December 2020 arXiv papers — page 15

J. Nathan Kutz

Approximation techniques have been historically important for solving differential equations, both as initial value problems and boundary value problems. The integration of numerical, analytic and perturbation methods and techniques can help produce meaningful approximate solutions for many modern problems in the engineering and physical sciences. An overvie

Rayna Dimitrova, Bernd Finkbeiner, Hazem Torfah

Automata over infinite words, also known as omega-automata, play a key role in the verification and synthesis of reactive systems. The spectrum of omega-automata is defined by two characteristics: the acceptance condition (e.g. B\"uchi or parity) and the determinism (e.g., deterministic or nondeterministic) of an automaton. These characteristics play a cruci

Qingyang Liu, Guanyu Hu, Binqi Ye, Susan Wang

Unblinded sample size re-estimation (SSR) is often planned in a clinical trial when there is large uncertainty about the true treatment effect. For Proof-of Concept (PoC) in a Phase II dose finding study, contrast test can be adopted to leverage information from all treatment groups. In this article, we propose two-stage SSR designs using frequentist conditi

Aiying Duan, Chaowei Jiang, Zhenjun Zhou, Xueshang Feng

It remains unclear how solar flares are triggered and in what conditions they can be eruptive with coronal mass ejections. Magnetic flux ropes (MFRs) has been suggested as the central magnetic structure of solar eruptions, and their ideal instabilities including mainly the kink instability (KI) and torus instability (TI) provide important candidates for trig

Tao Pu, Tianshui Chen, Yuan Xie, Hefeng Wu

Recognizing human emotion/expressions automatically is quite an expected ability for intelligent robotics, as it can promote better communication and cooperation with humans. Current deep-learning-based algorithms may achieve impressive performance in some lab-controlled environments, but they always fail to recognize the expressions accurately for the uncon

Bernd Finkbeiner, Lennart Haas, Hazem Torfah

Hyperproperties elevate the traditional view of trace properties form sets of traces to sets of sets of traces and provide a formalism for expressing information-flow policies. For trace properties, algorithms for verification, monitoring, and synthesis are typically based on a representation of the properties as omega-automata. For hyperproperties, a simila

Motoko Fujiwara, Junji Hisano, Chihiro Kanai, Takashi Toma

Electric dipole moments (EDMs) of charged leptons arise from a new source of CP violation in the lepton sector. In this paper, we calculate the EDMs of the charged leptons in the minimal scotogenic model with two singlet fermions, and the models extended with one or two triplet fermions instead of the singlet fermions, taking into account the constraints of

Lu Wang, Dong Guo, Guotai Wang, Shaoting Zhang

Despite that deep learning has achieved state-of-the-art performance for medical image segmentation, its success relies on a large set of manually annotated images for training that are expensive to acquire. In this paper, we propose an annotation-efficient learning framework for segmentation tasks that avoids annotations of training images, where we use an

Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong

Knowledge distillation (KD) is essential for training non-autoregressive translation (NAT) models by reducing the complexity of the raw data with an autoregressive teacher model. In this study, we empirically show that as a side effect of this training, the lexical choice errors on low-frequency words are propagated to the NAT model from the teacher model. T

Tom Baumeister, Bernd Finkbeiner, Hazem Torfah

Reactive synthesis transforms a specification of a reactive system, given in a temporal logic, into an implementation. The main advantage of synthesis is that it is automatic. The main disadvantage is that the implementation is usually very difficult to understand. In this paper, we present a new synthesis process that explains the synthesized implementation

Mehdi Mashayekhi, Nirav Ajmeri, George F. List, Munindar P. Singh

Multiagent systems provide a basis for developing systems of autonomous entities and thus find application in a variety of domains. We consider a setting where not only the member agents are adaptive but also the multiagent system viewed as an entity in its own right is adaptive. Specifically, the social structure of a multiagent system can be reflected in t

Jin Gyu Lee, Stephan Trenn, Hyungbo Shim

In this paper, we introduce a nonlinear time-varying coupling law, which can be designed in a fully decentralized manner and achieves approximate synchronization with arbitrary precision, under only mild assumptions on the individual vector fields and the underlying (undirected) graph structure. The proposed coupling law is motivated by the so-called funnel

T. Congy, G. A. El, M. A. Hoefer, M. Shearer

Long time dynamics of the smoothed step initial value problem or dispersive Riemann problem for the Benjamin-Bona-Mahony (BBM) equation $u_t + uu_x = u_{xxt}$ are studied using asymptotic methods and numerical simulations. The catalog of solutions of the dispersive Riemann problem for the BBM equation is much richer than for the related, integrable, Korteweg

