February 2019 arXiv papers — page 12

S. Seki, M. Garst, J. Waizner, R. Takagi

Magnetic skyrmions, topological solitons characterized by a two-dimensional swirling spin texture, have recently attracted attention as stable particle-like objects. In a three-dimensional system, a skyrmion can extend in the third dimension forming a robust and flexible string structure, whose unique topology and symmetry are anticipated to host nontrivial

Alireza Sadeghi, Gang Wang, Georgios B. Giannakis

Caching is envisioned to play a critical role in next-generation content delivery infrastructure, cellular networks, and Internet architectures. By smartly storing the most popular contents at the storage-enabled network entities during off-peak demand instances, caching can benefit both network infrastructure as well as end users, during on-peak periods. In

Pengyu Chen, Xuping Zhang, Zhitao Zhang

In this paper, we investigate the global existence, uniqueness and asymptotic stability of time $\omega$-periodic classical solution for a class of extended Fisher-Kolmogorov equations with delays and general nonlinear term. We establish a general framework to find time $\omega$-periodic solutions for nonlinear extended Fisher-Kolmogorov equations with delay

Samuel L. Rudge, Daniel S. Kosov

The waiting time distribution has, in recent years, proven to be a useful statistical tool for characterising transport in nanoscale quantum transport. In particular, as opposed to moments of the distribution of transferred charge, which have historically been calculated in the long-time limit, waiting times are able to detect non-renewal behaviour in mesosc

Jingyi Wang, Jianwen Feng, Yijun Lou, Guanrong Chen

In this technical note, we propose a practicable quantized sampled velocity data coupling protocol for synchronization of a set of harmonic oscillators. The coupling protocol is designed in a quantized way via interconnecting the velocities encoded by a uniform quantizer with a zooming parameter in either a fixed or an adjustable form over a directed communi

Amir Gholami, Kurt Keutzer, George Biros

Residual neural networks can be viewed as the forward Euler discretization of an Ordinary Differential Equation (ODE) with a unit time step. This has recently motivated researchers to explore other discretization approaches and train ODE based networks. However, an important challenge of neural ODEs is their prohibitive memory cost during gradient backpropog

Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk

We investigate the internal representations that a recurrent neural network (RNN) uses while learning to recognize a regular formal language. Specifically, we train a RNN on positive and negative examples from a regular language, and ask if there is a simple decoding function that maps states of this RNN to states of the minimal deterministic finite automato

Shaorong Yan, Aaron Steven White

We propose a novel framework for modeling event-related potentials (ERPs) collected during reading that couples pre-trained convolutional decoders with a language model. Using this framework, we compare the abilities of a variety of existing and novel sentence processing models to reconstruct ERPs. We find that modern contextual word embeddings underperform

Joshua J. D'Agostino, Lisa J. Kewley, Brent A. Groves, Anne Medling

In the optical spectra of galaxies, methods for the separation of line emission arising from star formation and an additional hard component, such as shocks or AGN, is well-understood and possible with current diagnostics. However, such diagnostics fail when attempting to separate and define line emission which arises from shocked gas, and that arising from

Rui Shu, Hung H. Bui, Jay Whang, Stefano Ermon

The recognition network in deep latent variable models such as variational autoencoders (VAEs) relies on amortized inference for efficient posterior approximation that can scale up to large datasets. However, this technique has also been demonstrated to select suboptimal variational parameters, often resulting in considerable additional error called the amor

Xuan-Jian He, Jun Jia, Gao-Feng Jiao, L. Q. Chen

A novel two-mode non-degenerate squeezed light is generated based on a four-wave mixing (4WM) process driven by two pump fields crossing at a small angle. By exchanging the roles of the pump beams and the probe and conjugate beams, we have demonstrated the frequency-degenerate two-mode squeezed light with separated spatial patterns. Different from a 4WM proc

Shahriar Talebi, Marwan A. Simaan, Zhihua Qu

All-Against-One (AAO) games are a special class of multi-player games where all players except one are in direct conflict with the remaining player. In the case of Linear Quadratic Differential (LQD) games, the AAO structure can be used to describe a situation where all players except one are trying to regulate the state of the system (drive it towards the o

Sen Zhang, Xin Ma, Hongwang Lu, Weikai He

Echolocating bats locate the targets by echolocation. Many theoretical frameworks have been suggested the abilities of bats are related to the shapes of bats ears, but few artificial bat-like ears have been made to mimic the abilities, the difficulty of which lies in the determination of the elevation angle of the target. In this study, we present a device w

