arXiv papers from October 2018

Yu-An Wang, Yu-Kai Huang, Tzu-Chuan Lin, Shang-Yu Su

Automatic melody generation has been a long-time aspiration for both AI researchers and musicians. However, learning to generate euphonious melodies has turned out to be highly challenging. This paper introduces 1) a new variant of variational autoencoder (VAE), where the model structure is designed in a modularized manner in order to model polyphonic and dy

Zahra Sadeghi

In this paper, convolutional layers of pre-trained VGG16 model are analyzed. The analysis is based on the responses of neurons to the images of classes in ImageNet database. First, a visualization method is proposed in order to illustrate the learned content of each neuron. Next, single and multi-faceted neurons are investigated based on the diversity of neu

C. R. Granstrom, R. -X. Liang, Y. Li, P. Li

To study how Andreev reflection (AR) is affected by itinerant antiferromagnetism, we perform $d$-wave AR spectroscopy with superconducting YBa$_2$Cu$_3$O$_{7-\delta}$ on TiAu and on variously-oxidized Nb (NbO$_x$) samples. X-ray photoelectron spectroscopy is also used on the latter to measure their surface oxide composition. Below the N\'eel temperatures ($T

Gaurush Hiranandani, Raghav Somani, Oluwasanmi Koyejo, Sreangsu Acharyya

Exploiting low-rank structure of the user-item rating matrix has been the crux of many recommendation engines. However, existing recommendation engines force raters with heterogeneous behavior profiles to map their intrinsic rating scales to a common rating scale (e.g. 1-5). This non-linear transformation of the rating scale shatters the low-rank structure o

Yong Wang

Based on our previous work on algebraic laws for true concurrency, we design a structured parallel programming language for true concurrency called PPL. Different to most programming languages, PPL has an explicit parallel operator as an essential operator, including its operational, denotational and axiomatic semantics. PPL can structure a truly concurrent

Nicholas L. Jobbitt, Simon J. Patchett, Yashar Alizadeh, Michael F. Reid

Zeeman spectroscopy is used to demonstrate that phenomenological crystal-field parameters determined for the two $C_1$ point-group sites in Er$^{3+}$:Y$_2$SiO$_5$ may be transferred to other ions. The two crystallographic six- and seven-coordinate substitutional sites may be distinguished by comparing the spectra with crystal-field calculations.

Samuel J. Ferguson

We model the quantities appearing in Internal Revenue Service (IRS) tax guidance for calculating the health insurance premium tax credit created by the Patient Protection and Affordable Care Act, also called Obamacare. We ask the question of whether there is a procedure, computable by hand, which can calculate the appropriate premium tax credit for any house

Ying-Ying Lee

Partial mean with generated regressors arises in several econometric problems, such as the distribution of potential outcomes with continuous treatments and the quantile structural function in a nonseparable triangular model. This paper proposes a nonparametric estimator for the partial mean process, where the second step consists of a kernel regression on r

Beau Johnston, Greg Falzon, Josh Milthorpe

OpenCL is an attractive model for heterogeneous high-performance computing systems, with wide support from hardware vendors and significant performance portability. To support efficient scheduling on HPC systems it is necessary to perform accurate performance predictions for OpenCL workloads on varied compute devices, which is challenging due to diverse comp

Hugh Harvey, James Keen, Chester Robinson, James Roff

Group work, where students work on projects to overcome challenges together, has numerous advantages, including learning of important transferable skills, better learning experience and increased motivation. However, in many academic systems the advantages of group projects clash with the need to assign individualised marks to students. A number of different

Jian Zhang, Avner May, Tri Dao, Christopher Ré

We investigate how to train kernel approximation methods that generalize well under a memory budget. Building on recent theoretical work, we define a measure of kernel approximation error which we find to be more predictive of the empirical generalization performance of kernel approximation methods than conventional metrics. An important consequence of this

Jackeline Moreno, Michael S. Vogeley, Gordon T. Richards

This work develops application techniques for stochastic modelling of Active Galactic Nuclei (AGN) variability as a probe of accretion disk physics. Stochastic models, specifically Continuous Auto-Regressive Moving Average (CARMA) models, characterize lightcurves by estimating delay timescales that describe movements away from and toward equilibrium (mean fl

Ru Zhang, Chunfang Devon Lin, Pritam Ranjan

A comprehensive understanding of the population growth of a variety of pests is often crucial for efficient crop management. Our motivating application comes from calibrating a two-delay blowfly (TDB) model which is used to simulate the population growth of Panonychus ulmi (Koch) or European red mites that infest on apple leaves and diminish the yield. We fo