Dake Zheng, Xinyu Wu, Jianxin Pang

Mainly because of the heavy computational costs, the real-time whole-body obstacle avoidance for the redundant manipulators has not been well implemented. This paper presents an approach that can ensure that the whole-body of a redundant manipulator can avoid moving obstacles in real-time during the execution of a task. The manipulator is divided into end-ef

MacKenzie K. Warrens, Grant M. Gorman, Stephen J. Bradshaw, Thomas C. Killian

We present a study of the expansion of an ultracold neutral plasma (UCNP) with an initial density distribution that decays exponentially in space, created by photoionizing atoms shortly after their release from a quadrupole (or biconic cusp) magnetic trap. A characteristic ion acoustic timescale is evident in the evolution of the plasma size and velocity, in

Dake Zheng, Xinyu Wu, Jianxin Pang

In this paper, based on Dynamical Systems (DS), we present an obstacle avoidance method that take into account workspace constraint for serial manipulators. Two modulation matrices that consider the effect of an obstacle and the workspace of a manipulator are determined when the obstacle does not intersect the workspace boundary and when the obstacle interse

Yao Yu, Yu-Kuo Hsiao

The anti-triplet charmed baryon decays with the light scalar mesons are rarely measured, whereas the recent observation of the Cabibbo-favored $\Lambda_c^+\to \Lambda\eta\pi^+$ decay hints a possible $\Lambda_c^+\to\Lambda a_0(980)^+,a_0(980)^+\to \eta\pi^+$ process. We hence study the $\Lambda_c^+\to\Lambda a_0(980)^+$ decay. Particularly, it is found that

Wei-Jun Zhang, Guang-Zhao Xu, Li-Xing You, Cheng-Jun Zhang

We report a compact, scalable, and high-performance superconducting nanowire single-photon detector (SNSPD) array by using a multichannel optical fiber array-coupled configuration. For single pixels with an active area of 18 um in diameter and illuminated at the telecom wavelength of 1550 nm, we achieved a pixel yield of 13/16 on one chip, an average system

Godwin Badu-Marfo, Bilal Farooq, Zachary Patterson

In this work, we develop a privacy-by-design generative model for synthesizing the activity diary of the travel population using state-of-art deep learning approaches. This proposed approach extends literature on population synthesis by contributing novel deep learning to the development and application of synthetic travel data while guaranteeing privacy pro

Anatoly Sidorov, Maria Shishanina

This article deals with the process of managing the social and economic development of municipal formations. It highlights characteristics and key issues that arise during management at the municipal level. In order to minimize the impact of the described issues, it is suggested to consider municipal social and economic development as a semistructured system

Tomohiro Tamaya, Takeo Kato

We theoretically investigate the piezo-optic effect of high-harmonic generation (HHG) in shear-strained semiconductors. By focusing on a typical semiconductor, GaAs, we show that there is optical activity, meaning different responses to right-handed and left-handed elliptically polarized electric fields. We also show that this optical activity is more pronou

Gabriel Gonzalez

The motivation for this theoretical paper comes from recent experiments of a heat transfer system of two thermally coupled rings rotating in opposite directions with equal angular velocities that present anti-parity-time (APT) symmetry. The theoretical model predicted a rest-to-motion temperature distribution phase transition during the symmetry breaking for

Jia-Ming Cheng, Zheng-Wei Zhou, Guang-Can Guo, Han Pu

We consider a hybrid atom-optomechanical system consisting of a mechanical membrane inside an optical cavity and an atomic Bose-Einstein condensate outside the cavity. The condensate is confined in an optical lattice potential formed by a traveling laser beam reflected off one cavity mirror. We derive the cavity-mediated effective atom-atom interaction poten

Qi Zhao, Shuchang Lyu, Yuewen Li, Yujing Ma

Remote sensing (RS) scene classification is a challenging task to predict scene categories of RS images. RS images have two main characters: large intra-class variance caused by large resolution variance and confusing information from large geographic covering area. To ease the negative influence from the above two characters. We propose a Multi-granularity

He-Jing Hong, Ze-Chun Hu

Let $\mu_n$ be the standard Gaussian measure on $\mathbb{R}^n$ and $X$ be a random vector on $\mathbb{R}^n$ with the law $\mu_n$. U-conjecture states that if $f$ and $g$ are two polynomials on $\mathbb{R}^n$ such that $f(X)$ and $g(X)$ are independent, then there exist an orthogonal transformation $L$ on $\mathbb{R}^n$ and an integer $k$ such that $f\circ L$