N. Ripunjay Acharya, Feng-Kun Guo, Ulf-G. Meißner, Chien-Yeah Seng

The accuracy of the lattice QCD computation of hadron-hadron scattering at low isospin depends critically on the ability to compute correlation functions with fermionic disconnected Wick contractions. This happens, for instance, in isospin $I=0$ $\pi\pi$ scattering, which receives contributions from rectangular and vacuum types of contractions among other ea

Samer Houri, Daiki Hatanaka, Yaroslav M. Blanter, Hiroshi Yamaguchi

The aim of this work is to theoretically investigate the possibility of Kerr frequency combs in mechanical systems. In particular, whether microelectrome-chanical devices (MEMS) can be used to generate frequency combs in a manner that is analogous to the optical frequency combs generated in optical microresona-tors with Kerr-type nonlinearity. The analysis a

Hongkang Yang, Esteban G. Tabak

The clustering problem, and more generally, latent factor discovery --or latent space inference-- is formulated in terms of the Wasserstein barycenter problem from optimal transport. The objective proposed is the maximization of the variability attributable to class, further characterized as the minimization of the variance of the Wasserstein barycenter. Exi

Alejandro Lopez-Bezanilla

Evidence of flat-band magnetism and half-metallicity in compressed twisted bilayer graphene is provided with first-principles calculations. We show that dynamic band-structure engineering in twisted bilayer graphene is possible by controlling the chemical composition with extrinsic doping, the interlayer coupling strength with pressure, and the magnetic orde

Alexander D'Amour

Unobserved confounding is a central barrier to drawing causal inferences from observational data. Several authors have recently proposed that this barrier can be overcome in the case where one attempts to infer the effects of several variables simultaneously. In this paper, we present two simple, analytical counterexamples that challenge the general claims t

M. Freedman, M. B. Hastings

There exists an index theory to classify strictly local quantum cellular automata in one dimension. We consider two classification questions. First, we study to what extent this index theory can be applied in higher dimensions via dimensional reduction, finding a classification by the first homology group of the manifold modulo torsion. Second, in two dimens

Panpan Yu, Qingna Li

Image ranking is to rank images based on some known ranked images. In this paper, we propose an improved linear ordinal distance metric learning approach based on the linear distance metric learning model. By decomposing the distance metric $A$ as $L^TL$, the problem can be cast as looking for a linear map between two sets of points in different spaces, mean

Behnam Malmir, Shing I Chang

This paper describes a method to convert Microsoft Kinect coordinates into gait parameters in order to detect a person's gait change. The proposed method can help quantify the progress of physical therapy. Microsoft Kinect, a popular platform for video games, was used to generate 25 joints to form a human skeleton, and then the proposed method converted the

E. Sonbas, K. S. Dhuga, E. Gogus

By comparing the ratio of flux densities in the X-ray and UV wavebands by way of the spectral optical-X-Ray index, $\alpha_{ox}$, we explore the relation between the emissions in the respective wavebands for a number of ULXs with known optical counterparts. We present a significant (anti)correlation between $\alpha_{ox}$ and the L(2500 A)-UV luminosity. In c

Amin Jalali, Zhi Ding

In recent release of the new cellular standard known as 5G New Radio (5G-NR), the physical downlink control channel (PDCCH) has adopted polar codes for error protection. Similar to 4G-LTE, each active user equipment (UE) must blindly detect its own PDCCH in the downlink search space. This work investigates new ways to improve the accuracy of PDCCH blind dete

Chen-Te Ma, Hongfei Shu

We study the integrability from the spectral form factor in the Chern-Simons formulation. The effective action in the higher spin sector was not derived so far. Therefore, we begin from the SL(3) Chern-Simons higher spin theory. Then the dimensional reduction in this Chern-Simons theory gives the SL(3) reparametrization invariant Schwarzian theory, which is

Yingjie Zhang, Pengfei Liu, Hongyi Sun, Hu Xu

It is recently noted that in certain centrosymmetric compounds, spin-orbit interaction couples each local sector that lacks inversion symmetry and thus leads to visible spin polarization effects in the real space, dubbed as 'hidden spin polarization (HSP)'. However, observable spin polarization of a given local sector suffers interference by its inversion pa

