November 2018 arXiv papers — page 70

Zhenxing Zhang, P. Z. Zhao, Tenghui Wang, Liang Xiang

Nonadiabatic holonomic quantum computation has received increasing attention due to its robustness against control errors as well as high-speed realization. The original protocol of nonadiabatic holonomic one-qubit gates has been experimentally demonstrated with superconducting transmon qutrit. However, the original protocol requires two noncommuting gates t

Filippos Koliopanos, Georgios Vasilopoulos, Johannes Buchner, Chandreyee Maitra

Methods. We analyzed broadband XMM-Newton and NuSTAR observations of NGC 300 ULX1, performing phase-averaged and phase-resolved spectroscopy. We compared two physically motivated models for the source spectrum: Non-thermal accretion column emission modeled by a power law with high-energy exponential roll-off (AC model) vs multicolor thermal emission from an

Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson, Jesper Jensen

Humans tend to change their way of speaking when they are immersed in a noisy environment, a reflex known as Lombard effect. Current speech enhancement systems based on deep learning do not usually take into account this change in the speaking style, because they are trained with neutral (non-Lombard) speech utterances recorded under quiet conditions to whic

Emanuele Parrinello, Ayse Unsal, Petros Elia

The work explores the fundamental limits of coded caching in heterogeneous networks where multiple ($N_0$) senders/antennas, serve different users which are associated (linked) to shared caches, where each such cache helps an arbitrary number of users. Under the assumption of uncoded cache placement, the work derives the exact optimal worst-case delay and Do

Amandeep Singh Bhatia, Ajay Kumar

With increasing advancements in technology, it is expected that the emergence of a quantum computer will potentially break many of the public-key cryptosystems currently in use. It will negotiate the confidentiality and integrity of communications. In this regard, we have privacy protectors (i.e. Post-Quantum Cryptography), which resists attacks by quantum c

Yoichi Higashi, Huiming Zhang, Yasunori Mawatari

Magnetization loss on a twisted superconducting (SC) tape in a ramped magnetic field is theoretically investigated through the use of a power law for the electric field--current density characteristics and a sheet current approximation. First, the Maxwell equation in a helicoidal coordinate system is derived to model a twisted SC tape, taking account of the

A. M. Sobolev, A. P. Bisyarina, S. Yu. Gorda, A. M. Tatarnikov

We report variation of K-band infrared (IR) emission in the vicinity of the G025.65+1.05 water and methanol maser source. New observational data were obtained with 2.5m telescope of the Caucasian Mountain Observatory (CMO) of Moscow State University on 2017-09-21 during the strong water maser flare. We found that the IR source situated close to the maser pos

Yoshihiro Nishiyama

The quantum Ising chain with the interaction decaying as a power law $1/r^{1+σ}$ of the distance between spins $r$ was investigated numerically. A particular attention was paid to the low-energy spectrum, namely, the single-magnon and two-magnon-bound-state masses, $m_{1,2}$, respectively, in the ordered phase. It is anticipated that for each $σ$, the scaled

Y. Shimajiri, Ph. Andre, P. Palmeirim, D. Arzoumanian

Herschel observations have emphasized the role of molecular filaments in star formation. However, the origin and evolution of these filaments are not yet well understood, partly because of the lack of kinematic information. To examine whether the B211/B213 filament is accreting background gas due to its gravitational potential, we produced a toy accretion mo

Amer Rasheed, Aziz Belmiloudi

In this article, we study the error and stability of the proposed numerical scheme in order to solve a two dimensional anisotropic phase-field model with convection and externally applied magnetic field in an isothermal solidification of binary alloys. The proposed numerical scheme is based on mixed finite element method satisfying the CFL condition. A parti

Xiaolin Li, Min Zhang, Yixing Wang, Min Zhang

Numerical modeling of viscoelastic properties is critical to developing the structure-property relationship of polymer nanocomposites. While it is recognized that the altered polymer region near filler particles, the interphase, significantly contributes to enhancements of composite properties, the spatial distribution of interphase properties is rarely cons

Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alex Bronstein

Representing a graph as a vector is a challenging task; ideally, the representation should be easily computable and conducive to efficient comparisons among graphs, tailored to the particular data and analytical task at hand. Unfortunately, a "one-size-fits-all" solution is unattainable, as different analytical tasks may require different attention t

Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson, Jesper Jensen

Audio-visual speech enhancement (AV-SE) is the task of improving speech quality and intelligibility in a noisy environment using audio and visual information from a talker. Recently, deep learning techniques have been adopted to solve the AV-SE task in a supervised manner. In this context, the choice of the target, i.e. the quantity to be estimated, and the

Takumi Iritani, for HAL QCD Collaboration

In lattice QCD, both direct method and HAL QCD method are used to investigate the two-baryon systems. We show that due to the contamination of the scattering excited states, it is challenging to measure the eigenenergy from the temporal correlation in the direct method, while the HAL QCD method can extract the information of the interaction from both scatter

Minggang Zeng, Jatin Nitin Kumar, Zeng Zeng, Ramasamy Savitha

A fast and accurate predictive tool for polymer properties is demanding and will pave the way to iterative inverse design. In this work, we apply graph convolutional neural networks (GCNN) to predict the dielectric constant and energy bandgap of polymers. Using density functional theory (DFT) calculated properties as the ground truth, GCNN can achieve remark

Oliber Passon, Thomas Zügge, Johannes Grebe-Ellis

Elementary particle physics is gradually implemented into science curricula at high school level. However, common presentations on educational, semi-technical or popular level contain or support severe misconceptions. We discuss in particular the notion of `particle', the interaction between them and the use of Feynman diagrams. In many cases the true no

Meng Zhang, Youyi Zheng

We introduce Hair-GANs, an architecture of generative adversarial networks, to recover the 3D hair structure from a single image. The goal of our networks is to build a parametric transformation from 2D hair maps to 3D hair structure. The 3D hair structure is represented as a 3D volumetric field which encodes both the occupancy and the orientation informatio

Dong-Yang Wang, Cheng-Hua Bai, Shutian Liu, Shou Zhang

In the usual optomechanical systems, the stability of the systems severely limits those researches of the macroscopic quantum effects. We study an usual cavity optomechanical system where the frequency of the optical mode is shaken periodically. We find that, when the optical shaking frequency is large enough, the shake of the optical mode can stabilize the

Subhasish Chaki, Rajarshi Chakrabarti

A prime example of non-equilibrium or active environment is a biological cell. In order to understand in-vivo functioning of biomolecules such as proteins, chromatins, a description beyond equilibrium is absolutely necessary. In this context, biomolecules have been modeled as Rouse chains in Gaussian active bath. However, these non-equilibrium fluctuations i

Sergey Pankov

Policy gradient methods are very attractive in reinforcement learning due to their model-free nature and convergence guarantees. These methods, however, suffer from high variance in gradient estimation, resulting in poor sample efficiency. To mitigate this issue, a number of variance-reduction approaches have been proposed. Unfortunately, in the challenging

Moritz Kulessa, Alejandro Molina, Carsten Binnig, Benjamin Hilprecht

Interactive visualizations are arguably the most important tool to explore, understand and convey facts about data. In the past years, the database community has been working on different techniques for Approximate Query Processing (AQP) that aim to deliver an approximate query result given a fixed time bound to support interactive visualizations better. How

Y. P. Shen, B. Guo, Z. H. Li, Y. J. Li

The ${}^{12}\mathrm{C}(α,γ){}^{16}\mathrm{O}$ reaction plays a key role in the evolution of stars with masses of $M >$ 0.55 $M_\odot$. The cross-section of the ${}^{12}\mathrm{C}(α,γ){}^{16}\mathrm{O}$ reaction within the Gamow window ($E_\textrm{c.m.}$ = 300 keV, $T_\textrm9$ = 0.2) is extremely small (about $10^{-17}$ barn), which makes the direct measurem

Leo Laugier, Daniil Bash, Jose Recatala, Hong Kuan Ng

We introduce the use of Crystal Graph Convolutional Neural Networks (CGCNN), Fully Connected Neural Networks (FCNN) and XGBoost to predict thermoelectric properties. The dataset for the CGCNN is independent of Density Functional Theory (DFT) and only relies on the crystal and atomic information, while that for the FCNN is based on a rich attribute list mined

Sang Won Bae, Arpita Baral, Priya Ranjan Sinha Mahapatra

An annulus is, informally, a ring-shaped region, often described by two concentric circles. The maximum-width empty annulus problem asks to find an annulus of a certain shape with the maximum possible width that avoids a given set of $n$ points in the plane. This problem can also be interpreted as the problem of finding an optimal location of a ring-shaped o