Munan Ning, Cheng Bian, Chenglang Yuan, Kai Ma

Accuracy segmentation of brain structures could be helpful for glioma and radiotherapy planning. However, due to the visual and anatomical differences between different modalities, the accurate segmentation of brain structures becomes challenging. To address this problem, we first construct a residual block based U-shape network with a deep encoder and shall

Mario Palasciano

In a single-state repeated game, zero-determinant strategies can unilaterally force functions of the payoffs to take values in particular closed intervals. When the explicit use of a determinant is absent from the analysis, they are instead called autocratic. We extend their study to the setting of finite state games with deterministic transitions. For a giv

Yao Wang, Yuan Wan

We study the energy and spin transport of the classical spin liquid hosted by the pyrochlore Heisenberg antiferromagnet in the large $S$ limit. Molecular dynamics calculation suggests that both the energy and spin diffusion constants approach finite limits as the temperature tends to zero. We explain our results in terms of an effective disorder model, where

Yutian Chen, Xiaowei Xu, Dewen Zeng, Yiyu Shi

Coronary artery disease (CAD) is the most common cause of death globally, and its diagnosis is usually based on manual myocardial segmentation of Magnetic Resonance Imaging (MRI) sequences. As the manual segmentation is tedious, time-consuming and with low applicability, automatic myocardial segmentation using machine learning techniques has been widely expl

Munir Hiabu, Enno Mammen, Joseph T. Meyer

We introduce a novel interpretable tree based algorithm for prediction in a regression setting. Our motivation is to estimate the unknown regression function from a functional decomposition perspective in which the functional components correspond to lower order interaction terms. The idea is to modify the random forest algorithm by keeping certain leaves af

Naoki Matsui

We consider the following nonlinear Schr\"{o}dinger equation with double power nonlinearity \[ i\frac{\partial u}{\partial t}+\Delta u+|u|^{\frac{4}{N}}u+|u|^{p-1}u=0,\quad 1<p<1+\frac{4}{N} \] in $\mathbb{R}^N$. For $N=1,2,3$, Le Coz-Martel-Rapha\"{e}l (2016) construct a minimal-mass blow-up solution. Moreover, the previous study derives blow-up rate of the

Hongwei Shi, Shengling Wang, Qin Hu, Xiuzhen Cheng

Bitcoin has witnessed a prevailing transition that employing transaction fees paid by users rather than subsidy assigned by the system as the main incentive for mining.

Y. -Y. Liu, S. G. J. Philips, L. A. Orona, N. Samkharadze

RF reflectometry offers a fast and sensitive method for charge sensing and spin readout in gated quantum dots. We focus in this work on the implementation of RF readout in accumulation-mode gate-defined quantum dots, where the large parasitic capacitance poses a challenge. We describe and test two methods for mitigating the effect of the parasitic capacitanc

Bhav Jain, Sean Elliott

The hippocampus is often attributed to episodic memory formation and storage in the mammalian brain; in particular, Alme et al. showed that hippocampal area CA3 forms statistically independent representations across a large number of environments, even if the environments share highly similar features. This lack of overlap between spatial maps indicates the

Wei Tao, Wei Li, Zhisong Pan, Qing Tao

Averaging scheme has attracted extensive attention in deep learning as well as traditional machine learning. It achieves theoretically optimal convergence and also improves the empirical model performance. However, there is still a lack of sufficient convergence analysis for strongly convex optimization. Typically, the convergence about the last iterate of g

Federico Echenique, Masaki Miyashita, Yuta Nakamura, Luciano Pomatto

We propose a model of incomplete \textit{twofold multiprior preferences}, in which an act $f$ is ranked above an act $g$ only when $f$ provides higher utility in a worst-case scenario than what $g$ provides in a best-case scenario. The model explains failures of contingent reasoning, captured through a weakening of the state-by-state monotonicity (or dominan

Jun Ma

Automatic evaluation of myocardium and pathology plays an important role in the quantitative analysis of patients suffering from myocardial infarction. In this paper, we present a cascaded convolutional neural network framework for myocardial infarction segmentation and classification in delayed-enhancement cardiac MRI. Specifically, we first use a 2D U-Net

Xiaoou Ding, Hongzhi Wang, Jiaxuan Su, Chen Wang

Both the volume and the collection velocity of time series generated by monitoring sensors are increasing in the Internet of Things (IoT). Data management and analysis requires high quality and applicability of the IoT data. However, errors are prevalent in original time series data. Inconsistency in time series is a serious data quality problem existing wid

