November 2019 arXiv papers — page 40

Ruturaj Gole, Haixia Wu, Subho Ghose

Ultrasound images are one of the most widely used techniques in clinical settings to analyze and detect different organs for study or diagnoses of diseases. The dependence on subjective opinions of experts such as radiologists calls for an automatic recognition and detection system that can provide an objective analysis. Previous work done on this topic is l

Oishik Chatterjee, Ganesh Ramakrishnan, Sunita Sarawagi

Scarcity of labeled data is a bottleneck for supervised learning models. A paradigm that has evolved for dealing with this problem is data programming. An existing data programming paradigm allows human supervision to be provided as a set of discrete labeling functions (LF) that output possibly noisy labels to input instances and a generative modelfor consol

Oleksandr Kravets

We study the categories of singularities coming from Landau-Ginzburg models given by the invertible polynomials. Such categories appear on the B-side of the Berglund-Hübsch mirror symmetry. We provide an efficient method of computing morphism spaces in these categories and explicitly construct full strongly exceptional collections in the cases of small dimen

Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor, Sid C. Bundy

In the area of credit risk analytics, current Bankruptcy Prediction Models (BPMs) struggle with (a) the availability of comprehensive and real-world data sets and (b) the presence of extreme class imbalance in the data (i.e., very few samples for the minority class) that degrades the performance of the prediction model. Moreover, little research has compared

Chao Liu, Heming Sun, Junan Chen, Zhengxue Cheng

In this paper, a dual learning-based method in intra coding is introduced for PCS Grand Challenge. This method is mainly composed of two parts: intra prediction and reconstruction filtering. They use different network structures, the neural network-based intra prediction uses the full-connected network to predict the block while the neural network-based reco

Shuangjian Guo, Xiaohui Zhang, Shengxiang Wang

Let $(L, α)$ be a Hom-Lie-Yamaguti superalgebra. We first introduce the representation and cohomology theory of Hom-Lie-Yamaguti superalgebras. Furthermore, we introduce the notions of generalized derivations and representations of $(L, α)$ and present some properties. Finally, we investigate the deformations of $(L, α)$ by choosing some suitable cohomology.

Arjun Singhvi, Kevin Houck, Arjun Balasubramanian, Mohammed Danish Shaikh

The increased use of micro-services to build web applications has spurred the rapid growth of Function-as-a-Service (FaaS) or serverless computing platforms. While FaaS simplifies provisioning and scaling for application developers, it introduces new challenges in resource management that need to be handled by the cloud provider. Our analysis of popular serv

Yuxiao Liu, Yi Wang, Pei Yong, Ning Zhang

Cascading failures have become a severe threat to interconnected modern power systems. The ultrahigh complexity of the interconnected networks is the main challenge toward the understanding and management of cascading failures. In addition, high penetration of wind power integration introduces large uncertainties and further complicates the problem into a ma

Dongdong Chen, Mohammad Golbabaee, Pedro A. Gomez, Marion I. Menzel

Magnetic Resonance Fingerprinting (MRF) methods typically rely on dictionary matching to map the temporal MRF signals to quantitative tissue parameters. These methods suffer from heavy storage and computation requirements as the dictionary size grows. To address these issues, we proposed an end to end fully convolutional neural network for MRF reconstruction

Jun Gao, Wei Bi, Xiaojiang Liu, Junhui Li

Neural conversation models such as encoder-decoder models are easy to generate bland and generic responses. Some researchers propose to use the conditional variational autoencoder(CVAE) which maximizes the lower bound on the conditional log-likelihood on a continuous latent variable. With different sampled la-tent variables, the model is expected to generate

Chao Zhao, Snigdha Chaturvedi

Opinion summarization from online product reviews is a challenging task, which involves identifying opinions related to various aspects of the product being reviewed. While previous works require additional human effort to identify relevant aspects, we instead apply domain knowledge from external sources to automatically achieve the same goal. This work prop

Hyoungjin Lim, Gwonsoo Che, Wonyeol Lee, Hongseok Yang

We present an algorithm for marginalising changepoints in time-series models that assume a fixed number of unknown changepoints. Our algorithm is differentiable with respect to its inputs, which are the values of latent random variables other than changepoints. Also, it runs in time O(mn) where n is the number of time steps and m the number of changepoints,

Tianyang Zhang, Rui Ma

Identify the cells' nuclei is the important point for most medical analyses. To assist doctors finding the accurate cell' nuclei location automatically is highly demanded in the clinical practice. Recently, fully convolutional neural network (FCNs) serve as the back-bone in many image segmentation, like liver and tumer segmentation in medical field,

