November 2018 arXiv papers — page 33

Yves Andreé

The homological conjectures, which date back to Peskine, Szpiro and Hochster in the late sixties, make fundamental predictions about syzygies and intersection problems in commutative algebra. They were settled long ago in the presence of a base field and led to tight closure theory, a powerful tool to investigate singularities in characteristic p. Recently,

Guozhu Dong, Sai Kiran Pentukar

This paper presents a method called One-class Classification using Length statistics of Emerging Patterns Plus (OCLEP+).

Mehmet Turan, Sofiya Ostrovska, Ahmet Yaşar Özban

Given random variables $X$ and $Y$ having finite moments of all orders, their uncorrelatedness set is defined as the set of all pairs $(j,k)\in{\mathbb N}^2,$ for which $X^j$ and $Y^k$ are uncorrelated. It is known that, broadly put, any subset of ${\mathbb N}^2$ can serve as an uncorrelatedness set. This claim ceases to be true for random variables with pre

Ivano Salvo, Agnese Pacifico

The Euler's Sieve refines the Sieve of Eratosthenes to compute prime numbers, by crossing off each non prime number just once. Euler's Sieve is considered hard to be faithfully and efficiently coded as a purely functional stream based program. We propose three Haskell programs implementing the Euler's Sieve, all based on the idea of generating just once each

Benjamin Basso, Andrei V. Belitsky

There is a number of indications that scattering amplitudes in the Aharony-Bergman-Jafferis-Maldacena theory might have a dual description in terms of a holonomy of a supergauge connection on a null polygonal contour in a way analogous to the four-dimensional maximally supersymmetric Yang-Mills theory. However, so far its explicit implementations evaded a su

Itay Glazer, Yotam I. Hendel

Let $K$ be a field of characteristic zero, $X$ and $Y$ be smooth $K$-varieties, and let $G$ be a algebraic $K$-group. Given two algebraic morphisms $\varphi:X\rightarrow G$ and $\psi:Y\rightarrow G$, we define their convolution $\varphi*\psi:X\times Y\to G$ by $\varphi*\psi(x,y)=\varphi(x)\cdot\psi(y)$. We then show that this operation yields morphisms with

Whitney K. Newey, Sami Stouli

Multidimensional heterogeneity and endogeneity are important features of a wide class of econometric models. With control variables to correct for endogeneity, nonparametric identification of treatment effects requires strong support conditions. To alleviate this requirement, we consider varying coefficients specifications for the conditional expectation fun

Matteo Cavaleri, Daniele D'Angeli, Alfredo Donno

This paper introduces a new graph construction, the permutational power of a graph, whose adjacency matrix is obtained by the composition of a permutation matrix with the adjacency matrix of the graph. It is shown that this construction recovers the classical zig-zag product of graphs when the permutation is an involution, and it is in fact more general. We

Alexandra Dumitrescu, Simone Santini

We present a collection of algorithms to filter a stream of documents in such a way that the filtered documents will cover as well as possible the interest of a person, keeping in mind that, at any given time, the offered documents should not only be relevant, but should also be diversified, in the sense not only of avoiding nearly identical documents, but a

Ziyao Tang, Yongxi Lu, Tara Javidi

One of the greatest challenges in the design of a real-time perception system for autonomous driving vehicles and drones is the conflicting requirement of safety (high prediction accuracy) and efficiency. Traditional approaches use a single frame rate for the entire system. Motivated by the observation that the lack of robustness against environmental factor

M. Z. Ahmad, J. F. Peters

This article introduces proximal cell complexes in a hyperconnected space. Hyperconnectedness encodes how collections of path-connected sub-complexes in a Alexandroff-Hopf-Whitehead CW space are near to or far from each other. Several main results are given, namely, a hyper-connectedness form of CW (Closure Finite Weak topology) complex, the existence of con

Amandeep Singh Bhatia, Mandeep Kaur Saggi

The study of tensor network theory is an important field and promises a wide range of experimental and quantum information theoretical applications. Matrix product state is the most well-known example of tensor network states, which provides an effective and efficient representation of one-dimensional quantum systems. Indeed, it lies at the heart of density

H. W. L. Naus, R. Versluis

Surface codes based on stabilizer circuits may pave the way for large scale fault-tolerant quantum computation. The surface code uses only single- and two-qubit gates and the error threshold falls close to 1% for a large range of errors. Among the most promising candidates to physically implement such circuits and codes are superconducting qubits coupled by