Xingyu Wang, Chen Dong, Shanghong Zhao, Yong Liu

The measurement-device-independent (MDI) QKD is considered to be an alternative to overcome the currently trusted satellite paradigm. However, the feasibility of the space-based MDI-QKD remains unclear in terms of the factors: the high-loss uplink between a ground station and a satellite, the limited duration when two ground stations are simultaneously visib

Michael E. Tobar, Raymond Y. Chiao, Maxim Goryachev

An active electrical network contains a voltage or current source that creates electromagnetic energy through a method of transduction that enables the separation of opposite polarity charges from an external source. The end result is the creation of an active dipole with a permanent polarisation and a non-zero electric vector curl. The external energy input

Björn W. Schuller, Harry Coppock, Alexander Gaskell

The COVID-19 pandemic has affected the world unevenly; while industrial economies have been able to produce the tests necessary to track the spread of the virus and mostly avoided complete lockdowns, developing countries have faced issues with testing capacity. In this paper, we explore the usage of deep learning models as a ubiquitous, low-cost, pre-testing

Rangrang Zhang, Tusheng Zhang

In this paper, we established a quadratic transportation cost inequality for scalar stochastic conservation laws driven by multiplicative noise. The doubling variables method plays an important role.

Delilah E. A. Gates, S. James Gates

On the basis of comparing eigenvalues of an operator ${\hat {\mathbf{\cal C}}}{}^{({\cal R})}$, that proved useful in distinguishing how off-shell 4D, $\cal N$ = 1 supermultiplets become off-shell 4D, $\cal N$ = 2 supermultiplets, the double tensor supermultiplet is shown to be radically different for other known multiplets. This suggests difficulties, if no

Rhinithaa P. Thanalakshme, Ali Kanj, JunHwan Kim, Elias Wilken-Resman

Electromagnetic signals in the ultra-low frequency (ULF) range below 3 kHz are well suited for underwater and underground wireless communication thanks to low signal attenuation and high penetration depth. However, it is challenging to design ULF transmitters that are simultaneously compact and energy efficient using traditional approaches, e.g., using coils

Michael Gutperle, Christoph F. Uhlemann

We use holography to study codimension-2 surface defects in 5d SCFTs engineered by $(p,q)$ 5-brane webs. The three-dimensional defects are realized by D3-branes ending on the brane web. We identify the holographic representation of the defects in Type IIB $AdS_6$ solutions as probe D3-branes, and study conformal and non-conformal defects which, respectively,

Khristo N. Boyadzhiev

We study inverse factorial series and their relation to Stirling numbers of the first kind. We prove a special representation of the polylogarithm function in terms of series with such numbers. Using various identities for Stirling numbers of the first kind we construct a number of expansions of functions in terms of inverse factorial series where the coeffi

G. Guijarro

In this Thesis, we report a detailed study of the ground-state properties of a set of quantum few- and many-body systems in one and two dimensions with different types of interactions by using Quantum Monte Carlo methods. Nevertheless, the main focus of this work is the study of the ground-state properties of an ultracold Bose system with dipole-dipole inter

Viny Saajan Victor, Pramod Vadiraja, Jan-Tobias Sohns, Heike Leitte

With the advent of state-of-the-art machine learning and deep learning technologies, several industries are moving towards the field. Applications of such technologies are highly diverse ranging from natural language processing to computer vision. Object recognition is one such area in the computer vision domain. Although proven to perform with high accuracy

Jiahao Guo, Pramesh Singh, Kevin E. Bassler

Various attempts have been made in recent years to solve the Resolution Limit (RL) problem in community detection by considering variants of the modularity metric in the detection algorithms. These metrics purportedly largely mitigate the RL problem and are preferable to modularity in many realistic scenarios. However, they are not generally suitable for ana

Ajay Singh, Trevor Brown, Ali Mashtizadeh

Safe memory reclamation (SMR) algorithms suffer from a trade-off between bounding unreclaimed memory and the speed of reclamation. Hazard pointer (HP) based algorithms bound unreclaimed memory at all times, but tend to be slower than other approaches. Epoch based reclamation (EBR) algorithms are faster, but do not bound memory reclamation. Other algorithms f

Matan Orbach, Orith Toledo-Ronen, Artem Spector, Ranit Aharonov

Current TSA evaluation in a cross-domain setup is restricted to the small set of review domains available in existing datasets. Such an evaluation is limited, and may not reflect true performance on sites like Amazon or Yelp that host diverse reviews from many domains. To address this gap, we present YASO - a new TSA evaluation dataset of open-domain user re