Chuang Li, Lun-Hui Hu, Fu-Chun Zhang

In a superconducting topological insulator, superconducting vortex line may trap 1-dimensional topological band with Majorana zero modes (MZMs) localized at its ends. In this work, we study the effect of hexagonal warping to the vortex phase transition. We carry out both analytical calculations based on a semiclassical formula and numerical calculations base

Huijuan Ma, Limin Peng, Chiung-Yu Huang, Haoda Fu

Progression of chronic disease is often manifested by repeated occurrences of disease-related events over time. Delineating the heterogeneity in the risk of such recurrent events can provide valuable scientific insight for guiding customized disease management. In this paper, we present a new modeling framework for recurrent event data, which renders a flexi

Shunsuke Tsuzuki, Yu Nishiyama

In machine learning, a nonparametric forecasting algorithm for time series data has been proposed, called the kernel spectral hidden Markov model (KSHMM). In this paper, we propose a technique for short-term wind-speed prediction based on KSHMM. We numerically compared the performance of our KSHMM-based forecasting technique to other techniques with machine

Yusuke Suyama

We give a necessary and sufficient condition for a generalized Bott manifold to be Fano or weak Fano. As a consequence we characterize Fano Bott manifolds.

Guang-Juan Wang, Lu Meng, Shi-Lin Zhu

In the framework of the heavy baryon chiral perturbation theory (HBChPT), we calculate the radiative decay amplitudes of the singly heavy baryons up to the next-to-next-to-leading order (NNLO). In the numerical analysis, we adopt the heavy quark symmetry to relate some low energy constants (LECs) with those LECs in the calculation of the magnetic moments. We

Nicola Paradiso, Anh-Tuan Nguyen, Karl Enzo Kloss, Christoph Strunk

We show the results of two-terminal and four-terminal transport measurements on few-layer NbSe$_2$ devices at large current bias. In all the samples measured, transport characteristics at high bias are dominated by a series of resistance jumps due to nucleation of phase slip lines, the two dimensional analogue of phase slip centers. In point contact devices

Cong Xiao, Jihang Zhu, Bangguo Xiong

To account for the anomalous/spin Hall conductivities and spin-orbit torque in the zeroth order of electron scattering time in strongly spin-orbit coupled systems, the Boltzmann transport theory in the case of weak disorder-potentials has been augmented by adding some interband coherence effects by hand. In this work these interband coherence terms are deriv

Masashi Yoshikawa, Koji Mineshima, Hiroshi Noji, Daisuke Bekki

In logic-based approaches to reasoning tasks such as Recognizing Textual Entailment (RTE), it is important for a system to have a large amount of knowledge data. However, there is a tradeoff between adding more knowledge data for improved RTE performance and maintaining an efficient RTE system, as such a big database is problematic in terms of the memory usa

Yuto Kinoshita, Noriaki Kida, Yusuke Magasaki, Takeshi Morimoto

Terahertz lights are usually generated through the optical rectification process within a femtosecond laser pulse in non-centrosymmetric materials. Here, we report a new generation mechanism of terahertz lights based upon a photoinduced phase transition (PIPT), in which an electronic structure is rapidly changed by a photoirradiation. When a ferroelectric or

Norbert Hungerbühler, Gideon Villiger

In the Euclidean plane, two intersecting circles or two circles which are tangent to each other clearly do not carry a finite Steiner chain. However, in this paper we will show that such exotic Steiner chains exist in finite Miquelian Möbius planes of odd order. We state and prove explicit conditions in terms of the order of the plane and the capacitance of

Viktor Könye, Masao Ogata

We study the transversal magnetoconductivity and magnetoresistance of a massive Dirac fermion gas. This can be used as a simple model for gapped Dirac materials. In the zero-mass limit, the case of gapless Dirac semimetals is also studied. In the case of Weyl semimetals, to reproduce the nonsaturating linear magnetoresistance seen in experiments, the use of

Kyoungjae Lee, Jaeyong Lee, Lizhen Lin

In this paper, we study the high-dimensional sparse directed acyclic graph (DAG) models under the empirical sparse Cholesky prior. Among our results, strong model selection consistency or graph selection consistency is obtained under more general conditions than those in the existing literature. Compared to Cao, Khare and Ghosh (2017), the required condition

Vu Phi Tran, Matthew Garratt, Ian R. Petersen

This paper tackles the distributed leader-follower (L-F) control problem for heterogeneous mobile robots in unknown environments requiring obstacle avoidance, inter-robot collision avoidance, and reliable robot communications. To prevent an inter-robot collision, we employ a virtual propulsive force between robots. For obstacle avoidance, we present a novel

