible to changes in the lattice distortion. Here we show how the spin interaction and resultant magnon formation change with the modification i

Stefano Tomasi, Dominic M. Rouse, Erik M. Gauger, Brendon W. Lovett

Coherence-enhanced light harvesting has not been directly observed experimentally, despite theoretical evidence that coherence can significantly enhance light-harvesting performance. The main experimental obstacle has been the difficulty in isolating the effect of coherence in the presence of confounding variables. Recent proposals for externally controlling

Ke Wang, Sai Ma, Junlan Chen, Jianbo Lu

Recently, the philosophy of visual saliency and attention has started to gain popularity in the robotics community. Therefore, this paper aims to mimic this mechanism in SLAM framework by using saliency prediction model. Comparing with traditional SLAM that treated all feature points as equal important in optimization process, we think that the salient featu

Zoltán M. Balogh, Alexandru Kristály

By using optimal mass transport theory we prove a sharp isoperimetric inequality in ${\sf CD} (0,N)$ metric measure spaces assuming an asymptotic volume growth at infinity. Our result extends recently proven isoperimetric inequalities for normed spaces and Riemannian manifolds to a nonsmooth framework. In the case of $n$-dimensional Riemannian manifolds with

Yasuyoshi Ito, Masaki Ogawa

In this paper, we consider decompositions of 3-manifolds with three handlebodies. We classify such decompositions of the 3-sphere and lens spaces with small genera. These decompositions admit operations called stabilizations. We also determine whether these decompositions are stabilized.

Aksh Garg, Sana Salehi, Marianna La Rocca, Rachael Garner

With COVID-19 cases rising rapidly, deep learning has emerged as a promising diagnosis technique. However, identifying the most accurate models to characterize COVID-19 patients is challenging because comparing results obtained with different types of data and acquisition processes is non-trivial. In this paper we designed, evaluated, and compared the perfor

Jiesen Wang, Yoni Nazarathy, Thomas Taimre

We consider a collection of statistically identical two-state continuous time Markov chains (channels). A controller continuously selects a channel with the view of maximizing infinite horizon average reward. A switching cost is paid upon channel changes. We consider two cases: full observation (all channels observed simultaneously) and partial observation (

Tomohiro Ishikawa, Shoki Iwaguchi, Yuta Michimura, Masaki Ando

DECIGO is the future Japanese gravitational wave detector in outer space. We previously set the default design parameters to provide a good target sensitivity to detect the primordial gravitational waves (GWs). However, the updated upper limit of the primordial GWs by the Planck observations motivated us for further optimization of the target sensitivity. Pr

Sandeep Ranjan

TV serials are a popular source of entertainment. The ongoing COVID19 lockdown has a high probability of degrading the publics mental health. The Government of India started the retelecast of yesteryears popular TV serials on public broadcaster Doordarshan from 28th March 2020 to 31st July 2020. Tweets corresponding to the Doordarshan hashtag were mined to c

Sanjay Ghosh, Arpan Garai

Image downscaling is one of the widely used operations in image processing and computer graphics. It was recently demonstrated in the literature that kernel-based convolutional filters could be modified to develop efficient image downscaling algorithms. In this work, we present a new downscaling technique which is based on kernel-based image filtering concep

Mamikon Gulian, Ari Frankel, Laura Swiler

We develop a framework for Gaussian processes regression constrained by boundary value problems. The framework may be applied to infer the solution of a well-posed boundary value problem with a known second-order differential operator and boundary conditions, but for which only scattered observations of the source term are available. Scattered observations o

Xianxu Hou, Xiaokang Zhang, Linlin Shen, Zhihui Lai

Although significant progress has been made in synthesizing high-quality and visually realistic face images by unconditional Generative Adversarial Networks (GANs), there still lacks of control over the generation process in order to achieve semantic face editing. In addition, it remains very challenging to maintain other face information untouched while edi