Spencer L. Gordon, Bijan Mazaheri, Yuval Rabani, Leonard J. Schulman

We give an algorithm for source identification of a mixture of $k$ product distributions on $n$ bits. This is a fundamental problem in machine learning with many applications. Our algorithm identifies the source parameters of an identifiable mixture, given, as input, approximate values of multilinear moments (derived, for instance, from a sufficiently large

Davide Nunes, Luis Antunes

TensorX is a Python library for prototyping, design, and deployment of complex neural network models in TensorFlow. A special emphasis is put on ease of use, performance, and API consistency. It aims to make available high-level components like neural network layers that are, in effect, stateful functions, easy to compose and reuse. Its architecture allows f

Diana Kirk, Stephen G. MacDonell

It is widely acknowledged by researchers and practitioners that software development methodologies are generally adapted to suit specific project contexts. Research into practices-as-implemented has been fragmented and has tended to focus either on the strength of adherence to a specific methodology or on how the efficacy of specific practices is affected by

Shota Ono, Daigo Kobayashi

In the warm dense regime, where the electron temperature is increased to the same order of the Fermi temperature, the dynamical stability of elemental metals depends on its electronic band structure as well as its crystal structure. It has been known that phonon hardening occurs due to an enhanced internal pressure caused by electron excitations as in close-

Arnaud Fickinger, Simon Zhuang, Andrew Critch, Dylan Hadfield-Menell

We introduce the concept of a multi-principal assistance game (MPAG), and circumvent an obstacle in social choice theory, Gibbard's theorem, by using a sufficiently collegial preference inference mechanism. In an MPAG, a single agent assists N human principals who may have widely different preferences. MPAGs generalize assistance games, also known as coopera

Jie Hao, Linfeng Song, Liwei Wang, Kun Xu

The task of dialogue rewriting aims to reconstruct the latest dialogue utterance by copying the missing content from the dialogue context. Until now, the existing models for this task suffer from the robustness issue, i.e., performances drop dramatically when testing on a different domain. We address this robustness issue by proposing a novel sequence-taggin

Bilal Raza, Stephen G. MacDonell, Tony Clear

This paper reports our extended analysis of the recent literature addressing global software engineering (GSE), using a new Systematic Snapshot Mapping (SSM) technique. The primary purpose of this work is to understand what issues are being addressed and how research is being carried out in GSE -- and comparatively, what work is not being conducted. We carri

Sergio Gaete, Alejandro Jofre, Rodrigo Lecaros, Gino Montecinos

For underground mine, the current usual technique for ore extraction is block caving, which generates and induces seismic activity in the mine. To understand block caving method is one of the most challenging problems in underground mining. This method relies on gravity to break and transport large amounts of ore and waste. The state of art in damage models

Fabio Belloni

The $^{11}$B$(p,\alpha)2\alpha$ fusion reaction is particularly attractive for energy production purposes because of its aneutronic character and the absence of radioactive species among reactants and products. Its exploitation in the thermonuclear regime, however, appears to be prohibitive due to the low reactivity of the $^{11}$B fuel at temperatures up to

Xinyang Lu, Dejan Slepcev

We propose a model for finding one-dimensional structure in a given measure. Our approach is based on minimizing an objective functional which combines the average-distance functional to measure the quality of the approximation and penalizes the curvature, similarly to the elastica functional. Introducing the curvature penalization overcomes some of the shor

Yan Mary He, Hongming Nie

We study angles of multipliers of repelling cycles for hyperbolic rational maps in $\mathbb C(z)$. For a fixed $K \gg 1$, we show that almost all intervals of length $2\pi/K$ in $(-\pi,\pi]$ contain a multiplier angle with the property that the norm of the multiplier is bounded above by a polynomial in $K$.