Shangxi Wu, Jitao Sang, Kaiyuan Xu, Jiaming Zhang

This study provides a new understanding of the adversarial attack problem by examining the correlation between adversarial attack and visual attention change. In particular, we observed that: (1) images with incomplete attention regions are more vulnerable to adversarial attacks; and (2) successful adversarial attacks lead to deviated and scattered attention

Tatiana Latychevskaia, Conrad Escher, Hans-Werner Fink

We investigate imaging of moire structures in free-standing twisted bilayer graphene (TBG) carried out by transmission electron microscopy (TEM) in diffraction and in-line Gabor holography modes. Electron diffraction patterns of TBG acquired at typical TEM electron energies of 80 - 300 keV exhibit the diffraction peaks caused by diffraction on individual lay

Federica Parisi, Tiziano Squartini, Diego Garlaschelli

Due to the interconnectedness of financial entities, estimating certain key properties of a complex financial system (e.g. the implied level of systemic risk) requires detailed information about the structure of the underlying network. However, since data about financial linkages are typically subject to confidentiality, network reconstruction techniques bec

Krzysztof Maziarz, Mingxing Tan, Andrey Khorlin, Marin Georgiev

Neural Architecture Search has shown potential to automate the design of neural networks. Deep Reinforcement Learning based agents can learn complex architectural patterns, as well as explore a vast and compositional search space. On the other hand, evolutionary algorithms offer higher sample efficiency, which is critical for such a resource intensive applic

W. J. Schuster, J. G. Fernández-Trincado, E. Moreno

The 3D Galactic orbits of stars in the two groups G18-39 and G21-22 pertaining to the Galactic halo have been computed in a Galactic potential including a Galactic bar. The orbits have been related with the orbital structure of resonant orbits on the Galactic plane created by the bar component. We find that the majority of stars in both groups are trapped ma

Andrew Dancer

We analyse properties of hypertoric manifolds of infinite topological type, including their topology and complex structures. We show that our manifolds have the homotopy type of an infinite union of compact toric varieties. We also discuss hypertoric analogues of the periodic Ooguri-Vafa spaces.

M. Gasperini

A brief introduction to gravitational waves, addressing those questions that nowadays more and more frequently arise within a large audience (not only of insiders): what is a gravity wave, how can it be detected and, above all, what impact on modern physical theories may have their recent discovery? Interested readers can also find a few simple technical det

S. Aouini, T. Sahdane, A. Mhirech, L. Bahmad

The aim of this paper is to investigate the magnetic properties of the M_n B_i magnetic systems by using the Monte Carlo simulation. Indeed, we analyzed the effect of the number of layers on the magnetic properties of the compound M_n B_i. The magnetization, the binder cumulant, the Curie temperature and the hysteresis cycle are also calculated in this work.

Marius Thomas, Björn Bornkamp, Martin Posch, Franz König

Identifying subgroups of patients with an enhanced response to a new treatment has become an area of increased interest in the last few years. When there is knowledge about possible subpopulations with an enhanced treatment effect before the start of a trial it might be beneficial to set up a testing strategy, which tests for a significant treatment effect n

Tien-Cuong Dinh, Duc-Viet Vu

We recover results by Ullmo-Yafaev and Peterzil-Starchenko on the closure of the image of an algebraic variety in a compact complex torus. Our approach uses directed closed currents and allows us to extend the result for dimension 1 flows to the setting of commutative complex Lie groups which are not necessarily compact. A version of the classical Ax-Lindema

Rong-Cheng Tu, Xian-Ling Mao, Bo-Si Feng, Bing-Bing Bian

Recently, similarity-preserving hashing methods have been extensively studied for large-scale image retrieval. Compared with unsupervised hashing, supervised hashing methods for labeled data have usually better performance by utilizing semantic label information. Intuitively, for unlabeled data, it will improve the performance of unsupervised hashing methods

Deepak K. Gupta, Fred van Keulen, Matthijs Langelaar

Multiresolution topology optimization (MTO) methods involve decoupling of the design and analysis discretizations, such that a high-resolution design can be obtained at relatively low analysis costs. Recent studies have shown that the MTO method can be approximately 3 and 30 times faster than the traditional topology optimization method for 2D and 3D problem

Alfred Czogała, Przemysław Koprowski, Beata Rothkegel

Given a self-equivalence of a global function field, its wild set is the set of points where the self-equivalence fails to preserve parity of valuation. In this paper we describe structure of finite wild sets.