Vladimir S. Gerdjikov, Rossen I. Ivanov, Aleksander A. Stefanov

The present paper is dedicated to integrable models with Mikhailov reduction groups $G_R \simeq \mathbb{D}_h.$ Their Lax representation allows us to prove, that their solution is equivalent to solving Riemann-Hilbert problems, whose contours depend on the realization of the $G_R$-action on the spectral parameter. Two new examples of Nonlinear Evolution Equat

Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis

"How much is my data worth?" is an increasingly common question posed by organizations and individuals alike. An answer to this question could allow, for instance, fairly distributing profits among multiple data contributors and determining prospective compensation when data breaches happen. In this paper, we study the problem of data valuation by utilizing

Suryansh Kumar

A simple prior free factorization algorithm \cite{dai2014simple} is quite often cited work in the field of Non-Rigid Structure from Motion (NRSfM). The benefit of this work lies in its simplicity of implementation, strong theoretical justification to the motion and structure estimation, and its invincible originality. Despite this, the prevailing view is, th

Ali Cheraghian, Shafin Rahman, Lars Petersson

Recent deep learning architectures can recognize instances of 3D point cloud objects of previously seen classes quite well. At the same time, current 3D depth camera technology allows generating/segmenting a large amount of 3D point cloud objects from an arbitrary scene, for which there is no previously seen training data. A challenge for a 3D point cloud re

Hans Raj Tiwary, Victor Verdugo, Andreas Wiese

Linear programming is a powerful method in combinatorial optimization with many applications in theory and practice. For solving a linear program quickly it is desirable to have a formulation of small size for the given problem. A useful approach for this is the construction of an extended formulation, which is a linear program in a higher dimensional space

Carina Curto, Christopher Langdon, Katherine Morrison

To any inhibition-dominated threshold-linear network (TLN) we can associate a directed graph that captures the pattern of strong and weak inhibition between neurons. Robust motifs are graphs for which the structure of fixed points in the network is independent of the choice of connectivity matrix $W$, and whose dynamics are thus greatly constrained. This mak

Hamid Karimi, Jiliang Tang

On the one hand, nowadays, fake news articles are easily propagated through various online media platforms and have become a grand threat to the trustworthiness of information. On the other hand, our understanding of the language of fake news is still minimal. Incorporating hierarchical discourse-level structure of fake and real news articles is one crucial

Hector O. Silva, Nicolás Yunes

The x-ray emission of hot spots on the surface of neutron stars is the prime target of the Neutron star Interior Composition Explorer (NICER). These x-ray pulse profiles not only encode information of the bulk properties of these stars, which teaches us about matter at supranuclear densities, but also about the spacetime curvature around them which teaches u

C. Dalfó, M. A. Fiol

In this paper, we describe a semi-discrete method for a numerical resolution of a type of partial differential equations, called the method of lines (MOL). This method is based on the discretization of all but one of the variables of the problem. We illustrate this method by solving the Laplace equation in Cartesian coordinates. We compare the concepts used

Ainagul Jumabekova, Julien Berger, Denys Dutykh, Hervé Le Meur

The goal of this study is to propose an efficient numerical model for the predictions of capillary adsorption phenomena in a porous material. The Scharfetter-Gummel numerical scheme is proposed to solve an advection-diffusion equation with gravity flux. Its advantages such as accuracy, relaxed stability condition, and reduced computational cost are discussed

Hasan Zakeri, Panos J. Antsaklis

Analysis and resilient design of Cyber-physical Systems have greatly benefited from energy based concepts of passivity and dissipativity. Recently, there has been much research devoted to the use of passivity indices in different components of Cyber-physical systems. Passivity indices are measures of passivity, indicating how passive a system is or how far i

Chih-Hong Cheng, Dhiraj Gulati, Rongjie Yan

We provide a summary over architectural approaches that can be used to construct dependable learning-enabled autonomous systems, with a focus on automated driving. We consider three technology pillars for architecting dependable autonomy, namely diverse redundancy, information fusion, and runtime monitoring. For learning-enabled components, we additionally s

Patrick Buchfink, Ashish Bhatt, Bernard Haasdonk

Parametric high-fidelity simulations are of interest for a wide range of applications. But the restriction of computational resources renders such models to be inapplicable in a real-time context or in multi-query scenarios. Model order reduction (MOR) is used to tackle this issue. Recently, MOR is extended to preserve specific structures of the model throug