Hamid Eghbal-zadeh, Werner Zellinger, Gerhard Widmer

Generative Adversarial Networks have surprising ability for generating sharp and realistic images, though they are known to suffer from the so-called mode collapse problem. In this paper, we propose a new GAN variant called Mixture Density GAN that while being capable of generating high-quality images, overcomes this problem by encouraging the Discriminator

M. A. López-Osorio, E. Martínez-Pascual, G. Nápoles-Cañedo, J. J. Toscano

We construct a consistent quantum field theory of a dimensionally reduced self-interacting scalar field. The Kaluza-Klein dimensional reduction on the well-known $\Phi^{4}$ scalar theory, on a certain $(4+n)$ spacetime with an arbitrary number of extra dimensions, induces a four dimensional reduced theory with scalar fields: the zeroth mode (`light' field) a

Cesar O. Perez-Regalado, Raul Quiroga-Barranco

The bicomplex Bergman spaces are studied for any bounded bicomplex domain. Its Bergman kernel is computed in terms of the kernels of the complex projections of the domain. We also introduce two additional reproducing kernel Hilbert spaces and relate its kernels to that of the bicomplex Bergman space.

Julia Cen, Andreas Fring, Thomas Frith

We propose time-dependent Darboux (supersymmetric) transformations that provide a scheme for the calculation of explicitly time-dependent solvable non-Hermitian partner Hamiltonians. Together with two Hermitian Hamilitonians the latter form a quadruple of Hamiltonians that are related by two time-dependent Dyson equations and two intertwining relations in fo

Hongyang R. Zhang, Vatsal Sharan, Moses Charikar, Yingyu Liang

We consider the tensor completion problem of predicting the missing entries of a tensor. The commonly used CP model has a triple product form, but an alternate family of quadratic models, which are the sum of pairwise products instead of a triple product, have emerged from applications such as recommendation systems. Non-convex methods are the method of choi

Haoyu Wang, Vivek Kulkarni, William Yang Wang

We introduce a new method DOLORES for learning knowledge graph embeddings that effectively captures contextual cues and dependencies among entities and relations. First, we note that short paths on knowledge graphs comprising of chains of entities and relations can encode valuable information regarding their contextual usage. We operationalize this notion by

Maarten Sap, Ronan LeBras, Emily Allaway, Chandra Bhagavatula

We present ATOMIC, an atlas of everyday commonsense reasoning, organized through 877k textual descriptions of inferential knowledge. Compared to existing resources that center around taxonomic knowledge, ATOMIC focuses on inferential knowledge organized as typed if-then relations with variables (e.g., "if X pays Y a compliment, then Y will likely return the

Boris Tsvelikhovskiy

We show that there are infinitely many nonisomorphic quandle structures on any topogical space $X$ of positive dimension. In particular, we disprove the conjecture, asserting that there are no nontrivial quandle structures on the closed unit interval $[0,1]$.

Daniel Emaasit

$\textit{Pymc-learn}$ is a Python package providing a variety of state-of-the-art probabilistic models for supervised and unsupervised machine learning. It is inspired by $\textit{scikit-learn}$ and focuses on bringing probabilistic machine learning to non-specialists. It uses a general-purpose high-level language that mimics $\textit{scikit-learn}$. Emphasi

Matthew O'Kelly, Aman Sinha, Hongseok Namkoong, John Duchi

While recent developments in autonomous vehicle (AV) technology highlight substantial progress, we lack tools for rigorous and scalable testing. Real-world testing, the $\textit{de facto}$ evaluation environment, places the public in danger, and, due to the rare nature of accidents, will require billions of miles in order to statistically validate performanc

Sorawis Sangtawesin, Bo L. Dwyer, Srikanth Srinivasan, James J. Allred

The nitrogen vacancy (NV) center in diamond exhibits spin-dependent fluorescence and long spin coherence times under ambient conditions, enabling applications in quantum information processing and sensing. NV centers near the surface can have strong interactions with external materials and spins, enabling new forms of nanoscale spectroscopy. However, NV spin

Minghuang Ma, Hadi Pouransari, Daniel Chao, Saurabh Adya

The interest and demand for training deep neural networks have been experiencing rapid growth, spanning a wide range of applications in both academia and industry. However, training them distributed and at scale remains difficult due to the complex ecosystem of tools and hardware involved. One consequence is that the responsibility of orchestrating these com

