December 2020 arXiv papers — page 53

Igor F. Herbut, Julia M. Link

We show that the general low-energy Bogoliubov-de Genness Hamiltonian in a multiband superconductor with broken time reversal and preserved inversion symmetry is a generator of real four-dimensional representation of $SO(4)$. In the particular representation such an effective Hamiltonian is a purely imaginary matrix, and it is proportional to the antisymmetr

Oliver Richardson, Joseph Y Halpern

We introduce Probabilistic Dependency Graphs (PDGs), a new class of directed graphical models. PDGs can capture inconsistent beliefs in a natural way and are more modular than Bayesian Networks (BNs), in that they make it easier to incorporate new information and restructure the representation. We show by example how PDGs are an especially natural modeling t

David Kohel

We introduce the twisted $\boldsymbol{\mu}_4$-normal form for elliptic curves, deriving in particular addition algorithms with complexity $9\mathbf{M} + 2\mathbf{S}$ and doubling algorithms with complexity $2\mathbf{M} + 5\mathbf{S} + 2\mathbf{m}$ over a binary field. Every ordinary elliptic curve over a finite field of characteristic 2 is isomorphic to one

Luiz Renato Fontes, Susana Frómeta, Leonel Zuaznábar

We derive the scaling limit for the Hierarchical Random Hopping dynamics for the non cascading 2-GREM at low temperatures and time scales where the dynamics is close to equilibrium. The {\em fine tuning} phenomenon plays a role (under certain choices of parameters of the model), yielding three dynamical regimes. In contrast to the {\em cascading} case, the p

Ashley Chontos, Daniel Huber, Travis A. Berger, Hans Kjeldsen

Asteroseismology of bright stars has become increasingly important as a method to determine fundamental properties (in particular ages) of stars. The Kepler Space Telescope initiated a revolution by detecting oscillations in more than 500 main-sequence and subgiant stars. However, most Kepler stars are faint, and therefore have limited constraints from indep

M. Hohlmann

Crosstalk characteristics such as pulse amplitude and shape are studied with a simple PSpice model of the capacitive couplings within an MPGD. The crosstalk pulse shape can be understood as due to a CR-differentiator. Crosstalk can occur simultaneously through more than one capacitive coupling path. The crosstalk signals on these paths add differently if the

Yongming Qu, Ilya Lipkovich

The current COVID-19 pandemic poses numerous challenges for ongoing clinical trials and provides a stress-testing environment for the existing principles and practice of estimands in clinical trials. The pandemic may increase the rate of intercurrent events (ICEs) and missing values, spurring a great deal of discussion on amending protocols and statistical a

Amin Aboubrahim, Tarek Ibrahim, Michael Klasen, Pran Nath

It is shown that a decaying neutralino in a supergravity unified framework is a viable candidate for dark matter. Such a situation arises in the presence of a hidden sector with ultraweak couplings to the visible sector where the neutralino can decay into the hidden sector's lightest supersymmetric particle (LSP) with a lifetime larger than the lifetime of t

Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri

We consider the sample complexity of learning with adversarial robustness. Most prior theoretical results for this problem have considered a setting where different classes in the data are close together or overlapping. Motivated by some real applications, we consider, in contrast, the well-separated case where there exists a classifier with perfect accuracy

Jie Shen

We study {\em online} active learning of homogeneous halfspaces in $\mathbb{R}^d$ with adversarial noise where the overall probability of a noisy label is constrained to be at most $\nu$. Our main contribution is a Perceptron-like online active learning algorithm that runs in polynomial time, and under the conditions that the marginal distribution is isotrop

Yonatan Sanz Perl, Hernan Bocaccio, Ignacio Perez-Ipina, Steven Laureys

The cognitive functions of human and non-human primates rely on the dynamic interplay of distributed neural assemblies. As such, it seems unlikely that cognition can be supported by macroscopic brain dynamics at the proximity of thermodynamic equilibrium. We confirmed this hypothesis by investigating electrocorticography data from non human primates undergoi

James Queeney, Ioannis Ch. Paschalidis, Christos G. Cassandras

In order for reinforcement learning techniques to be useful in real-world decision making processes, they must be able to produce robust performance from limited data. Deep policy optimization methods have achieved impressive results on complex tasks, but their real-world adoption remains limited because they often require significant amounts of data to succ