Jan Dvořák, Zdeněk Hanzálek

The portfolio of models offered by car manufacturing groups often includes many variants (i.e., different car models and their versions). With such diversity in car models, variant management becomes a formidable task. Thus, there is an effort to keep the variants as close as possible. This simple requirement forms a big challenge in the area of communicatio

Anna Belova, Igors Gorbovickis

The multiplier $λ_n$ of a periodic orbit of period $n$ can be viewed as a (multiple-valued) algebraic function on the space of all complex quadratic polynomials $p_c(z)=z^2+c$. We provide a numerical algorithm for computing critical points of this function (i.e., points where the derivative of the multiplier with respect to the complex parameter $c$ vanishes

Leon Bungert, Martin Burger, Daniel Tenbrinck

In this work we investigate the computation of nonlinear eigenfunctions via the extinction profiles of gradient flows. We analyze a scheme that recursively subtracts such eigenfunctions from given data and show that this procedure yields a decomposition of the data into eigenfunctions in some cases as the 1-dimensional total variation, for instance. We discu

Qinye Tang, Xiaozhe Wang

Sustained oscillations in power systems are dangerous. There are various mechanisms, for instance, limit cycle and forced oscillation, that may lead to sustained oscillations, which nevertheless are hard to differentiate. In this paper, a novel periodogram-based method to distinguish different oscillation mechanism is proposed, which can quantitatively extra

Shromona Ghosh, Somil Bansal, Alberto Sangiovanni-Vincentelli, Sanjit A. Seshia

We consider the problem of extracting safe environments and controllers for reach-avoid objectives for systems with known state and control spaces, but unknown dynamics. In a given environment, a common approach is to synthesize a controller from an abstraction or a model of the system (potentially learned from data). However, in many situations, the relatio

Kit Newton, Qin Li, Andrew Stuart

Many naturally-occuring models in the sciences are well-approximated by simplified models, using multiscale techniques. In such settings it is natural to ask about the relationship between inverse problems defined by the original problem and by the multiscale approximation. We develop an approach to this problem and exemplify it in the context of optical tom

Karthikeya S Parunandi, Suman Chakravorty

Traditional stochastic optimal control methods that attempt to obtain an optimal feedback policy for nonlinear systems are computationally intractable. In this paper, we derive a decoupling principle between the open loop plan, and the closed loop feedback gains, that leads to a perturbation feedback control based solution to optimal control problems under a

Jin Wu

Magnetometer is a significant sensor for integrated navigation. However, it suffers from many kinds of unknown dynamic magnetic disturbances. We study the problem of online estimating such disturbances via a nonlinear optimization aided by intermediate quaternion estimation from inertial fusion. The proposed optimization is constrained by geographical distri

Afroza Shirin, Fabio Della Rossa, Isaac Klickstein, John Russell

The Glucose-Insulin-Glucagon nonlinear model [1-4] accurately describes how the body responds to exogenously supplied insulin and glucagon in patients affected by Type I diabetes. Based on this model, we design infusion rates of either insulin (monotherapy) or insulin and glucagon (dual therapy) that can optimally maintain the blood glucose level within desi

Tin Lai, Fabio Ramos, Gilad Francis

Sampling efficiency in a highly constrained environment has long been a major challenge for sampling-based planners. In this work, we propose Rapidly-exploring Random disjointed-Trees* (RRdT*), an incremental optimal multi-query planner. RRdT* uses multiple disjointed-trees to exploit local-connectivity of spaces via Markov Chain random sampling, which utili

Johan Helsing, Anders Karlsson

An integral equation-based numerical method for scattering from multi-dielectric cylinders is presented. Electromagnetic fields are represented via layer potentials in terms of surface densities with physical interpretations. The existence of null-field representations then adds superior flexibility to the modeling. Local representations are used for fast fi

Liyong Lin, Sander Thuijsman, Yuting Zhu, Simon Ware

In this work, we propose and develop a new discrete-event based actuator attack model on the closed-loop system formed by the plant and the supervisor. We assume the actuator attacker partially observes the execution of the closed-loop system and eavesdrops the control commands issued by the supervisor. The attacker can modify each control command on a speci

Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen

Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals. Scaling up the posterior inference for massive-scale matrices is challenging and requires distributing both data and computation over many workers, making communication the main comput

Ulrike Malmendier, Demian Pouzo, Victoria Vanasco

How do macro-financial shocks affect investor behavior and market dynamics? Recent evidence on experience effects suggests a long-lasting influence of personally experienced outcomes on investor beliefs and investment, but also significant differences across older and younger generations. We formalize experience-based learning in an OLG model, where differen

Percy Deift

The author discusses integrability of Hamiltonian dynamical systems in the aftermath of KdV. The author also discusses the role of integrable systems in certain numerical computations, particularly the computation of the eigenvalues of a random symmetric matrix.

