November 2020 arXiv papers — page 9

Gabriel S. Gusmão, Adhika P. Retnanto, Shashwati C. da Cunha, Andrew J. Medford

Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes. Here, we utilize feed-forward artificial neural networks as basis functions to solve ordinary differential equations (ODEs) constrained by dif

Brennan Sprinkle, Sam Wilken, Shake Karapetyan, Michio Tanaka

We study the driven collective dynamics of a colloidal monolayer sedimentating down an inclined plane. The action of the gravity force parallel to the bottom wall creates a flow around each colloid, and the hydrodynamic interactions among the colloids accelerate the sedimentation as the local density increases. This leads to the creation of a universal "tria

Sanal Shivaprasad

Given a compact Riemann surface $Y$ and a positive integer $m$, Narasimhan and Simha defined a measure on $Y$ associated to the $m$-th tensor power of the canonical line bundle. We study the limit of this measure on holomorphic families of Riemann surfaces with semistable reduction. The convergence takes place on a hybrid space whose central fiber is the ass

Cameron Musco, Christopher Musco, David P. Woodruff

In $masked\ low-rank\ approximation$, one is given $A \in \mathbb{R}^{n \times n}$ and binary mask matrix $W \in \{0,1\}^{n \times n}$. The goal is to find a rank-$k$ matrix $L$ for which: $$cost(L) = \sum_{i=1}^{n} \sum_{j = 1}^{n} W_{i,j} \cdot (A_{i,j} - L_{i,j} )^2 \leq OPT + ε\|A\|_F^2 ,$$ where $OPT = \min_{rank-k\ \hat{L}} cost(\hat L)$ and $ε$ is a g

Insoon Yang

Standard stochastic control methods assume that the probability distribution of uncertain variables is available. Unfortunately, in practice, obtaining accurate distribution information is a challenging task. To resolve this issue, we investigate the problem of designing a control policy that is robust against errors in the empirical distribution obtained fr

Abraham P. Vinod, Meeko M. K. Oishi

Probabilistic guarantees of safety and performance are important in constrained dynamical systems with stochastic uncertainty. We consider the stochastic reachability problem, which maximizes the probability that the state remains within time-varying state constraints (i.e., a ``target tube''), despite bounded control authority. This problem subsumes

A. M. Kordbacheh, S. S. Szigeti, A. M. Martin

We theoretically investigate the optical focusing of a rubidium Bose-Einstein condensate onto a planar surface. Our analysis uses a Gaussian variational method that includes the effects of two-body atom-atom interactions and three-body recombination losses. The essential factors such as the width, peak density and atom loss rate of the focused BEC profile on

Cody Fleming, Carl Elks, Georgios Bakirtzis, Stephen C. Adams

Cyber-physical systems (CPS) are often defended in the same manner as information technology (IT) systems -- by using perimeter security. Multiple factors make such defenses insufficient for CPS. Resiliency shows potential in overcoming these shortfalls. Techniques for achieving resilience exist; however, methods and theory for evaluating resilience in CPS a

Seth K. Asante, Bianca Dittrich, Hal M. Haggard

The first computation of a spin foam dynamics that provides a test of the quantum equations of motions of gravity is presented. Specifically, a triangulation that includes an inner edge is treated. The computation leverages the recently introduced effective spin foam models, which are particularly numerically efficient. Previous work has raised the concern o

Samuel M. Wallace, Marco A. Alsina, Jean-François Gaillard

Analysis of x-ray absorption spectroscopy (XAS) data often involves the removal of artifacts or glitches from the acquired signal, a process commonly known as deglitching. Glitches result either from specific orientations of monochromator crystals or from scattering by crystallites in the sample itself. Since the precise energy or wavelength location and the

Nils Gubela, Julian Lyczak

We complete the study of points of bounded height on irreducible non-normal cubic surfaces by doing the point count on the cubic surface $W$ given by $t_0^2 t_2 = t_1^2 t_3$ over any number field. We show that the order of growth agrees with a conjecture by Batyrev and Manin and that the constant reflects the geometry of the variety as predicted by a conject

Rafael Belchior, Sérgio Guerreiro, André Vasconcelos, Miguel Correia

The complexity of a business environment often causes organizations to produce several inconsistent views on the same business process, leading to fragmentation and inefficiencies. Business process view integration attempts to produce an integrated view from different views of the same model, facilitating the management of models. To study trends around busi