S. Y. Novak

The $T$-test is probably the most popular statistical test; it is routinely recommended by the textbooks. The applicability of the test relies upon the validity of normal or Student's approximation to the distribution of Student's statistic $\,t_n$. However, the latter assumption is not valid as often as assumed. We show that normal or Student's approximatio

Laura DeMarco, Niki Myrto Mavraki

Suppose $\mathcal{E} \to B$ is a non-isotrivial elliptic surface defined over a number field, for smooth projective curve $B$. Let $k$ denote the function field $\overline{\mathbb{Q}}(B)$ and $E$ the associated elliptic curve over $k$. In this article, we construct adelically metrized $\mathbb{R}$-divisors $\overline{D}_X$ on the base curve $B$ over a number

Sergei Kiselev, Andrey Kupavskii

We show that any proper coloring of a Kneser graph $KG_{n,k}$ with $n-2k+2$ colors contains a trivial color (i.e., a color consisting of sets that all contain a fixed element), provided $n>(2+\varepsilon)k^2$, where $\varepsilon\to 0$ as $k\to \infty$. This bound is essentially tight. This is a consequence of a more general result on the minimum number of no

Ioannis Gkioulekas, Steven J. Gortler, Louis Theran, Todd Zickler

Let $\mathbf{p}$ be a configuration of $n$ points in $\mathbb{R}^d$ for some $n$ and some $d \ge 2$. Each pair of points defines an edge, which has a Euclideanlength in the configuration. A path is an ordered sequence of the points, and a loop is a path that begins and ends at the same point. A path or loop, as a sequence of edges, also has a Euclidean lengt

Quan Sun, Sunil M. Dogra, Christopher Edwards, Datao Gong

The analog front-end for the Low Gain Avalanche Detector (LGAD) based precision timing application in the CMS Endcap Timing Layer (ETL) has been prototyped in a 65 nm CMOS mini-ASIC named ETROC0. Serving as the very first prototype of ETL readout chip (ETROC), ETROC0 aims to study and demonstrate the performance of the analog frontend, with the goal to achie

Ida Kantor

A well-known theorem in plane geometry states that any set of $n$ non-collinear points in the plane determines at least $n$ lines. Chen and Chv\'{a}tal asked whether an analogous statement holds within the framework of finite metric spaces, with lines defined using the notion of {\em betweenness}. In this paper, we prove that in the plane with the $L_1$ (als

Benoît de Courson, Léo Fitouchi, Jean-Philippe Bouchaud, Michael Benzaquen

The ability to learn from others (social learning) is often deemed a cause of human species success. But if social learning is indeed more efficient (whether less costly or more accurate) than individual learning, it raises the question of why would anyone engage in individual information seeking, which is a necessary condition for social learning's efficacy

David H. Wei

It is shown that a class of separately frustration-free (SFF) Hamiltonians can be Monte Carlo simulated efficiently on a classical computing machine, because such an SFF Hamiltonian corresponds to a Gibbs wavefunction whose nodal structure is efficiently computable by solving a small subsystem associated with a low-dimensional configuration subspace. It is f

Mikhail Grinberg, Kari Vilonen, Ting Xue

Let G|V, G connected, reductive over C, be a stable polar representation in the sense of [DK], satisfying some mild additional hypotheses. Given a G-equivariant rank one local system L on the general fiber of the quotient map f : V --> V/G, we compute the Fourier transform of the corresponding nearby cycle sheaf P on the zero-fiber of f. This provides a part

Jingbo Liu

We give a complete solution to an open problem of Thomas Cover in 1987 about the capacity of a relay channel in the general discrete memoryless setting without any additional assumptions. The key step in our approach is to lower bound a certain soft-max of a stochastic process by convex geometry methods, which is based on two ideas: First, the soft-max is lo

Xuerui Wang, Tigran Mkhoyan, Iren Mkhoyan, Roeland De Breuker

This paper deals with the simultaneous gust and maneuver load alleviation problem of a seamless active morphing wing. The incremental nonlinear dynamic inversion with quadratic programming control allocation and virtual shape functions (denoted as INDI-QP-V) is proposed to fulfill this goal. The designed control allocator provides an optimal solution while s

Valentin Deaconu

Given a self-similar groupoid action $(G,E)$ on the path space of a finite graph, we study the associated Exel-Pardo \'etale groupoid ${\mathcal G}(G,E)$ and its $C^*$-algebra $C^*(G,E)$. We review some facts about groupoid actions, skew products and semi-direct products and generalize a result of Renault about similarity of groupoids which resembles Takai d

Joren Brunekreef, Marcus Reitz

It is an open question whether fluctuations at the Planck scale in a non-perturbative theory of quantum gravity behave in such a way that the resulting semi-classical geometry can be modelled by a space that admits (approximate) Killing symmetries. We have investigated whether the notion of approximate Killing vector fields is suitable to address this questi

Jorge F. Lazo, Sara Moccia, Emanuele Frontoni, Elena De Momi

Breast cancer is one of the deadliest cancer worldwide. Timely detection could reduce mortality rates. In the clinical routine, classifying benign and malignant tumors from ultrasound (US) imaging is a crucial but challenging task. An automated method, which can deal with the variability of data is therefore needed. In this paper, we compared different Convo