Matthew D. Watson, Pavel Dudin, Luke C. Rhodes, Daniil V. Evtushinsky

We revisit the electronic structure of BaFe$_2$As$_2$, the archetypal parent compound of the Fe-based superconductors, using angle-resolved photoemission spectroscopy (ARPES). Our high-resolution measurements of samples detwinned by the application of a mechanical strain reveal a highly anisotropic 3D Fermi surface in the low temperature magnetic phase. By c

Walid Saad, Mehdi Bennis, Mingzhe Chen

The ongoing deployment of 5G cellular systems is continuously exposing the inherent limitations of this system, compared to its original premise as an enabler for Internet of Everything applications. These 5G drawbacks are currently spurring worldwide activities focused on defining the next-generation 6G wireless system that can truly integrate far-reaching

Jorge Campos-Gonzalez-Angulo, Raphael F. Ribeiro, Joel Yuen-Zhou

In the regime of ensemble vibrational strong coupling (VSC), a macroscopic number $N$ of molecular transitions couple to each resonant cavity mode, yielding two hybrid light-matter (polariton) modes, and a reservoir of $N-1$ dark states whose chemical dynamics are essentially those of the bare molecules. This fact is seemingly in opposition to the recently r

Eric S. Perlman, Mark Birkinshaw, Matthias Kadler, Serguei Komissarov

Jets are a ubiquitous part of the accretion process, seen in a wide variety of objects ranging from active galaxies (AGN) to X-ray binary stars and even newly formed stars. AGN jets are accelerated by the supermassive black hole of their host galaxy by a coupling between the magnetic field and inflowing material. They are the source for many exciting phenome

W. Pan, W. Kang, M. P. Lilly, J. L. Reno

We report on detailed experimental studies of a high-quality heterojunction insulated-gate field-effect transistor (HIGFET) to probe the particle-hole symmetry (PHS) of the FQHE states about half-filling in the lowest Landau level. The HIGFET was specially designed to vary the density of a two-dimensional electronic system under constant magnetic fields. We

Kristoffer Glover

We consider the problem of optimally stopping a Brownian bridge with an unknown pinning time so as to maximise the value of the process upon stopping. Adopting a Bayesian approach, we assume the stopper has a general continuous prior and is allowed to update their belief about the value of the pinning time through sequential observations of the process. Unce

Gergana Todorova, Anastasios Noulas

Ambulance services worldwide are of vital importance to population health. Timely responding to incidents by dispatching an ambulance vehicle to the location a call came from can offer significant benefits to patient care across a number of medical conditions. Moreover, identifying the reasons that drive ambulance activity at an area not only can improve the

Beka Ergemlidze, Tao Jiang, Abhishek Methuku

Let $t$ be an integer such that $t\geq 2$. Let $K_{2,t}^{(3)}$ denote the triple system consisting of the $2t$ triples $\{a,x_i,y_i\}$, $\{b,x_i,y_i\}$ for $1 \le i \le t$, where the elements $a, b, x_1, x_2, \ldots, x_t,$ $y_1, y_2, \ldots, y_t$ are all distinct. Let $ex(n,K_{2,t}^{(3)})$ denote the maximum size of a triple system on $n$ elements that does

Jonas Latz

The subject of this article is the introduction of a new concept of well-posedness of Bayesian inverse problems. The conventional concept of (Lipschitz, Hellinger) well-posedness in [Stuart 2010, Acta Numerica 19, pp. 451-559] is difficult to verify in practice and may be inappropriate in some contexts. Our concept simply replaces the Lipschitz continuity of

Carlos E. Yaguna

The first-year results from DEAP-3600, a single-phase liquid argon direct-detection dark matter experiment, were recently reported. At first sight, they seem to provide no new constraints, as the limit lies well within the region already excluded by three different xenon experiments: LUX, PandaX-II, and XENON1T. We point out, however, that this conclusion is

Stephen Ugwuanyi, James Irvine

Internet of Things (IoT) is the new industrial slogan for connecting intelligent and unintelligent devices to the web. The problem of security of data transfer, interoperability of different proposed methodologies, the ubiquity of Wi-Fi and the development of low power consuming MCUs has broadened the search for the best alternative technology for IoT in the

