February 2019 arXiv papers — page 26

Tam W. Nguyen, Marco M. Nicotra, Emanuele Garone

This technical note focuses on the control of a quadrotor unmanned aerial vehicle (UAV) tethered to the ground. The control objective is to stabilize the UAV to the desired position while ensuring that the cable remains taut at all times. A cascade control scheme is proposed. The inner loop controls the attitude of the UAV. The outer loop gives the attitude

Mingwei Tang, Gytis Dudas, Trevor Bedford, Vladimir N. Minin

Phylodynamics is a set of population genetics tools that aim at reconstructing demographic history of a population based on molecular sequences of individuals sampled from the population of interest. One important task in phylodynamics is to estimate changes in (effective) population size. When applied to infectious disease sequences such estimation of popul

Daniël Kroes, Sam Spiro

We consider Catalan-pair graphs, a family of graphs that can be viewed as representing certain interactions between pairs of objects which are enumerated by the Catalan numbers. In this paper we study random Catalan-pair graphs and deduce various properties of these random graphs. In particular, we asymptotically determine the expected number of edges and is

Shou-Peng Lyu, Li Yu, Jian-Wei Huang, Cheng-Tian Lin

The detailed information of the electronic structure is the key for understanding the nature of charge density wave (CDW) order and its relationship with superconducting order in microscopic level. In this paper, we present high resolution laser-based angle-resolved photoemission spectroscopy (ARPES) study on the three-dimensional (3D) hole-like Fermi surfac

Carlos Pérez-González, Ricard Alert, Carles Blanch-Mercader, Manuel Gómez-González

Development, regeneration and cancer involve drastic transitions in tissue morphology. In analogy with the behavior of inert fluids, some of these transitions have been interpreted as wetting transitions. The validity and scope of this analogy are unclear, however, because the active cellular forces that drive tissue wetting have been neither measured nor th

David Yevick, Yong Hwan Lee

We demonstrate that a temperature schedule for single-spin flip transition matrix calculations can be simply and rapidly generated by monitoring the average size of the Wolff clusters at a set of discrete temperatures. Optimizing this schedule yields a potentially interesting quantity related to the fractal structure of Ising clusters. We also introduce a te

Mohammad Aminisharifabad, Qingyu Yang

Resistance Spot Welding (RSW) is an important manufacturing process that attracts increasing attention in automotive industry. However, due to the complexity of the manufacturing process, the corresponding product quality shows significant inconsistencies even under the same process setup. This paper develops a statistical method to capture the inconsistence

Fenglian Yang, Liang Yan

In this study, we consider an ensemble Kalman inversion (EKI) for the numerical solution of time-fractional diffusion inverse problems (TFDIPs). Computational challenges in the EKI arise from the need for repeated evaluations of the forward model. We address this challenge by introducing a non-intrusive reduced basis (RB) method for constructing surrogate mo

Zhicheng Hu, Zhenning Cai, Yanli Wang

We propose a Hermite spectral method for the spatially inhomogeneous Boltzmann equation. For the inverse-power-law model, we generalize an approximate quadratic collision operator defined in the normalized and dimensionless setting to an operator for arbitrary distribution functions. An efficient algorithm with a fast transform is introduced to discretize th

Nicola Forti, Giorgio Battistelli, Luigi Chisci, Bruno Sinopoli

This paper deals with secure state estimation of cyber-physical systems subject to switching (on/off) attack signals and injection of fake packets (via either packet substitution or insertion of extra packets). The random set paradigm is adopted in order to model, via Random Finite Sets (RFSs), the switching nature of both system attacks and the injection of

Esmaeil Naderi, Khashayar Khorasani

We propose a framework for inversion-based estimation of certain categories of faults in discrete-time linear systems. The fault signal, as an unknown input, is reconstructed from its projections onto two subspaces. One projection is achieved through an algebraic operation, whereas the other is given by a dynamic filter whose poles coincide with the transmis

Zixiao Ma, Zhaoyu Wang, Yishen Wang, Ruisheng Diao

The Western Electricity Coordinating Council (WECC) composite load model is a newly developed load model that has drawn great interest from the industry. To analyze its dynamic characteristics with both mathematical and engineering rigor, a detailed mathematical model is needed. Although WECC composite load model is available in commercial software as a modu