Paolo Ghiggini, Klaus Niederkrüger-Eid

We prove, in a geometric way, that the standard contact structure on the real projective space of dimension $2n-1$ is not Liouville fillable for $n \ge 3$ and odd. We also prove that, for all $n$, semipositive fillings of those contact structures are simply connected. Finally we give yet another proof of the Eliashberg-Floer-McDuff theorem on the diffeomorph

Neeraj Kumar, Daniel Lokshtanov, Saket Saurabh, Subhash Suri

Given two points s and t in the plane and a set of obstacles defined by closed curves, what is the minimum number of obstacles touched by a path connecting s and t? This is a fundamental and well-studied problem arising naturally in computational geometry, graph theory (under the names Min-Color Path and Minimum Label Path), wireless sensor networks (Barrier

Ellen Yi-Ge, Rui Fan, Zechun Liu, Zhiqiang Shen

Keypoints of objects reflect their concise abstractions, while the corresponding connection links (CL) build the skeleton by detecting the intrinsic relations between keypoints. Existing approaches are typically computationally-intensive, inapplicable for instances belonging to multiple classes, and/or infeasible to simultaneously encode connection informati

Pip Goodman

Let $r>2$ and $\ell$ be primes. In this paper we study the mod $\ell$ Galois representations attached to curves of the form $y^r = f(x)$ where $f$ is monic and has coefficients belonging to the $r$-th cyclotomic field. We provide conditions on the coefficients (and degree) of $f$ which allow one to verify the mod $\ell$ image is large outside of a (typically

Joshua Sobel, Noah Bertram, Chen Ding, Fatemeh Nargesian

Analyzing patterns in a sequence of events has applications in text analysis, computer programming, and genomics research. In this paper, we consider the all-window-length analysis model which analyzes a sequence of events with respect to windows of all lengths. We study the exact co-occurrence counting problem for the all-window-length analysis model. Our f

Ishan Jindal, Ranit Aharonov, Siddhartha Brahma, Huaiyu Zhu

Deep neural models achieve some of the best results for semantic role labeling. Inspired by instance-based learning that utilizes nearest neighbors to handle low-frequency context-specific training samples, we investigate the use of memory adaptation techniques in deep neural models. We propose a parameterized neighborhood memory adaptive (PNMA) method that

Yichen Zhang, Feng Qiu, Tianqi Hong, Zhaoyu Wang

Self-healing capability is one of the most critical factors for a resilient distribution system, which requires intelligent agents to automatically perform restorative actions online, including network reconfiguration and reactive power dispatch. These agents should be equipped with a predesigned decision policy to meet real-time requirements and handle high

Xiaolong Hans Han

We bound the $L^2$-norm of an $L^2$ harmonic $1$-form in an orientable cusped hyperbolic $3$-manifold $M$ by its topological complexity, measured by the Thurston norm, up to a constant depending on $M$. It generalizes two inequalities of Brock-Dunfield. We also study the sharpness of the inequalities in the closed and cusped cases, using the interaction of m

David A. Herron, Gaven J. Martin

We present an analytical proof that certain natural metric planar universal covers are Hadamard metric spaces. In particular if $\rho=\varphi\circ u$ where $u$ is locally Lipschitz and subharmonic in $\Omega$, $\varphi$ is positive and increasing on an interval containing $u(\Omega)$ with $\log\varphi$ convex, and if the metric space $(\Omega,\rho(z)|dz|)$ i

N. S. Witte, P. E. Greenwood

We explore the analytic properties of the density function $ h(x;\gamma,\alpha) $, $ x \in (0,\infty) $, $ \gamma > 0 $, $ 0 < \alpha < 1 $ which arises from the domain of attraction problem for a statistic interpolating between the supremum and sum of random variables. The parameter $ \alpha $ controls the interpolation between these two cases, while $ \gam

Riccardo Messina, Annika Ott, Christoph Kathmann, Svend-Age Biehs

We theoretically study the thermal relaxation of many-body systems under the action of oscillating external fields. When the magnitude or the orientation of a field is modulated around values where the pairwise heat-exchange conductances depend non-linearly on this field, we demonstrate that the time symmetry is broken during the evolution of temperatures ov

Andrei Babichenko, Kazuya Kawasetsu, David Ridout, William Stewart

The Nappi-Witten model is a Wess-Zumino-Witten model in which the target space is the nonreductive Heisenberg group $H_4$. We consider the representation theory underlying this conformal field theory. Specifically, we study the category of weight modules, with finite-dimensional weight spaces, over the associated affine vertex operator algebra $\mathsf{H}_4$