Amir Zadeh, Chengfeng Mao, Kelly Shi, Yiwei Zhang

The complex world around us is inherently multimodal and sequential (continuous). Information is scattered across different modalities and requires multiple continuous sensors to be captured. As machine learning leaps towards better generalization to real world, multimodal sequential learning becomes a fundamental research area. Arguably, modeling arbitraril

Shengwen Yang, Bing Ren, Xuhui Zhou, Liping Liu

Federated Learning is a new distributed learning mechanism which allows model training on a large corpus of decentralized data owned by different data providers, without sharing or leakage of raw data. According to the characteristics of data dis-tribution, it could be usually classified into three categories: horizontal federated learning, vertical federate

Canran Xu, Ming Wu

Learning representations for feature interactions to model user behaviors is critical for recommendation system and click-trough rate (CTR) predictions. Recent advances in this area are empowered by deep learning methods which could learn sophisticated feature interactions and achieve the state-of-the-art result in an end-to-end manner. These approaches requ

Jing Pan, Weian Sheng, Santanu Dey

A unique challenge for e-commerce recommendation is that customers are often interested in products that are more advanced than their already purchased products, but not reversed. The few existing recommender systems modeling unidirectional sequence output a limited number of categories or continuous variables. To model the ordered sequence, we design the fi

Maziar Sanjabi, Sina Baharlouei, Meisam Razaviyayn, Jason D. Lee

We study the optimization problem for decomposing $d$ dimensional fourth-order Tensors with $k$ non-orthogonal components. We derive \textit{deterministic} conditions under which such a problem does not have spurious local minima. In particular, we show that if $κ= \frac{λ_{max}}{λ_{min}} < \frac{5}{4}$, and incoherence coefficient is of the order $O(\frac{1

Hiroaki Minoura, Ryo Yonetani, Mai Nishimura, Yoshitaka Ushiku

Forecasting human activities observed in videos is a long-standing challenge in computer vision, which leads to various real-world applications such as mobile robots, autonomous driving, and assistive systems. In this work, we present a new visual forecasting task called crowd density forecasting. Given a video of a crowd captured by a surveillance camera, o

Haris Aziz, Hau Chan, Barton E. Lee, Bo Li

We consider the facility location problem in the one-dimensional setting where each facility can serve a limited number of agents from the algorithmic and mechanism design perspectives. From the algorithmic perspective, we prove that the corresponding optimization problem, where the goal is to locate facilities to minimize either the total cost to all agents

M Saiful Bari, Shafiq Joty, Prathyusha Jwalapuram

Recently, neural methods have achieved state-of-the-art (SOTA) results in Named Entity Recognition (NER) tasks for many languages without the need for manually crafted features. However, these models still require manually annotated training data, which is not available for many languages. In this paper, we propose an unsupervised cross-lingual NER model tha

Frank Noé, Gianni De Fabritiis, Cecilia Clementi

Many aspects of the study of protein folding and dynamics have been affected by the recent advances in machine learning. Methods for the prediction of protein structures from their sequences are now heavily based on machine learning tools. The way simulations are performed to explore the energy landscape of protein systems is also changing as force-fields ar

Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen

Community question answering (CQA) gains increasing popularity in both academy and industry recently. However, the redundancy and lengthiness issues of crowdsourced answers limit the performance of answer selection and lead to reading difficulties and misunderstandings for community users. To solve these problems, we tackle the tasks of answer selection and

Sonali Patil, Tanmay Prakash, Bharath Comandur, Avinash Kak

Our goal here is threefold: [1] To present a new dense-stereo matching algorithm, tMGM, that by combining the hierarchical logic of tSGM with the support structure of MGM achieves 6-8\% performance improvement over the baseline SGM (these performance numbers are posted under tMGM-16 in the Middlebury Benchmark V3 ); and [2] Through an exhaustive quantitative

Ryoya Fukasaku, Michitaka Furuya, Akihiro Higashitani

For a graph $G$, let $χ(G)$ denote the chromatic number. In graph theory, the following famous conjecture posed by Hedetniemi has been studied: For two graphs $G$ and $H$, $χ(G\times H)=\min\{χ(G),χ(H)\}$, where $G \times H$ is the tensor product of $G$ and $H$. In this paper, we give a reduction of Hedetniemi&#39;s conjecture to an inclusion relation proble

M. Syafiq Johar

In this work, we are going to find sufficient conditions on the initial triaxial Bianchi IX metric on some 4-dimensional manifolds foliated by homogeneous S3 for a Type I singularity to occur when it is flowed under the Ricci flow. This work generalises the study on rotationally symmetric manifolds done by Angenent and Isenberg as well as the work of Isenber