Mochen Yang, Edward McFowland, Gordon Burtch, Gediminas Adomavicius

Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to 'mine' variables of interest from available data, followed by the inclusion of those variables into an econometric framework, with the objective of est

J. A. Carrillo, K. Lin

We consider a degenerate chemotaxis model with two-species and two-stimuli in dimension $d\geq 3$ and find two critical curves intersecting at one same point which separate the global existence and blow up of weak solutions to the problem. More precisely, above these curves (i.e. subcritical case), the problem admits a global weak solution obtained by the li

Kshitij Goel, Wennie Tabib, Nathan Michael

This paper develops a communication-efficient distributed mapping approach for rapid exploration of a cave by a multi-robot team. Subsurface planetary exploration is an unsolved problem challenged by communication, power, and compute constraints. Prior works have addressed the problems of rapid exploration and leveraging multiple systems to increase explorat

Rishab Khincha, Soundarya Krishnan, Tirtharaj Dash, Lovekesh Vig

In this paper, our focus is on constructing models to assist a clinician in the diagnosis of COVID-19 patients in situations where it is easier and cheaper to obtain X-ray data than to obtain high-quality images like those from CT scans. Deep neural networks have repeatedly been shown to be capable of constructing highly predictive models for disease detecti

Katherine J. Meyer, Richard P. McGehee

Although mathematical models do not fully match reality, robustness of dynamical objects to perturbation helps bridge from theoretical to real-world dynamical systems. Classical theories of structural stability and isolated invariant sets treat robustness of qualitative dynamics to sufficiently small errors. But they do not indicate just how large a perturba

Sofia Morena del Pozo, Helmut Laufs, Vincent Bonhomme, Steven Laureys

The dynamic core hypothesis posits that consciousness is correlated with simultaneously integrated and differentiated assemblies of transiently synchronized brain regions. We represented time-dependent functional interactions using dynamic brain networks, and assessed the integrityof the dynamic core by means of the flexibility and largest multilayer module

Faruk Temur

Recently in joint work with E. Sert, we proved sharp boundedness results on discrete fractional integral operators along binary quadratic forms. Present work vastly enhances the scope of those results by extending boundedness to bivariate quadratic polynomials. We achieve this in part by establishing connections to problems on concentration of lattice points

Daniel Gratzer, Jonathan Sterling

We argue that locally Cartesian closed categories form a suitable doctrine for defining dependent type theories, including non-extensional ones. Using the theory of sketches, one may define syntactic categories for type theories in a style that resembles the use of Martin-L\"of's Logical Framework, following the "judgments as types" principle. The concentrat

Lukas Hoyer, Dengxin Dai, Yuhua Chen, Adrian Köring

Training deep networks for semantic segmentation requires large amounts of labeled training data, which presents a major challenge in practice, as labeling segmentation masks is a highly labor-intensive process. To address this issue, we present a framework for semi-supervised semantic segmentation, which is enhanced by self-supervised monocular depth estima

Mimi Dai

We introduce the concept of intermittency dimension for the magnetohydrodynamics (MHD) to quantify the intermittency effect. With dependence on the intermittency dimension, we derive phenomenological laws for intermittent MHD turbulence with and without the Hall effect. In particular, scaling laws of dissipation wavenumber, energy spectra and structure funct

Yu-Hang Xiao, David Ramírez, Peter J. Schreier, Cheng Qian

Target detection is an important problem in multiple-input multiple-output (MIMO) radar. Many existing target detection algorithms were proposed without taking into consideration the quantization error caused by analog-to-digital converters (ADCs). This paper addresses the problem of target detection for MIMO radar with one-bit ADCs and derives a Rao's test-

Silvia Nappini, Luca D'Amario, Marco Favaro, Simone Dal Zilio

The Beamline for Advanced diCHroism (BACH) of the Istituto Officina dei Materiali-Consiglio Nazionale delle Ricerche (IOM-CNR), operating at Elettra synchrotron in Trieste (Italy), works in the extreme ultra violet (EUV)-soft X-ray photon energy range with selectable light polarization, high energy resolution, brilliance and time resolution. The beamline off

Koushik Pal, Yi Xia, Jiahong Shen, Jiangang He

The development of efficient thermal energy management devices such as thermoelectrics, barrier coatings, and thermal data-storage disks often relies on compounds that possess very low lattice thermal conductivity ($\kappa_l$). Here, we present the computational prediction of a large family of 628 thermodynamically stable quaternary chalcogenides, AMM'Q$_3$

