April 2020 arXiv papers — page 50

Benjamin Nguyen-Van-Yen, Pierre Del Moral, Bernard Cazelles

We present a new Bayesian inference method for compartmental models that takes into account the intrinsic stochasticity of the process. We show how to formulate a SIR-type Markov jump process as the solution of a stochastic differential equation with respect to a Poisson Random Measure (PRM), and how to simulate the process trajectory deterministically from

Grant Olney Passmore, Simon Cruanes, Denis Ignatovich, Dave Aitken

We describe Imandra, a modern computational logic theorem prover designed to bridge the gap between decision procedures such as SMT, semi-automatic inductive provers of the Boyer-Moore family like ACL2, and interactive proof assistants for typed higher-order logics. Imandra's logic is computational, based on a pure subset of OCaml in which all functions are

Dmitry Beliaev, Atul Shekhar, Vlad Margarint

We consider a family of Bessel Processes that depend on the starting point $x$ and dimension $\delta$, but are driven by the same Brownian motion. Our main result is that almost surely the first time a process hits $0$ is jointly continuous in $x$ and $\delta$, provided $\delta\le 0$. As an application, we show that the SLE($\kappa$) welding homeomorphism is

Eugenio Giannelli, Noelia Rizo, Benjamin Sambale, A. A. Schaeffer Fry

Let p be a prime larger than 3 and let G be a finite group. We prove that G is p-solvable of p-length at most 2 if there are at most two distinct character degrees relatively prime to p in the principal p-block of G. This generalizes a theorem of Isaacs-Smith, as well as a recent result of three of the present authors.

Hamza Boumaza, David Langlois, Karim Noui

We study the late cosmological evolution, from the nonrelativistic matter dominated era to the dark energy era, in modified gravity models described by Degenerate Higher-Order Scalar-Tensor (DHOST) theories. They represent the most general scalar-tensor theories propagating a single scalar degree of freedom and include Horndeski and Beyond Horndeski theories

Gh. Sadeghi, M. S. Moslehian, A. Talebi

We employ some techniques involving projections in a von Neumann algebra to establish some maximal inequalities such as the strong and weak symmetrization, Levy, Levy-Skorohod, and Ottaviani inequalities in the realm of the quantum probability spaces.

Shiyang Yan, Yang Hua, Neil Robertson

Image description generation plays an important role in many real-world applications, such as image retrieval, automatic navigation, and disabled people support. A well-developed task of image description generation is image captioning, which usually generates a short captioning sentence and thus neglects many of fine-grained properties, e.g., the informatio

Daniel Gribel, Thibaut Vidal, Michel Gendreau

Stochastic block models (SBMs) are often used to find assortative community structures in networks, such that the probability of connections within communities is higher than in between communities. However, classic SBMs are not limited to assortative structures. In this study, we discuss the implications of this model-inherent indifference towards assortati

C. W. Fink, S. L. Watkins, T. Aramaki, P. L. Brink

In this letter, we present the performance of a $100~\mu\mathrm{m}\times 400~\mu\mathrm{m} \times 40~\mathrm{nm}$ tungsten (W) Transition-Edge Sensor (TES) with a critical temperature of 40 mK. This device has a measured noise equivalent power (NEP) of $1.5\times 10^{-18}\ \mathrm{W}/\sqrt{\mathrm{Hz}}$, in a bandwidth of $2.6$ kHz, indicating a resolution f

A. Sozza, M. Cencini, F. De Lillo, G. Boffetta

We investigate the effects of turbulent fluctuations on the Lagrangian statistics of absorption of a scalar field by tracer particles, as a model for nutrient uptake by suspended non-motile microorganisms. By means of extensive direct numerical simulations of an Eulerian-Lagrangian model we quantify, in terms of the Sherwood number, the increase of the scala

Yonatan Woodbridge, Gal Elidan, Ami Wiesel

Quantifying uncertainty in predictions or, more generally, estimating the posterior conditional distribution, is a core challenge in machine learning and statistics. We introduce Convex Nonparanormal Regression (CNR), a conditional nonparanormal approach for coping with this task. CNR involves a convex optimization of a posterior defined via a rich dictionar

David Gepner, Lennart Meier

Following ideas of Lurie, we give in this article a general construction of equivariant elliptic cohomology without restriction to characteristic zero. Specializing to the universal elliptic curve we obtain in particular equivariant spectra of topological modular forms. We compute the fixed points of these spectra for the circle group and more generally for