Anum Ali, Nuria González-Prelcic, Robert W. Heath, Amitava Ghosh

Vehicle-to-everything (V2X) communication in the mmWave band is one way to achieve high data-rates for applications like infotainment, cooperative perception, and augmented reality assisted driving etc. MmWave communication relies on large antennas arrays, and configuring these arrays poses high training overhead. In this article, we motivate the use of infr

Jiahua Chen, Aneesha Manne, Rebecca Mendum, Poonam Sahoo

Many people believe that it is disadvantageous for members aligning with a minority party to cluster in cities, as this makes it easier for the majority party to gerrymander district boundaries to diminish the representation of the minority. We examine this effect by exhaustively computing the average representation for every possible $5\times 5$ grid of pop

L. Polcar, O. Semerák

Motivated by black holes surrounded by accretion structures, we consider in this series static and axially symmetric black holes &#34;perturbed&#34; gravitationally as being encircled by a thin disc or a ring. In previous papers, we employed several different methods to detect, classify and evaluate chaos which can occur, due to the presence of the additiona

Zhiwei Wang, Hui Liu, Jiliang Tang, Songfan Yang

Robust language processing systems are becoming increasingly important given the recent awareness of dangerous situations where brittle machine learning models can be easily broken with the presence of noises. In this paper, we introduce a robust word recognition framework that captures multi-level sequential dependencies in noised sentences. The proposed fr

Yuming Shang

The noisy labeling problem has been one of the major obstacles for distant supervised relation extraction. Existing approaches usually consider that the noisy sentences are useless and will harm the model&#39;s performance. Therefore, they mainly alleviate this problem by reducing the influence of noisy sentences, such as applying bag-level selective attenti

Ari Arapostathis, Hassan Hmedi, Guodong Pang

We study ergodic properties of Markovian multiclass many-server queues which are uniform over scheduling policies, as well as the size n of the system. The system is heavily loaded in the Halfin-Whitt regime, and the scheduling policies are work-conserving and preemptive. We provide a unified approach via a Lyapunov function method that establishes Foster-Ly

Guannan He, Rebecca Ciez, Panayiotis Moutis, Soummya Kar

The useful life of electrochemical energy storage (EES) is a critical factor to EES planning, operation, and economic assessment. Today, systems commonly assume a physical end-of-life criterion, retiring EES when the remaining capacity reaches a threshold below which the EES is of little use because of functionality degradation. Here, we propose an economic

Ming Zhu, Busra Celikkaya, Parminder Bhatia, Chandan K. Reddy

Entity linking is the task of linking mentions of named entities in natural language text, to entities in a curated knowledge-base. This is of significant importance in the biomedical domain, where it could be used to semantically annotate a large volume of clinical records and biomedical literature, to standardized concepts described in an ontology such as

Shahn Majid

We take a fresh look at the geometrization of logic using the recently developed tools of `quantum Riemannian geometry' applied in the digital case over the field $\Bbb F_2=\{0,1\}$, extending de Morgan duality to this context of differential forms and connections. The 1-forms correspond to graphs and the exterior derivative of a subset amounts to the arrows

D. Haskel, G. Fabbris, J. H. Kim, L. S. I. Veiga

The effect of compression on the magnetic ground state of Sr$_2$IrO$_4$ is studied with x-ray resonant techniques in the diamond anvil cell. The weak interlayer exchange coupling between square-planar 2D IrO$_2$ layers is readily modified upon compression, with a crossover between magnetic structures around 7 GPa mimicking the effect of an applied magnetic f

David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin

We improve the recently-proposed "MixMatch" semi-supervised learning algorithm by introducing two new techniques: distribution alignment and augmentation anchoring. Distribution alignment encourages the marginal distribution of predictions on unlabeled data to be close to the marginal distribution of ground-truth labels. Augmentation anchoring feeds multiple

K. D. Elworthy, Xue-Mei Li

We use a basic martingale method to show a differentiation formula for the derivatives $$d(P_tf)(x_0)(v_0)={1\over t} E f(x_t) \int_0^t \langle Y(x_s)(v_s),dB_t\rangle_{R^m}.$$ These are proved first on $R^n$, then on manifolds. Afterwards for solutions of heat equations on differential forms, and a second order formula.