D. Wang, J. Liu, J. Zhang, S. Raza

Ewald summation is an important technique used to deal with long-range Coulomb interaction. While it is widely used in simulations of molecules and solid state materials, many important results are dispersed in literature and their implementations are often buried deep in large software packages. Since reliable and systematic calculation of Coulomb interacti

Ali Teimouri

Infinite derivative theory of gravity is a modification to the general theory of relativity. Such modification maintains the massless graviton as the only true physical degree of freedom and avoids ghosts. Moreover, this class of modified gravity can address classical singularities. In this thesis some essential aspects of an infinite derivative theory of gr

Tatsu-Hiko Miura

We consider the three-dimensional incompressible Navier--Stokes equations in a curved thin domain with Navier's slip boundary conditions. The curved thin domain is defined as a region between two closed surfaces which are very close to each other and degenerates into a given closed surface as its width tends to zero. We establish the global-in-time existence

Mike Lockwood, Ivan D. Finch, Aude Chambodut, Luke A. Barnard

Paper 1 [Lockwood et al., 2018] generated annual means of a new version of the $aa$ geomagnetic activity index which includes corrections for secular drift in the geographic coordinates of the auroral oval, thereby resolving the difference between the centennial-scale change in the northern and southern hemisphere indices, $aa_N$ and $aa_S$. However, other h

Aditya Grover, Tudor Achim, Stefano Ermon

Several algorithms for solving constraint satisfaction problems are based on survey propagation, a variational inference scheme used to obtain approximate marginal probability estimates for variable assignments. These marginals correspond to how frequently each variable is set to true among satisfying assignments, and are used to inform branching decisions d

Nikos I. Karachalios, Paris Kyriazopoulos, Konstantinos Vetas

We show by direct numerical simulations that spatiotemporally localized wave forms, strongly reminiscent of the Peregrine rogue wave, can be excited by vanishing initial conditions for the periodically driven nonlinear Schr\"odinger equation. The emergence of the Peregrine-type waveforms can be potentially justified, in terms of the existence and modulationa

Roman Vetter, Jürgen O. Schumacher

In almost 30 years of PEM fuel cell modeling, countless numerical models have been developed in science and industrial applications, almost none of which have been fully disclosed to the public. There is a large need for standardization and establishing a common ground not only in experimental characterization of fuel cells, but also in the development of si

Mike Lockwood, Aude Chambodut, Luke A. Barnard, Mathew J. Owens

Originally complied for 1868-1967 and subsequently continued so that it now covers 150 years, the $aa$ index has become a vital resource for studying space climate change. However, there have been debates about the inter-calibration of data from the different stations. In addition, the effects of secular change in the geomagnetic field have not previously be

Arash Pourkia

Burau representation of the Artin braid group remains as one of the very important representations for the braid group. Partly, because of its connections to the Alexander polynomial which is one of the first and most useful invariants for knots and links. In the present work, we show that interesting representations of braid group could be achieved using a

Donatella Donatelli

In this paper we consider a fluid dynamic model which describes the atmospheric flow and we perform an asymptotic analysis for different time and length scales. In particular we will focus on the two following cases: when the Mach number dominates on the Rossby number yielding an incompressible regime or when the high rotating (low Rossby number) and incompr

Vahid Reza Shajiee, Ali Tofighi

In this paper, the electroweak phase transition, the gravitational waves and the dark matter issues are investigated in two scalar singlet extension of the standard model. The detectability of the gravitational wave signals are discussed by comparing the results with the sensitivity curves of $\mathbf{eLISA}$, $\mathbf{ALIA}$, $\mathbf{DECIGO}$ and $\mathbf{

Jeet Desai, Amol Marathe

We propose homotopy analysis method in combination with Galerkin projections to obtain transition curves of Mathieu-like equations. While constructing homotopy, we think of convergence-control parameter as a function of embedding parameter and call it a convergence-control function. Homotopy analysis provides a relation between the parameters of Mathieu equa

Andreas Leopold Knutsen

Let $S \subset \mathbb{P}^g$ be a smooth $K3$ surface of degree $2g-2$, $g \geq 3$. We classify all the cases for which $h^0(\mathcal{N}_{S/\mathbb{P}^g}(-2)) \neq 0$ and the cases for which $h^0(\mathcal{N}_{S/\mathbb{P}^g}(-2)) < h^0(\mathcal{N}_{C/\mathbb{P}^{g-1}}(-2))$ for $C \subset \mathbb{P}^{g-1}$ a general canonical curve section of $S$.