Mikala Ørsnes Jansen

We identify the exit path $\infty$-category of the reductive Borel-Serre compactification as the nerve of a $1$-category defined purely in terms of rational parabolic subgroups and their unipotent radicals. As an immediate consequence, we identify the fundamental group of the reductive Borel-Serre compactification, recovering a result of Ji-Murty-Saper-Scher

John Skilling, Kevin H. Knuth

The theories of quantum mechanics and relativity dramatically altered our understanding of the universe ushering in the era of modern physics. Quantum theory deals with objects probabilistically at small scales, whereas relativity deals classically with motion in space and time. We show here that the mathematical structures of quantum theory and of relativit

Kevin Denamganaï, James Alfred Walker

The drivers of compositionality in artificial languages that emerge when two (or more) agents play a non-visual referential game has been previously investigated using approaches based on the REINFORCE algorithm and the (Neural) Iterated Learning Model. Following the more recent introduction of the \textit{Straight-Through Gumbel-Softmax} (ST-GS) approach, t

Yuntao Xu, Ayed Al Sayem, Chang-Ling Zou, Linran Fan

We report intracavity Bragg scattering induced by photorefractive (PR) effect in high-Q lithium niobate (LN) ring resonators at cryogenic temperatures. We show that, when a cavity mode is strongly excited, the PR effect imprints a long-lived periodic space-charge field. This residual field in turn creates a refractive index modulation pattern that dramatical

Juan P. Madrid

A new radio map of the Abell 85 Brightest Cluster Galaxy (BCG) was obtained with the Karl G. Jansky Very Large Array (VLA). With a resolution of 0.02", this radio image shows two kiloparsec-scale bipolar jets emanating from the active galactic nucleus of the Abell 85 BCG. The galaxy core appears as a single entity on the new radio map. It has been assumed th

Lingfeng Tao, Michael Bowman, Jiucai Zhang, Xiaoli Zhang

In human-robot cooperation, the robot cooperates with humans to accomplish the task together. Existing approaches assume the human has a specific goal during the cooperation, and the robot infers and acts toward it. However, in real-world environments, a human usually only has a general goal (e.g., general direction or area in motion planning) at the beginni

Petr Henyš, Danas Sutula, Jiří Kopal, Michal Kuchař

Structural stiffness plays an important role in engineering design. The analysis of stiffness requires precise experiments and computational models that can be difficult or time-consuming to procure. A novel relation between modal and static stiffness based on modal decomposition is introduced in this study. This relation allows analysing the smallest struct

Mehmet Dogan, Marvin L. Cohen

A new experimental study by Snider et al. [Nature 586, 373-377 (2020)] reported behavior in a high-pressure carbon-sulfur-hydrogen system that has been interpreted by the authors as superconductivity at room temperature. The sudden drop of electrical resistance at a critical temperature and the change of the R vs. T behavior with an applied magnetic field po

Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard

Air pollution is one of the most important causes of mortality in the world. Monitoring air pollution is useful to learn more about the link between health and pollutants, and to identify areas for intervention. Such monitoring is expensive, so it is important to place sensors as efficiently as possible. Bayesian optimisation has proven useful in choosing se

Maciej Sypetkowski, Jakub Jasiulewicz, Zbigniew Wojna

In this paper, we present augmentation inside the network, a method that simulates data augmentation techniques for computer vision problems on intermediate features of a convolutional neural network. We perform these transformations, changing the data flow through the network, and sharing common computations when it is possible. Our method allows us to obta

Shantanu Shahane, Purushotam Kumar, Surya Pratap Vanka

Flow over bluff bodies has multiple engineering applications and thus, has been studied for decades. The lift and drag coefficients are practically important in the design of many components such as automobiles, aircrafts, buildings etc. These coefficients vary significantly with Reynolds number and geometric parameters of the bluff body. In this study, we h

Mihaela Vatasescu

In [Phys. Rev. A 82, 042103 (2010)], the authors showed that "for a class of the non-Markovian master equations in time-local forms", the quantum Fisher information (QFI) flow can be decomposed into additive subflows corresponding to different dissipative channels. However, the paper does not specify the class of non-Markovian time-local master equations for

Madhuparna Das

We present a proof of Selberg's Central Limit Theorem for automorphic $L$-functions of degree 2 using Radziwi\l\l\space and Soundararajan's method. Additionally, we prove the independence of the automorphic $L$-functions associated with the sequence of primitive holomorphic cusp forms.