Van-Khoa Nguyen, Santiago Agudelo

Ocean dynamics constitute a source of incertitude in determining the ocean's role in complex climatic phenomena. Current observation systems have limitations in achieving sufficiently statistical precision for three-dimensional oceanic data. It is crucial knowledge to describe the behavior of internal ocean structures. We present the data-driven approaches w

Kazushi Aoyama, Hikaru Kawamura

The hedgehog lattice, a three-dimensional periodic array of magnetic monopoles and antimonopoles, is known to be realized in the presence of the Dzyaloshinskii-Moriya (DM) interaction. Here, we demonstrate by means of Monte Carlo simulations that the hedgehog lattice is induced by not the DM interaction but frustration in classical Heisenberg antiferromagnet

Diogo Pires, Yasser Omar, João Seixas

The currently predicted increase in computational demand for the upcoming High-Luminosity Large Hadron Collider (HL-LHC) event reconstruction, and in particular jet clustering, is bound to challenge present day computing resources, becoming an even more complex combinatorial problem. In this paper, we show that quantum annealing can tackle dijet event cluste

Marcel Jackson, Wen Ting Zhang

The variety generated by the Brandt semigroup ${\bf B}_2$ can be defined within the variety generated by the semigroup ${\bf A}_2$ by the single identity $x^2y^2\approx y^2x^2$. Edmond Lee asked whether or not the same is true for the monoids ${\bf B}_2^1$ and ${\bf A}_2^1$. We employ an encoding of the homomorphism theory of hypergraphs to show that there i

Robi Bhattacharjee, Michal Moshkovitz

We investigate $k$-means clustering in the online no-substitution setting when the input arrives in \emph{arbitrary} order. In this setting, points arrive one after another, and the algorithm is required to instantly decide whether to take the current point as a center before observing the next point. Decisions are irrevocable. The goal is to minimize both t

Valentino Constantinou, Mori Kabiri

The United States is the largest distributor of legal services in the world, representing a $437 billion market. Of this, corporate legal departments pay law firms $80 billion for their services. Every month, legal departments receive and process invoices from these law firms and legal service providers. Legal invoice review is and has been a pain point for

Sergio Albeverio, Carlo Marinelli, Elisa Mastrogiacomo

We study the dependence of mild solutions to linear stochastic evolution equations on Hilbert space driven by Wiener noise, with drift having linear part of the type $A+\varepsilon G$, on the parameter $\varepsilon$. In particular, we study the limit and the asymptotic expansions in powers of $\varepsilon$ of these solutions, as well as of functionals thereo

Julia Siekiera, Stefan Kramer

The exploration of selected single nucleotide polymorphisms (SNPs) to identify genetic diversity between different sequencing population pools (Pool-seq) is a fundamental task in genetic research. As underlying sequence reads and their alignment are error-prone and univariate statistical solutions only take individual positions of the genome into account, th

Mariusz Mirek, Tomasz Z. Szarek, Błażej Wróbel

We prove that the discrete spherical maximal functions (in the spirit of Magyar, Stein and Wainger) corresponding to the Euclidean spheres in $\mathbb Z^d$ with dyadic radii have $\ell^p(\mathbb Z^d)$ bounds for all $p\in[2, \infty]$ independent of the dimensions $d\ge 5$. An important part of our argument is the asymptotic formula in the Waring problem for

M. A. Mojarro, R. Carrillo-Bastos, Jesús A. Maytorena

We explore the effect of valley-contrasting gaps in the optical response of two-dimensional anisotropic tilted Dirac systems. We study the spectrum of intraband and interband transitions through the joint density of states (JDOS), the optical conductivity tensor, and the Drude spectral weight. The energy bands present an indirect gap in each valley. Thus a n

Audrey Do, Matthew Duong, Alex McDaniel, Collin O'Connor

We study the possibility that an extended cosmic-ray leptonic and/or hadronic halo is at the origin of the large-scale gamma-ray emission detected from the Andromeda Galaxy (M31). We consider a broad ensemble of non-homogeneous diffusion scenarios and of cosmic-ray injection sources. We find that cosmic-ray electrons and protons could be, and very likely are

S. S. Melnyk, O. V. Usatenko, V. A. Yampol'skii

We study the random processes with non-local memory and obtain new solutions of the Mori-Zwanzig equation describing non-markovian systems. We analyze the system dynamics depending on the amplitudes $\nu$ and $\mu_0$ of the local and non-local memory and pay attention to the line in the ($\nu$, $\mu_0$)-plane separating the regions with asymptotically statio

Irene Drelichman, Ricardo G. Durán

We obtain a Bourgain-Br\'ezis-Mironescu formula on the limit behaviour of a modified fractional Sobolev seminorm when $s\nearrow 1$, which is valid in arbitrary bounded domains. In the case of extension domains, we recover the classical result.