Tingting Li, Cheng Feng, Chris Hankin

Network diversity has been widely recognized as an effective defense strategy to mitigate the spread of malware. Optimally diversifying network resources can improve the resilience of a network against malware propagation. This work proposes an efficient method to compute such an optimal deployment, in the context of upgrading a legacy Industrial Control Sys

Flaviano Morone, Gino Del Ferraro, Hernán A. Makse

Collapses of dynamical systems into irrecoverable states are observed in ecosystems, human societies, financial systems and network infrastructures. Despite their widespread occurrence and impact, these events remain largely unpredictable. In searching for the causes for collapse and instability, theoretical investigations have so far been unable to determin

Yuichi Togashi

The activity of biological cells is primarily based on chemical reactions and typically modeled as a reaction-diffusion system. Cells are, however, highly crowded with macromolecules, including a variety of molecular machines such as enzymes. The working cycles of these machines are often coupled with their internal motion (conformational changes). In the cr

Nathaniel Harms

We present an algorithm for testing halfspaces over arbitrary, unknown rotation-invariant distributions. Using $\tilde O(\sqrt{n}\epsilon^{-7})$ random examples of an unknown function $f$, the algorithm determines with high probability whether $f$ is of the form $f(x) = sign(\sum_i w_ix_i-t)$ or is $\epsilon$-far from all such functions. This sample size is

Dimitris Bertsimas, Ryan Cory-Wright

The sparse portfolio selection problem is one of the most famous and frequently-studied problems in the optimization and financial economics literatures. In a universe of risky assets, the goal is to construct a portfolio with maximal expected return and minimum variance, subject to an upper bound on the number of positions, linear inequalities and minimum i

K. Buchardt, C. Furrer, M. Steffensen

The idea of forward rates stems from interest rate theory. It has natural connotations to transition rates in multi-state models. The generalization from the forward mortality rate in a survival model to multi-state models is non-trivial and several definitions have been proposed. We establish a theoretical framework for the discussion of forward rates. Furt

Man Hon Yau, C. A. R. Sa de Melo

We discuss the Chern number spectrum of ultra-cold fermions in square optical lattices as a function of artificial magnetic, Zeeman and spin-orbit fields that can be tuned independently. We show the existence of topological quantum phase transitions induced by Zeeman and spin-orbit fields, where the total number and chirality of edge states change for fixed

Daniel Goldfarb

Deep neural networks (DNN) are black box algorithms. They are trained using a gradient descent back propagation technique which trains weights in each layer for the sole goal of minimizing training error. Hence, the resulting weights cannot be directly explained. Using Topological Data Analysis (TDA) we can get an insight on how the neural network is thinkin

Yijun Xiao, Tiancheng Zhao, William Yang Wang

We introduce an improved variational autoencoder (VAE) for text modeling with topic information explicitly modeled as a Dirichlet latent variable. By providing the proposed model topic awareness, it is more superior at reconstructing input texts. Furthermore, due to the inherent interactions between the newly introduced Dirichlet variable and the conventiona

David Shea Vela-Vick, C. -M. Michael Wong

We show that the bordered-sutured Floer invariant of the complement of a tangle in an arbitrary 3-manifold $Y$, with minimal conditions on the bordered-sutured structure, satisfies an unoriented skein exact triangle. This generalizes a theorem by Manolescu for links in $S^3$. We give a theoretical proof of this result by adapting holomorphic polygon counts t

George M. Fuller, Alexander Kusenko, David Radice, Volodymyr Takhistov

Neutron-rich material ejected from neutron star-neutron star (NS-NS) and neutron star-black hole (NS-BH) binary mergers is heated by nuclear processes to temperatures of a few hundred keV, resulting in a population of electron-positron pairs. Some of the positrons escape from the outer layers of the ejecta. We show that the population of low-energy positrons

Yikuan Li, Chun Jiang

In this paper, ultra-broad band optical signal amplification are analyzed and demonstrated by utilizing supercontinuum generation propagating over the photonic crystal fiber. The coupled nonlinear Schroodinger equation containing parametric process and stimulated Raman scattering effect was analyzed and solved to calculate the variation of signal gain with f

Tom Banks, Willy Fischler

We review arguments that the cosmological constant (c.c.) should not be thought of as a local contribution to the energy density, but rather as an infrared boundary condition specifying particular models of quantum gravity.