L. Q. Lai, J. Chen, Q. H. Liu, Y. B. Yu

In the presence of a nonlocal potential in molecular device systems, generally the charge conservation cannot be satisfied, and in literatures the modifications of the conventional definition of current were given to solve this problem. We demonstrate that, however, the nonconservation is not due to the invalidation of the conventional definition of current,

Moslem Zamani

In this paper, we study some bounds for nonconvex quadratically constrained quadratic programs. We propose two types of bounds for quadratically constrained quadratic programs, quadratic and cubic bounds. For quadratic bounds, we use affine functions as Lagrange multipliers. We demonstrate that most semi-definite relaxations can be obtained as the dual of a

Tiancheng Zhao, Kaige Xie, Maxine Eskenazi

Defining action spaces for conversational agents and optimizing their decision-making process with reinforcement learning is an enduring challenge. Common practice has been to use handcrafted dialog acts, or the output vocabulary, e.g. in neural encoder decoders, as the action spaces. Both have their own limitations. This paper proposes a novel latent action

Hai Wang, Dian Yu, Kai Sun, Jianshu Chen

Remarkable success has been achieved in the last few years on some limited machine reading comprehension (MRC) tasks. However, it is still difficult to interpret the predictions of existing MRC models. In this paper, we focus on extracting evidence sentences that can explain or support the answers of multiple-choice MRC tasks, where the majority of answer op

Radu Tudor Ionescu, Andrei M. Butnaru

In this paper, we propose a novel representation for text documents based on aggregating word embedding vectors into document embeddings. Our approach is inspired by the Vector of Locally-Aggregated Descriptors used for image representation, and it works as follows. First, the word embeddings gathered from a collection of documents are clustered by k-means i

D. Tourret, M. M. Francois, A. J. Clarke

We present a mathematical formulation of a multiscale model for solidification with convective flow in the liquid phase. The model is an extension of the dendritic needle network approach for crystal growth in a binary alloy. We propose a simple numerical implementation based on finite differences and step-wise approximations of parabolic dendritic branches

Genly Leon, Andronikos Paliathanasis

We examine the phase space of Hořava-Lifshitz cosmology for a wide range of self-interacting potentials for the scalar field under the detailed-balance condition and without imposing it, by means of the powerful method of $f$-devisers. A compactification approach is performed for the exponential potential and for potentials beyond the exponential one, extend

Adrián Lozano-Durán, H. Jane Bae, Miguel P. Encinar

Turbulent flows in the presence of walls may be apprehended as a collection of momentum- and energy-containing eddies (energy-eddies), whose sizes differ by many orders of magnitude. These eddies follow a self-sustaining cycle, i.e., existing eddies are seeds for the inception of new ones, and so forth. Understanding this process is critical for the modellin

G. Ramalho, J. P. B. C. de Melo, K. Tsushima

The ratios of the baryon electric ($G_E$) to magnetic ($G_M$) form factors, $G_E/G_M$, can provide us with important information on the structure of baryons in vacuum as demonstrated in recent studies for the proton and neutron systems. It has been argued that the corresponding in-medium ratios, $G_E^\ast/G_M^\ast$, can also provide useful information on the

Naoki Kitazawa

The Reeb graph of a function on a smooth manifold is the graph obtained as the space of all connected components of level sets such that the set of all vertices coincides with the set of all connected components of level sets including singular points. Reeb graphs are fundamental and important in the algebraic and differential topological theory of Morse fun

Mohsen Khani, Afshin Zarei

We have provided a pure model-theoretic proof for the decidability of the additive structure of the integers together with the function {f} sending {x} to {[ϕx]} where ϕ is the golden ratio.

Michele DIncecco, Stefano Squartini, Mingjun Zhong

Non-intrusive load monitoring (NILM) is a technique to recover source appliances from only the recorded mains in a household. NILM is unidentifiable and thus a challenge problem because the inferred power value of an appliance given only the mains could not be unique. To mitigate the unidentifiable problem, various methods incorporating domain knowledge into

Boris Khesin, Cheng Yang

The binormal (or vortex filament) equation provides the localized induction approximation of the 3D incompressible Euler equation. We present explicit solutions of the binormal equation in higher-dimensions that collapse in finite time. The local nature of this phenomenon suggests the appearance of singularity in nearby vortex blob solutions of the Euler equ