J. M. Grau Ribas

We consider the Last-Success-Problem with $n$ independent Bernoulli random variables with parameters $p_i>0$. We improve the lower bound provided by F.T. Bruss for the probability of winning and provide an alternative proof to the one given for the lower bound ($1/e$) when $R:=\sum_{i=1}^n (p_i/(1-p_i))\geq1$. We also consider a modification of the game whic

Rupak Mukherjee, Rajaraman Ganesh

Since the advent of Taylor-Woltjer theory [J B Taylor, PRL, 33, 1139 (1974), L Woltjer, PNAS, 44, 489 (1958)], it has been widely believed that situations with perfectly conducting boundaries and near ideal conditions, the final state of MHD system would be force-free Taylor-Woltjer states defined as $\vec{\nabla} \times \vec{B} = \alpha \vec{B}$ with $\alph

Weihong Xu, Xiaohu You, Chuan Zhang, Yair Be'ery

In this paper, we present a sparse neural network decoder (SNND) of polar codes based on belief propagation (BP) and deep learning. At first, the conventional factor graph of polar BP decoding is converted to the bipartite Tanner graph similar to low-density parity-check (LDPC) codes. Then the Tanner graph is unfolded and translated into the graphical repres

Abhijit Guha Roy, Sailesh Conjeti, Nassir Navab, Christian Wachinger

We introduce Bayesian QuickNAT for the automated quality control of whole-brain segmentation on MRI T1 scans. Next to the Bayesian fully convolutional neural network, we also present inherent measures of segmentation uncertainty that allow for quality control per brain structure. For estimating model uncertainty, we follow a Bayesian approach, wherein, Monte

Shuang Zhou, H. J. Mo, Cheng Li, Zheng Zheng

We analyze the stellar initial mass functions (IMF) of a large sample of early type galaxies (ETGs) provided by MaNGA. The large number of IFU spectra of individual galaxies provide high signal-to-noise composite spectra that are essential for constraining IMF and to investigate possible radial gradients of the IMF within individual galaxies. The large sampl

Karan N. Chadha, Ankur A. Kulkarni

In recent work (Pandit and Kulkarni [Discrete Applied Mathematics, 244 (2018), pp. 155--169]), the independence number of a graph was characterized as the maximum of the $\ell_1$ norm of solutions of a Linear Complementarity Problem (\LCP) defined suitably using parameters of the graph. Solutions of this LCP have another relation, namely, that they correspon

Kazem Ardaneh

Relativistic unmagnetized cloud-plasma interaction is analyzed by performing linear analysis and particle-in-cell simulation. This course consists of an electron-ion cloud injected into a stationary ambient plasma and has long been a favorite topic in laboratory and space plasmas. An oblique electromagnetic instability dominates the unstable spectrum. In the

Dinesh Khandelwal, Suyash Agrawal, Parag Singla, Chetan Arora

Auxiliary information can be exploited in machine learning models using the paradigm of evidence based conditional inference. Multi-modal techniques in Deep Neural Networks (DNNs) can be seen as perturbing the latent feature representation for incorporating evidence from the auxiliary modality. However, they require training a specialized network which can m

Dahun Kim, Donghyeon Cho, In So Kweon

Self-supervised tasks such as colorization, inpainting and zigsaw puzzle have been utilized for visual representation learning for still images, when the number of labeled images is limited or absent at all. Recently, this worthwhile stream of study extends to video domain where the cost of human labeling is even more expensive. However, the most of existing

Hyeoncheol Cho, Insung S. Choi

We present a three-dimensional graph convolutional network (3DGCN), which predicts molecular properties and biochemical activities, based on 3D molecular graph. In the 3DGCN, graph convolution is unified with learning operations on the vector to handle the spatial information from molecular topology. The 3DGCN model exhibits significantly higher performance

Ye Xu

I study the possibility of directly detecting Ultra-high energy (UHE from now on) WIMPs by the IceCube experiment, via the WIMPs interaction with the nuclei in the ice. I evaluate galactic and extragalactic UHE WIMP and astrophysical and atmospheric neutrino event rates at energy range of 10 TeV - 10 PeV. I assume UHE WIMPs $\chi$ are only from the decay of