Yibei Li, Yu Yao, Xiaoming Hu

In this paper, the problem of finite horizon inverse optimal control (IOC) is investigated, where the quadratic cost function of a dynamic process is required to be recovered based on the observation of optimal control sequences. We propose the first complete result of the necessary and sufficient condition for the existence of corresponding LQ cost function

Kavosh Asadi, Evan Cater, Dipendra Misra, Michael L. Littman

When environmental interaction is expensive, model-based reinforcement learning offers a solution by planning ahead and avoiding costly mistakes. Model-based agents typically learn a single-step transition model. In this paper, we propose a multi-step model that predicts the outcome of an action sequence with variable length. We show that this model is easy

Amaru Cuba Gyllensten, Magnus Sahlgren

Sentiment and topic analysis are common methods used for social media monitoring. Essentially, these methods answers questions such as, "what is being talked about, regarding X", and "what do people feel, regarding X". In this paper, we investigate another venue for social media monitoring, namely issue ownership and agenda setting, which are concepts from p

Thais Bardini Idalino, Lucia Moura

Cover-free families are set systems used as solutions for a large variety of problems, and in particular, problems where we deal with $n$ elements and want to identify $d$ invalid ones among them by performing only $t$ tests ($t \leq n$). We are specially interested in cryptographic problems, and we note that some of these problems need cover-free families w

Karl J. Kreder

Blockchains have shown great promise as peer-to-peer digital currency systems over the past 10 years. However, with increased popularity, the demand for processing transactions has also grown leading to increased costs, confirmation times, and limited blockchain utility. There have been a number of proposals on how to scale blockchains, such as Plasma, Polka

Nghia Doan, Seyyed Ali Hashemi, Elie Ngomseu Mambou, Thibaud Tonnellier

Polar codes are the first class of error correcting codes that provably achieve the channel capacity at infinite code length. They were selected for use in the fifth generation of cellular mobile communications (5G). In practical scenarios such as 5G, a cyclic redundancy check (CRC) is concatenated with polar codes to improve their finite length performance.

John E. Herr, Kevin Koh, Kun Yao, John Parkhill

The answers to many unsolved problems lie in the intractable chemical space of molecules and materials. Machine learning techniques are rapidly growing in popularity as a way to compress and explore chemical space efficiently. One of the most important aspects of machine learning techniques is representation through the feature vector, which should contain t

Xiaowei Zhang, Peter W. Glynn

Affine jump-diffusions constitute a large class of continuous-time stochastic models that are particularly popular in finance and economics due to their analytical tractability. Methods for parameter estimation for such processes require ergodicity in order establish consistency and asymptotic normality of the associated estimators. In this paper, we develop

David J. Miller, Xinyi Hu, Zhen Xiang, George Kesidis

Naive Bayes spam filters are highly susceptible to data poisoning attacks. Here, known spam sources/blacklisted IPs exploit the fact that their received emails will be treated as (ground truth) labeled spam examples, and used for classifier training (or re-training). The attacking source thus generates emails that will skew the spam model, potentially result

Yu Sun, Shiqi Xu, Yunzhe Li, Lei Tian

The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser within an iterative algorithm. In this paper, we propose a new online PnP algorithm for Fourier ptychographic microscopy (FPM) based on the fast iterative shrinkage/threshold algorithm

Su Wang, Rahul Gupta, Nancy Chang, Jason Baldridge

Paraphrasing is rooted in semantics. We show the effectiveness of transformers (Vaswani et al. 2017) for paraphrase generation and further improvements by incorporating PropBank labels via a multi-encoder. Evaluating on MSCOCO and WikiAnswers, we find that transformers are fast and effective, and that semantic augmentation for both transformers and LSTMs lea

Yujia Wang, David J. Miller, George Kesidis

This paper addresses detection of a reverse engineering (RE) attack targeting a deep neural network (DNN) image classifier; by querying, RE's aim is to discover the classifier's decision rule. RE can enable test-time evasion attacks, which require knowledge of the classifier. Recently, we proposed a quite effective approach (ADA) to detect test-time evasion

Daniel Sáez Trigueros, Li Meng, Margaret Hartnett

Starting in the seventies, face recognition has become one of the most researched topics in computer vision and biometrics. Traditional methods based on hand-crafted features and traditional machine learning techniques have recently been superseded by deep neural networks trained with very large datasets. In this paper we provide a comprehensive and up-to-da

Kry Yik Chau Lui, Gavin Weiguang Ding, Ruitong Huang, Robert J. McCann

In this paper, we investigate Dimensionality reduction (DR) maps in an information retrieval setting from a quantitative topology point of view. In particular, we show that no DR maps can achieve perfect precision and perfect recall simultaneously. Thus a continuous DR map must have imperfect precision. We further prove an upper bound on the precision of Lip