Eric E. Severson, David Haley, David Doty

We study the composability of discrete chemical reaction networks (CRNs) that stably compute (i.e., with probability 0 of error) integer-valued functions $f:\mathbb{N}^d\to\mathbb{N}$. We consider output-oblivious CRNs in which the output species is never a reactant (input) to any reaction. The class of output-oblivious CRNs is fundamental, appearing in earl

Pushpalatha C. Bhat, Geoffrey N. Taylor

The International Committee for Future Accelerators (ICFA) has been in existence for well over four decades. Its mission is to facilitate international collaboration in the construction and use of accelerators for high energy physics. This report presents, after a brief introduction, some recent activities of ICFA and its panels. The International Linear Col

Jae Sung Park, Dinesh Manocha

We present an efficient algorithm to compute tight upper bounds of collision probability between two objects with positional uncertainties, whose error distributions are represented with non-Gaussian forms. Our approach can handle noisy datasets from depth sensors, whose distributions may correspond to Truncated Gaussian, Weighted Samples, or Truncated Gauss

Marko J. Rančić, Silas Hoffman, Constantin Schrade, Jelena Klinovaja

We study the coupling between a singlet-triplet qubit realized in a double quantum dot to a topological qubit realized by spatially well-separated Majorana bound states. We demonstrate that the singlet-triplet qubit can be leveraged for readout of the topological qubit and for supplementing the gate operations that cannot be performed by braiding of Majorana

Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine

Q-learning methods represent a commonly used class of algorithms in reinforcement learning: they are generally efficient and simple, and can be combined readily with function approximators for deep reinforcement learning (RL). However, the behavior of Q-learning methods with function approximation is poorly understood, both theoretically and empirically. In

D. Gaiotto, T. Johnson-Freyd, E. Witten

We explore the dynamics of a simple class of two-dimensional models with $(0,1)$ supersymmetry, namely sigma-models with target $S^3$ and the minimal possible set of fields. For any nonzero value of the Wess--Zumino coupling $k$, we describe a superconformal fixed point to which we conjecture that the model flows in the infrared. For $k=0$, we conjecture tha

Parinya Ekparinya, Vincent Gramoli, Guillaume Jourjon

In this paper, we explore vulnerabilities and countermeasures of the recently proposed blockchain consensus based on proof-of-authority. The proof-of-work blockchains, like Bitcoin and Ethereum, have been shown both theoretically and empirically vulnerable to double spending attacks. This is why Byzantine fault tolerant consensus algorithms have gained popul

Christian Fries, Peter Kohl-Landgraf, Björn Paffen, Stefanie Weddigen

In this note we describe the application of existing smart contract technologies with the aim to construct a new digital representation of a financial derivative contract. We compare several existing DLT based technologies. We provide a detailed description of two separate prototypes which are able to be executed on a centralized and on a DLT platform respec

Friedrich Martin Schneider, Andreas Thom

We study harmonic functions and Poisson boundaries for Borel probability measures on general (i.e., not necessarily locally compact) topological groups, and we prove that a second-countable topological group is amenable if and only if it admits a fully supported, regular Borel probability measure with trivial Poisson boundary. This generalizes work of Kaiman

Guodong Zhu, Peng Wei

This paper addresses the air traffic flow management research problem of determining reroute, ground delay and air delay for flights using stochastic weather forecast information. The overall goal is to minimize system-wide reroute and delay costs. This problem is a primary concern in United States and especially in its northeastern region, and is also the k

Don Daniel, William T. Taitano, Luis Chacón

Upon application of a sufficiently strong electric field, electrons break away from thermal equilibrium and approach relativistic speeds. These highly energetic runaway electrons (MeV) play a significant role in tokamak disruption physics, and therefore their accurate understanding is essential to develop reliable mitigation strategies. For this purpose, we

Sophie Arnaud-Haond, Solenn Stoeckel, Diane Bailleul

Seagrass meadows are among the most important coastal ecosystems, in terms of both spatial extent and ecosystem services, but they are also declining worldwide. Understanding the drivers of seagrass meadow dynamics is essential for designing sound management, conservation, and restoration strategies. However, the poor knowledge of the effect of clonality on