Rafael Roman Otero, Alex Aravind

Delivering hands-on practice laboratories for introductory courses on operating systems is a difficult task. One of the main sources of the difficulty is the sheer size and complexity of the operating systems software. Consequently, some of the solutions adopted in the literature to teach operating systems laboratory consider smaller and simpler systems, gen

Yunjae Jung, Donghyeon Cho, Dahun Kim, Sanghyun Woo

In this paper, we address the problem of unsupervised video summarization that automatically extracts key-shots from an input video. Specifically, we tackle two critical issues based on our empirical observations: (i) Ineffective feature learning due to flat distributions of output importance scores for each frame, and (ii) training difficulty when dealing w

Yaochen Li, Yuehu Liu, Jihua Zhu, Shiqi Ma

Scene model construction based on image rendering is an indispensable but challenging technique in computer vision and intelligent transportation systems. In this paper, we propose a framework for constructing 3D corridor-based road scene models. This consists of two successive stages: road detection and scene construction. The road detection is realized by

Omid Mohamad Nezami, Mark Dras, Stephen Wan, Cecile Paris

There has been much recent work on image captioning models that describe the factual aspects of an image. Recently, some models have incorporated non-factual aspects into the captions, such as sentiment or style. However, such models typically have difficulty in balancing the semantic aspects of the image and the non-factual dimensions of the caption; in add

Sándor Lökös

Measurement of quantumstatistical correlation functions in high energy nuclear physics is an important tool to investigate the QCD phase diagram. It may be used to search for the critical point, and also to understand underlying processes such as in-medium mass modifications or partially coherent particle production. Furthermore, the measurements of the femt

Maya D. Glinchuk, Anna N. Morozovska, Yunseok Kim, Sergei V. Kalinin

Recent observations of unusual ferroelectricity in thin films of HfO_2 and related materials have attracted broad interest to the materials and led to the emergence of a number of competing models for observed behaviors. Here we develop the electrochemical mechanism of observed ferroelectric-like behaviors, namely the collective phenomena of elastic and elec

Yi Tay, Luu Anh Tuan, Siu Cheung Hui

Recurrent neural networks (RNNs) such as long short-term memory and gated recurrent units are pivotal building blocks across a broad spectrum of sequence modeling problems. This paper proposes a recurrently controlled recurrent network (RCRN) for expressive and powerful sequence encoding. More concretely, the key idea behind our approach is to learn the recu

Aigul Nugmanova, Andrei Smirnov, Galina Lavrentyeva, Irina Chernykh

The article describes the new approach for quality improvement of automated dialogue systems for customer support service. Analysis produced in the paper demonstrates the dependency of the quality of the retrieval-based dialogue system quality on the choice of negative responses. The proposed approach implies choosing the negative samples according to the di

Yuya Ominato, Ai Yamakage, Kentaro Nomura

We theoretically study the electric polarization in magnetic topological nodal semimetal thin films. In magnetically doped topological insulators, topological nodal semimetal phases emerge once the exchange coupling overcomes the band gap. Changing the magnetization direction, nodal structure is modulated and the system becomes topological nodal point or lin

Song-Hai Zhang, Zhengping Zhou, Bin Liu, Xin Dong

In this work, we propose a novel topic consisting of two dual tasks: 1) given a scene, recommend objects to insert, 2) given an object category, retrieve suitable background scenes. A bounding box for the inserted object is predicted in both tasks, which helps downstream applications such as semi-automated advertising and video composition. The major challen

Sabri Boughorbel, Fethi Jarray, Neethu Venugopal, Haithum Elhadi

In this paper we are interested in the prediction of preterm birth based on diagnosis codes from longitudinal EHR. We formulate the prediction problem as a supervised classification with noisy labels. Our base classifier is a Recurrent Neural Network with an attention mechanism. We assume the availability of a data subset with both noisy and clean labels. Fo

G. Arregui, O. Ortíz, M. Esmann, C. M. Sotomayor-Torres

Inspired by concepts developed for fermionic systems in the framework of condensed matter physics, topology and topological states are recently being explored also in bosonic systems. The possibility of engineering systems with unidirectional wave propagation and protected against disorder is at the heart of this growing interest. Topogical acoustic effects