Matthew de Courcy-Ireland, Michael Magee

For each prime $p$, we study the eigenvalues of a 3-regular graph on roughly $p^2$ vertices constructed from the Markoff surface. We show they asymptotically follow the Kesten-McKay law, which also describes the eigenvalues of a random regular graph. The proof is based on the method of moments and takes advantage of a natural group action on the Markoff surf

Daniel Sáez Trigueros, Li Meng, Margaret Hartnett

In this paper we investigate the feasibility of using synthetic data to augment face datasets. In particular, we propose a novel generative adversarial network (GAN) that can disentangle identity-related attributes from non-identity-related attributes. This is done by training an embedding network that maps discrete identity labels to an identity latent spac

L. C. Suárez-González, G. Quintero Angulo, A. Pérez Martínez, H. Pérez Rojas

We study the thermodynamic properties of a neutral vector boson gas in presence of a constant magnetic field, by means of a semi-classical approach that allows to introduce the spin in the non-relativistic spectrum of the bosons. Bose-Einstein condensation is obtained and it turns out to depend on all the parameters involved in the problem: temperature, part

Geordie George, Angel Lozano, Martin Haenggi

This paper presents analytical expressions for the signal-to-interference ratio (SIR) and the spectral efficiency in macrocellular networks with massive MIMO conjugate beamforming, both with a uniform and a channel-dependent power allocation. These expressions, which apply to very general network geometries, are asymptotic in the strength of the shadowing. T

Vikram Ravi, Abraham Loeb

The possibility of Fast Radio Burst (FRB) emission being suppressed at low frequencies, resulting in a cutoff of the average rest-frame spectrum, has been raised as an explanation for the lack of detections at meter wavelengths. We examine propagation effects that could cause this suppression, and find that a low-frequency spectral cutoff may be generic rega

Adi Pick, Alexander Cerjan, Steven G Johnson

We present an \emph{ab-initio} semi-analytical solution for the noise spectrum of complex-cavity micro-structured lasers, including central Lorentzian peaks at the multimode lasing frequencies and additional sidepeaks due to relaxation-oscillation (RO) dynamics. In~Ref.~1, we computed the central-peak linewidths by solving generalized laser rate equations, w

X. Saad-Olivera, A. Costa de Souza, F. Roig, D. Nesvorny

We perform dynamical fits to the Transit Timing Variations (TTVs) of Kepler-419b. The TTVs from 17 Kepler quarters are obtained from Holczer et al (2016, ApJS 225,9). The dynamical fits are performed using the MultiNest Bayesian inference tool, coupled to an efficient symplectic N-body integrator. We find that the existing TTV data alone are able to uniquely

David T. Frayer, Frank Ghigo, Ronald J. Maddalena

Recent measurements at Q-band (43 GHz) have verified the improved performance of the GBT provided by the updated gravity model that was deployed in the fall of 2014. The measured gain curve is indistinguishable from 1.0 over an elevation range from 15 degrees to 80 degrees. This represents a significant improvement on the previous gain curve from 2009 that s

Samira Samadi, Uthaipon Tantipongpipat, Jamie Morgenstern, Mohit Singh

We investigate whether the standard dimensionality reduction technique of PCA inadvertently produces data representations with different fidelity for two different populations. We show on several real-world data sets, PCA has higher reconstruction error on population A than on B (for example, women versus men or lower- versus higher-educated individuals). Th

Amber Srivastava, Mayank Baranwal, Srinivasa Salapaka

Typically clustering algorithms provide clustering solutions with prespecified number of clusters. The lack of a priori knowledge on the true number of underlying clusters in the dataset makes it important to have a metric to compare the clustering solutions with different number of clusters. This article quantifies a notion of persistence of clustering solu

Mosab Khayat, Arif Ghafoor

Many evaluation methods have been applied to assess the usefulness of visual analytics solutions. These methods are branching from a variety of origins with different assumptions, and goals. We provide a high-level overview of the process employed in each method using the generic evaluation model "GEM" that generalizes the process of usefulness evaluation. T

Piotr M. Hajac, Sarah Reznikoff, Mariusz Tobolski

We define an admissible decomposition of a graph $E$ into subgraphs $F_1$ and $F_2$, and consider the intersection graph $F_1\cap F_2$ as a subgraph of both $F_1$ and $F_2$. We prove that, if the graph $E$ is row finite and its decomposition into the subgraphs $F_1$ and $F_2$ is admissible, then the graph C*-algebra $C^*(E)$ of $E$ is the pullback C*-algebra