Marcos R. A. Arcodía, Mauricio Bellini, Roldao da Rocha

Dirac linear spinor fields were obtained from non-linear Heisenberg spinors, in the literature. Here we extend that idea by considering not only Dirac spinor fields but spinor fields in any of the Lounesto's classes. When one starts considering all these classes of fields, the question of providing a classification for the Heisenberg spinor naturally ari

Thorsten Glüsenkamp

Counting experiments often rely on Monte Carlo simulations for predictions of Poisson expectations. The accompanying uncertainty from the finite Monte Carlo sample size can be incorporated into parameter estimation by modifying the Poisson likelihood. We first review previous Frequentist methods of this type by Barlow et al, Bohm et al, and Chirkin, as well

Massimo Ventrucci, Daniela Cocchi, Gemma Burgazzi, Alex Laini

Lack of independence in the residuals from linear regression motivates the use of random effect models in many applied fields. We start from the one-way anova model and extend it to a general class of one-factor Bayesian mixed models, discussing several correlation structures for the within group residuals. All the considered group models are parametrized in

Sayan Chakrabarti, Debaprasad Maity, Wadbor Wahlang

Fermi arcs are disconnected contour of Fermi surface, which can be observed in the pseudo-gap phase of high temperature superconductors. Aiming to understand this pseudo-gap phenomena, we study a holographic Fermionic system coupled with a massive scalar field in an AdS black hole background. Depending on the boundary condition on the scalar field mode, we d

Ashia Wilson, Lester Mackey, Andre Wibisono

We present a family of algorithms, called descent algorithms, for optimizing convex and non-convex functions. We also introduce a new first-order algorithm, called rescaled gradient descent (RGD), and show that RGD achieves a faster convergence rate than gradient descent provided the function is strongly smooth -- a natural generalization of the standard smo

Leonid Barenboim, Gal Oren

We consider the Backup Placement problem in networks in the $\mathcal{CONGEST}$ distributed setting. Given a network graph $G = (V,E)$, the goal of each vertex $v \in V$ is selecting a neighbor, such that the maximum number of vertices in $V$ that select the same vertex is minimized. The backup placement problem was introduced by Halldorsson, Kohler, Patt-Sh

Mohammad Rashidi, Jeremiah Croshaw, Kieran Mastel, Marcus Tamura

As the development of atom scale devices transitions from novel, proof-of-concept demonstrations to state-of-the-art commercial applications, automated assembly of such devices must be implemented. Here we present an automation method for the identification of defects prior to atomic fabrication via hydrogen lithography using deep learning. We trained a conv

N. A. Carella

The first estimate of the upper bound $μ(π)\leq42$ of the irrationality measure of the number $π$ was computed by Mahler in 1953, and more recently it was reduced to $μ(π)\leq7.6063$ by Salikhov in 2008. Here, it is shown that $π$ has the same irrationality measure $μ(π)=μ(α)=2$ as almost every irrational number $α>0$.

Ioannis Z. Emiris, Vasilis Margonis, Ioannis Psarros

Randomized dimensionality reduction has been recognized as one of the fundamental techniques in handling high-dimensional data. Starting with the celebrated Johnson-Lindenstrauss Lemma, such reductions have been studied in depth for the Euclidean $(\ell_2)$ metric, but much less for the Manhattan $(\ell_1)$ metric. Our primary motivation is the approximate n

Guillaume Salha, Romain Hennequin, Viet Anh Tran, Michalis Vazirgiannis

In this paper, we present a general framework to scale graph autoencoders (AE) and graph variational autoencoders (VAE). This framework leverages graph degeneracy concepts to train models only from a dense subset of nodes instead of using the entire graph. Together with a simple yet effective propagation mechanism, our approach significantly improves scalabi

J. A. Armario, D. L. Flannery

Generalized perfect binary arrays (GPBAs) were used by Jedwab to construct perfect binary arrays. A non-trivial GPBA can exist only if its energy is $2$ or a multiple of $4$. This paper introduces generalized optimal binary arrays (GOBAs) with even energy not divisible by $4$, as analogs of GPBAs. We give a procedure to construct GOBAs based on a characteriz

Kayvan Bijari, Hadi Zare, Emad Kebriaei, Hadi Veisi

Over the last few years, machine learning over graph structures has manifested a significant enhancement in text mining applications such as event detection, opinion mining, and news recommendation. One of the primary challenges in this regard is structuring a graph that encodes and encompasses the features of textual data for the effective machine learning