Sirisha Rambhatla, Nikos D. Sidiropoulos, Jarvis Haupt

We propose a technique to develop (and localize in) topological maps from light detection and ranging (Lidar) data. Localizing an autonomous vehicle with respect to a reference map in real-time is crucial for its safe operation. Owing to the rich information provided by Lidar sensors, these are emerging as a promising choice for this task. However, since a L

Eurika Kaiser, J. Nathan Kutz, Steven L. Brunton

The Koopman and Perron Frobenius transport operators are fundamentally changing how we approach dynamical systems, providing linear representations for even strongly nonlinear dynamics. Although there is tremendous potential benefit of such a linear representation for estimation and control, transport operators are infinite-dimensional, making them difficult

Sirisha Rambhatla, Xingguo Li, Jarvis Haupt

Localizing targets of interest in a given hyperspectral (HS) image has applications ranging from remote sensing to surveillance. This task of target detection leverages the fact that each material/object possesses its own characteristic spectral response, depending upon its composition. As $\textit{signatures}$ of different materials are often correlated, ma

Sirisha Rambhatla, Xingguo Li, Jineng Ren, Jarvis Haupt

We consider the task of localizing targets of interest in a hyperspectral (HS) image based on their spectral signature(s), by posing the problem as two distinct convex demixing task(s). With applications ranging from remote sensing to surveillance, this task of target detection leverages the fact that each material/object possesses its own characteristic spe

Sebastián Donoso, Andreas Koutsogiannis, Wenbo Sun

Exploiting the recent work of Tao and Ziegler on a concatenation theorem on factors, we find explicit characteristic factors for multiple averages along polynomials on systems with commuting transformations, and use them to study criteria of joint ergodicity for sequences of the form $(T^{p_{1,j}(n)}_{1}\cdot\ldots\cdot T^{p_{d,j}(n)}_{d})_{n\in\mathbb{Z}},$

Fréderic Godin, Anjishnu Kumar, Arpit Mittal

In this paper, we investigate the challenges of using reinforcement learning agents for question-answering over knowledge graphs for real-world applications. We examine the performance metrics used by state-of-the-art systems and determine that they are inadequate for such settings. More specifically, they do not evaluate the systems correctly for situations

Jinho Choi

In this paper, we propose a compressive random access (CRA) scheme using multiple resource blocks (RBs) to support massive connections for machine type communications (MTC). The proposed CRA scheme is scalable. As a result, if the number of devices increases, more RBs can be added to support them. Thanks to multiple RBs, we can employ fast retrial between RB

Yotam Fine

Let $G,D_{0},D_{1}$ be finite groups such that $D_{0}\trianglelefteq D_{1}$ are groups of automorphisms of $G$ that contain the inner automorphisms of $G$. Assume that $D_{1}/D_{0}$ has a normal $2$-complement and that $D_{1}$ acts fixed-point-freely on the set of $D_{0}$-conjugacy classes of involutions of $G$ (i.e., $C_{D_{1}}(a)D_{0}<D_{1}$ for every invo

Hong Xiao, Eky Febrianto, Qiaoling Zhang, Fehmi Cirak

We introduce an immersed high-order discontinuous Galerkin method for solving the compressible Navier-Stokes equations on non-boundary-fitted meshes. The flow equations are discretised with a mixed discontinuous Galerkin formulation and are advanced in time with an explicit time marching scheme. The discretisation meshes may contain simplicial (triangular or

Isaac Oscar Gariano, Marco Servetto, Alex Potanin

In this paper we use pre existing language support for type modifiers and object capabilities to enable a system for sound runtime verification of invariants. Our system guarantees that class invariants hold for all objects involved in execution. Invariants are specified simply as methods whose execution is statically guaranteed to be deterministic and not a

ATLAS, CMS Collaborations

Manuscript of volume 2 of the Yellow Report on the "Workshop on the Physics of HL-LHC and perspectives at HE-LHC" containing the notes produced by the ATLAS and CMS collaborations as input to the Yellow Report volume 1.