Huangxing Lin, Xueyang Fu, Changxing Jing, Xinghao Ding

Existing methods for single images raindrop removal either have poor robustness or suffer from parameter burdens. In this paper, we propose a new Adjacent Aggregation Network (A^2Net) with lightweight architectures to remove raindrops from single images. Instead of directly cascading convolutional layers, we design an adjacent aggregation architecture to bet

Somayeh Asadifar, Mohsen Kahani, Saeedeh Shekarpour

Question Answering (QA) systems provide easy access to the vast amount of knowledge without having to know the underlying complex structure of the knowledge. The research community has provided ad hoc solutions to the key QA tasks, including named entity recognition and disambiguation, relation extraction and query building. Furthermore, some have integrated

Qi Chen, Biao Zhang, Labao Zhang, Rui Ge

Niobium Nitride (NbN) nanowire is the most popular detection material of superconducting nanowire single photon detectors (SNSPDs) for high repetition rate and high efficiency. However, it has been assumed to be difficult for fabricating SNSPDs with arrays over large area, which are critical components of quantum imaging, linear optical quantum computing, sa

Xiaoxiang Chai

We show that the mass of an asymptotically hyperbolic manifold with a noncompact boundary can be evaluated via the Ricci tensor and the second fundamental form by using purely coordinates. The method is analog to Miao-Tam's approach to the asymptotically flat manifold.

Steven P. Bos, Sebastiaan Y. Haffert, Christoph U. Keller

Precise modelling of the (off-axis) point spread function (PSF) to identify geometrical and polarization aberrations is important for many optical systems. In order to characterise the PSF of the system in all Stokes parameters, an end-to-end simulation of the system has to be performed in which Maxwells equations are rigorously solved. We present the first

Heinrich Söbke, Maria Reichelt

Game-based technologies and mobile learning aids open up many opportunities for learners; however, evidence-based decisions on their appropriate use are necessary. This explorative study (N = 100) examines the role of game elements in university education using a game-based learning app for mobile devices. The educational goal of the app is to support studen

Steven P. Bos, David S. Doelman, Jos de Boer, Emiel H. Por

We present designs for fully achromatic vector Apodizing Phase Plate (vAPP) coronagraphs, that implement low polarization leakage solutions and achromatic beam-splitting, enabling observations in broadband filters. The vAPP is a pupil plane optic, inducing the phase through the inherently achromatic geometric phase. We discuss various implementations of the

Kwokwai Chan, Naichung Conan Leung, Changzheng Li

We construct pseudotoric structures (\`{a} la Tyurin) on the two-step flag variety $F\ell_{1, n-1; n}$, and explain a general relation between pseudotoric structures and special Lagrangian torus fibrations, the latter of which are important in the study of SYZ mirror symmetry. As an application, we speculate how our constructions can explain the number of te

J. Hong, H. -N. Hwang, A. T. NDiaye, J. Liang

When Fe, which is a typical ferromagnet using d- or f-orbital states, is combined with 2D materials such as graphene, it offers many opportunities for spintronics. The origin of 2D magnetism is from magnetic insulating behaviors, which could result in magnetic excitations and also proximity effects. However, the phenomena were only observed at extremely low

Thitipat Sainapha

The possibility to modify both quarks sum rules and the DGLAP evolution equation are investigated. In presence of anomalous baryon global symmetry, the quark sum rules are no longer the same as usual. In addition, the DGLAP equation is also changed to be self-consistent with modified sum rules. This way of modification turns out to satisfy the Sakharov's bar

Rudra Narayan Padhan, K. C. Pati

This paper is devoted to the characterization of all finite dimensional nilpotent Lie algebras $L$ with $S^{2}(L)=0,1,2,3$, where we define $dim ~\mathcal{M}^{2}(L) = \dfrac{1}{3}n(n-1)(n-2)+3-S^{2}(L).$

Sourav Chatterjee

Wilson loop expectation in 4D $\mathbb{Z}_2$ lattice gauge theory is computed to leading order in the weak coupling regime. This is the first example of a rigorous theoretical calculation of Wilson loop expectation in the weak coupling regime of a 4D lattice gauge theory. All prior results are either inequalities or strong coupling expansions.

Xue Rui, Robert Klie

The presence of oxygen vacancy, as well as ordering of vacancies plays an important role in determining the electronic, ionic and thermal transport properties of many transition metal oxide materials. Controlling the concentration of oxygen vacancies as well as the structures or domains of ordered oxygen vacancies has been the subject of many experimental an

Chengbin Xu, Tengfei Zhao

In this paper, we give a simple proof of scattering result for the Schr\"odinger equation with combined term $i\pa_tu+\Delta u=|u|^2u-|u|^4u$ in dimension three, that avoids the concentrate compactness method. The main new ingredient is to extend the scattering criterion to energy-critical.