Soheila Molaei, Hadi Zare, Hadi Veisi

There are many real-world knowledge based networked systems with multi-type interacting entities that can be regarded as heterogeneous networks including human connections and biological evolutions. One of the main issues in such networks is to predict information diffusion such as shape, growth and size of social events and evolutions in the future. While t

László Kozma

Permutation patterns and pattern avoidance have been intensively studied in combinatorics and computer science, going back at least to the seminal work of Knuth on stack-sorting (1968). Perhaps the most natural algorithmic question in this area is deciding whether a given permutation of length $n$ contains a given pattern of length $k$. In this work we give

J. A. Armario, D. L. Flannery

We introduce the notion of quasi-orthogonal cocycle. This is motivated in part by the maximal determinant problem for square $\{\pm 1\}$-matrices of size congruent to $2$ modulo $4$. Quasi-orthogonal cocycles are analogous to the orthogonal cocycles of algebraic design theory. Equivalences with new and known combinatorial objects afforded by this analogy, su

Piet Groeneboom

Let $\hat f_n$ be the nonparametric maximum likelihood estimator of a decreasing density. Grenander characterized this as the left-continuous slope of the least concave majorant of the empirical distribution function. For a sample from the uniform distribution, the asymptotic distribution of the $L_2$-distance of the Grenander estimator to the uniform densit

Daniel Hackmann

We derive the Lévy-Khintchine representation of the Wiener-Hopf factors for the Normal Inverse Gaussian (NIG) process as well as a representation which is similar to the moment generating function (MGF) of a generalized gamma convolution (GGC). We show, via this representation, that for some parameters the Wiener-Hopf factors are, in fact, the MGFs of GGCs.

Fedor Bogomolov, Hang Fu

Let $E$ be an elliptic curve and $π:E\to\mathbb{P}^{1}$ a standard double cover identifying $\pm P\in E$. It is known that for some torsion points $P_{i}\in E$, $1\leq i\leq4$, the cross ratio of $\{π(P_{i})\}_{i=1}^{4}$ is independent of $E$. In this article, we will give a complete classification of such quadruples.

Salvador López-Martínez, Alexis Molino

In this paper we prove the nonexistence of nontrivial solution to \begin{equation*} \begin{cases} -Δu =f(u) &\text{in }Ω, \\ u=0 &\text{on } \partial Ω, \end{cases} \end{equation*} being $Ω\subset \mathbb{R}^N$ ($N\in \mathbb{N}$) a bounded domain and $f$ locally Lispchitz with non-positive primitive.

Jun Hu, Limin Ma

Asymptotic expansions are derived for eigenvalues produced by both the Crouzeix-Raviart element and the enriched Crouzeix--Raviart element. The expansions are optimal in the sense that extrapolation eigenvalues based on them admit a fourth order convergence provided that exact eigenfunctions are smooth enough. The major challenge in establishing the expansio

Fakhar ul Hassan, Anwaar Ali, Mohamed Rahouti, Siddique Latif

Blockchain is challenging the status quo of the central trust infrastructure currently prevalent in the Internet towards a design principle that is underscored by decentralization, transparency, and trusted auditability. In ideal terms, blockchain advocates a decentralized, transparent, and more democratic version of the Internet. Essentially being a trusted

Wojciech Dybalski, Alessandro Pizzo

We consider the massless Nelson model with two types of massive particles which we call atoms and electrons. The atoms interact with photons via an infrared regular form-factor and thus they are Wigner-type particles with sharp mass-shells. The electrons have an infrared singular form-factor and thus they are infraparticles accompanied by soft-photon clouds

Yakir Aharonov, Eliahu Cohen, David H. Oaknin

Conditional probabilities in quantum systems which have both initial and final boundary conditions are commonly evaluated using the Aharonov-Bergmann-Lebowitz rule. In this short note we present a seemingly disturbing paradox that appears when applying the rule to systems with slightly broken degeneracies. In these cases we encounter a singular limit - the p

Yoshinobu Kamishima

We study positive definite quaternionic contact $(4n+3)$-manifolds ($qc$-manifold for short). Just like the $CR$-structure contains the class of Sasaki manifolds, the $qc$-structure admits a class of $3$-Sasaki manifolds with integrable distribution isomorphic to $\mathfrak{su}(2)$. A big difference concerning the integrable complementary $qc$-distribution $