Debra Meloy Elmegreen, Bruce G. Elmegreen, Bradley C. Whitmore, Rupali Chandar

The Clusters, Clumps, Dust, and Gas in Extreme Star-Forming Galaxies (CCDG) survey with the Hubble Space Telescope includes multi-wavelength imaging of 13 galaxies less than 100 Mpc away spanning a range of morphologies and sizes, from Blue Compact Dwarfs (BCDs) to luminous infrared galaxies (LIRGs), all with star formation rates in excess of hundreds of sol

Ohjoon Kwon, Doyu Lee, Woohyun Chung, Danho Ahn

The Center for Axion and Precision Physics research at the Institute for Basic Science is searching for axion dark matter using ultra-low temperature microwave resonators. We report the exclusion of the axion mass range 10.7126$-$10.7186 $\mu$eV with near Kim-Shifman-Vainshtein-Zakharov (KSVZ) coupling sensitivity and the range 10.16$-$11.37 $\mu$eV with abo

Han Lin Shang, Ruofan Xu

We consider forecasting functional time series of extreme values within a generalised extreme value distribution (GEV). The GEV distribution can be characterised using the three parameters (location, scale and shape). As a result, the forecasts of the GEV density can be accomplished by forecasting these three latent parameters. Depending on the underlying da

Masoud Razban, Javad Dargahi, Benoit Boulet

Embolization, stroke, ischaemic lesion, and perforation remain significant concerns in endovascular interventions. Intravascular sensing of tool interaction with the arteries is advantageous to minimize such complications and enhance navigation safety. Intraluminal information is currently limited due to the lack of intravascular contact sensing technologies

J. Verjauw, A. Potočnik, M. Mongillo, R. Acharya

The coherence of state-of-the-art superconducting qubit devices is predominantly limited by two-level-system defects, found primarily at amorphous interface layers. Reducing microwave loss from these interfaces by proper surface treatments is key to push the device performance forward. Here, we study niobium resonators after removing the native oxides with a

Kessys L. P. Oliveira, Bruno S. Castro, Helton Saulo, Roberto Vila

The length-biased Birnbaum-Saunders distribution is both useful and practical for environmental sciences. In this paper, we initially derive some new properties for the length-biased Birnbaum-Saunders distribution, showing that one of its parameters is the mode and that it is bimodal. We then introduce a new regression model based on this distribution. We im

Renato Calleja, Carlos García-Azpeitia, Jean-Philippe Lessard, J. D. Mireles James

The present work studies the continuation class of the regular $n$-gon solution of the $n$-body problem. For odd numbers of bodies between $n = 3$ and $n = 15$ we apply one parameter numerical continuation algorithms to the energy/frequency variable, and find that the figure eight choreography can be reached starting from the regular $n$-gon. The continuatio

Aliaksei Mikhailiuk, Maria Perez-Ortiz, Dingcheng Yue, Wilson Suen

Increasing popularity of high-dynamic-range (HDR) image and video content brings the need for metrics that could predict the severity of image impairments as seen on displays of different brightness levels and dynamic range. Such metrics should be trained and validated on a sufficiently large subjective image quality dataset to ensure robust performance. As

P. Gothen, A. Guedes de Oliveira

It is well known that a rigid motion of the Euclidean plane can be written as the composition of at most three reflections. It is perhaps not so widely known that a similar result holds for Euclidean space in any number of dimensions. The purpose of the present article is, firstly, to present a natural proof of this result in dimension 3 by explicitly constr

Marcos A. G. Garcia, Kunio Kaneta, Yann Mambrini, Keith A. Olive

We analyze in detail the perturbative decay of the inflaton oscillating about a generic form of its potential $V(\phi) = \phi^k$, taking into account the effects of non-instantaneous reheating. We show that evolution of the temperature as a function of the cosmological scale factor depends on the spin statistics of the final state decay products when $k > 2$