Juan Ignacio Musmarra, Mauricio Bellini

We study the emission of large-scales wavelength space-time waves during the inflationary expansion of the universe, produced by back-reaction effects. As an example, we study an inflationary model with variable time scale, where the scale factor of the universe grows as a power of time. The coarse-grained field to describe space-time waves is defined by usi

Eugen Solowjow, Ines Ugalde, Yash Shahapurkar, Juan Aparicio

Universal grasping of a diverse range of previously unseen objects from heaps is a grand challenge in e-commerce order fulfillment, manufacturing, and home service robotics. Recently, deep learning based grasping approaches have demonstrated results that make them increasingly interesting for industrial deployments. This paper explores the problem from an au

Mainuddin Ahmad Jonas, David Evans

Deep Neural Networks (DNNs) are often vulnerable to adversarial examples.Several proposed defenses deploy an ensemble of models with the hope that, although the individual models may be vulnerable, an adversary will not be able to find an adversarial example that succeeds against the ensemble. Depending on how the ensemble is used, an attacker may need to fi

V. A. Lebedev

The paper focuses on two issues important for design and operation of bunch-by-bunch transverse damper in a very large hadron collider, where fast damping is required to suppress beam instabilities and noise induced emittance growth. The first issue is associated with kick variation along a bunch which affects the damping of head-tail modes. The second issue

Leandro R. Costa, Daniel Aloise, Luca G. Gianoli, Andrea Lodi

The popularity of drones is rapidly increasing across the different sectors of the economy. Aerial capabilities and relatively low costs make drones the perfect solution to improve the efficiency of those operations that are typically carried out by humans (e.g., building inspection, photo collection). The potential of drone applications can be pushed even f

Nathan A. Wagner, Brett D. Wick

We prove the weighted $L^p$ regularity of the ordinary Bergman and Cauchy-Szeg\H{o} projections on strongly pseudoconvex domains $D$ in $\mathbb{C}^n$ with near minimal smoothness for appropriate generalizations of the $B_p/A_p$ classes. In particular, the $B_p/A_p$ Muckenhoupt type condition is expressed relative to balls in a quasi-metric that arises as a

Larissa C. Shimomura, George Fletcher, Nikolay Yakovets

We propose Graph Generating Dependencies (GGDs), a new class of dependencies for property graphs. Extending the expressivity of state of the art constraint languages, GGDs can express both tuple- and equality-generating dependencies on property graphs, both of which find broad application in graph data management. We provide the formal definition of GGDs, an

Shakeel Raja

In this paper we introduce a novel feature augmentation approach for generating structured musical compositions comprising melodies and harmonies. The proposed method augments a connectionist generation model with count-down to song conclusion and meter markers as extra input features to study whether neural networks can learn to produce more aesthetically p

Yasitha Warahena Liyanage, Daphney-Stavroula Zois, Charalampos Chelmis

Joint feature selection and classification in an online setting is essential for time-sensitive decision making. However, most existing methods treat this coupled problem independently. Specifically, online feature selection methods can handle either streaming features or data instances offline to produce a fixed set of features for classification, while onl

Catalina Sobrino Figaredo, Martin Haas, Michael Ramolla, Rolf Chini

We monitored the z=0.158 quasar 3C273 between 2015 and 2019 in the optical (BVrz) and near-infrared (JHK) with the aim to perform dust reverberation mapping. Accounting for host galaxy and accretion disk contributions, we obtained pure dust light curves in JHK. Cross correlations between the V-band and the dust light curves yield an average rest-frame delay

Michel Adès, Matthieu Dufour, Serge B. Provost, Marie-Claude Vachon

The main objective of this paper consists in creating a new class of copulae from various joint distributions occurring in connection with certain Brownian motion processes. We focus our attention on the distributions of univariate Brownian motions having a drift parameter and their maxima and on correlated bivariate Brownian motions by considering the maxim

Anton Ryabtsev

In this paper, we consider the conjugate gradient method for solving the problem of minimizing a quadratic function with additive noise in the gradient. Three concepts of noise were considered: antagonistic noise in the linear term, stochastic noise in the linear term, and noise in the quadratic term, as well as combinations of the first and second with the

Tianchen Qian, Michael A. Russell, Linda M. Collins, Predrag Klasnja

Although there is much excitement surrounding the use of mobile and wearable technology for the purposes of delivering interventions as people go through their day-to-day lives, data analysis methods for constructing and optimizing digital interventions lag behind. Here, we elucidate data analysis methods for primary and secondary analyses of micro-randomize

Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang

Deep learning based forecasting methods have become the methods of choice in many applications of time series prediction or forecasting often outperforming other approaches. Consequently, over the last years, these methods are now ubiquitous in large-scale industrial forecasting applications and have consistently ranked among the best entries in forecasting

David Burghoff

Multiheterodyne techniques using frequency combs -- light sources whose lines are perfectly evenly-spaced -- have revolutionized optical science. By beating an unknown signal with the many lines of a comb, its spectrum is recovered. However, these techniques have been restricted to measuring coherent sources, such as lasers. In this work, we demonstrate a ne

Caterina Balzotti, Mirko D'Ovidio, Paola Loreti

In this paper we consider the fractional SIS epidemic model ($\alpha$-SIS model) in the case of constant population size. We provide a representation of the explicit solution to the fractional model and we illustrate the results by numerical schemes. A comparison with the limit case when the fractional order $\alpha \uparrow 1$ (the SIS model) is also given.

Edward B. Jenkins, Cecile Gry

We measured 304 absorption features in the ultraviolet and visible spectra of the star 51 Oph, which is known to have a debris disk with a high inclination. We analyzed the relative populations of atoms in excited fine-structure and metastable levels that are maintained by optical pumping and collisional excitation by electrons, and we found that most of the

Jason McCullough, Alexandra Seceleanu

Let $k$ be a field of characteristic $0$. Using the method of idealization, we show that there is a non-Koszul, quadratic, Artinian, Gorenstein, standard graded $k$-algebra of regularity $3$ and codimension $8$, answering a question of Mastroeni, Schenck, and Stillman. We also show that this example is minimal in the sense that no other idealization that is

Urs Gasser, Marcello Ienca, James Scheibner, Joanna Sleigh

Data collection and processing via digital public health technologies are being promoted worldwide by governments and private companies as strategic remedies for mitigating the COVID-19 pandemic and loosening lockdown measures. However, the ethical and legal boundaries of deploying digital tools for disease surveillance and control purposes are unclear, and

Michael Scheutzow, Juni Schindler

Consider a discrete time Markov chain with rather general state space which has an invariant probability measure $\mu$. There are several sufficient conditions in the literature which guarantee convergence of all or $\mu$-almost all transition probabilities to $\mu$ in the total variation (TV) metric: irreducibility plus aperiodicity, equivalence properties

Hirofumi Inaguma, Shun Kiyono, Kevin Duh, Shigeki Karita

We present ESPnet-ST, which is designed for the quick development of speech-to-speech translation systems in a single framework. ESPnet-ST is a new project inside end-to-end speech processing toolkit, ESPnet, which integrates or newly implements automatic speech recognition, machine translation, and text-to-speech functions for speech translation. We provide

Ognjen Perišić

We report the results of our study of approved drugs as potential treatments for COVID 19, based on the application of various bioinformatics predictive methods. The drugs studied include chloroquine, ivermectin, remdesivir, sofosbuvir, boceprevir, and {\alpha}-difluoromethylornithine (DMFO). Our results indicate that these small molecules selectively bind t

Visweswara Sai Prashanth Dintyala, Arpit Narechania, Joy Arulraj

The emergence of database-as-a-service platforms has made deploying database applications easier than before. Now, developers can quickly create scalable applications. However, designing performant, maintainable, and accurate applications is challenging. Developers may unknowingly introduce anti-patterns in the application's SQL statements. These anti-patter

Wenjia Wang, Yi-Hui Zhou

Classical canonical correlation analysis (CCA) requires matrices to be low dimensional, i.e. the number of features cannot exceed the sample size. Recent developments in CCA have mainly focused on the high-dimensional setting, where the number of features in both matrices under analysis greatly exceeds the sample size. These approaches impose penalties in th

S. T. Linden, E. J. Murphy, D. Dong, E. Momjian

We present 3, 15, and 33 GHz imaging towards galaxy nuclei and extranuclear star-forming regions using the Karl G. Jansky Very Large Array as part of the Star Formation in Radio Survey. With $3-33$ GHz radio spectra, we measured the spectral indices and corresponding thermal (free-free) emission fractions for a sample of 335 discrete regions having significa

Alessandro Casalino, Lorenzo Sebastiani

In this paper we study the perturbation theory of the recently proposed Regularized Lovelock Gravity, on the curved FLRW space-time. We provide the first order perturbation equations both in the scalar and tensor sector in the presence of an additional minimally coupled scalar field. A general expression for the velocity of gravitational waves at the generic