Chi Sun, Xipeng Qiu, Xuanjing Huang

Chinese is a logographic writing system, and the shape of Chinese characters contain rich syntactic and semantic information. In this paper, we propose a model to learn Chinese word embeddings via three-level composition: (1) a convolutional neural network to extract the intra-character compositionality from the visual shape of a character; (2) a recurrent n

Carlos L. Benavides-Riveros, Miguel A. L. Marques

We derive an equation for the time evolution of the natural occupation numbers for fermionic systems with more than two electrons. The evolution of such numbers is connected with the symmetry-adapted generalized Pauli exclusion principle, as well as with the evolution of the natural orbitals and a set of many-body relative phases. We then relate the evolutio

Yuedong Chen, Jianfeng Wang, Shikai Chen, Zhongchao Shi

Deep learning based facial expression recognition (FER) has received a lot of attention in the past few years. Most of the existing deep learning based FER methods do not consider domain knowledge well, which thereby fail to extract representative features. In this work, we propose a novel FER framework, named Facial Motion Prior Networks (FMPN). Particularl

Dmitry Karlovets

A quantum state of an electron influences its electromagnetic field. If a spatial profile of the electron wave packet is not Gaussian, the particle may acquire additional intrinsic multipole moments, which alter its field, especially at small distances. Here the fields of a vortex electron with orbital angular momentum $\ell$ are obtained in a form of a mult

Vinod Kumar, Aga Shahee, S. Kundu, M. Baenitz

We present the synthesis and a detailed investigation of structural and magnetic properties of polycrystalline Ba(TiO)Cu$_{4}$(PO$_{4}$)$_{4}$ (BTCPO) via x-ray diffraction, magnetic susceptibility, heat capacity, and $^{31}$P Nuclear Magnetic Resonance (NMR) measurements. BTCPO has a 2D layered structure with interlinked Cu$_{4}$O$_{12}$ tetramer units. A b

Yun Zhou, Tie-Jun Xiao, Jun Cao, Yun-An Yan

We derive the formula of energy flux for the hierarchical equations of motion (HEOM) method with the help of stochastic decoupling technique. The resulting expression is a combination of the terms in the first two layers of the hierarchy. The formula is applied to a three-level "heat engine" coupled respectively to three baths, of which two for heat

Delaram Kahrobaei, Antonio Tortora, Maria Tota

In this paper we generalize the definition of a multilinear map to arbitrary groups and develop a novel idea of multilinear cryptosystem using nilpotent group identities.

Hideto Asashiba, Yuya Mizuno, Ken Nakashima

We study 2-term tilting complexes of Brauer tree algebras in terms of simplicial complexes. We show the symmetry and convexity of the simplicial complexes as lattice polytopes. Via a geometric interpretation of derived equivalences, we show that the $f$-vector of simplicial complexes of Brauer tree algebras only depends the number of the edges of the Brauer

Satya S. Malladi, Alan L. Erera, Chelsea C. White

We investigate the potential added value of being able to relocate production capacity, relative to fixed production capacity, in a network of multiple, geographically distributed manufacturing sites. There is a growing interest in production capacity that can be geographically relocated; e.g., modular units for pharmaceutical intermediates. It shows promise

André Izidoro, Bertram Bitsch, Sean N. Raymond, Anders Johansen

At least 30\% of main sequence stars host planets with sizes of between 1 and 4 Earth radii and orbital periods of less than 100 days. We use N-body simulations including a model for gas-assisted pebble accretion and disk--planet tidal interaction to study the formation of super-Earth systems. We show that the integrated pebble mass reservoir creates a bifur

Bertram Bitsch, André Izidoro, Anders Johansen, Sean N. Raymond

Giant planets migrate though the protoplanetary disc as they grow. We investigate how the formation of planetary systems depends on the radial flux of pebbles through the protoplanetary disc and on the planet migration rate. Our N-body simulations confirm previous findings that Jupiter-like planets in orbits outside the water ice line originate from embryos

Geoff Goodell, Tomaso Aste

Current architectures to validate, certify, and manage identity are based on centralised, top-down approaches that rely on trusted authorities and third-party operators. We approach the problem of digital identity starting from a human rights perspective, with a primary focus on identity systems in the developed world. We assert that individual persons must