Frédéric Champagnat, Cédric Herzet

In this communication, we address the problem of approximating the atoms of a parametric dictionary, commonly encountered in the context of sparse representations in "continuous" dictionaries. We focus on the case of translation-invariant dictionaries, where the inner product between atoms only depends on the difference between parameters. We investigate the

Alexander V Turbiner, Juan Carlos del Valle

It is shown that for the one-dimensional quantum anharmonic oscillator with potential $V(x)= x^2+g^2 x^4$ the Perturbation Theory (PT) in powers of $g^2$ (weak coupling regime) and the semiclassical expansion in powers of $\hbar$ for energies coincide. It is related to the fact that the dynamics in $x$-space and in $(gx)$-space corresponds to the same energy

Noah Brüstle, Tal Elbaz, Hamed Hatami, Onur Kocer

Let $H$ be a fixed undirected graph on $k$ vertices. The $H$-hitting set problem asks for deleting a minimum number of vertices from a given graph $G$ in such a way that the resulting graph has no copies of $H$ as a subgraph. This problem is a special case of the hypergraph vertex cover problem on $k$-uniform hypergraphs, and thus admits an efficient $k$-fac

Mauricio Allendes Cerda, Daniel Coronel

We give an almost dynamical characterization of inter-model sets with Euclidean internal space. This characterization is similar to previous results for general inter-model sets obtained independently by Baake, Lenz and Moody, and Aujogue. The new ingredients are two additional conditions on the rank of the Abelian group generated by the set of internal diff

Mohamed Sayed, Gabriel Brostow

We wish to detect specific categories of objects, for online vision systems that will run in the real world. Object detection is already very challenging. It is even harder when the images are blurred, from the camera being in a car or a hand-held phone. Most existing efforts either focused on sharp images, with easy to label ground truth, or they have treat

Sagnik Das, Hassan Ahmed Sial, Ke Ma, Ramon Baldrich

Automatic document content processing is affected by artifacts caused by the shape of the paper, non-uniform and diverse color of lighting conditions. Fully-supervised methods on real data are impossible due to the large amount of data needed. Hence, the current state of the art deep learning models are trained on fully or partially synthetic images. However

Daniel Evans, Jiadong Chen, Geoffroy Hautier, Wenhao Sun

High Entropy Alloys (HEAs) contain near equimolar amounts of five or more elements and are a compelling space for materials design. Great emphasis is placed on identifying HEAs that form a homogeneous solid-solution, but the design of such HEAs is hindered by the difficulty of navigating stability relationships in high-component spaces. Traditional phase dia

Gauri Deshpande, Björn W. Schuller

The Coronavirus (COVID-19) pandemic has been the research focus world-wide in the year 2020. Several efforts, from collection of COVID-19 patients' data to screening them for the virus's detection are taken with rigour. A major portion of COVID-19 symptoms are related to the functioning of the respiratory system, which in-turn critically influences the human

Diego Bueso, Maria Piles, Gustau Camps-Valls

Granger causality (GC) is undoubtedly the most widely used method to infer cause-effect relations from observational time series. Several nonlinear alternatives to GC have been proposed based on kernel methods. We generalize kernel Granger causality by considering the variables cross-relations explicitly in Hilbert spaces. The framework is shown to generaliz

Anton Smerdov, Andrey Somov, Evgeny Burnaev, Bo Zhou

Current research in eSports lacks the tools for proper game practising and performance analytics. The majority of prior work relied only on in-game data for advising the players on how to perform better. However, in-game mechanics and trends are frequently changed by new patches limiting the lifespan of the models trained exclusively on the in-game logs. In

Stefan Perlega

A new proof for the embedded resolution of surface singularities in a three-dimensional smooth ambient space over algebraically closed fields of arbitrary characteristic. The proof makes use of an upper semicontinuous resolution invariant which prescribes the center in each step of the resolution algorithm. The resolution invariant strictly decreases under e

Yang-Hui He

We briefly overview how, historically, string theory led theoretical physics first to precise problems in algebraic and differential geometry, and thence to computational geometry in the last decade or so, and now, in the last few years, to data science. Using the Calabi-Yau landscape -- accumulated by the collaboration of physicists, mathematicians and comp