Yuan Zheng, Xueming Shao, Zheng Chen, Wenjie Zhao

This paper is concerned with a Minimum-Time Intercept Problem (MTIP), for which a Dubins vehicle is guided from a position with a prescribed initial orientation angle to intercept a moving target in minimum time. Some geometric properties for the solution of the MTIP are presented, showing that the solution path must lie in a sufficient family of 4 candidate

Zhaowei Zhu, Tongliang Liu, Yang Liu

The presence of label noise often misleads the training of deep neural networks. Departing from the recent literature which largely assumes the label noise rate is only determined by the true label class, the errors in human-annotated labels are more likely to be dependent on the difficulty levels of tasks, resulting in settings with instance-dependent label

Lukas Bolte, Nicole Immorlica, Matthew O. Jackson

We study the consequences of job markets' heavy reliance on referrals. Referrals lead to more opportunities for workers to be hired, which lead to better matches and increased productivity, but also disadvantage job-seekers with few or no connections to employed workers, increasing inequality. Coupled with homophily, referrals also lead to immobility. We ide

A. A. Katanin

We study momentum dependence of static magnetic susceptibility $\chi(q)$ in paramagnetic phase of Heisenberg magnets and its relation to critical behavior within nonlinear sigma model (NLSM) at arbitrary dimension $2<d<4$. In the first order of $1/N$ expansion, where $N$ is the number of spin components, we find $\chi(q)\propto[q^{2}+\xi^{-2}(1+f(q\xi ))]^{-

Jong-Phil Lee

We analyze the $B$ anomalies associated with the $B\to D^{(*)}\tau\nu$ decays in the unparticle model. The fraction of the branching ratios $R(D^{(*)})$ and other parameters related to the polarization are fitted to the experimental data by minimizing $\chi^2$. The best-fit values are $R(D)_{\rm best}=0.371$ and $R(D^*)_{\rm best}=0.266$ which are still larg

Jun Ikeda, Hiroyuki Seshime, Xueting Wang, Toshihiko Yamasaki

With expansion of the video advertising market, research to predict the effects of video advertising is getting more attention. Although effect prediction of image advertising has been explored a lot, prediction for video advertising is still challenging with seldom research. In this research, we propose a method for predicting the click through rate (CTR) o

Shiqi Sheng, Haijun Yang, Liuhua Mu, Zixin Wang

We experimentally demonstrated that the AYFFF self-assemblies adsorbed with various monovalent cations (Na+, K+, and Li+) show unexpectedly super strong paramagnetism. The key to the super strong paramagnetism lies in the hydrated cation-{\pi} interactions between the monovalent cations and the aromatic rings in the AYFFF assemblies, which endows the AYFFF-c

Tomohiro Hayase, Suguru Yasutomi, Takashi Katoh

Selective forgetting or removing information from deep neural networks (DNNs) is essential for continual learning and is challenging in controlling the DNNs. Such forgetting is crucial also in a practical sense since the deployed DNNs may be trained on the data with outliers, poisoned by attackers, or with leaked/sensitive information. In this paper, we form

Shuchen Guo

We study stochastic SQG equations on the torus $\mathbb{T}^2$ with multiplicative transport noise in the $L^2$-setting. Under a suitable scaling of the noise, we show that the solutions converge weakly to the unique solution to the deterministic dissipative SQG equation. A similar scaling limit result is proved also for the stochastic 2D inviscid critical Bo

Liye Mei, Yalan Yu, Yueyun Weng, Xiaopeng Guo

Chromosome karyotype analysis is of great clinical importance in the diagnosis and treatment of diseases, especially for genetic diseases. Since manual analysis is highly time and effort consuming, computer-assisted automatic chromosome karyotype analysis based on images is routinely used to improve the efficiency and accuracy of the analysis. Due to the str

Yuto Aizawa, Masato Kimura, Kazunori Matsui

We prove a universal approximation property (UAP) for a class of ODENet and a class of ResNet, which are simplified mathematical models for deep learning systems with skip connections. The UAP can be stated as follows. Let $n$ and $m$ be the dimension of input and output data, and assume $m\leq n$. Then we show that ODENet of width $n+m$ with any non-polynom