T. R. Govindarajan, Nikhil Kalyanapuram

In this letter, we propose a new model of fuzzy dark matter based on Stueckelberg theory. Dark matter is treated as a Bose-Einstein condensate of Stueckelberg particles and the resulting cosmological effects are analyzed. Fits are understood for the density and halo sizes of such particles and comparison with existing models is made. Certain attractive prope

Ahmed Abdelkader, Chandrajit L. Bajaj, Mohamed S. Ebeida, Ahmed H. Mahmoud

Polyhedral meshes are increasingly becoming an attractive option with particular advantages over traditional meshes for certain applications. What has been missing is a robust polyhedral meshing algorithm that can handle broad classes of domains exhibiting arbitrarily curved boundaries and sharp features. In addition, the power of primal-dual mesh pairs, exe

Cheng-Jun Xia, Toshiki Maruyama, Nobutoshi Yasutake, Toshitaka Tatsumi

We study the interface effects of quark-hadron mixed phase in compact stars. The properties of nuclear matter are obtained based on the relativistic-mean-field model. For the quark phase, we adopt perturbation model with running quark masses and coupling constant. At certain choices of parameter sets, it is found that varying the quark-hadron interface tensi

Nikita Medvedev

This contribution discusses challenges in the modeling of formation of the warm dense matter (WDM) state in solids exposed to femtosecond X-ray free-electron laser pulses. It is based upon our previously reported code XTANT (X-ray-induced Thermal And Nonthermal Transition; N. Medvedev et. al, 4open 1, 3, 2018), which combines tight-binding (TB) molecular dyn

Yu. A. Lashko, V. S. Vasilevsky, G. F. Filippov

Matrix elements of potential energy are examined in detail. We consider a model problem - a particle in a central potential. The most popular forms of central potential are taken up, namely, square-well potential, Gaussian, Yukawa and exponential potentials. We study eigenvalues and eigenfunctions of the potential energy matrix constructed with oscillator fu

Amirnezam Amiri, Saeed Tavasoli, Gianfranco De Zotti

Motivated by the apparently conflicting results reported in the literature on the effect of environment on nuclear activity, we have carried out a new analysis by comparing the fraction of galaxies hosting active galactic nuclei (AGNs) in the most overdense regions (rich galaxy clusters) and the most underdense ones (voids) in the local universe. Exploiting

K. Srivastava, K. Sood, S. K. Srivastava

The main purpose of this paper is to present the spherical characterization of Legendre curves in $3$-dimensional quasi-Sasakian pseudo-metric manifolds. Furthermore, null Legendre curves are also characterized in this class of manifold.

Matthias C. Caro

The problem of learning Boolean linear functions from quantum examples w.r.t. the uniform distribution can be solved on a quantum computer using the Bernstein-Vazirani algorithm. A similar strategy can be applied in the case of noisy quantum training data, as was observed in arXiv:1702.08255v2 [quant-ph]. However, extensions of these learning algorithms beyo

Mathieu Benoit

The physics aims at the proposed future CLIC high-energy linear $e^+ e^-$ collider pose challenging demands on the performance of the detector system. In particular the vertex and tracking detectors have to combine precision measurements with robustness against the expected high rates of beam-induced backgrounds. A spatial resolution of a few microns and a m

Chilong Lin

In this manuscript, we present an explicit way to describe the violation of CP symmetry in the standard model (SM) of electroweak interactions. In such a way, complex Cabbibo-Kobayashi-Maskawa (CKM) matrices are achieved which stand for the violation of CP symmetry. At the beginning, two necessary but not sufficient conditions for yielding a complex CKM matr

Surajit Mondal, Atul Mohan, Divya Oberoi, John S. Morgan

Solar radio emission, especially at metre-wavelengths, is well known to vary over small spectral ($\lesssim$100\,kHz) and temporal ($<1$\,s) spans. It is comparatively recently, with the advent of a new generation of instruments, that it has become possible to capture data with sufficient resolution (temporal, spectral and angular) that one can begin to char

Oleksiy Dovgoshey

Characterizations of pseudoultrametric-preserving functions and semimetric-preserving functions are found. The structural properties of pseudoultrametrics which can be represented as a composition of an ultrametric and ultrametric-pseudoultrametric-preserving function are found. A dual form of Pongsriiam-Termwuttipong characterization of the ultrametric-pres

Zuling Chang, Martianus Frederic Ezerman, Adamas Aqsa Fahreza

We propose a general greedy algorithm for binary de Bruijn sequences, called Generalized Prefer-Opposite (GPO) Algorithm, and its modifications. By identifying specific feedback functions and initial states, we demonstrate that most previously-known greedy algorithms that generate binary de Bruijn sequences are particular cases of our new algorithm.