J. Baumeister, A. Leitao

We investigate the iterative methods proposed by Maz'ya and Kozlov (see [KM1], [KM2]) for solving ill-posed inverse problems modeled by partial differential equations. We consider linear evolutionary problems of elliptic, hyperbolic and parabolic types. Each iteration of the analyzed methods consists in the solution of a well posed problem (boundary value pr

Tim Johnson, Oleg Smirnov

We study a spatial, one-shot prisoner's dilemma (PD) model in which selection operates on both an organism's behavioral strategy (cooperate or defect) and its choice of when to implement that strategy across a set of discrete time slots. Cooperators evolve to fixation regularly in the model when we add time slots to lattices and small-world networks, and the

Anubha Kabra, Anu Agarwal, Anil Singh Parihar

Rapid advancements in the E-commerce sector over the last few decades have led to an imminent need for personalised, efficient and dynamic recommendation systems. To sufficiently cater to this need, we propose a novel method for generating top-k recommendations by creating an ensemble of clustering with reinforcement learning. We have incorporated DB Scan cl

Sam Greydanus, Dmitry Kobak

Although deep learning models have taken on commercial and political relevance, key aspects of their training and operation remain poorly understood. This has sparked interest in science of deep learning projects, many of which require large amounts of time, money, and electricity. But how much of this research really needs to occur at scale? In this paper,

Ashod Khederlarian, Carmen Almasri, Leonid Klushin

We explore semi-dilute and concentrated oligomers and polymers in a broad range of polymerization indices N ranging from 1 to a 100 and in a range of monomer number densities $\phi$ from 0.1 to 0.8 via molecular dynamics simulations and under good solvent conditions. This parameter range covers both no-overlap and strong chain overlap regimes, as quantified

Yuxiang Xie, Meng Xu, Evan Chow, Xiaolin Shi

Effectively measuring, understanding, and improving mobile app performance is of paramount importance for mobile app developers. Across the mobile Internet landscape, companies run online controlled experiments (A/B tests) with thousands of performance metrics in order to understand how app performance causally impacts user retention and to guard against ser

K. Rajpurohit, D. Wittor, R. J. van Weeren, F. Vazza

Radio relics are diffuse, extended synchrotron sources that originate from shock fronts generated during cluster mergers. The massive merging galaxy cluster MACS J0717.5+3745 hosts one of the more complex relics known to date. We present upgraded Giant Metrewave Radio Telescope band 3 (300-500 MHz) and band 4 (550-850 MHz) observations. These new observation

Michael Hippke

The Creator of the universe could place a message on the most cosmic of all billboards, the Cosmic Microwave Background (CMB) sky. It was proposed by Hsu & Zee (2006) to to search for such a message in the CMB angular power spectrum. I process the temperature measurements taken by the Planck and WMAP satellites and extract the binary bit-stream. I estimate t

George Christodoulou, Elias Koutsoupias, Annamaria Kovacs

The Nisan-Ronen conjecture states that no truthful mechanism for makespan-minimization when allocating $m$ tasks to $n$ unrelated machines can have approximation ratio less than $n$. Over more than two decades since its formulation, little progress has been made in resolving it and the best known lower bound is still a small constant. This work makes progres

Peng Huang, Fang-Fang Yuan

Following the initial work of Calcagni et al. on the black holes in multi-fractional theories, we focus on the Schwarzschild black hole in multi-fractional theory with q-derivatives. After presenting its Hawking and Hayward temperatures in detail, we verify these results by appealing to the well-known Hamilton-Jacobi and null geodesic methods of the tunnelli

Francesco Alessio, Glenn Barnich, Martin Bonte

The partition function of gravitons with Casimir-type boundary conditions is worked out. The simplest box that allows one to achieve full analytical control consists of a slab geometry with two infinite parallel planes separated by a distance d. In this setting, linearized gravity, like electromagnetism, is equivalent to two free massless scalar fields, one

Lukas Cedenblad, Noemi Schaffer, Anders Johansen, B. Mehlig

We investigate the possibility of erosion of planetesimals in a protoplanetary disk. We use theory and direct numerical simulations (Lattice Boltzmann Method) to calculate the erosion of large -- much larger than the mean-free-path of gas molecules -- bodies of different shapes in flows. We find that erosion follows a universal power-law in time, at intermed

Tanvir Ahamed, Bo Zou, Nahid Parvez Farazi, Theja Tulabandhula

This paper investigates the problem of assigning shipping requests to ad hoc couriers in the context of crowdsourced urban delivery. The shipping requests are spatially distributed each with a limited time window between the earliest time for pickup and latest time for delivery. The ad hoc couriers, termed crowdsourcees, also have limited time availability a