Joseph Gubeladze

We show that: (1) unimodular simplices in a lattice 3-polytope cover a neighborhood of the boundary of the polytope if and only if the polytope is very ample, (2) the convex hull of lattice points in every ellipsoid in R^3 has a unimodular cover, and (3) for every d at least 5, there are ellipsoids in R^d, such that the convex hulls of the lattice points in

Lue Pan

We show that the action of Hecke operators away from $p$ on the space of ($p$-adic) overconvergent modular forms is ($p$-adically) locally analytic in a certain sense. As a corollary, the action of the Hecke algebra can be extended naturally to an action of rigid functions on its generic fiber. This directly determines the Hodge-Tate-Sen weights of Galois re

Matthew O. Jackson, Agathe Pernoud

We analyze how interdependencies between organizations in financial networks can lead to multiple possible equilibrium outcomes. A multiplicity arises if and only if there exists a certain type of dependency cycle in the network that allows for self-fulfilling chains of defaults. We provide necessary and sufficient conditions for banks' solvency in any equil

Hong Guo, Xiao-Mei Kuang, Eleftherios Papantonopoulos, Bin Wang

Black hole spontaneous scalarization has been attracting more and more attention as it circumvents the well-known no-hair theorems. In this work, we study the scalarization in Einstein-scalar-Gauss-Bonnet theory with a probe scalar field in a black hole background with different curvatures. We first probe the signal of black hole scalarization with positive

Eric D'Hoker, Thomas T. Dumitrescu, Efrat Gerchkovitz, Emily Nardoni

Motivated by applications to soft supersymmetry breaking, we revisit the expansion of the Seiberg-Witten solution around the multi-monopole point on the Coulomb branch of pure $SU(N)$ $\mathcal{N}=2$ gauge theory in four dimensions. At this point $N-1$ mutually local magnetic monopoles become massless simultaneously, and in a suitable duality frame the gauge

Matthew O. Jackson, Agathe Pernoud

We provide an overview of the relationship between financial networks and systemic risk. We present a taxonomy of different types of systemic risk, differentiating between direct externalities between financial organizations (e.g., defaults, correlated portfolios and firesales), and perceptions and feedback effects (e.g., bank runs, credit freezes). We also

Runsheng Yu, Yu Gong, Xu He, Bo An

A common challenge in personalized user preference prediction is the cold-start problem. Due to the lack of user-item interactions, directly learning from the new users' log data causes serious over-fitting problem. Recently, many existing studies regard the cold-start personalized preference prediction as a few-shot learning problem, where each user is the

Ye-Ming Meng, Jing Zhang, Peng Zhang, Chao Gao

Tensor network, which originates from quantum physics, is emerging as an efficient tool for classical and quantum machine learning. Nevertheless, there still exists a considerable accuracy gap between tensor network and the sophisticated neural network models for classical machine learning. In this work, we combine the ideas of matrix product state (MPS), th

Hamzeh Asgharnezhad, Afshar Shamsi, Roohallah Alizadehsani, Abbas Khosravi

Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of these networks is always questionable due to being developed using small datasets and failing to report their

Fu Li, Tian Li, Girish S. Agarwal

Decoherence remains one of the most serious challenges to the implementation of quantum technology. It appears as a result of the transformation over time of a quantum superposition state into a classical mixture due to the quantum system interacting with the environment. Since quantum systems are never completely isolated from their environment, decoherence

Henry Setiyanto, Muhammad Muslim Syaifullah, I Made Adyatmika, Dian Ayu Setyorini

Nonylphenol ethoxylate (NPE 10) is a non ionic surfactant which is synthesized from alkylphenol ethoxylate. The accumulation of NPE-10 in wastewater will endanger the ecosystem as well as human being. At present, by an advancement of technology NPE 10 can be degraded indirectly by using an electrochemically treatment. Thus, this study aimed to evaluate the p

Randell Heyman

Let $x$ be a positive integer. We give an asymptotic result for $\omega(\operatorname{lcm}(m,n))$ summed over all positive integers $m$ and $n$ with $mn \le x$. This answers an open question posed in a recent paper.