Qiwei Li, Shuang Jiang, Andrew Y. Koh, Guanghua Xiao

The advances of next-generation sequencing technology have accelerated study of the microbiome and stimulated the high throughput profiling of metagenomes. The large volume of sequenced data has encouraged the rise of various studies for detecting differentially abundant taxonomic features across healthy and diseased populations, with the ultimate goal of de

Julian Theis, Houshang Darabi

Process Mining is a famous technique which is frequently applied to Software Development Processes, while being neglected in Human-Computer Interaction (HCI) recommendation applications. Organizations usually train employees to interact with required IT systems. Often, employees, or users in general, develop their own strategies for solving repetitive tasks

Sibo Zheng

In the context of supersymmetry, the two-loop Barr-Zee diagrams which induce CP-violating electric dipole moment of electron due to superpartners simultaneously yield CP-conserving magnetic dipole moment of muon. In this paper, we derive the coherence between the electric and magnetic dipole moments at two-loop level due to stops, charginos or neutralinos-ch

Alon Harell, Stephen Makonin, Ivan V. Bajić

Non-intrusive load monitoring (NILM) helps meet energy conservation goals by estimating individual appliance power usage from a single aggregate measurement. Deep neural networks have become increasingly popular in attempting to solve NILM problems; however, many of them are not causal which is important for real-time application. We present a causal 1-D con

Jushan Bai, Junlong Feng

We show that when a high-dimensional data matrix is the sum of a low-rank matrix and a random error matrix with independent entries, the low-rank component can be consistently estimated by solving a convex minimization problem. We develop a new theoretical argument to establish consistency without assuming sparsity or the existence of any moments of the erro

Victoria Hwang, Anna B. Stephenson, Sofia Magkiriadou, Jin-Gyu Park

Disordered packings of colloidal spheres show angle-independent structural color when the particles are on the scale of the wavelength of visible light. Previous work has shown that the positions of the peaks in the reflectance spectra can be predicted accurately from a single-scattering model that accounts for the effective refractive index of the material.

R. J. Koch, T. Konstantinova, M. Abeykoon, A. Wang

We report pair distribution function measurements of the iron-based superconductor FeSe above and below the structural transition temperature. Structural analysis reveals a local orthorhombic distortion with a correlation length of about 4 nm at temperatures where an average tetragonal symmetry is observed. The analysis further demonstrates that the local di

Peter Krafft, Brian Keegan, Seth Frey

Whether we recognize it or not, the Internet is rife with exciting and original institutional forms that are transforming social organization on and offline. Issues of governance in these Internet platforms and other digital institutions have posed a challenge for software engineers, many of whom have little exposure to the relevant history or theory of inst

Saikat Sur, Anupam Ghosh

Measure synchronization is a well-known phenomenon in coupled classical Hamiltonian systems over last two decades. In this paper, synchronization for coupled Harper system is investigated in both classical and quantum contexts. The concept of measure synchronization involves with the phase space and it seems that the measure synchronization is restricted in

Zheng Yang, Hang Lei, Weizhong Qian

This paper reports on the development of a formal symbolic process virtual machine (FSPVM) denoted as FSPVM-E for verifying the reliability and security of Ethereum-based services at the source code level of smart contracts, and a Coq proof assistant is employed for both programming the system and for proving its correctness. The current version of FSPVM-E a

Andre Nies

Some notions from algorithmic randomness are extended to measures and to quantum states. There is a lot on group theory and its relation to logic. This includes some new results on oligomorphic groups. There&#39;s also metric spaces and Scott rank, and interpretability.

Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh

Verification of neural networks enables us to gauge their robustness against adversarial attacks. Verification algorithms fall into two categories: exact verifiers that run in exponential time and relaxed verifiers that are efficient but incomplete. In this paper, we unify all existing LP-relaxed verifiers, to the best of our knowledge, under a general conve

Yuki Maehara

Dimitri Ara&#39;s 2-quasi-categories, which are certain presheaves over André Joyal&#39;s 2-cell category $Θ_2$, are an example of a concrete model that realises the abstract notion of $(\infty,2)$-category. In this paper, we prove that the 2-quasi-categories and the fibrations into them can be characterised using the inner horn inclusions and the equivalenc

Ling Zhang, Le Lu, Xiaosong Wang, Robert M. Zhu

Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment and surgical planning. Recent advances of convolutional networks have demonstrated higher accuracy than traditional mathematical models in predicting future tumor volumes. This indicates that deep learning-based techniques m

B. A. Tay

We study general transformation on the density matrix of two-level system that keeps the expectation value of observable invariant. We introduce a set of generators that yields hermiticity and trace preserving general transformation which casts the transformation into simple form. The general transformation is in general not factorized and not completely pos

Aditya Sood, Feng Xiong, Shunda Chen, Ramez Cheaito

Layered two-dimensional (2D) materials have highly anisotropic thermal properties between the in-plane and cross-plane directions. In general, it is thought that cross-plane thermal conductivities ($κ_z$) are low, and therefore c-axis phonon mean free paths (MFPs) are small. Here, we measure $κ_z$ across MoS$_2$ films of varying thickness (20 to 240 nm) and

Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani

Efficient audio synthesis is an inherently difficult machine learning task, as human perception is sensitive to both global structure and fine-scale waveform coherence. Autoregressive models, such as WaveNet, model local structure at the expense of global latent structure and slow iterative sampling, while Generative Adversarial Networks (GANs), have global

Elena Smirnova, Elvis Dohmatob, Jérémie Mary

Real-world applications require RL algorithms to act safely. During learning process, it is likely that the agent executes sub-optimal actions that may lead to unsafe/poor states of the system. Exploration is particularly brittle in high-dimensional state/action space due to increased number of low-performing actions. In this work, we consider risk-averse ex

A. Deliege, A. Cioppa, M. Van Droogenbroeck

Neural networks designed for the task of classification have become a commodity in recent years. Many works target the development of more effective networks, which results in a complexification of their architectures with more layers, multiple sub-networks, or even the combination of multiple classifiers, but this often comes at the expense of producing uni

Mahendra K. Verma

In this paper we show similarities between turbulence and financial systems. Motivated by similarities between the two systems, we construct a multiscale model for hierarchical financial structures that exhibits a constant cascade of wealth from large financial entities to small financial entities. According to our model, large and intermediate scale financi

Xi Zhu, Mingbin Xu, Hui Jiang

In this paper, we present our method of using fixed-size ordinally forgetting encoding (FOFE) to solve the word sense disambiguation (WSD) problem. FOFE enables us to encode variable-length sequence of words into a theoretically unique fixed-size representation that can be fed into a feed forward neural network (FFNN), while keeping the positional informatio

Louis Crane

We investigate looking for black hole starships using very high energy gamma ray telescopes. We find they would be above the threshhold of visibility although there are many unknown factors.

Andre D. Domingos Cavalcanti, Marcelo M. Cavalcanti, Wellington J. Correa, Zayd Hajjej

We study a nonlocal evolution equation modeling the deformation of a bridge, either a footbridge or a suspension bridge. Contrarily to the previous literature we prove the asymptotic stability of the considered model with a minimum amount of damping which represents less cost of material. The result is also numerically proved.

Yang Sun, Feng Zhang, Huajing Song, Mikhail I. Mendelev

We investigated the homogenous nucleation of the stoichiometric B2 and B33 phases in the Ni50Zr50 alloy using the persistent embryo method and the classical nucleation theory. The two phases become very close competitors at large supercoolings, which is consistent with the experimental observations. In the case of the B2 phase, the linear temperature depende

Yoshikazu Giga, Qing Liu, Hiroyoshi Mitake

We introduce a discrete scheme for second order fully nonlinear parabolic PDEs with Caputo&#39;s time fractional derivatives. We prove the convergence of the scheme in the framework of the theory of viscosity solutions. The discrete scheme can be viewed as a resolvent-type approximation.

John W. Price

The elastic scattering process $Λp\toΛp$ offers insights on multiple problems in nuclear physics. $\mathrm{SU}(3)_F$ symmetry implies a close agreement between the $Λp$ and $pp$ scattering cross sections. The $Λp$ elastic scattering cross section can also illuminate the structure of neutron stars. A data-mining project was started using multiple CLAS data se