Sharon M. McNicholas, Paul D. McNicholas, Daniel A. Ashlock

An evolutionary algorithm (EA) is developed as an alternative to the EM algorithm for parameter estimation in model-based clustering. This EA facilitates a different search of the fitness landscape, i.e., the likelihood surface, utilizing both crossover and mutation. Furthermore, this EA represents an efficient approach to "hard" model-based clustering and s

N. Agafonova, A. Alexandrov, A. Anokhina, S. Aoki

OPERA is a long-baseline experiment designed to search for $\nu_{\mu}\to\nu_{\tau}$ oscillations in appearance mode. It was based at the INFN Gran Sasso laboratory (LNGS) and took data from 2008 to 2012 with the CNGS neutrino beam from CERN. After the discovery of $\nu_\tau$ appearance in 2015, with $5.1\sigma$ significance, the criteria to select $\nu_\tau$

Ankit Aggarwal

In this paper, we revisit the question of identifying Soft Graviton theorem in higher (even) dimensions with Ward identities associated with Asymptotic symmetries. Building on the prior work of \cite{strominger}, we compute, from first principles, the (asymptotic) charge associated to Supertranslation symmetry in higher even dimensions and show that (i) thes

Avik Mondal, Chantal Nguyen, Xiao Ma, Ahmed E. Elbanna

Trabecular bone is a lightweight, compliant material organized as a web of struts and rods (trabeculae) that erode with age and the onset of bone diseases like osteoporosis, leading to increased fracture risk. The traditional diagnostic marker of osteoporosis, bone mineral density (BMD), has been shown in ex vivo experiments to correlate poorly with fracture

Ataollah Mesgarnejad, Chunzhou Pan, Randall M. Erb, Sandra J. Shefelbine

While cracks in isotropic homogeneous materials propagate straight, perpendicularly to the tensile axis, cracks in natural and synthetic composites deflect from a straight path, often increasing the toughness of the material. Here we combine experiments and simulations to identify materials properties that predict whether cracks propagate straight or kink on

Daoming Lyu, Fangkai Yang, Bo Liu, Steven Gustafson

Deep reinforcement learning (DRL) has gained great success by learning directly from high-dimensional sensory inputs, yet is notorious for the lack of interpretability. Interpretability of the subtasks is critical in hierarchical decision-making as it increases the transparency of black-box-style DRL approach and helps the RL practitioners to understand the

Patricio Gallardo, Jesus Martinez-Garcia, Cristiano Spotti

The 'moduli continuity method' permits an explicit algebraisation of the Gromov-Hausdorff compactification of K\"ahler-Einstein metrics on Fano manifolds in some fundamental examples. In this paper, we apply such method in the 'log setting' to describe explicitly some compact moduli spaces of K-polystable log Fano pairs. We focus on situations when the angle

Piotr Kot, Jonathan Parnell, Sina Habibian, Carola Straßer

We study the band dispersion of graphene with randomly distributed structural defects using two complementary methods, exact diagonalization of the tight-binding Hamiltonian and implementing a self-consistent T matrix approximation. We identify three distinct types of impurities resulting in qualitatively different spectra in the vicinity of the Dirac point.

Dennis Sullivan

Using the combinatorics of two interpenetrating face centered cubic lattices together with the part of calculus naturally encoded in combinatorial topology, we construct from first principles a lattice model of 3D incompressible hydrodynamics on triply periodic three space. Actually the construction applies to every dimension, but has special duality feature

T. D. Russell, N. Degenaar, R. Wijnands, J. van den Eijnden

IGR J17591$-$2342 is a 527-Hz accreting millisecond X-ray pulsar that was discovered in outburst in 2018 August. In this paper, we present quasi-simultaneous radio and X-ray monitoring of this source during the early part of the outburst. IGR J17591$-$2342 is highly absorbed in X-rays, with an equivalent hydrogen absorption along the line of sight, $N_{\rm H

Alp Bassa, Peter Beelen

We study a family $\psi^{\lambda}$ of $\mathbb F_q[T]$-Drinfeld modules, which is a natural analog of Legendre elliptic curves. We then find a surprising recurrence giving the corresponding Deuring polynomial $H_{p(T)}(\lambda)$ characterising supersingular Legendre Drinfeld modules $\psi^{\lambda}$ in characteristic $p(T)$.