Tongyang Xu

This work investigates the possibility of using non-orthogonal multi-carrier waveforms to defend against eavesdropping attacks. The sophisticated detection required for non-orthogonal signals provides a natural defence mechanism in secure communications. However, brute-force tactics such as maximum likelihood detection would break the defence by attempting a

Marco Bonatto, Alissa S. Crans, Timur Nasybullov, Glen T. Whitney

We introduce the notion of an orbit series in a quandle. Using this notion we define four families of quandles based on finiteness conditions on their orbit series. Intuitively, the classes tOS and tOSn correspond to finitary compositions of trivial quandles while the classes OS and OSn correspond to finitary compositions of connected quandles. We study prop

Shashwat Shivam, Yorai Wardi, Magnus Egerstedt, Aris Kanellopoulos

This paper concerns an application of a recently-developed nonlinear tracking technique to trajectory control of autonomous vehicles at traffic intersections. The technique uses a flow version of the Newton-Raphson method for controlling a predicted system-output to a future reference target. Its implementations are based on numerical solutions of ordinary d

Long Chen, Hanjia Lyu, Tongyu Yang, Yu Wang

During the COVID-19 pandemic, "Chinese Virus" emerged as a controversial term for coronavirus. To some, it may seem like a neutral term referring to the physical origin of the virus. To many others, however, the term is in fact attaching ethnicity to the virus. While both arguments appear reasonable, quantitative analysis of the term's real-world usage is la

Thiago Pinguello de Andrade, Ademir Pastor

This paper establishes suficient conditions for the orbital stability of one-parameter spatially periodic traveling-wave solutions for one-dimensional dispersive equations. Our method of proof combines known techniques with some new ideas. As a consequence of our result, we give several applications for well known dispersive equations. Extension of the theor

Andrius Tamosiunas, Hans A. Winther, Kazuya Koyama, David J. Bacon

Generative adversarial networks (GANs) have been recently applied as a novel emulation technique for large scale structure simulations. Recent results show that GANs can be used as a fast, efficient and computationally cheap emulator for producing novel weak lensing convergence maps as well as cosmic web data in 2-D and 3-D. However, like any algorithm, the

Daniele Gregoris, Yen Chin Ong, Bin Wang

Our Universe has an arrow of time. In accordance with the second law of thermodynamics, entropy has been increasing ever since the Big Bang. The fact that matter is in thermal equilibrium in the very early Universe, as indicated by the cosmic microwave background, has led to the idea that gravitational entropy must be very low in the beginning. Penrose propo

Benjamin Billot, Eleanor D. Robinson, Adrian V. Dalca, Juan Eugenio Iglesias

Partial voluming (PV) is arguably the last crucial unsolved problem in Bayesian segmentation of brain MRI with probabilistic atlases. PV occurs when voxels contain multiple tissue classes, giving rise to image intensities that may not be representative of any one of the underlying classes. PV is particularly problematic for segmentation when there is a large

Andriy Mulyar, Bridget T. McInnes

Clinical notes contain an abundance of important but not-readily accessible information about patients. Systems to automatically extract this information rely on large amounts of training data for which their exists limited resources to create. Furthermore, they are developed dis-jointly; meaning that no information can be shared amongst task-specific system

Gemma De las Cuevas, Andreas Klingler, Tim Netzer

It is well-known that tensor decompositions show separations, that is, that constraints on local terms (such as positivity) may entail an arbitrarily high cost in their representation. Here we show that many of these separations disappear in the approximate case. Specifically, for every approximation error $\varepsilon$ and norm, we define the approximate ra

Christine O'Donnell, Edward E. Prather, Peter Behroozi

General-education college astronomy courses offer instructors both a unique audience and a unique challenge. For many students, such a course may be their first time encountering a standalone astronomy class, and it is also likely one of the last science courses they will take. Thus, in a single semester, primary course goals often include both imparting kno

David Dentelski, Vladyslav Kozii, Jonathan Ruhman

Unconventional superconductivity has been discovered in a variety of doped materials, including topological insulators, semimetals and twisted bilayers. A unifying property of these systems is strong orbital hybridization, which involves pairing of states with non-trivial Bloch wave functions. In contrast to naive expectation, many of these superconductors a

George Georgiou, Konstantinos Sfetsos, Konstantinos Siampos

We continue our study of $\lambda$-deformed $\sigma$-models by setting up a $1/k$ perturbative expansion around the free field point for cosets, in particular for the $\lambda$-deformed $SU(2)/U(1)$ coset CFT. We construct an interacting field theory in which all deformation effects are manifestly encoded in the interaction vertices. Using this we reproduce