Narayanaswamy Balakrishnan, Ritwik Bhattacharya

In life-testing experiments, it is often of interest to predict unobserved future failure times based on observed early failure times. A point best linear unbiased predictor (BLUP) has been developed in this context by Kaminsky and Nelson (1975). In this article, we develop joint BLUPs of two future failure times based on early failure times by minimizing th

Xuefei Ning, Junbo Zhao, Wenshuo Li, Tianchen Zhao

Convolutional neural networks (CNNs) are vulnerable to adversarial examples, and studies show that increasing the model capacity of an architecture topology (e.g., width expansion) can bring consistent robustness improvements. This reveals a clear robustness-efficiency trade-off that should be considered in architecture design. In this paper, considering sce

Teguh Budianto, Tomohiro Nakai, Kazunori Imoto, Takahiro Takimoto

Generative adversarial networks (GANs) have shown promise for various problems including anomaly detection. When anomaly detection is performed using GAN models that learn only the features of normal data samples, data that are not similar to normal data are detected as abnormal samples. The present approach is developed by employing a dual-encoder in a bidi

Yu Zheng, Duyu Chen, Lei liu, Houlong Zhuang

We discover two distinct topological pathways through which the pentagonal Cairo tiling (P5), a structural model for single-layer $AB_2$ pyrite materials, respectively transforms into a crystalline rhombus-hexagon (C46) tiling and random rhombus-pentagon-hexagon (R456) tilings, by continuously introducing the Stone-Wales (SW) topological defects. We find the

Stephen Whitelam, Isaac Tamblyn

Within simulations of molecules deposited on a surface we show that neuroevolutionary learning can design particles and time-dependent protocols to promote self-assembly, without input from physical concepts such as thermal equilibrium or mechanical stability and without prior knowledge of candidate or competing structures. The learning algorithm is capable

Cesar Bartolo-Perez, Wayesh Qarony, Soroush Ghandiparsi, Ahmed S. Mayet

Silicon photodetectors operating at near-infrared wavelengths with high-speed and high sensitivity are becoming critical for emerging applications, such as Light Detection and Ranging Systems (LIDAR), quantum communications, and medical imaging. However, such photodetectors present a bandwidth-absorption trade-off at those wavelengths that have limited their

Thejs Brinckmann, Jae Hyeok Chang, Marilena LoVerde

We perform a comprehensive study of cosmological constraints on non-standard neutrino self-interactions using cosmic microwave background (CMB) and baryon acoustic oscillation data. We consider different scenarios for neutrino self-interactions distinguished by the fraction of neutrino states allowed to participate in self-interactions and how the relativist

Nicolò Burzillà, Breno L. Giacchini, Tibério de Paula Netto, Leonardo Modesto

In the present work we investigate the Newtonian limit of higher-derivative gravity theories with more than four derivatives in the action, including the non-analytic logarithmic terms resulting from one-loop quantum corrections. The first part of the paper deals with the occurrence of curvature singularities of the metric in the classical models. It is show

Hui Chen, Hongkuan Zhang, Qian Wu, Yu Huang

Synthetic dimensions can be rendered in the physical space and this has been achieved with photonics and cold atomic gases, however, little to no work has been succeeded in acoustics because acoustic wave-guides cannot be weakly coupled in a continuous fashion. Here, we establish the theoretical principles and for the first time manufacture acoustic crystals

Alberto Takase

We consider separable 2D discrete Schr\"odinger operators generated by 1D almost Mathieu operators. For fixed Diophantine frequencies we prove that for sufficiently small couplings the spectrum must be an interval. This complements a result by J. Bourgain establishing that for fixed couplings the spectrum has gaps for some (positive measure) Diophantine freq