Francescantonio Oliva

We prove existence of solutions to problems whose model is $$\begin{cases} \displaystyle -\Delta_p u + u^q = \frac{f}{u^\gamma} & \text{in}\ \Omega, \newline u\ge0 &\text{in}\ \Omega,\newline u=0 &\text{on}\ \partial\Omega, \end{cases}$$ where $\Omega$ is an open bounded subset of $\mathbb{R}^N$ ($N\ge2$), $\Delta_p u$ is the $p$-laplacian operator for $1\le

Bridget Eileen Tenner

We consider polygonal tilings of certain regions and use these to give intuitive definitions of tiling-based perimeter and area. We apply these definitions to rhombic tilings of Elnitsky polygons, computing sharp bounds and average values for perimeter tiles in convex centrally symmetric 2n-gons. These bounds and values have implications for the combinatoric

M. Baker, Paolo Cea, Volodymyr Chelnokov, Leonardo Cosmai

We report on the chromoelectric and chromomagnetic fields generated by a static quark-antiquark pair at zero temperature in pure gauge SU(3). From the spatial structure of chromoelectric field we extract its nonperturbative part and discuss its properties.

Jiaming Chen, Ali Valehi, Abolfazl Razi

An important paradigm in smart health is developing diagnosis tools and monitoring a patient's heart activity through processing Electrocardiogram (ECG) signals is a key example, sue to high mortality rate of heart-related disease. However, current heart monitoring devices suffer from two important drawbacks: i) failure in capturing inter-patient variability

Nikolaos Dionelis

This report focuses on algorithms that perform single-channel speech enhancement. The author of this report uses modulation-domain Kalman filtering algorithms for speech enhancement, i.e. noise suppression and dereverberation, in [1], [2], [3], [4] and [5]. Modulation-domain Kalman filtering can be applied for both noise and late reverberation suppression an

John D. Treado, Zhe Mei, Lynne Regan, Corey S. O'Hern

Dense packing of hydrophobic residues in the cores of globular proteins determines their stability. Recently, we have shown that protein cores possess packing fraction $\phi \approx 0.56$, which is the same as dense, random packing of amino acid-shaped particles. In this article, we compare the structural properties of protein cores and jammed packings of am

Erhan Bayraktar, Jakša Cvitanić, Yuchong Zhang

We consider a stochastic tournament game in which each player is rewarded based on her rank in terms of the completion time of her own task and is subject to cost of effort. When players are homogeneous and the rewards are purely rank dependent, the equilibrium has a surprisingly explicit characterization, which allows us to conduct comparative statics and o

Anthony Bagnall, Hoang Anh Dau, Jason Lines, Michael Flynn

In 2002, the UCR time series classification archive was first released with sixteen datasets. It gradually expanded, until 2015 when it increased in size from 45 datasets to 85 datasets. In October 2018 more datasets were added, bringing the total to 128. The new archive contains a wide range of problems, including variable length series, but it still only c

Negin Alemazkoor, Hadi Meidani

Connected vehicles disseminate detailed data, including their position and speed, at a very high frequency. Such data can be used for accurate real-time analysis, prediction and control of transportation systems. The outstanding challenge for such analysis is how to continuously collect and process extremely large volumes of data. To address this challenge,

Prashnna K Gyawali, Cameron Knight, Sandesh Ghimire, B. Milan Horacek

While deep representation learning has become increasingly capable of separating task-relevant representations from other confounding factors in the data, two significant challenges remain. First, there is often an unknown and potentially infinite number of confounding factors coinciding in the data. Second, not all of these factors are readily observable. I

Zdeněk Stuchlík, Daniel Charbulák, Jan Schee

We construct the light escape cones of isotropic spot sources of radiation residing in special classes of reference frames in the Kerr-de Sitter (KdS) black hole spacetimes, namely, in the fundamental class of 'non-geodesic' locally non-rotating reference frames (LNRFs), and two classes of 'geodesic' frames, the radial geodesic frames (RGFs), both falling an

S. Guddala, R. Bushati, M. Li, A. B. Khanikaev

Recent advances in condensed matter physics have shown that the valley degree of freedom of electrons in 2D materials with hexagonal symmetry, such as graphene, h-BN, and TMDs, can be efficiently exploited, leading to the emergent field of valleytronics, which offers unique opportunities for efficient data transfer, computing and storage. The ability to coup

Yifeng Tao, Bruno Godefroy, Guillaume Genthial, Christopher Potts

Crucial information about the practice of healthcare is recorded only in free-form text, which creates an enormous opportunity for high-impact NLP. However, annotated healthcare datasets tend to be small and expensive to obtain, which raises the question of how to make maximally efficient uses of the available data. To this end, we develop an LSTM-CRF model