Kaushal Bhogale, Nishant Shankar, Adheesh Juvekar, Asutosh Padhi

Although modern face verification systems are accessible and accurate, they are not always robust to pose variance and occlusions. Moreover, accurate models require a large amount of data to train. We structure our experiments to operate on small amounts of data obtained from an NGO that funds ophthalmic surgeries. We set up our face verification task as tha

Johannes Hosle

In this manuscript, we study the inequalities between measures of convex bodies implied by comparison of their projections and sections. Recently, Giannopoulos and Koldobsky proved that if convex bodies $K, L$ satisfy $|K|θ^{\perp}| \le |L \cap θ^{\perp}|$ for all $θ\in S^{n-1}$, then $|K| \le |L|$. Firstly, we study the reverse question: in particular, we s

Ben Elias

We initiate the study of Gaitsgory's central sheaves using complexes of Soergel bimodules, in extended affine type A. We conjecture that the complex associated to the standard representation can be flattened to a central complex in finite type A, which is the complex sought after in a conjecture of Gorsky-Negut-Rasmussen.

Fan Wang, Bo Zhou, Ke Chen, Tingxiang Fan

Combining deep neural networks with reinforcement learning has shown great potential in the next-generation intelligent control. However, there are challenges in terms of safety and cost in practical applications. In this paper, we propose the Intervention Aided Reinforcement Learning (IARL) framework, which utilizes human intervened robot-environment intera

Jonathan Fernandes

We compute special unipotent Arthur packets for real reductive groups in many cases. We list the cases that lead to incomplete answers, and in those cases, provide a suitable set of representations that could lead to a complete description of the special Arthur packet. In the process of achieving this goal we classify theta forms of a given even complex nilp

Ali Khodabakhsh, Orestis Papadigenopoulos, Jannik Matuschke, Jimmy Horn

We propose a novel way to use Electric Vehicles (EVs) as dynamic mobile energy storage with the goal to support grid balancing during peak load times. EVs seeking parking in a busy/expensive inner city area, can get free parking with a valet company in exchange for being utilized for grid support. The valet company would have an agreement with the local util

Yizhen Zhong, Luke Rasmussen, Yu Deng, Jennifer Pacheco

The automatic development of phenotype algorithms from Electronic Health Record data with machine learning (ML) techniques is of great interest given the current practice is very time-consuming and resource intensive. The extraction of design patterns from phenotype algorithms is essential to understand their rationale and standard, with great potential to a

Kohei Kamada

Recent gamma-ray observations of TeV blazars exhibits the deficits of the secondary GeV cascade photons. This suggests the existence of the intergalactic magnetic fields, which may have a primordial origin. One of the mechanisms that can produce primordial magnetic fields is so-called the chiral plasma instability, where the (hyper) magnetic fields are desta

Siddharth Maddali, Marc Allain, Wonsuk Cha, Ross Harder

Coherent X-ray beams with energies $\geq 50$ keV can potentially enable three-dimensional imaging of atomic lattice distortion fields within individual crystallites in bulk polycrystalline materials through Bragg coherent diffraction imaging (BCDI). However, the undersampling of the diffraction signal due to Fourier space compression at high X-ray energies r

Yifei Li

We derive an equation that is analogous to a well-known symmetric function identity: $\sum_{i=0}^n(-1)^ie_ih_{n-i}=0$. Here the elementary symmetric function $e_i$ is the Frobenius characteristic of the representation of $\mathcal{S}_i$ on the top homology of the subset lattice $B_i$, whereas our identity involves the representation of $\mathcal{S}_n\times \

Yuan Luo, Peter Szolovits

This paper presents a Lisp architecture for a portable NLP system, termed LAPNLP, for processing clinical notes. LAPNLP integrates multiple standard, customized and in-house developed NLP tools. Our system facilitates portability across different institutions and data systems by incorporating an enriched Common Data Model (CDM) to standardize necessary data

Elad Aigner-Horev, Yury Person

Given a dense subset $A$ of the first $n$ positive integers, we provide a short proof showing that for $p=ω(n^{-2/3})$ the so-called {\sl randomly perturbed} set $A \cup [n]_p$ a.a.s. has the property that any $2$-colouring of it has a monochromatic Schur triple, i.e.\ a triple of the form $(a,b,a+b)$. This result is optimal since there are dense sets $A$, f