Lu Jiang, Di Huang, Mason Liu, Weilong Yang

Performing controlled experiments on noisy data is essential in understanding deep learning across noise levels. Due to the lack of suitable datasets, previous research has only examined deep learning on controlled synthetic label noise, and real-world label noise has never been studied in a controlled setting. This paper makes three contributions. First, we

Ernst D. Larsson, Geng Dong, Valera Veryazov, Ulf Ryde

The lytic polysaccharide monooxygenase (LPMO) enzymes boost polysaccharide depolymerization through oxidative chemistry, which has fueled the hope for more energy-efficient production of biofuel. We have recently proposed a mechanism for the oxidation of the polysaccharide substrate (Hedeg{\aa}rd & Ryde, Chem. Sci. 2018, 9, 3866). In this mechanism, complexe

Lachlann McArthur, Melissa A. Humphries

Multi-model mimicry (MMM) is a flexible model selection technique for comparison of multiple, non-nested models on any desired goodness-of-fit criteria. Applicable to any set of candidate models that are 1) able to be fit to observed data, 2) can simulate new sets of data under the models, and 3) have a metric by which a dataset&#39;s goodness-of-fit to the

Brian Giraldo, Wenchang Yeh, Nobuhiko P. Kobayashi

Crystallization of thin film materials by exploiting laser induced crystallization has been advancing for the past four decades. This unique thin film technique has been predominantly used in processing thin film materials made of a single chemical element; however, harnessing this technique to extend its use for thin film materials containing multiple chemi

Purushottam D. Dixit

The Gibbs-Boltzmann distribution offers a physically interpretable way to massively reduce the dimensionality of high dimensional probability distributions where the extensive variables are `features' and the intensive variables are `descriptors'. However, not all probability distributions can be modeled using the Gibbs-Boltzmann form. Here, we present TMI:

Pierre-Jean Meyer, Murat Arcak

We propose a new approach to compute an interval over-approximation of the finite time reachable set for a large class of nonlinear systems. This approach relies on the notions of sensitivity matrices, which are the partial derivatives representing the variations of the system trajectories in response to variations of the initial states. Using interval arith

Mark R. Krumholz, Roland M. Crocker, Siyao Xu, A. Lazarian

Starburst galaxies are efficient $\gamma$-ray producers, because their high supernova rates generate copious cosmic ray (CR) protons, and their high gas densities act as thick targets off which these protons can produce neutral pions and thence $\gamma$-rays. In this paper we present a first-principles calculation of the mechanisms by which CRs propagate thr

Pierre-Jean Meyer, He Yin, Astrid H. Brodtkorb, Murat Arcak

We propose a hierarchical control framework for the synthesis of correct-by-construction controllers for nonlinear control-affine systems with respect to reach-avoid-stay specifications. We first create a low-dimensional continuous abstraction of the system and use Sum-of-Squares (SOS) programming to obtain a low-level controller ensuring a bounded error bet

Joshua D. Martin, J. Carlson, Huaiyu Duan

Neutrinos emitted deep within a supernova explosion experience a self-induced index of refraction. In the stationary, one-dimensional (1D) supernova "bulb model", this self-induced refraction can lead to a collective flavor transformation which is coherent among different neutrino momentum modes. Such collective oscillations can produce partial swaps of the

Kyu-Hwan Lee, Dongwen Liu, Thomas Oliver

A correction factor naturally arises in the theory of p-adic Kac--Moody groups. In this paper, we expand the correction factor into a sum of irreducible characters of the underlying Kac--Moody algebra. We derive a formula for the coefficients, which lie in the ring of power series with integral coefficients. In the case that the Weyl group is a universal Cox

Rufus Boyack, Joseph Maciejko

Recent sign-problem-free quantum Monte Carlo simulations of (2+1)-dimensional lattice quantum electrodynamics (QED$_3$) with $N_f$ flavors of fermions on the square lattice have found evidence of continuous quantum phase transitions between a critical phase and a gapped valence-bond-solid (VBS) phase for flavor numbers $N_f=4$, $6$, and $8$. We derive the cr

K. D. Elworthy, Xue-Mei Li

An approach to analysis on path spaces of Riemannian manifolds is described. The spaces are furnished with `Brownian motion' measure which lies on continuous paths, though differentiation is restricted to directions given by tangent paths of finite energy. An introduction describes the background for paths on ${\mathbb R}^m$ and Malliavin calculus. For manif

Zhiyun Lu, Liangliang Cao, Yu Zhang, Chung-Cheng Chiu

In this paper, we propose to use pre-trained features from end-to-end ASR models to solve speech sentiment analysis as a down-stream task. We show that end-to-end ASR features, which integrate both acoustic and text information from speech, achieve promising results. We use RNN with self-attention as the sentiment classifier, which also provides an easy visu