Hoang Pham, Jason Woodworth, Mohsen Amini Salehi

Cloud computing has become a potential resource for businesses and individuals to outsource their data to remote but highly accessible servers. However, potentials of the cloud services have not been fully unleashed due to users' concerns about security and privacy of their data in the cloud. User-side encryption techniques can be employed to mitigate the se

Rim Assouel, Mohamed Ahmed, Marwin H Segler, Amir Saffari

Generating novel molecules with optimal properties is a crucial step in many industries such as drug discovery. Recently, deep generative models have shown a promising way of performing de-novo molecular design. Although graph generative models are currently available they either have a graph size dependency in their number of parameters, limiting their use

Rafael D. Sorkin, Yasaman K. Yazdi, Nosiphiwo Zwane

To a significant extent, the metrical and topological properties of spacetime can be described purely order-theoretically. The $K^+$ relation has proven to be useful for this purpose, and one could wonder whether it could serve as the primary causal order from which everything else would follow. In that direction, we prove, by defining a suitable order-theor

Yu Zeng, Kebei Jiang, Jie Chen

One of the most crucial tasks in seismic reflection imaging is to identify the salt bodies with high precision. Traditionally, this is accomplished by visually picking the salt/sediment boundaries, which requires a great amount of manual work and may introduce systematic bias. With recent progress of deep learning algorithm and growing computational power, a

Anatolii Puhalskii

We use Hamilton equations to find optimal paths to big queues in Jackson networks. They are shown to be given by fluid trajectories of the dual network. The fluid equations are shown to be dual to the Hamilton equations. Thus, a version of the extended Onzager-Machlup principle is proved: a fluctuation trajectory is the time reversal of a relaxation trajecto

Pak Lun Kevin Ding, Yikang Li, Baoxin Li

The research on hashing techniques for visual data is gaining increased attention in recent years due to the need for compact representations supporting efficient search/retrieval in large-scale databases such as online images. Among many possibilities, Mean Average Precision(mAP) has emerged as the dominant performance metric for hashing-based retrieval. On

Eric Boyers, Mohit Pandey, David K. Campbell, Anatoli Polkovnikov

Adiabatic evolution is a common strategy for manipulating quantum states and has been employed in diverse fields such as quantum simulation, computation and annealing. However, adiabatic evolution is inherently slow and therefore susceptible to decoherence. Existing methods for speeding up adiabatic evolution require complex many-body operators or are diffic

Yarden Mazor, Andrea Alù

Highly confined surface waves present unique opportunities to enhance light interactions with localized emitters or molecules. Hyperbolic dispersion in metasurfaces allows us to tailor and manipulate surface waves, enhancing the local density of states over broad bandwidths. So far, propagation on this platform was mainly studied in planar geometries, which

CMS Collaboration

A search is presented for resonant production of second-generation sleptons ($\tilde{\mu}_L$, $\tilde{\nu}_\mu$) via the $R$-parity-violating coupling $\lambda'_{211}$ to quarks, in events with two same-sign muons and at least two jets in the final state. The smuon (muon sneutrino) is expected to decay into a muon and a neutralino (chargino), which will then

Minhae Kwon, Juhyeon Lee, Hyunggon Park

In this paper, we propose a distributed solution to design a multi-hop ad hoc network where mobile relay nodes strategically determine their wireless transmission ranges based on a deep reinforcement learning approach. We consider scenarios where only a limited networking infrastructure is available but a large number of wireless mobile relay nodes are deplo

Juliano C. S. Neves

In spite of successful tests, the standard cosmological model, the $\Lambda$CDM model, possesses the most problematic concept: the initial singularity, also known as the big bang. In this paper---by adopting the Kantian difference between to think of an object and to cognize an object---it is proposed a degree of scientificity using fuzzy sets. Thus, the not

Xiu Yang, David Barajas-Solano, Guzel Tartakovsky, Alexandre Tartakovsky

In this work, we propose a new Gaussian process regression (GPR)-based multifidelity method: physics-informed CoKriging (CoPhIK). In CoKriging-based multifidelity methods, the quantities of interest are modeled as linear combinations of multiple parameterized stationary Gaussian processes (GPs), and the hyperparameters of these GPs are estimated from data vi