Edward Hermann Haeusler

This article shows yet another proof of NP=CoNP$. In a previous article, we proved that NP=PSPACE and from it we can conclude that NP=CoNP immediately. The former proof shows how to obtain polynomial and, polynomial in time checkable Dag-like proofs for all purely implicational Minimal logic tautologies. From the fact that Minimal implicational logic is PSPA

Isaac Lucas-Gómez, Abelardo López-Fernández, Brenda Karen González-Pérez, M. Rivas-Castillo Andrea

The present Health Crisis tests the response of modern science and medicine to finding treatment for a new COVID-19 disease. The presentation on the world stage of antivirals such as remdesivir, obeys to the continuous investigation of biologically active molecules with multiple theoretical, computational and experimental tools. Diseases such as COVID:19 rem

Torsten Heinrich, Jangho Yang, Shuanping Dai

Understanding the microeconomic details of technological catch-up processes offers great potential for informing both innovation economics and development policy. We study the economic transition of the PR China from an agrarian country to a high-tech economy as one example for such a case. It is clear from past literature that rapidly rising productivity le

Ayan Bhattacharjee, Sandip K. Chakrabarti

Recent studies show that accretion flows around weakly magnetic Neutron Stars undergo multiple shocks, before reaching the surface of the star, which contribute to the spectral and timing variabilities observed in the X-Rays. Here, we report, for the first time, the spectral properties of a unified model of shocked accretion flows around Neutron Stars, based

Ronald DeVore, Boris Hanin, Guergana Petrova

Neural Networks (NNs) are the method of choice for building learning algorithms. Their popularity stems from their empirical success on several challenging learning problems. However, most scholars agree that a convincing theoretical explanation for this success is still lacking. This article surveys the known approximation properties of the outputs of NNs w

Xiangci Li, Gully Burns, Nanyun Peng

Even for domain experts, it is a non-trivial task to verify a scientific claim by providing supporting or refuting evidence rationales. The situation worsens as misinformation is proliferated on social media or news websites, manually or programmatically, at every moment. As a result, an automatic fact-verification tool becomes crucial for combating the spre

Lennart Klebl, Zachary A. H. Goodwin, Arash A. Mostofi, Dante M. Kennes

Electron-electron interactions are intrinsically long ranged, but many models of strongly interacting electrons only take short-ranged interactions into account. Here, we present results of atomistic calculations including both long-ranged and short-ranged electron-electron interactions for the magnetic phase diagram of twisted bilayer graphene and demonstra

Gweneth McKinley, Marcus Michelen, Will Perkins

We derive asymptotic formulas for the number of integer partitions with given sums of $j$th powers of the parts for $j$ belonging to a finite, non-empty set $J \subset \mathbb N$. The method we use is based on the `principle of maximum entropy' of Jaynes. This principle leads to an intuitive variational formula for the asymptotics of the logarithm of the num

William J. Henney

Broad Raman-scattered wings of hydrogen lines can be used to map neutral gas illuminated by high-mass stars in star forming regions. Raman scattering transforms far-ultraviolet starlight from the wings of the Lyman beta line (1022 Angstrom to 1029 Angstrom) to red visual light in the wings of the H alpha line (6400 Angstrom to 6700 Angstrom). Analysis of spa

Lucas S. Palacios, Serguei Tchoumakov, Maria Guix, Ignasio Pagonabarraga

Collective guidance of out-of-equilibrium systems without using external fields is a challenge of paramount importance in active matter, ranging from bacterial colonies to swarms of self-propelled particles. Designing strategies to guide active matter and exploiting enhanced diffusion associated to its motion will provide insights for application from sensin

Vishwanath Saragadam, Michael DeZeeuw, Richard Baraniuk, Ashok Veeraraghavan

We introduce a novel video-rate hyperspectral imager with high spatial, and temporal resolutions. Our key hypothesis is that spectral profiles of pixels in a super-pixel of an oversegmented image tend to be very similar. Hence, a scene-adaptive spatial sampling of an hyperspectral scene, guided by its super-pixel segmented image, is capable of obtaining high