Xin Xing, Zhigen Zhao, Jun S. Liu

Simultaneously finding multiple influential variables and controlling the false discovery rate (FDR) for linear regression models is a fundamental problem. We here propose the Gaussian Mirror (GM) method, which creates for each predictor variable a pair of mirror variables by adding and subtracting a randomly generated Gaussian perturbation, and proceeds wit

P. Chris Fragile

Across black hole (BH) and neutron star (NS) low-mass X-ray binaries (LMXBs), there appears to be some correlation between certain high- and low-frequency quasi-periodic oscillations (QPOs). In a previous paper, we showed that for BH LMXBs, this could be explained by the simultaneous oscillation and precession of a hot, thick, torus-like corona. In the curre

Taichi Uyama, Thayne Currie, Yasunori Hori, Robert J. De Rosa

We present $\kappa$ Andromeda b's photometry and astrometry taken with Subaru/SCExAO+HiCIAO and Keck/NIRC2, combined with recently published SCExAO/CHARIS low-resolution spectroscopy and published thermal infrared photometry to further constrain the companion's atmospheric properties and orbit. $\kappa$ And b's Y/Y-K colors are redder than field dwarfs, cons

Peter Gangl

We present a level-set based topology optimization algorithm for design optimization problems involving an arbitrary number of different materials, where the evolution of a design is solely guided by topological derivatives. Our method can be seen as an extension of the algorithm that was introduced in (Amstutz, Andrae 2006) for two materials to the case of

Kayleigh Campbell, Laura Staugler, Andrea Arnold

The classic Hodgkin-Huxley model is widely used for understanding the electrophysiological dynamics of a single neuron. While applying a constant current to the system results in a single voltage spike, it is possible to produce more interesting dynamics by applying time-varying currents, which may not be experimentally measurable. The aim of this work is to

Erick G. Rocha, Emanuel P. Santos, Bruno J. dos Santos, Samuel S. de Albuquerque

L\'evy flights for light have been demonstrated in disordered systems with and without optical gain, and remained unobserved in ordered ones. In the present letter, we investigate, numerically and experimentally, L\'evy flights for light in ordered systems due to an ordered (conventional) laser. The statistical analysis was performed on the intensity fluctua

Thomas F. Giesen, Bhaswati Mookerjea, Guido W. Fuchs, Alexander A. Breier

We report the first detection of the isotopologues 13CCC and C13CC. We used the heterodyne receivers GREAT and upGREAT on board SOFIA to search for the ro-vibrational transitions Q(2) and Q(4) of 13CCC and C13CC at 1.9 THz along the line of sight towards SgrB2(M). For both species the ro-vibrational absorption lines Q(2) and Q(4) have been identified, primar

Kyle Bushick, Kelsey A. Mengle, Sieun Chae, Emmanouil Kioupakis

Rutile germanium dioxide (r-GeO$_2$) is a recently predicted ultrawide-band-gap semiconductor with potential applications in high-power electronic devices, for which the carrier mobility is an important material parameter that controls the device efficiency. We apply first-principles calculations based on density functional and density functional perturbatio

Nahuel Andrés, Fouad Sahraoui, Sebastien Galtier, Lina Z. Hadid

The first complete estimation of the compressible energy cascade rate $|\varepsilon_\text{C}|$ at magnetohydrodynamic (MHD) and sub-ion scales is obtained in the Earth's magnetosheath using Magnetospheric MultiScale (MMS) spacecraft data and an exact law derived recently for {\it compressible} Hall MHD turbulence. A multi-spacecraft technique is used to comp

Claudio Genovese, Sandro Sorella

The molecular dissociation energy has often been explained and discussed in terms of singlet bonds, formed by bounded pairs of valence electrons. In this work we use a highly correlated resonating valence bond ansatz, providing a consistent paradigm for the chemical bond, where spin fluctuations are shown to play a crucial role. Spin fluctuations are known t

P. M. Ferreira, B. L. Gonçalves

We analyse the possibility of charge breaking minima developing in the Higgs triplet model, and under what conditions they are deeper than charge-preserving ones. Analytical expressions relating the depth of minima of different types are deduced. A global symmetry of the model leads to increased stability for charge-preserving vacua. However, if that symmetr

Chiara M. F. Mingarelli, Stephen R. Taylor, B. S. Sathyaprakash, Will M. Farr

In this paper we provide a comprehensive derivation of the energy density in the stochastic gravitational-wave background $\Omega_\mathrm{gw}(f)$, and show how this quantity is measured in ground-based detectors such as Laser Interferometer Gravitational-Wave Observatory (LIGO), space-based Laser Interferometer Space Antenna (LISA), and Pulsar Timing Arrays.