P. B. Aneesh, Sumanta Chakraborty, Sk Jahanur Hoque, Amitabh Virmani

In the last few years, there has been significant interest in understanding the stationary comparison version of the first law of black hole mechanics in the vielbein formulation of gravity. Several authors have pointed out that to discuss the first law in the vielbein formulation one must extend the Iyer-Wald Noether charge formalism appropriately. Jacobson

Biman B Nath, Pushpita Das, M. S. Oey

We consider the size distribution of superbubbles in a star forming galaxy. Previous studies have tried to explain the distribution by using adiabatic self-similar evolution of wind driven bubbles, assuming that bubbles stall when pressure equilibrium is reached. We show, with the help of hydrodynamical numerical simulations, that this assumption is not vali

B. A. Cook, Charlie Conroy, Pieter van Dokkum

We present spatially-resolved measurements of star formation histories (SFHs), metallicities, and distances in three nearby elliptical galaxies and the bulge of M31 derived using the pixel color-magnitude diagram (pCMD) technique. We compute pCMDs from archival $\textit{HST}$ photometry of M87, M49, NGC 3377 and M31, and fit the data using the new code $\tex

Xizhi Han, Sean A. Hartnoll, Jorrit Kruthoff

Large $N$ matrix quantum mechanics is central to holographic duality but not solvable in the most interesting cases. We show that the spectrum and simple expectation values in these theories can be obtained numerically via a `bootstrap' methodology. In this approach, operator expectation values are related by symmetries -- such as time translation and $SU(N)

Giuseppe Ortolano, Elena Losero, Ivano Ruo Berchera, Stefano Pirandola

The final goal of quantum hypothesis testing is to achieve quantum advantage over all possible classical strategies. In the protocol of quantum reading this advantage is achieved for information retrieval from an optical memory, whose generic cell stores a bit of information in two possible lossy channels. For this protocol, we show, theoretically and experi

Davide Lazzati, Riccardo Ciolfi, Rosalba Perna

GRB 170817A was a subluminous short gamma-ray burst detected about 1.74 s after the gravitational wave signal GW170817 from a binary neutron star (BNS) merger. It is now understood as an off-axis event powered by the cocoon of a relativistic jet pointing 15 to 30 degrees away from the direction of observation. The cocoon was energized by the interaction of t

Christopher Cain, Anson D'Aloisio, Vid Iršič, Matthew McQuinn

We examine the impact of baryon-dark matter relative velocities on intergalactic small-scale structure and the 21 cm signal during reionization. Streaming velocities reduced clumping in the intergalactic medium (IGM) on mass scales of $\sim 10^4 - 10^8$ M$_{\odot}$. This effect produced a distinct baryon acoustic oscillation (BAO) feature in the 21 cm power

Syuhei Iguro, Ryoutaro Watanabe

We investigate the semi-leptonic decays of $\bar B \to D^{(*)} \ell\bar\nu$ in terms of the Heavy-Quark-Effective-Theory (HQET) parameterization for the form factors, which is described with the heavy quark expansion up to $\mathcal O(1/m_c^2)$ beyond the simple approximation considered in the original CLN parameterization. An analysis with this setup was fi

W. L. Kimmy Wu, Pavel Motloch, Wayne Hu, Marco Raveri

We apply a tension metric $Q_\textrm{UDM}$, the update difference in mean parameters, to understand the source of the difference in the measured Hubble constant $H_0$ inferred with cosmic microwave background lensing measurements from the Planck satellite ($H_0=67.9^{+1.1}_{-1.3}\, \mathrm{km/s/Mpc}$) and from the South Pole Telescope ($H_0=72.0^{+2.1}_{-2.5

Dillon Brout, Daniel Scolnic

The use of Type Ia Supernovae (SNe Ia) as cosmological tools has motivated significant effort to: understand what drives the intrinsic scatter of SN Ia distance modulus residuals after standardization, characterize the distribution of SN Ia colors, and explain why properties of the host galaxies of the SNe correlate with SN Ia distance modulus residuals. We

Bin Liu, Dong Lai

We study the dynamics of merging compact binaries near a rotating supermassive black hole (SMBH) in a hierarchical triple configuration. We include various general relativistic effects that couple the inner orbit, the outer orbit and the spin of the SMBH. During the orbital decay due to gravitational radiation, the inner binary can encounter an "apsidal prec