A. Leitao

We investigate the Cauchy problem for elliptic operators with $C^\infty$-coefficients at a regular set $\Omega \subset R^2$, which is a classical example of an ill-posed problem. The Cauchy data are given at the subset $\Gamma \subset \partial\Omega$ and our objective is to reconstruct the trace of the $H^1(\Omega)$ solution of an elliptic equation at $\part

Jonas Lampart, Peter Pickl

We consider the quantum dynamics of a large number $N$ of interacting bosons coupled a tracer particle, i.e. a particle of another kind, on a torus. We assume that in the initial state the bosons essentially form a homogeneous Bose-Einstein condensate, with some excitations. With an appropriate mean-field scaling of the interactions, we prove that the effect

George Cazenavette, Calvin Murdock, Simon Lucey

Despite their unmatched performance, deep neural networks remain susceptible to targeted attacks by nearly imperceptible levels of adversarial noise. While the underlying cause of this sensitivity is not well understood, theoretical analyses can be simplified by reframing each layer of a feed-forward network as an approximate solution to a sparse coding prob

Francesco Fumagalli, Martino Garonzi, Attila Maróti

Let $G$ be the symmetric group of degree $n$. Let $\omega(G)$ be the maximal size of a subset $S$ of $G$ such that $\langle x,y \rangle = G$ whenever $x,y \in S$ and $x \neq y$ and let $\sigma(G)$ be the minimal size of a family of proper subgroups of $G$ whose union is $G$. We prove that both functions $\sigma(G)$ and $\omega(G)$ are asymptotically equal to

Sella Nevo, Gal Elidan, Avinatan Hassidim, Guy Shalev

Floods are among the most common and deadly natural disasters in the world, and flood warning systems have been shown to be effective in reducing harm. Yet the majority of the world's vulnerable population does not have access to reliable and actionable warning systems, due to core challenges in scalability, computational costs, and data availability. In thi

Emanuele Dolera, Stefano Favaro, Edoardo Mainini

This paper presents a new approach to the classical problem of quantifying posterior contraction rates (PCRs) in Bayesian statistics. Our approach relies on Wasserstein distance, and it leads to two main contributions which improve on the existing literature of PCRs. The first contribution exploits the dynamic formulation of Wasserstein distance, for short r

Niko Hauzenberger, Michael Pfarrhofer, Anna Stelzer

In this paper, we investigate the effectiveness of conventional and unconventional monetary policy measures by the European Central Bank (ECB) conditional on the prevailing level of uncertainty. To obtain exogenous variation in central bank policy, we rely on high-frequency surprises in financial market data for the euro area (EA) around policy announcement

Bryan Cai, John P. A. Ioannidis, Eran Bendavid, Lu Tian

To make informative public policy decisions in battling the ongoing COVID-19 pandemic, it is important to know the disease prevalence in a population. There are two intertwined difficulties in estimating this prevalence based on testing results from a group of subjects. First, the test is prone to measurement error with unknown sensitivity and specificity. S

Aimo Winkelmann, Grzegorz Cios, Tomasz Tokarski, Piotr Bała

Crystals of the chemical elements manganese, tellurium, and selenium can show the effects of handedness. In order to sense the possible effects of a changing sense of chirality on the properties of samples from these elements, the potential presence of two, enantiomorphic, physically different, variants of these elemental crystal structures needs to be resol

Mikhail Skopenkov

We study linearization of lattice gauge theory. Linearized theory approximates lattice gauge theory in the same manner as the loop O(n)-model approximates the spin O(n)-model. Under mild assumptions, we show that the expectation of an observable in linearized Abelian gauge theory coincides with the expectation in the Ising model with random edge-weights. We

Maxime Labonne, Jorge López, Claude Poletti, Jean-Baptiste Munier

This paper proposes a novel framework to predict traffic flows' bandwidth ahead of time. Modern network management systems share a common issue: the network situation evolves between the moment the decision is made and the moment when actions (countermeasures) are applied. This framework converts packets from real-life traffic into flows containing relevant

Weijun Luo

Neural network forms the foundation of deep learning and numerous AI applications. Classical neural networks are fully connected, expensive to train and prone to overfitting. Sparse networks tend to have convoluted structure search, suboptimal performance and limited usage. We proposed the novel uniform sparse network (USN) with even and sparse connectivity