Huicheng Liu

Stock market prediction is one of the most attractive research topic since the successful prediction on the market's future movement leads to significant profit. Traditional short term stock market predictions are usually based on the analysis of historical market data, such as stock prices, moving averages or daily returns. However, financial news also

Johannes T. N. Krebs, Jürgen E. Franke

Functional times series have become an integral part of both functional data and time series analysis. This paper deals with the functional autoregressive model of order 1 and the autoregression bootstrap for smooth functions. The regression operator is estimated in the framework developed by Ferraty and Vieu [2004] and Ferraty et al. [2007] which is here ex

Cheng-Hua Bai, Dong-Yang Wang, Shou Zhang, Shutian Liu

We consider a hybrid optomechanical system which is composed of the atomic ensemble and a standard optomechanical cavity driven by the periodically modulated external laser field. We investigate the asymptotic behaviors of Heisenberg operator first moments and clearly show the approaching process between the exact numerical results and analytical solutions.

Xiaoxiang Chai

We study Hawking mass and the Huisken's isoperimetric mass evaluated on surfaces with boundary. The convergence to an ADM mass defined on asymptotically flat manifold with a non-compact boundary are proved.

Lu Qi, Yan Xing, Hong-Fu Wang, Ai-Dong Zhu

We propose a novel scheme to simulate Z_2 topological insulators via one-dimensional (1D) cavity optomechanical cells array. The direct mapping between 1D cavity optomechanical cells array and 2D quantum spin Hall (QSH) system can be achieved by using diagonalization and dimensional reduction methods. We show that the topological features of the present mode

Mohamed Akrout, Amir-massoud Farahmand, Tory Jarmain

We present a skin condition classification methodology based on a sequential pipeline of a pre-trained Convolutional Neural Network (CNN) and a Question Answering (QA) model. This method enables us to not only increase the classification confidence and accuracy of the deployed CNN system, but also enables the emulation of the conventional approach of doctors

M. Kohno

The Pauli rearrangement potential given by the second-order diagram is evaluated for a nucleon optical model potential (OMP) with $G$ matrices of the nucleon-nucleon interaction in chiral effective field theory. The results obtained in nuclear matter are applied for $^{40}$Ca in a local-density approximation. The repulsive effect is of the order of 5MeV at t

Yevgeniy Vorobeychik, Michael Pritchard

We propose a framework for cyber risk assessment and mitigation which models attackers as formal planners and defenders as interdicting such plans. We illustrate the value of plan interdiction problems by first modeling network cyber risk through the use of formal planning, and subsequently formalizing an important question of prioritizing vulnerabilities fo

Prasanta Kumar Barik

In this paper we study the continuous coagulation and multiple fragmentation equation for the mean-field description of a system of particles taking into account the combined effect of the coagulation and the fragmentation processes in which a system of particles growing by successive mergers to form a bigger one and a larger particle splits into a finite nu

Nathan Lindzey

A family of perfect matchings of $K_{2n}$ is $t$-$intersecting$ if any two members share $t$ or more edges. We prove for any $t \in \mathbb{N}$ that every $t$-intersecting family of perfect matchings has size no greater than $(2(n-t) - 1)!!$ for sufficiently large $n$, and that equality holds if and only if the family is composed of all perfect matchings tha

Daniel Wolf Savin, James F. Babb, Paul M. Bellan, Crystal Brogan

About two generations ago, a large part of AMO science was dominated by experimental high energy collision studies and perturbative theoretical methods. Since then, AMO science has undergone a transition and is now dominated by quantum, ultracold, and ultrafast studies. But in the process, the field has passed over the complexity that lies between these two

Yu Hao, Xien Liu, Ji Wu, Ping Lv

Despite the great success of word embedding, sentence embedding remains a not-well-solved problem. In this paper, we present a supervised learning framework to exploit sentence embedding for the medical question answering task. The learning framework consists of two main parts: 1) a sentence embedding producing module, and 2) a scoring module. The former is

Guanfa Wang, Yong Wang

In this paper, we investigate the stability of Boltzmann equation with large external potential in $\mathbb{T}^3$. For a class of initial data with large oscillations in $L^\infty_{x,v}$ around the local Maxwellian, we prove the existence of a global solution to the Boltzmann equation provided the initial perturbation is suitably small in $L^2$-norm. The lar

Vincent Casser, Soeren Pirk, Reza Mahjourian, Anelia Angelova

Learning to predict scene depth from RGB inputs is a challenging task both for indoor and outdoor robot navigation. In this work we address unsupervised learning of scene depth and robot ego-motion where supervision is provided by monocular videos, as cameras are the cheapest, least restrictive and most ubiquitous sensor for robotics. Previous work in unsupe