Nicola Guglielmi, Valeria Simoncini

Given a matrix $A\in \R^{n\times n}$ and a tall rectangular matrix $B \in \R^{n\times q}$, $q < n$, we consider the problem of making the pair $(A,B)$ dissipative, that is the determination of a {\it feedback} matrix $K \in \R^{q\times n}$ such that the field of values of $A-B K$ lies in the left half open complex plane. We review and expand classical result

Manuel Servin, Moises Padilla, Guillermo Garnica, Gonzalo Paez

Here we show how to design phase-shifting algorithms (PSAs) for nonuniform phase-shifted fringe patterns using their frequency transfer function (FTF). Assuming that the nonuniform/nonlinear (NL) phase-steps are known, we introduce the desired zeroes in the FTF to obtain the specific NL-PSA formula. The advantage of designing NL-PSAs based on their FTF is th

Elaheh Bakhshaei, Alessandro Bombini

We construct a new family of three-charge $\frac{1}{8}-$BPS smooth solutions that have the same charges as the supersymmetric D1D5P Black Hole and are non-invariant under rotations of the compact manifold. We work in type IIB string theory on $T^4$ and we show how the supergravity and BPS equations reduce to a linear system, arranged in two `layers' of parti

Nina Poerner, Masoud Jalili Sabet, Benjamin Roth, Hinrich Schütze

Count-based word alignment methods, such as the IBM models or fast-align, struggle on very small parallel corpora. We therefore present an alternative approach based on cross-lingual word embeddings (CLWEs), which are trained on purely monolingual data. Our main contribution is an unsupervised objective to adapt CLWEs to parallel corpora. In experiments on b

Tousif Islam

Eventual flattening of velocity dispersion profiles of some galactic globular clusters in the Milky Way cannot be explained in the framework of Newtonian gravity and hence in general theory of relativity in the weak field limit, without resorting to the occurrence of tidal effects. We explore the possibility of explaining such deviation from expected Kepleri

Estelle Basor, Pavel Bleher, Robert Buckingham, Tamara Grava

We establish a representation of the joint moments of the characteristic polynomial of a CUE random matrix and its derivative in terms of a solution of the sigma-Painleve V equation. The derivation involves the analysis of a formula for the joint moments in terms of a determinant of generalised Laguerre polynomials using the Riemann-Hilbert method. We use th

Stefano Andriolo, Gary Shiu, Hagen Triendl, Thomas Van Riet

We construct novel classes of compact G2 spaces from lifting type IIA flux backgrounds with O6 planes. There exists an extension of IIA Calabi-Yau orientifolds for which some of the D6 branes (required to solve the RR tadpole) are dissolved in $F_2$ fluxes. The backreaction of these fluxes deforms the Calabi-Yau manifold into a specific class of SU(3)-struct

Niek Tax, Irene Teinemaa, Sebastiaan J. van Zelst

Data of sequential nature arise in many application domains in forms of, e.g. textual data, DNA sequences, and software execution traces. Different research disciplines have developed methods to learn sequence models from such datasets: (i) in the machine learning field methods such as (hidden) Markov models and recurrent neural networks have been developed

Praveen K. Bommineni, Nydia Roxana Varela-Rosales, Marco Klement, Michael Engel

Colloids are rarely perfectly uniform but follow a distribution of sizes, shapes, and charges. This dispersity can be inherent (static) or develop and change over time (dynamic). Despite a long history of research, the conditions under which non-uniform particles crystallize and which crystal forms is still not well understood. Here, we demonstrate that hard

Lukas Fleischer, Trevor Jack

We investigate the computational complexity for determining various properties of a finite transformation semigroup given by generators. We introduce a simple framework to describe transformation semigroup properties that are decidable in $\mathsf{AC^0}$. This framework is then used to show that the problems of deciding whether a transformation semigroup is

Daniela Rolf, Christian Lotze, Constantin Czekelius, Benjamin W. Heinrich

The magnetic properties of metal-organic complexes are strongly influenced by conformational changes in the ligand. The flexibility of Fe-tetra-pyridyl-porphyrin molecules leads to different adsorption configurations on a Au(111) surface. By combining low-temperature scanning tunneling spectroscopy and atomic force microscopy, we resolve a correlation of the

Simon Portegies Zwart

We analyze the position of the two populations of blue stragglers in the globular cluster M30 in the Hertzsprung-Russell diagram. Both populations of blue stragglers are brighter than the cluster's turn-off, but one population (the blue blue-stragglers) align along the zero-age main-sequence whereas the (red) population is elevated in brightness (or colour)