Rohit J. Kate, Noah Pearce, Debesh Mazumdar, Vani Nilakantan

Acute kidney injury (AKI) commonly occurs in hospitalized patients and can lead to serious medical complications. In order to optimally predict AKI before it develops at any time during a hospital stay, we present a novel framework in which AKI is continually predicted automatically from EHR data over the entire hospital stay instead of at only one particula

Giacomo Mauro D'Ariano, Marco Erba, Paolo Perinotti

Quantum walks (QWs) describe the evolution of quantum systems on graphs. An intrinsic degree of freedom---called the coin and represented by a finite-dimensional Hilbert space---is associated to each node. Scalar quantum walks are QWs with a one-dimensional coin. We propose a general strategy allowing one to construct scalar QWs on a broad variety of graphs,

Mukul Bhattacharya, Pawan Kumar

We present a method to estimate the source properties of FRBs from observations by assuming a fixed DM contribution from a MW-like host galaxy, pulse temporal broadening models for turbulent plasma and a flat FRB energy spectrum. We then perform Monte Carlo simulations to constrain the properties of the FRB source, its host galaxy and scattering in the inter

Richa Tripathi, Amit Reza, Dinesh Garg

The application of machine learning (ML) techniques span a vast spectrum ranging from speech, face and character recognition, medical diagnosis, anomaly detection in data to the general classification, prediction, and regression problems. In the present work, we solve the problem of predicting R_0 for disease spreading on complex networks using the regressio

Jacob Fox, Ray Li

The hedgehog $H_t$ is a 3-uniform hypergraph on vertices $1,\dots,t+\binom{t}{2}$ such that, for any pair $(i,j)$ with $1\le i<j\le t$, there exists a unique vertex $k>t$ such that $\{i,j,k\}$ is an edge. Conlon, Fox, and R\"odl proved that the two-color Ramsey number of the hedgehog grows polynomially in the number of its vertices, while the four-color Rams

Xuhui Meng, George Em Karniadakis

We propose a new composite neural network (NN) that can be trained based on multi-fidelity data. It is comprised of three NNs, with the first NN trained using the low-fidelity data and coupled to two high-fidelity NNs, one with activation functions and another one without, in order to discover and exploit nonlinear and linear correlations, respectively, betw

Robert J. De Rosa, Paul Kalas

We present an investigation into the kinematics of HD 106906 using the newly released Gaia DR2 catalog to search for close encounters with other members of the Scorpius-Centaurus (Sco-Cen) association. HD 106906 is an eccentric spectroscopic binary that hosts both a large asymmetric debris disk extending out to at least 500 au and a directly imaged planetary

Xue-Ning Bai, Eve C. Ostriker, Illya Plotnikov, James M. Stone

The gyro-resonant cosmic-ray (CR) streaming instability is believed to play a crucial role in CR transport, leading to growth of Alfv\'en waves at small scales that scatter CRs, and impacts the interaction of CRs with the ISM on large scales. However, extreme scale separation ($\lambda \ll \rm pc$), low cosmic ray number density ($n_{\rm CR}/n_{\rm ISM} \sim

Amanda Folsom, Min-Joo Jang, Sam Kimport, Holly Swisher

In 2007, G.E. Andrews introduced the $(n+1)$-variable combinatorial generating function $R_n(x_1,x_2,\cdots,x_n;q)$ for ranks of $n$-marked Durfee symbols, an $(n+1)$-dimensional multisum, as a vast generalization to the ordinary two-variable partition rank generating function. Since then, it has been a problem of interest to understand the automorphic prope

Duvalier Madrid-Úsuga, Cristian E. Susa, John H. Reina

Understanding electron transfer in organic molecules is of great interest in quantum materials for light harvesting, energy conversion, and integration of molecules into solar cells. This, however, poses the challenge of designing specific optimal molecular structure for which the processes of ultrafast quantum coherence and electron transport are not so wel

Pierre Nazé, Marcus V. S. Bonança

The reliability of physical theories depends on whether they agree with well established physical laws. In this work, we address the compatibility of the Hamiltonian formulation of linear-response theory with the Second Law of Thermodynamics. In order to do so, we verify three complementary aspects often understood as statements of the Second Law: 1. No diss

Stefan Küchemann, Pascal Klein, Henning Fouckhardt, Sebastian Gröber

The concepts of the Coriolis and the centrifugal force are essential in various scientific fields and they are standard components of introductory physics lectures. In this paper we explore how students understand and apply concepts of rotating frames of reference in the context of an exemplary lecture demonstration experiment. We found in a $Predict-Observe

Michael I. Ganzburg

Let $V\subset\R^m$ be a centrally symmetric convex body and let $V^*\subset\R^m$ be its polar. We prove limit relations between the sharp constants in the multivariate Markov-Bernstein-Nikolskii type inequalities for algebraic polynomials on $V^*$ and the corresponding constants for entire functions of exponential type with the spectrum in $V$.