Dominik A. Riechers, Jacqueline A. Hodge, Riccardo Pavesi, Emanuele Daddi

We report the detection of CO($J$=2$\to$1) emission from three massive dusty starburst galaxies at $z$$>$5 through molecular line scans in the NSF's Karl G. Jansky Very Large Array (VLA) CO Luminosity Density at High Redshift (COLDz) survey. Redshifts for two of the sources, HDF 850.1 ($z$=5.183) and AzTEC-3 ($z$=5.298), were previously known. We revise a pr

David Montenegro, Giorgio Torrieri

We use linear response techniques to develop the previously proposed relativistic ideal fluid limit with a non-negligible spin density. We confirm previous results and obtain expressions for the microscopic transport coefficients using Kubo-like formulae and buld up the effective field theory from the computed correlation functions. We also confirm that pola

A. A. Ardentov, L. V. Lokutsievskiy, Yu. L. Sachkov

We consider a series of optimal control problems with 2-dimensional control lying in an arbitrary convex compact set $\Omega$. The considered problems are well studied for the case when $\Omega$ is a unit disc, but barely studied for arbitrary $\Omega$. We derive extremals to these problems in general case by using machinery of convex trigonometry, which all

Denis Wittor, Franco Vazza, Dongsu Ryu, Hyesung Kang

Observations of large-scale radio emissions prove the existence of shock accelerated cosmic-ray electrons in galaxy clusters, while the lack of detected $\gamma$-rays limits the acceleration of cosmic-ray protons in galaxy clusters. This challenges our understanding of how diffusive shock acceleration works. In this work, we couple the most updated recipes f

Matthew Kahle, Francisco Martinez-Figueroa, Alexander Soifer

Suppose that $n \ge 2$, and we wish to plant $k$ different types of trees in the squares of an $n \times n$ square grid. We can have as many of each type as we want. The only rule is that every pair of types must occur in an adjacent pair of squares somewhere in the grid. The question is: given $n$, what is the largest that $k$ can be? Denote this number by

Ville Vakkuri, Kai-Kristian Kemell

As Artificial Intelligence (AI) systems exert a growing influence on society, real-life incidents begin to underline the importance of AI Ethics. Though calls for more ethical AI systems have been voiced by scholars and the general public alike, few empirical studies on the topic exist. Similarly, few tools and methods designed for implementing AI ethics int

Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine

One of the great promises of robot learning systems is that they will be able to learn from their mistakes and continuously adapt to ever-changing environments. Despite this potential, most of the robot learning systems today are deployed as a fixed policy and they are not being adapted after their deployment. Can we efficiently adapt previously learned beha

Andrew V. Sutherland

We describe the practical implementation of an average polynomial-time algorithm for counting points on superelliptic curves defined over $\mathbb Q$ that is substantially faster than previous approaches. Our algorithm takes as input a superelliptic curves $y^m=f(x)$ with $m\ge 2$ and $f\in \mathbb Z[x]$ any squarefree polynomial of degree $d\ge 3$, along wi

Arturo J. Nic May, Eric J. Avila Vales

In this his paper, we studied the global dynamics of a two-strain flu model with a single-strain vaccine and general incidence rate. Four equilibrium points were obtained and the global dynamics of the model are completely determined via suitable lyapunov functions. We illustrate our results by some numerical simulations.

Iddo Ben-Ari, Hugo Panzo, Philip Speegle, R. Oliver VandenBerg

We consider the discrete-time voter model on complete bipartite graphs and study the quasi-stationary distribution (QSD) for the model as the size of one of the partitions tends to infinity while the other partition remains fixed. We show that the QSDs converge weakly to a nontrivial limit which features a consensus with the exception of a random number of d

Kajal Das

In this article, we prove that if two warped cones corresponding to two finitely generated groups with free, isometric, measure-preserving, actions on two compact metric spaces with probability measures are level-wise quasi-isometric (with some extra natural assumptions), then the corresponding groups are uniformly measured equivalent (UME). It was earlier k

Radek Machulka, Jan Perina, Ondrej Haderka, Alessia Allevi

Strong correlations between the signal and idler beams imprinted during their generation dominantly determine the properties of twin beams. They are also responsible for the waves in intensity coherence observed in the wave-vector space of a twin beam propagating in a nonlinear crystal in the regime with pump depletion. These waves start to develop at certai

Daniel Peralta-Salas, Radu Slobodeanu

We present new explicit tight and overtwisted contact structures on the (round) 3-sphere and the (flat) 3-torus for which the ambient metric is weakly compatible. Our proofs are based on the construction of nonvanishing curl eigenfields using suitable families of Jacobi or trigonometric polynomials. As a consequence, we show that the contact sphere theorem o