Anupam Kundu, Mohsen Pourahmadi

Estimating the unconstrained mean and covariance matrix is a popular topic in statistics. However, estimation of the parameters of $N_p(\mu,\Sigma)$ under joint constraints such as $\Sigma\mu = \mu$ has not received much attention. It can be viewed as a multivariate counterpart of the classical estimation problem in the $N(\theta,\theta^2)$ distribution. In

Isao Shoji, Masahiro Nozawa

A geometric method to analyze nonlinear oscillations is discussed. We consider a nonlinear oscillation modeled by a second order ordinary differential equation without specifying the function form. By transforming the differential equation into the system of first order ordinary differential equations, the trajectory is embedded in $R^3$ as a curve, and ther

Zhengxi Chen, Xun Shen

A disturbance-aware predictive control policy is proposed for DC-AC power inverters with the receding horizon optimization approach. First, a discrete event-driven hybrid automaton model has been constructed for the nonlinear inverter system dynamics. A control problem of infinite discrete state-space transition sequence optimization is formulated. A recedin

Alla V. Bezvershenko, Catalin-Mihai Halati, Ameneh Sheikhan, Corinna Kollath

In recent years, one important experimental achievement was the strong coupling of quantum matter and quantum light. Realizations reach from ultracold atomic gases in high-finesse optical resonators to electronic systems coupled to THz cavities. The dissipative nature of the quantum light field and the global coupling to the quantum matter leads to many exci

Ryusuke Hamazaki

Extending notions of phase transitions to nonequilibrium realm is a fundamental problem for statistical mechanics. While it was discovered that critical transitions occur even for transient states before relaxation as the singularity of a dynamical version of free energy, their nature is yet to be elusive. Here, we show that spontaneous symmetry breaking can

Sorour E. Amiri, Bijaya Adhikari, John Wenskovitch, Alexander Rodriguez

Generating useful network summaries is a challenging and important problem with several applications like sensemaking, visualization, and compression. However, most of the current work in this space do not take human feedback into account while generating summaries. Consider an intelligence analysis scenario, where the analyst is exploring a similarity netwo

Soujanya Poria, Navonil Majumder, Devamanyu Hazarika, Deepanway Ghosal

We address the problem of recognizing emotion cause in conversations, define two novel sub-tasks of this problem, and provide a corresponding dialogue-level dataset, along with strong Transformer-based baselines. The dataset is available at https://github.com/declare-lab/RECCON. Introduction: Recognizing the cause behind emotions in text is a fundamental yet

Md Ashikuzzaman, Noushin Jafarpisheh, Sunil Rottoo, Pierre Brisson

Intraoperative tracking of surgical instruments is an inevitable task of computer-assisted surgery. An optical tracking system often fails to precisely reconstruct the dynamic location and pose of a surgical tool due to the acquisition noise and measurement variance. Embedding a Kalman Filter (KF) or any of its extensions such as extended and unscented Kalma

Xinwen Shu, Wenjie Zhang, Shuo Li, Ning Jiang

Optical transient surveys have led to the discovery of dozens of stellar tidal disruption events (TDEs) by massive black hole in the centers of galaxies. Despite extensive searches, X-ray follow-up observations have produced no or only weak X-ray detections in most of them. Here we report the discovery of delayed X-ray brightening around 140 days after the o

Ana M. Calle, Pedro A. Orellana, Jorge A. Otalora

In this work, we investigate the conductance and current correlations properties of a quantum topological inteferometer consisting of a QD coupled to two Majorana Bound States (MBSs) confined at both ends of a 1D topological superconductor ring nanowire. We analyze the ring in its topological non trivial and trivial phases to show that the tunneling conducta

Jun Zhang, Yao-Kun Lei, Yaqiang Zhou, Yi Isaac Yang

Deep learning is changing many areas in molecular physics, and it has shown great potential to deliver new solutions to challenging molecular modeling problems. Along with this trend arises the increasing demand of expressive and versatile neural network architectures which are compatible with molecular systems. A new deep neural network architecture, Molecu