Mincong Luo, Yin Tong, Jiachi Liu

One less addressed issue of deep reinforcement learning is the lack of generalization capability based on new state and new target, for complex tasks, it is necessary to give the correct strategy and evaluate all possible actions for current state. Fortunately, deep reinforcement learning has enabled enormous progress in both subproblems: giving the correct

Dave Moore, Maria I. Gorinova

Algebraic effects and handlers have emerged in the programming languages community as a convenient, modular abstraction for controlling computational effects. They have found several applications including concurrent programming, meta programming, and more recently, probabilistic programming, as part of Pyro's Poutines library. We investigate the use of

K. E. Harborne, C. Power, A. S. G. Robotham, L. Cortese

A primary goal of integral field spectroscopic (IFS) surveys is to provide a statistical census of galaxies classified by their internal kinematics. As a result, the observational spin parameter, $λ_R$, has become one of the most popular methods of quantifying the relative importance of velocity dispersion and rotation in supporting a galaxy's inner stru

Jing Shi, Jiaming Xu, Yiqun Yao, Bo Xu

Deep neural networks have shown superior performance in many regimes to remember familiar patterns with large amounts of data. However, the standard supervised deep learning paradigm is still limited when facing the need to learn new concepts efficiently from scarce data. In this paper, we present a memory-augmented neural network which is motivated by the p

Hui-Ming Wang, Bing-Qing Zhao, Tong-Xing Zheng

Device-to-device (D2D) communication raises new transmission secrecy protection challenges, since conventional physical layer security approaches, such as multiple antennas and cooperation techniques, are invalid due to its resource/size constraints. The full-duplex (FD) jamming receiver, which radiates jamming signals to confuse eavesdroppers when receiving

Kazumasa Fujiwara, Vladimir Georgiev, Tohru Ozawa

A class of self-similar solutions to the derivative nonlinear Schrödinger equations is studied. Especially, the asymptotics of profile functions are shown to posses a logarithmic phase correction. This logarithmic phase correction is obtained from the nonlinear interaction of profile functions. This is a remarkable difference from the pseudo-conformally inva

Mladen Pavicic

This a response to "Yes They Can! ..." (a comment on [5]) by J.S. Shaari et al. [9]. We show that the claims in the comment do not hold up and that all the conclusions obtained in [5] are correct. In particular, the two considered kinds of two-way communication protocols (ping-pong and LM05) under a quantum-man-in-the-middle (QMM) attack have neither

Fujun Hou

People employ their knowledge to recognize things. This paper is concerned with how to measure people's knowledge for recognition and how it changes. The discussion is based on three assumptions. Firstly, we construct two evolution process equations, of which one is for uncertainty and knowledge, and the other for uncertainty and ignorance. Secondly, by

Xihe Li, Ligong Wang

Given two graphs $G$ and $H$, the $k$-colored Gallai-Ramsey number $gr_k(G : H)$ is defined to be the minimum integer $n$ such that every $k$-coloring of the complete graph on $n$ vertices contains either a rainbow copy of $G$ or a monochromatic copy of $H$. In this paper, we consider $gr_k(K_3 : H)$ where $H$ is a connected graph with five vertices and at m

A. V. Suslov, A. B. Davydov, L. N. Oveshnikov, L. A. Morgun

We report the first experimental observation of superconductivity in Cd$_3$As$_2$ thin films without application of external pressure. Surface studies suggest that the observed transport characteristics are related to the polycrystalline continuous part of investigated films with homogeneous distribution of elements and the Cd-to-As ratio close to stoichiome

Beijiang Liu, Xian Xiong, Guoyi Hou, Shiming Song

BESIII is a currently running tau-charm factory with the largest samples of on threshold charm meson pairs, directly produced charmonia and some other unique datasets at BEPCII collider. Machine learning techniques have been employed to improve the performance of BESIII software. The studies for reweighing MC, particle identification and cluster reconstructi

Kai Li, Dong Hao

Enforcing cooperation among substantial agents is one of the main objectives for multi-agent systems. However, due to the existence of inherent social dilemmas in many scenarios, the free-rider problem may arise during agents' long-run interactions and things become even severer when self-interested agents work in collusion with each other to get extra b