Leonard Göke

Averting the impending harms of climate change requires to replace fossil fuels with renewables as a primary source of energy. Non-electric renewable potential being limited, this implies extending the use of electricity generated from wind and solar beyond the power sector, either by direct electrification or synthetic fuels. Modeling the transformation tow

Christina Hill, Mads C. Weber, Jannis Lehmann, Tariq Leinen

Bismuth vanadate (BiVO4) has recently been under focus for its potential use in photocatalysis thanks to its well-suited absorption edge in the visible light range. Here, we characterize the optical absorption of a BiVO4 single crystal as a function of temperature and polarization direction by reflectance and transmittance spectroscopy. The optical band gap

Arshyn Altybay, Michael Ruzhansky, Mohammed Elamine Sebih, Niyaz Tokmagambetov

In this paper, the space-fractional Schr\"{o}dinger equations with singular potentials are studied. Delta-like or even higher-order singularities are allowed. By using the regularising techniques, we introduce a family of 'weakened' solutions, calling them very weak solutions. The existence, uniqueness and consistency results are proved in an appropriate sen

Maxime Cauchois, Suyash Gupta, John Duchi

We develop conformal prediction methods for constructing valid predictive confidence sets in multiclass and multilabel problems without assumptions on the data generating distribution. A challenge here is that typical conformal prediction methods---which give marginal validity (coverage) guarantees---provide uneven coverage, in that they address easy example

David Conlon, Jacob Fox, Benny Sudakov, Yufei Zhao

We develop a sparse graph regularity method that applies to graphs with few 4-cycles, including new counting and removal lemmas for 5-cycles in such graphs. Some applications include: * Every $n$-vertex graph with no 5-cycle can be made triangle-free by deleting $o(n^{3/2})$ edges. * For $r \geq 3$, every $n$-vertex $r$-graph with girth greater than $5$ has

M. Katsanikas, V. J. García-Garrido, M. Agaoglou, S. Wiggins

In this paper we unveil the geometrical template of phase space structures that governs transport in a Hamiltonian system described by a potential energy surface with an entrance/exit channel and two wells separated by an index-1 saddle. For the analysis of the nonlinear dynamics mechanisms, we apply the method of Lagrangian descriptors, a trajectory-based s

A. Torres-Hernandez, F. Brambila-Paz, P. M. Rodrigo, E. De-la-Vega

The following document presents a possible solution and a brief stability analysis for a nonlinear system, which is obtained by studying the possibility of building a hybrid solar receiver; It is necessary to mention that the solution of the aforementioned system is relatively difficult to obtain through iterative methods since the system is apparently unsta

Pushpendu Ghosh, Ariel Neufeld, Jajati Keshari Sahoo

We employ both random forests and LSTM networks (more precisely CuDNNLSTM) as training methodologies to analyze their effectiveness in forecasting out-of-sample directional movements of constituent stocks of the S&P 500 from January 1993 till December 2018 for intraday trading. We introduce a multi-feature setting consisting not only of the returns with resp

He Zhang, Liang Zhang, Ang Lin, Congcong Xu

Messenger RNA (mRNA) vaccines are being used for COVID-19, but still suffer from the critical issue of mRNA instability and degradation, which is a major obstacle in the storage, distribution, and efficacy of the vaccine. Previous work showed that optimizing secondary structure stability lengthens mRNA half-life, which, together with optimal codons, increase

David Gepner, Francois Petit

We identify the type of $\mathbb{C}[[\hbar]]$-linear structure inherent in the $\infty$-categories which arise in the theory of Deformation Quantization modules. Using this structure, we show that the $\infty$-category of quasicoherent cohomologically complete DQ-modules is a deformation of the $\infty$-category of quasicoherent sheaves. We also obtain integ

Thomas Beck, David Jerison, Sarah Raynor

We study the regularity of minimizers of a two-phase free boundary problem. For a class of n-dimensional convex domains, we establish the Lipschitz continuity of the minimizer up to the fixed boundary under Neumann boundary conditions. Our proof uses an almost monotonicity formula for the Alt-Caffarelli-Friedman functional restricted to the convex domain. Th

Viswanatha V, Venkata Siva Reddy R, Ashwini Kumari P, Pradeep Kumar S

In this paper, the proposed system has demonstrated three ways of detecting alcohol level in the body of the car driver and prevent car driver from driving the vehicle by turning off the ignition system. It also sends messages to concerned people. In order to detect breath alcohol level MQ-3 sensor is included in this module along with a heartbeat sensor whi