S. S. Agaev, K. Azizi, H. Sundu

Spectroscopic parameters and decay channels of the vector resonance $Y(2175)$ are studied by considering it as a diquark-antidiquark state with the quark content $su\overline{s}\overline{u}$. The mass and coupling of the tetraquark $Y(2175)$ are calculated using the QCD two-point sum rules by taking into account various quark, gluon and mixed condensates up

N. Ya. Ivanov, A. V. Efremov, O. V. Teryaev

We consider the azimuthal $\cos \varphi$ and $\cos 2\varphi$ distributions and the Callan-Gross ratio $R={\rm d}\sigma_L/{\rm d}\sigma_T$ in heavy-quark pair electroproduction, $lN\rightarrow l^{\prime}Q\bar{Q}X$, as probes of linearly polarized gluons in unpolarized nucleons. Our analysis shows that the azimuthal asymmetries and Callan-Gross ratio are predi

Eugene Malygin, Roman Uklein, Elena Shablovinskaya, Aleksander Perepelitsyn

The most popular method of the broad-line region size estimation in active galactic nuclei (AGN) is the reverberation mapping based on measuring the time delay between the continuum flux and the flux in the emission lines. In our work, we apply the method of photometric reverberation mapping in mid-band filters, adapted for observations on the 1-m Zeiss-1000

Andrei Afanasev, Carl E. Carlson, Hao Wang

When polarized light is absorbed by an atom, the excited atomic system carries information about the initial polarization of light. For the light that carries an orbital angular momentum, or the twisted light, the polarization states are described by eight independent parameters, as opposed to three Stokes parameters for plane waves. We use a parameterizatio

Hannah Ashbach, Kiki Pichini

We prove that every set of n points in the plane has at most $(16+5/6)^n$ rectangulations. This improves upon a long-standing bound of Ackerman. Our proof is based on the cross-graph charging-scheme technique.

Siyuan Qiao, Huiyu Wang, Chenxi Liu, Wei Shen

In this paper, we study normalization methods for neural networks from the perspective of elimination singularity. Elimination singularities correspond to the points on the training trajectory where neurons become consistently deactivated. They cause degenerate manifolds in the loss landscape which will slow down training and harm model performances. We show

Saurabh Singh, Shankar Krishnan

Batch Normalization (BN) uses mini-batch statistics to normalize the activations during training, introducing dependence between mini-batch elements. This dependency can hurt the performance if the mini-batch size is too small, or if the elements are correlated. Several alternatives, such as Batch Renormalization and Group Normalization (GN), have been propo

Rejane Alves de Brito, Bertúlio de Lima Bernardo

The characterization of quantum correlations is crucial to the development of new quantum technologies and to understand how dramatically quantum theory departs from classical physics. Here we systematically study single- and multiparticle interference patterns produced by general two- and three-qubit systems. From this we establish on phenomenological groun

Andrea Leon, J. W. González, J. Mejía-López, F. Crasto de Lima

A monolayer of CrI$_3$ is a two-dimensional crystal that in its equilibrium configuration is a ferromagnetic semiconductor, however, two coupled layers can be ferromagnetic or antiferromagnetic depending on the stacking. We study the magnetic phase diagram upon the strain of the antiferromagnetically coupled bilayer with C2/m symmetry. We found that strain m

Konstantin Ushenin, Tatyana Nesterova, Dmitry Shmarko, Vladimir Sholokhov

A phase mapping is an approach to processing signals of electrograms recorded from the surface of cardiac tissue. The main concept of phase mapping is the application of the phase transformation with the aim to obtain signals with useful properties. In our study, we propose to use a simple sawtooth signal instead of a phase signal for processing of electrogr

Reyk Börner, Paul Schultz, Benjamin Ünzelmann, Deli Wang

Time lags occur in a vast range of real-world dynamical systems due to finite reaction times or propagation speeds. Here we derive an analytical approach to determine the asymptotic stability of synchronous states in networks of coupled inertial oscillators with constant delay. Building on the master stability formalism, our technique provides necessary and

Valentin V. Khoze, Frank Krauss, Matthias Schott

It is a common belief that the last missing piece of the Standard Model of particles physics was found with the discovery of the Higgs boson at the Large Hadron Collider. However, there remains a major prediction of quantum tunnelling processes mediated by instanton solutions in the Yang-Mills theory, that is still untested in the Standard Model. The direct