Takahiro Ueda, Mario Flock, Satoshi Okuzumi

We perform simulations of the dust and gas disk evolution to investigate the observational features of a dust-pileup at the dead-zone inner edge. We show that the total mass of accumulated dust particles is sensitive to the turbulence strength in the dead zone, $\alpha_{\rm dead}$, because of the combined effect of turbulence-induced particle fragmentation (

Xinzhi Wang, Shengcheng Yuan, Hui Zhang, Yi Liu

This paper focuses on sentiment mining and sentiment correlation analysis of web events. Although neural network models have contributed a lot to mining text information, little attention is paid to analysis of the inter-sentiment correlations. This paper fills the gap between sentiment calculation and inter-sentiment correlations. In this paper, the social

Zhen Lei, Jie Liu, Xiao Ren

The well-known Constantin-Lax-Majda (CLM) equation, an important toy model of the 3D Euler equations without convection, can develop finite time singularities [5]. De Gregorio modified the CLM model by adding a convective term [6], which is known important for fluid dynamics [10,14]. Presented are two results on the De Gregorio model. The first one is the gl

R. Banerjee, K. Sagiyama, G. H. Teichert, K. Garikipati

A graph theoretic perspective is taken for a range of phenomena in continuum physics in order to develop representations for analysis of large scale, high-fidelity solutions to these problems. Of interest are phenomena described by partial differential equations, with solutions being obtained by computation. The motivation is to gain insight that may otherwi

Ryosuke Hyakuna

In this paper, we establish a standard $L^p$-theory of solutions to one dimensional nonlinear Schr\"odinger equations with the power like nonlinearity. More precisely, we extend the following three well-known results in the $L^2$ space into $L^p$ setting: 1. Large data local well-posedness for subcritical nonlinearities, 2. Small data global well-posedness f

Zirui Wang, Zihang Dai, Barnabás Póczos, Jaime Carbonell

When labeled data is scarce for a specific target task, transfer learning often offers an effective solution by utilizing data from a related source task. However, when transferring knowledge from a less related source, it may inversely hurt the target performance, a phenomenon known as negative transfer. Despite its pervasiveness, negative transfer is usual

Alexandre Hocquet, Frédéric Wieber

Computational chemistry is a scientific field within which the computer is a pivotal element. This scientific community emerged in the 1980s and was involved with two major industries: the computer manufacturers and the pharmaceutical industry, the latter becoming a potential market for the former through molecular modeling software packages. We aim to addre

Siddique Latif, Muhammad Asim, Muhammad Usman, Junaid Qadir

Multishot Magnetic Resonance Imaging (MRI) has recently gained popularity as it accelerates the MRI data acquisition process without compromising the quality of final MR image. However, it suffers from motion artifacts caused by patient movements which may lead to misdiagnosis. Modern state-of-the-art motion correction techniques are able to counter small de

Hao Fu, Zhi-cheng Gong, Tian-hua Mao, Cheng-yu Shen

Geometric phase, which is acquired after a system undergoing cyclic evolution in the Hilbert space, is believed to be noise-resilient because it depends only on the global properties of the evolution path. Here, we report geometric control of energy transfer between two parametrically coupled mechanical modes in an optomechanical system. The parametric pump

Yu-Fei Wang, De-Liang Yao, Han-Qing Zheng

A production representation of partial-wave $S$ matrix is utilized to construct low-energy elastic pion-nucleon scattering amplitudes from cuts and poles on complex Riemann sheets. Among them, the contribution of left-hand cuts is estimated using the $\mathcal{O}(p^3)$ results obtained in covariant baryon chiral perturbation theory within the extended-on-nas

Ari Pakman, Liam Paninski

We develop methods for efficient amortized approximate Bayesian inference over posterior distributions of probabilistic clustering models, such as Dirichlet process mixture models. The approach is based on mapping distributed, symmetry-invariant representations of cluster arrangements into conditional probabilities. The method parallelizes easily, yields iid

Luca Lombardini

This doctoral thesis is devoted to the analysis of some minimization problems that involve nonlocal functionals. We are mainly concerned with the $s$-fractional perimeter and its minimizers, the $s$-minimal sets. We investigate the behavior of sets having (locally) finite fractional perimeter and we establish existence and compactness results for (locally) $