Nilesh Vyas, Romain Alleaume

Extending the functionality and overcoming the performance limitation under which QKD can operate requires either quantum repeaters or new security models. Investigating the latter option, we introduce the \textit{Quantum Computational Hybrid} (QCH) security model, where we assume that computationally secure encryption may only be broken after time much long

Gregory A. Wellenius, Swapnil Vispute, Valeria Espinosa, Alex Fabrikant

Social distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency dec

Haipeng Sun, Rui Wang, Kehai Chen, Masao Utiyama

Unsupervised neural machine translation (UNMT) has recently achieved remarkable results for several language pairs. However, it can only translate between a single language pair and cannot produce translation results for multiple language pairs at the same time. That is, research on multilingual UNMT has been limited. In this paper, we empirically introduce

Víctor Blanco, Alberto Japón, Justo Puerto

In this paper we propose novel methodologies to construct Support Vector Machine -based classifiers that takes into account that label noises occur in the training sample. We propose different alternatives based on solving Mixed Integer Linear and Non Linear models by incorporating decisions on relabeling some of the observations in the training dataset. The

Olugbenga Adeniran, Sivan Refaely-Abramson, Zhen-Fei Liu

A prototypical organic photovoltaic material is a heterojunction composed of the blend of regioregular poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C$_{61}$-butyric acid methyl ester (PCBM). Microscopic understanding of the energy conversion mechanism in this system involves the relationship between the electronic structure and the atomistic geometry of P3

Dennis Rätzel, Daniel Hartley, Osip Schwartz, Philipp Haslinger

Coherent control of quantum transitions -- indispensable in quantum technology -- generally relies on the interaction of quantum systems with electromagnetic radiation. Here, we theoretically demonstrate that the non-radiative electromagnetic near-field of a temporally modulated free-space electron beam can be utilized for coherent control of quantum systems

Zhuowen Zhao, Thomas R. Bieler, Javier LLorca, Philip Eisenlohr

An artificial neural network is used to evaluate the effectiveness of six metrics and their combinations to assess whether slip transfers across grain boundaries in coarse-grained oligocrystalline Al foils \citep{Bieler_etal2019_2,Alizadeh_etal2020}. This approach extends the one- or two-dimensional projections formerly applied to analyze slip transfer. The

Arshyn Altybay, Michael Ruzhansky, Mohammed Elamine Sebih, Niyaz Tokmagambetov

In this paper, we consider the heat equation with strongly singular potentials and prove that it has a "very weak solution". Moreover, we show the uniqueness and consistency results in some appropriate sense. The cases of positive and negative potentials are studied. Numerical simulations are done: one suggests so-called "laser heating and cooling" effects d

Marcel Bengs, Nils Gessert, Alexander Schlaefer

Autism spectrum disorder (ASD) is associated with behavioral and communication problems. Often, functional magnetic resonance imaging (fMRI) is used to detect and characterize brain changes related to the disorder. Recently, machine learning methods have been employed to reveal new patterns by trying to classify ASD from spatio-temporal fMRI images. Typicall

J. Johansson, A. Goobar, S. H. Price, A. Sagués Carracedo

We report the results from spectroscopic observations of the multiple images of the strongly lensed Type Ia supernova (SN Ia), iPTF16geu, obtained with ground based telescopes and the Hubble Space Telescope (HST). From a single epoch of slitless spectroscopy with HST, we can resolve spectra of individual lensed supernova images for the first time. This allow

Allen Liu, Renato Paes Leme, Martin Pal, Jon Schneider

We introduce a new decomposition technique for random variables that maps a generic instance of the prophet inequalities problem to a new instance where all but a constant number of variables have a tractable structure that we refer to as $(\varepsilon, \delta)$-smallness. Using this technique, we make progress on several outstanding problems in the area: -

Sanchari Sen, Balaraman Ravindran, Anand Raghunathan

Ensuring robustness of Deep Neural Networks (DNNs) is crucial to their adoption in safety-critical applications such as self-driving cars, drones, and healthcare. Notably, DNNs are vulnerable to adversarial attacks in which small input perturbations can produce catastrophic misclassifications. In this work, we propose EMPIR, ensembles of quantized DNN models

Viswanatha V, Venkata Siva Reddy R, Rajeswari

This article presents the characterization of analog and digital control loops using PID and PIDN control algorithms for bidirectional buck and boost converter (BBC). Control loops of BBC are designed and implemented in MATLAB code using transfer functions in time domain with unit step response and in frequency domain with bode plots and pole-zero plots. The