Clark Barwick

It turns out that one can read off facts about schemes up to universal homeomorphism from their Galois categories. Here we propose a first modest slate of entries in a dictionary between the geometric features of a perfectly reduced scheme (or morphism of such) and the categorical properties of its Galois category (or functor of such). The main thing that ma

Ana Ionesi, Hossein Ramezani, Jerome Jouffroy

This paper considers the on-line implementation of the modulating function method, for parameter and state estimation, for the model of an air-handling unit, the central element of HVAC systems. After recalling the few elements of the method, more attention is paid on issues related to its on-line implementation, issues for which we use two different techniq

Siddharth H. Nair, Ravi N. Banavar

This article develops variational integrators for a class of underactuated mechanical systems using the theory of discrete mechanics. Further, a discrete optimal control problem is formulated for the considered class of systems and subsequently solved using variational principles again, to obtain necessary conditions that characterize optimal trajectories. T

Chen Liu, Beatrice Riviere

In this paper, we derive a theoretical analysis of an interior penalty discontinuous Galerkin methods for solving the Cahn-Hilliard-Navier-Stokes model problem. We prove unconditional unique solvability of the discrete system, obtain unconditional discrete energy dissipation law, and derive stability bounds with a generalized chemical energy density. Converg

Jose Luis Gracia, Eugene O'Riordan

Numerical approximations to the solution of a linear singularly perturbed parabolic reaction-diffusion problem with incompatible bound\-ary-initial data are generated, The method involves combining the computational solution of a classical finite difference operator on a tensor product of two piecewise-uniform Shishkin meshes with an analytical function that

Pratik Suchde, Joerg Kuhnert

In this paper, we propose a novel meshfree Generalized Finite Difference Method (GFDM) approach to discretize PDEs defined on manifolds. Derivative approximations for the same are done directly on the tangent space, in a manner that mimics the procedure followed in volume-based meshfree GFDMs. As a result, the proposed method not only does not require a mesh

Christopher Müller, Sebastian Ullmann, Jens Lang

We study linear systems of equations arising from a stochastic Galerkin finite element discretization of saddle point problems with random data and its iterative solution. We consider the Stokes flow model with random viscosity described by the exponential of a correlated random process and shortly discuss the discretization framework and the representation

Sajeevi S. Withanage, Hirokjyoti Kalita, Hee-Suk Chung, Tania Roy

Chemical vapor deposition (CVD) is a powerful method employed for high quality monolayer crystal growth of 2D transition metal dichalcogenides with much effort invested toward improving the growth process. Here, we report a novel method for CVD based growth of monolayer molybdenum disulfide (MoS2) by using thermally evaporated thin films of molybdenum trioxi

Alberto Cabada, Lucía López-Somoza

In this paper we will show several properties of the Green's functions related to various boundary value problems of arbitrary even order. In particular, we will write the expression of the Green's functions related to the general differential operator of order 2n coupled to Neumann, Dirichlet and mixed boundary conditions, as a linear combination of

José R. Correa, Paul Dütting, Felix Fischer, Kevin Schewior

A central object in optimal stopping theory is the single-choice prophet inequality for independent, identically distributed random variables: Given a sequence of random variables $X_1,\dots,X_n$ drawn independently from a distribution $F$, the goal is to choose a stopping time $\tau$ so as to maximize $\alpha$ such that for all distributions $F$ we have $\m

Takumi Takahashi, Antti Tölli, Shinsuke Ibi, Seiichi Sampei

This paper proposes a novel layered belief propagation (BP) detector with a concatenated structure of two different BP layers for low-complexity large multi-user multi-input multi-output (MU-MIMO) detection based on statistical beams. To reduce the computational burden and the circuit scale on the base station (BS) side, the two-stage signal processing consi

Alex Kruckman, Minh Chieu Tran, Erik Walsberg

We define the interpolative fusion $T^*_\cup$ of a family $(T_i)_{i \in I}$ of first-order theories over a common reduct $T_\cap$, a notion that generalizes many examples of random or generic structures in the model-theoretic literature. When each $T_i$ is model-complete, $T^*_\cup$ coincides with the model companion of $T_\cup = \bigcup_{i \in I} T_i$. By o

Jwala Dhamala, Emmanuel Azuh, Abdullah Al-Dujaili, Jonathan Rubin

Timely prediction of clinically critical events in Intensive Care Unit (ICU) is important for improving care and survival rate. Most of the existing approaches are based on the application of various classification methods on explicitly extracted statistical features from vital signals. In this work, we propose to eliminate the high cost of engineering hand-