J. Queiruga

We study several deformations of the Skyrme model in three dimensions with self-dual sectors of arbitrary baryonic charge. We show that, for a family of background metrics as well as for a family of field dependent couplings, the model has one BPS sector, which may have any topological charge. We also study the gravitating case, where there are infinite BPS

Dominic A. Duffy, Igor P. Marko, Christian Fuchs, Timothy D. Eales

Type-II W-lasers have made an important contribution to the development of mid-infrared laser diodes. In this paper, we show that a similar approach can yield high performance lasers in the optical communications wavelength range. (GaIn)As/Ga(AsSb) type-II W structures emitting at 1255 nm have been realised on a GaAs substrate and exhibit low room temperatur

Abu Md Niamul Taufique, Andreas Savakis

Vehicle re-identification is an important computer vision task where the objective is to identify a specific vehicle among a set of vehicles seen at various viewpoints. Recent methods based on deep learning utilize a global average pooling layer after the backbone feature extractor, however, this ignores any spatial reasoning on the feature map. In this pape

Juan Isern, Francisco Barranco, Daniel Deniz, Juho Lesonen

Automated surveillance is essential for the protection of Critical Infrastructures (CIs) in future Smart Cities. The dynamic environments and bandwidth requirements demand systems that adapt themselves to react when events of interest occur. We present a reconfigurable Cyber Physical System for the protection of CIs using distributed cloud-edge smart video s

Inga Lev

In this paper, we show that the derivability problem for the primal propositional logic remains solvable in polynomial time upon adding a certain form of the principle of equivalent form substitution; and that, upon adding another form of this principle, it becomes co-NP-hard.

Sudip Mukherjee

We study the stochastically driven conserved Kardar-Parisi-Zhang (CKPZ) equation with quenched disorders. Short-ranged quenched disorders is found to be a relevant perturbation on the pure CKPZ equation at one dimension, and as a result, a new universality class different from pure CKPZ equation appears to emerge. At higher dimensions, quenched disorder turn

Carlos R. Mafra

These notes are a written version of my talk given at the CARMA workshop in June 2017, with some additional material. I presented a few concepts that have recently been used in the computation of tree-level scattering amplitudes (mostly using pure spinor methods but not restricted to it) in a context that could be of interest to the combinatorics community.

Jianmin Chen, Jun Yan, Panpan Zhang

The spreading pattern of COVID-19 differ a lot across the US states under different quarantine measures and reopening policies. We proposed to cluster the US states into distinct communities based on the daily new confirmed case counts via a nonnegative matrix factorization (NMF) followed by a k-means clustering procedure on the coefficients of the NMF basis

Adi Ditkowski, Anne Le Blanc, Chi-Wang Shu

Finite Difference methods (FD) are one of the oldest and simplest methods for solving partial differential equations (PDE). Block Finite Difference methods (BFD) are FD methods in which the domain is divided into blocks, or cells, containing two or more grid points, with a different scheme used for each grid point, unlike the standard FD method. It was shown

Valeri Lebedev

Up to present time the stochastic cooling was only tested and used at the microwave frequencies. Majority of these stochastic cooling systems operate without Schottky band overlap which greatly simplifies tuning of cooling systems and removes unwanted coupling between different cooling systems. A transition from the microwave stochastic cooling to the optica

Sudip Mukherjee, Abhik Basu

Physical understanding of how the interplay between symmetries and nonlinear effects can control the scaling and multiscaling properties in a coupled driven system, such as magnetohydrodynamic turbulence or turbulent binary fluid mixtures, remains elusive till the date. To address this generic issue, we construct a conceptual nonlinear hydrodynamic model, pa

Ivan Chajda, Helmut Länger

M. Busaniche, R. Cignoli, C. Tsinakis and A. M. Wille showed that every residuated lattice induces a residuation on its full twist product. For their construction they used also lattice operations. We generalize this problem to left-residuated groupoids which need not be lattice-ordered. Hence, for the full twist product we cannot use the same construction.

A. Leitao

We investigate the use of a functional analytical version of the Backus-Gilbert Method as a reconstruction strategy to get specific information about the solution of linear and slightly non-linear systems with Frech\'et derivable operators. Some a priori error estimates are shown and tested for two classes of problems: a nonlinear moment problem and a linear

Ádám Schweitzer

In this paper we study the capacity of Lorentzian polynomials. We give a new proof of a theorem of Br\"and\'en, Leake and Pak. Our approach is probabilistic in nature and uses a lemma about a certain distance of binomial distributions to distributions with fixed expected value.