Ben-Yang Li, Fang Chen, Heng-Na Xiong, Ling Tang

We did extensive research for the typical nanolaminate Mn+1AXn (n=1, 2, 3) ceramics focusing on the structural stability, the phase transition pressure of Ti2GaN (160 GPa) is far higher than that of Zr2GaN (92 GPa), meaning the strong M dependence of the same group, whereas Zr2AlN (98 GPa) has similar value with that of Zr2GaN, meaning the weak A dependence.

Anton Petrunin, Sergio Zamora Barrera

These notes are designed for those who either plan to work in differential geometry, or at least want to have a good reason not to do it. We discuss smooth curves and surfaces -- the main gate to differential geometry. We focus on the techniques that are absolutely essential for further study, keeping it problem-centered, elementary, visual, and virtually ri

Iain Beaton, Jason I. Brown

A polynomial is said to be unimodal if its coefficients are non-decreasing and then non-increasing. The domination polynomial of a graph $G$ is the generating function of the number of domination sets of each cardinality in $G$, and its coefficients have been conjectured to be unimodal. In this paper we will show the domination polynomial of paths, cycles an

Shuang Zhou, Lingchao Guo, Zhaoming Lu, Xiangming Wen

Recently, commodity Wi-Fi devices have been shown to be able to construct human pose images, i.e., human skeletons, as fine-grained as cameras. Existing papers achieve good results when constructing the images of subjects who are in the prior training samples. However, the performance drops when it comes to new subjects, i.e., the subjects who are not in the

Thomas Barthelmé, Kathryn Mann

We prove a rigidity result for group actions on the line whose elements have what we call "hyperbolic-like" dynamics. Using this, we give a spectral rigidity theorem for $\mathbb{R}$-covered Anosov flows on 3-manifolds, characterizing orbit equivalent flows in terms of the elements of the fundamental group represented by periodic orbits. As consequences of t

Thomas Schaefer

A new experiment (P. B. Patel et al., Science 370 (2020) 6521, 1222) involving resonantly interacting atoms confined by laser beams sheds light on momentum and energy diffusion in quantum fluids.

Haoyu He, Jing Zhang, Bhavani Thuraisingham, Dacheng Tao

Prior human parsing models are limited to parsing humans into classes pre-defined in the training data, which is not flexible to generalize to unseen classes, e.g., new clothing in fashion analysis. In this paper, we propose a new problem named one-shot human parsing (OSHP) that requires to parse human into an open set of reference classes defined by any sin

Rida Benhaddou

We look into the nonparametric regression estimation with additive and multiplicative noise and construct adaptive thresholding estimators based on Laguerre series. The proposed approach achieves asymptotically near-optimal convergence rates when the unknown function belongs to Laguerre-Sobolev space. We consider the problem under two noise structures; (1) {

Jiho Noh, Ramakanth Kavuluru

Biomedical word embeddings are usually pre-trained on free text corpora with neural methods that capture local and global distributional properties. They are leveraged in downstream tasks using various neural architectures that are designed to optimize task-specific objectives that might further tune such embeddings. Since 2018, however, there is a marked sh

Ruichu Cai, Zijian Li, Pengfei Wei, Jie Qiao

Domain adaptation is an important but challenging task. Most of the existing domain adaptation methods struggle to extract the domain-invariant representation on the feature space with entangling domain information and semantic information. Different from previous efforts on the entangled feature space, we aim to extract the domain invariant semantic informa

Yu Cheng, Bo Wang, Bo Yang, Robby T. Tan

Despite the recent progress, 3D multi-person pose estimation from monocular videos is still challenging due to the commonly encountered problem of missing information caused by occlusion, partially out-of-frame target persons, and inaccurate person detection. To tackle this problem, we propose a novel framework integrating graph convolutional networks (GCNs)