Sean M. Gholson, Ilarion V. Melnikov

We classify (0,2) Landau-Ginzburg theories that can flow to compact IR fixed points with equal left and right central charges strictly bounded by 3. Our result is a (0,2) generalization of the ADE classification of (2,2) Landau-Ginzburg theories that flow to N=2 minimal models. Unitarity requires the right-moving supersymmetric sector to fall into the standa

Chengshu Li, Étienne Lantagne-Hurtubise, Marcel Franz

We construct a supersymmetric model of interacting Majorana fermions on the kagome lattice. In the infinite-coupling limit, the model exhibits an extensively degenerate ground state manifold separated in two topological sectors, in addition to two parity supersectors. An exact solution for thin-torus geometries allows us to analytically construct the entire

Michael Rios, Alessio Marrani, David Chester

Some time ago, Sezgin, Bars and Nishino have proposed super Yang-Mills theories (SYM's) in $D=11+3$ and beyond. Using the "Magic Star" projection of $\mathfrak{e}_{8(-24)}$, we show that the geometric structure of SYM's in $11+3$ and $12+4$ space-time dimensions is recovered from the affine symmetry of the space $AdS_{4}\otimes S^{8}$, with t

Arash Dehghan Banadaki, Jason J. Maldonis, Paul M. Voyles, Srikanth Patala

The local arrangement of atoms is one of the most important predictors of mechanical and functional properties of materials. However, algorithms for identifying the geometrical arrangements of atoms in complex materials systems are lacking. To address this challenge, we present a point-pattern matching algorithm that can detect instances of a `template'

Kyriakos Papadopoulos, Nazli Kurt, Basil K. Papadopoulos

A list of all possible causal relations in the $2$-dimensional Minkowski space $M$ is exhausted, based on the duality between timelike and spacelike in this particular case, and thirty topologies are introduced, all of them encapsulating the causal structure of $M$. Generalisations of these results are discussed, as well as their significance in a discussion

F. C. D. Moraes, S. Ullah, M. G. A. Balanta, F. Iikawa

Time-resolved Kerr rotation measurements were performed in InGaAs/GaAs quantum wells nearby a doped Mn delta layer. Our magneto-optical results show a typical time evolution of the optically-oriented electron spin in the quantum well. Surprisingly, this is strongly affected by the Mn spins, resulting in an increase of the spin precession frequency in time. T

Janko Boehm

In this note for the joint meeting of DMV and GDM we illustrate with examples the role of computer algebra in university mathematics education. We discuss its potential in teaching algebra, but also computer algebra as a subject in its own right, its value in the context of practical programming projects and its role as a research topic in student papers.

Janko Boehm, Anne Frühbis-Krüger, Mirko Rahn

The design and implementation of parallel algorithms is a fundamental task in computer algebra. Combining the computer algebra system Singular and the workflow management system GPI-Space, we have developed an infrastructure for massively parallel computations in commutative algebra and algebraic geometry. In this note, we give an overview on the current cap

Ruidi Chen, Ioannis Paschalidis

We develop a prediction-based prescriptive model for learning optimal personalized treatments for patients based on their Electronic Health Records (EHRs). Our approach consists of: (i) predicting future outcomes under each possible therapy using a robustified nonlinear model, and (ii) adopting a randomized prescriptive policy determined by the predicted out

Utkan Güngördü, J. P. Kestner

Characterizing charge noise is of prime importance to the semiconductor spin qubit community. We analyze the echo amplitude data from a recent experiment [Yoneda et al., Nat. Nanotechnol. 13, 102 (2018)] and note that the data shows small but consistent deviations from a $1/f^α$ noise power spectrum at the higher frequencies in the measured range. We report

T. Shin, S. Adhikari, E. J. Baxter, C. Chang

We present a detection of the splashback feature around galaxy clusters selected using their Sunyaev-Zel'dovich (SZ) signal. Recent measurements of the splashback feature around optically selected galaxy clusters have found that the splashback radius, $r_{\rm sp}$, is smaller than predicted by N-body simulations. A possible explanation for this discrepan

Michael A. Hope, Kent J. Griffith, Bin Cui, Fang Gao

Metallization of initially insulating VO2 via ionic liquid electrolytes (electrolyte gating) has recently been a topic of much interest. It is clear that the metallization takes place electrochemically and there has previously been extensive evidence for the removal of small amounts of oxygen during ionic liquid gating. Hydrogen intercalation has also been p