Shaltiel Eloul, Daan Frenkel

We present simulations indicating that it should be possible to construct a switchable nano-scale fluid pump, driven by exothermic surface reactions. Such a pump could, for instance, be controlled electro-chemically. In our simulations we explore a simple illustration of such a pump. We argue that the simplicity of the pump design could make it attractive fo

Stefan Hoffmann

Most slowly synchronizing automata over binary alphabets are circular, i.e., containing a letter permuting the states in a single cycle, and their set of synchronizing words has maximal state complexity, which also implies complete reachability.Here, we take a closer look at generalized circular and completely reachable automata. We derive that over a binary

Alexander Mikhailovich Lyapunov

Lyapunov, A. (1896). On the series proposed by Hill for the representation of the motion of the moon. Proceedings of the Department of Physical Sciences of the Society of Natural History, Moscow, 1896, Vol. VIII, No. 1, 1-23. English translation of the Russian original. Translator: Thomas. S. Ligon, orcid 0000-0002-4067-876X.

Jie Qi, Andrew M. Cheung, S. Joseph Poon

High-entropy alloys, which exist in the high-dimensional composition space, provide enormous unique opportunities for realizing unprecedented structural and functional properties. A fundamental challenge, however, lies in how to predict the specific alloy phases and desirable properties accurately. This review article provides an overview of the data-driven

Chirag Manchanda, Mayank Kumar, Vikram Singh, Naba Hazarika

Diwali is among the most important Indian festivals, and elaborate firework displays mark the evening's festivities. This study assesses the impact of Diwali on the concentration, composition, and sources of ambient PM2.5. We observed the total PM2.5 concentrations to rise to 16 times the pre-firework levels, while each of the elemental, organic, and black c

Tiago J. Fonseca

We survey some key developments in the theory of transcendental numbers, paying special attention to Nesterenko's theorem on values of Eisenstein series and emphasizing its underlying geometric aspects. We finish with a brief discussion on periods and related open problems.

Rafal Sikora, for the STAR Collaboration

The measurement of the central exclusive production of charged hadron pairs $h^{+}h^{-}$ ($h = \pi, K, p$) by the STAR experiment at RHIC is reported. The data from proton-proton collisions at $\sqrt{s} = 200$ GeV were used in this study. The pairs of charged hadrons produced in the reaction $pp\to p^\prime+h^{+}h^{-}+p^\prime$ were reconstructed from the tr

Ioannis Vasileios Chremos, Andreas A. Malikopoulos

Emerging mobility systems such as connected and automated vehicles (CAVs) provide the most intriguing opportunity for more accessible, safe, and efficient transportation. CAVs are expected to significantly improve safety by eliminating the human factor and ensure transportation efficiency by allowing users to monitor transportation network conditions and mak

Phong Nguyen-Ha, Animesh Karnewar, Lam Huynh, Esa Rahtu

We propose a new cascaded architecture for novel view synthesis, called RGBD-Net, which consists of two core components: a hierarchical depth regression network and a depth-aware generator network. The former one predicts depth maps of the target views by using adaptive depth scaling, while the latter one leverages the predicted depths and renders spatially

Vladimir A. Dorodnitsyn, Roman Kozlov, Sergey V. Meleshko

The paper considers one-dimensional flows of a polytropic gas in the Lagrangian coordinates in three cases: plain one-dimensional flows, radially symmetric flows and spherically symmetric flows. The one-dimensional flow of a polytropic gas is described by one second-order partial differential equation in the Lagrangian variables. Lie group classification of

Muneto Nitta

We argue that strings (vortices) and monopoles are confined, when fields receiving nontrivial Aharonov-Bohm (AB) phases around a string develop vacuum expectation values (VEVs). We illustrate this in an $SU(2) \times U(1)$ gauge theory with charged triplet complex scalar fields admitting Alice strings and monopoles, by introducing charged doublet scalar fiel

Lennart Schäpermeier, Christian Grimme, Pascal Kerschke

Simultaneously visualizing the decision and objective space of continuous multi-objective optimization problems (MOPs) recently provided key contributions in understanding the structure of their landscapes. For the sake of advancing these recent findings, we compiled all state-of-the-art visualization methods in a single R-package (moPLOT). Moreover, we exte

Charbel Bou Hanna

Rosenfeld Conjectured in 1972 that there exists an integer K $\geq$ 8 such that any tournament of order n $\geq$ K contains any Hamiltonian oriented path. In 2000, Havet and Thomass\'e proved this conjecture for any tournament with exactly 3 exceptions. We give a simplified proof of this fact.