Bertram Bitsch, Chiara Battistini

The composition of the protoplanetary disc is linked to the composition of the host star, where a higher overall metallicity of the host star provides more building blocks for planets. However, most planet formation simulations only link the stellar iron abundance [Fe/H] to planet formation and [Fe/H] in itself is used as a proxy to scale all elements. But l

Lakshmi Annamalai, Anirban Chakraborty, Chetan Singh Thakur

Event-based cameras are bio-inspired novel sensors that asynchronously record changes in illumination in the form of events, thus resulting in significant advantages over conventional cameras in terms of low power utilization, high dynamic range, and no motion blur. Moreover, such cameras, by design, encode only the relative motion between the scene and the

Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar

We develop a communication-efficient distributed learning algorithm that is robust against Byzantine worker machines. We propose and analyze a distributed gradient-descent algorithm that performs a simple thresholding based on gradient norms to mitigate Byzantine failures. We show the (statistical) error-rate of our algorithm matches that of Yin et al.~\cite

Jie Wang, Sownak Bose, Carlos S. Frenk, Liang Gao

Cosmological models in which dark matter consists of cold elementary particles predict that the dark halo population should extend to masses many orders of magnitude below those at which galaxies can form. Here we report a cosmological simulation of the formation of present-day haloes over the full range of observed halo masses (20 orders of magnitude) when

K. Misra, L. Resmi, D. A. Kann, M. Marongiu

We present radio and optical afterglow observations of the TeV-bright long Gamma Ray Burst (GRB) 190114C at a redshift of $z=0.425$, which was detected by the MAGIC telescope. Our observations with ALMA, ATCA, and uGMRT were obtained by our low frequency observing campaign and range from $\sim1$ to $\sim140$ days after the burst and the optical observations

Oscar Fontanelli, Pedro Miramontes, Ricardo Mansilla

Science in the 21st century seems to be governed by novel approaches involving interdisciplinary work, systemic perspectives and complexity theory concepts. These new paradigms force us to leave aside our elder mechanistic approaches and embrace new starting points based on stochasticity, chaoticity, statistics and probability. In this work we review the fun

D. V. Osipov, A. N. Parshin

In this work we construct harmonic analysis on free Abelian groups of rank $2$, namely: we construct and investigate spaces of functions and distributions, Fourier transforms, actions of discrete and extended discrete Heisenberg groups. In case of the rank-$2$ value group of a two-dimensional local field with finite last residue field we connect this harmoni

Ayuki Kamada, Hee Jung Kim

Exothermic scatterings of dark matter (DM) produce DM particles with significant kick velocities inside DM halos. In collaboration with DM self-interaction, the excess kinetic energy of the produced DM particles is distributed to the others, which self-heats the DM particles as a whole. The DM self-heating is efficient towards the halo center, and the heat i

Sumaya Almanee, Arda Unal, Mathias Payer, Joshua Garcia

Android apps include third-party native libraries to increase performance and to reuse functionality. Native code is directly executed from apps through the Java Native Interface or the Android Native Development Kit. Android developers add precompiled native libraries to their projects, enabling their use. Unfortunately, developers often struggle or simply

Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani

We study the Personalized PageRank (PPR) algorithm, a local spectral method for clustering, which extracts clusters using locally-biased random walks around a given seed node. In contrast to previous work, we adopt a classical statistical learning setup, where we obtain samples from an unknown nonparametric distribution, and aim to identify sufficiently sali

Thomas R. Groechel, Zhonghao Shi, Roxanna Pakkar, Maja J. Matarić

Expressivity--the use of multiple modalities to convey internal state and intent of a robot--is critical for interaction. Yet, due to cost, safety, and other constraints, many robots lack high degrees of physical expressivity. This paper explores using mixed reality to enhance a robot with limited expressivity by adding virtual arms that extend the robot&#39

Michael R. Sinko, Sergio C. de la Barrera, Olivia Lanes, Kenji Watanabe

Two-dimensional (2D) transition-metal dichalcogenide superconductors have unique and desirable properties for integration with conventional superconducting circuits. However, fully superconducting contact must be made between the 2D material and three-dimensional (3D) superconductors in order to employ the standard microwave drive and readout of qubits in su

C. Froment, P. Antolin, V. M. J. Henriques, P. Kohutova

Thermal non-equilibrium (TNE) is a phenomenon that can occur in solar coronal loops when the heating is quasi-constant and highly-stratified. Under such heating conditions, coronal loops undergo cycles of evaporation and condensation. The recent observations of ubiquitous long-period intensity pulsations in coronal loops and their relationship with coronal r

Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi

Texts like news, encyclopedias, and some social media strive for objectivity. Yet bias in the form of inappropriate subjectivity - introducing attitudes via framing, presupposing truth, and casting doubt - remains ubiquitous. This kind of bias erodes our collective trust and fuels social conflict. To address this issue, we introduce a novel testbed for natur

Joaquim Roé, Tomasz Szemberg

The Newton--Okounkov body of a big divisor D on a smooth surface is a numerical invariant in the form of a convex polygon. We study the geometric significance of the shape of Newton--Okounkov polygons of ample divisors, showing that they share several important properties of Newton polygons on toric surfaces. In concrete terms, sides of the polygon are assoc

Steffen Kühn, Chintan Shah, José R. Crespo López-Urrutia, Keisuke Fujii

For more than 40 years, most astrophysical observations and laboratory studies of two key soft x-ray diagnostic $2p-3d$ transitions, $3C$ and $3D$, in Fe XVII ions found oscillator strength ratios $f(3C)/f(3D)$ disagreeing with theory, but uncertainties had precluded definitive statements on this much studied conundrum. Here, we resonantly excite these lines

H. Tanimura, N. Aghanim, V. Bonjean, N. Malavasi

We studied physical properties of matter in 24,544 filaments ranging from 30 to 100 Mpc in length, identified in the Sloan Digital Sky Survey (SDSS). We stacked the Comptonization y map produced by the Planck Collaboration around the filaments, excluding the resolved galaxy groups and clusters above a mass of ~3*10^13 Msun. We detected the thermal Sunyaev-Ze

Edward Gillen, Joshua T. Briegal, Simon T. Hodgkin, Daniel Foreman-Mackey

We determine rotation periods for 127 stars in the ~115 Myr old Blanco 1 open cluster using ~200 days of photometric monitoring with the Next Generation Transit Survey (NGTS). These stars span F5-M3 spectral types (1.2 $\gtrsim M \gtrsim$ 0.3 M$_{\odot}$) and increase the number of known rotation periods in Blanco 1 by a factor of four. We determine rotation

Charles X. Ling, Tanner Bohn

Humans can learn a variety of concepts and skills incrementally over the course of their lives while exhibiting many desirable properties, such as continual learning without forgetting, forward transfer and backward transfer of knowledge, and learning a new concept or task with only a few examples. Several lines of machine learning research, such as lifelong

Kenji Iohara, Philippe Malbos

This article presents the emergence of formal methods in theory of partial differential equations (PDE) in the french school of mathematics through Janet's work in the period 1913-1930. In his thesis and in a series of articles published during this period, M. Janet introduced an original formal approach to deal with the solvability of the problem of initial

Logan G. Wright, Pavel Sidorenko, Hamed Pourbeyram, Zachary M. Ziegler

Mode-locking is a process in which different modes of an optical resonator establish, through nonlinear interactions, stable synchronization. This self-organization underlies light sources that enable many modern scientific applications, such as ultrafast and high-field optics and frequency combs. Despite this, mode-locking has almost exclusively referred to

Adarsh S. Prasad, Jakob Hinney, Sahand Mahmoodian, Klemens Hammerer

Photons in a nonlinear medium can repel or attract each other, resulting in a strongly correlated quantum many-body system. Typically, such strongly correlated states of light arise from the extreme nonlinearity granted by quantum emitters that are strongly coupled to a photonic mode. However, in these approaches, unavoidable dissipation, like photon loss, b

Nikolai Krivulin

We consider a decision-making problem to evaluate absolute ratings of alternatives from the results of their pairwise comparisons according to two criteria, subject to constraints on the ratings. We formulate the problem as a bi-objective optimization problem of constrained matrix approximation in the Chebyshev sense in logarithmic scale. The problem is to a

Ezequiel Alvarez, Federico Lamagna, Manuel Szewc

We study the implementation of a Topic Model algorithm in four-top searches at the LHC as a test-probe of a not ideal system for applying this technique. We study this Topic Model behavior as its different hypotheses such as mutual reducibility and equal distribution in all samples shift from true. The four-top final state at the LHC is not only relevant bec

Andreas Banlaki, Aradhita Chattopadhyaya, Abhiram Kidambi, Thorsten Schimannek

In this paper we study compactifications of the ${\cal N}=2$ heterotic $E_8\times E_8$ string on $(K3\times T^2)/\mathbb{Z}_3$ with various gauge backgrounds and calculate the topological couplings in the effective supergravity action that arise from one-loop amplitudes. We then identify candidates for dual type IIA compactifications on Calabi-Yau threefolds