Vida Fathi, Jalal Arabneydi, Amir G. Aghdam

In this paper, we study the global convergence of model-based and model-free policy gradient descent and natural policy gradient descent algorithms for linear quadratic deep structured teams. In such systems, agents are partitioned into a few sub-populations wherein the agents in each sub-population are coupled in the dynamics and cost function through a set

Shin Hwei Tan, Chunfeng Hu, Ziqiang Li, Xiaowen Zhang

Many studies have shown the benefits of introducing open-source projects into teaching Software Engineering (SE) courses. However, there are several limitations of existing studies that limit the wide adaptation of open-source projects in a classroom setting, including (1) the selected project is limited to one particular project, (2) most studies only inves

Masoud Roudneshin, Jalal Arabneydi, Amir G. Aghdam

We study model-based and model-free policy optimization in a class of nonzero-sum stochastic dynamic games called linear quadratic (LQ) deep structured games. In such games, players interact with each other through a set of weighted averages (linear regressions) of the states and actions. In this paper, we focus our attention to homogeneous weights; however,

Maxim Goncharov

We generalize the notion of a Rota-Baxter operator on groups and the notion of a Rota-Baxter operator of weight 1 on Lie algebras and define and study the notion of a Rota-Baxter operator on a cocommutative Hopf algebra $H$. If $H=F[G]$ is the group algebra of a group $G$ or $H=U(\mathfrak{g})$ the universal enveloping algebra of a Lie algebra $\mathfrak{g}$

Rob Weston, Oiwi Parker Jones, Ingmar Posner

Simulating realistic radar data has the potential to significantly accelerate the development of data-driven approaches to radar processing. However, it is fraught with difficulty due to the notoriously complex image formation process. Here we propose to learn a radar sensor model capable of synthesising faithful radar observations based on simulated elevati

August DuMont Schütte, Jürgen Hetzel, Sergios Gatidis, Tobias Hepp

Privacy concerns around sharing personally identifiable information are a major practical barrier to data sharing in medical research. However, in many cases, researchers have no interest in a particular individual's information but rather aim to derive insights at the level of cohorts. Here, we utilize Generative Adversarial Networks (GANs) to create derive

Amitesh Singh, Kamlesh N Pathak

Many pulsar folding algorithms are currently deployed to generate strong SNRs for the total intensity profiles. But they require large observation times to improve the SNR effectively. New approaches to de-noise the pulsar total intensity data have sprung up over the years, powered by Machine learning and Deep learning algorithms. In the current work, effort

Marija Vella, João F. C. Mota

The remarkable performance of deep neural networks (DNNs) currently makes them the method of choice for solving linear inverse problems. They have been applied to super-resolve and restore images, as well as to reconstruct MR and CT images. In these applications, DNNs invert a forward operator by finding, via training data, a map between the measurements and

V. P. Goncharov

A single-layer model is used to construct the theory of straight-line jets. In addition to stationary states, the evolution of such jets admits transverse pulsations. The theory predicts that the period for warm jets pulsations is longer than the period of inertial oscillations caused by the Earth's rotation, while for cold jets pulsations, it is shorter. Th

Btool Hamoui, Abdulaziz Alashaikh, Eisa Alanazi

Background: The outbreak of the new coronavirus disease (COVID-19) has affected human life to a great extent on a worldwide scale. During the coronavirus pandemic, public health professionals at the early outbreak faced an extraordinary challenge to track and quantify the spread of disease. Objective: To investigate whether a digital surveillance model using

A. D. Dolgov, K. A. Postnov

Bulk of various astronomical observations of black holes suggest that virtually all observed black holes can be of primordial origin. A modified mechanism of the primordial black hole formation is described. A universal log-normal mass spectrum with a mean mass of around $\sim 10 M_\odot$ predicted by this mechanism is strongly confirmed by the LIGO/Virgo ob

Pichet Vanichchapongjaroen

In this work, we extend a theory which describes a linearly self-dual exact 3-form field in six dimensional spacetime within the formalism of arXiv:1511.08220 and arXiv:1903.12196 to an action which fully describes an M5-brane in the eleven-dimensional supergravity background. The action we obtain has all the required symmetries including kappa-symmetry. Alt