Rajkumar Biswas, Debasish Saha, Ranjini Bandyopadhyay

The settling dynamics of falling spheres inside a Laponite suspension is studied. Laponite is a colloidal synthetic clay that shows physical aging in aqueous suspension due to the spontaneous evolution of inter-particle electrostatic interactions. In our experiments, millimeter-sized steel balls are dropped in aqueous Laponite suspensions of different ages (

Edward Cottle, Florent Michel, Joseph Wilson, Nick New

The Convolutional Neural Network (CNN) is a state-of-the-art architecture for a wide range of deep learning problems, the quintessential example of which is computer vision. CNNs principally employ the convolution operation, which can be accelerated using the Fourier transform. In this paper, we present an optical hardware accelerator that combines silicon p

Tomás Capretto, Camen Piho, Ravin Kumar, Jacob Westfall

The popularity of Bayesian statistical methods has increased dramatically in recent years across many research areas and industrial applications. This is the result of a variety of methodological advances with faster and cheaper hardware as well as the development of new software tools. Here we introduce an open source Python package named Bambi (BAyesian Mo

Joanna Jureczko

In this paper we present the generalizations of results, given in the paper published in Georgian J. Math. 26(2019) no. 4, pp 591-598, towards point-finite families.

M. M. Günther, O. N. Rosmej, P. Tavana, M. Gyrdymov

Ultra-intense MeV photon and neutron beams are indispensable tools in many research fields such as nuclear, atomic and material science as well as in medical and biophysical applications. For astrophysical applications aimed for laboratory investigations, neutron fluxes in excess of 10$^{21}$ n/(cm$^2$ s) are required. Such ultra-high fluxes are unattainable

D. G. Sevostyanov, I. A. Aleksandrov, G. Plunien, V. M. Shabaev

The widely-used locally constant field approximation (LCFA) can be utilized in order to derive a simple closed-form expression for the total number of particles produced in the presence of a strong electromagnetic field of a general spatio-temporal configuration. A usual justification for this approximate approach is the requirement that the external field v

C. S. Chang, S. Ku, R. Hager, R. M. Churchill

Understanding and predicting divertor heat-load width ${\lambda}_q$ is a critically important problem for an easier and more robust operation of ITER with high fusion gain. Previous predictive simulation data for ${\lambda}_q$ using the extreme-scale edge gyrokinetic code XGC1 in the electrostatic limit under attached divertor plasma conditions in three majo

Soo Min Oh, Seung-Woo Son, Byungnam Kahng

Networks are ubiquitous in diverse real-world systems. Many empirical networks grow as the number of nodes increases with time. Percolation transitions in growing random networks can be of infinite order. However, when the growth of large clusters is suppressed under some effects, e.g., the Achlioptas process, the transition type changes to the second order.

Arunava Naha, Andre Teixeira, Anders Ahlen, Subhrakanti Dey

One of the most studied forms of attacks on the cyber-physical systems is the replay attack. The statistical similarities of the replay signal and the true observations make the replay attack difficult to detect. In this paper, we have addressed the problem of replay attack detection by adding watermarking to the control inputs and then performed resilient d

Sergey G. Bobkov, Alexey A. Naumov, Vladimir V. Ulyanov

Two--sided bounds are constructed for a probability density function of a weighted sum of chi-square variables. Both cases of central and non-central chi-square variables are considered. The upper and lower bounds have the same dependence on the parameters of the sum and differ only in absolute constants. The estimates obtained will be useful, in particular,

Andreas Piter, Philipp Otto, Hamza Alkhatib

Understanding the usage patterns for bike-sharing systems is essential in terms of supporting and enhancing operational planning for such schemes. Studies have demonstrated how factors such as weather conditions influence the number of bikes that should be available at bike-sharing stations at certain times during the day. However, the influences of these fa

Stéphane Guerrier, Christoph Kuzmics, Maria-Pia Victoria-Feser

Countries officially record the number of COVID-19 cases based on medical tests of a subset of the population with unknown participation bias. For prevalence estimation, the official information is typically discarded and, instead, small random survey samples are taken. We derive (maximum likelihood and method of moment) prevalence estimators, based on a sur

Neeraj Battan, Yudhik Agrawal, Veeravalli Saisooryarao, Aman Goel

Synthesis of long-term human motion skeleton sequences is essential to aid human-centric video generation with potential applications in Augmented Reality, 3D character animations, pedestrian trajectory prediction, etc. Long-term human motion synthesis is a challenging task due to multiple factors like, long-term temporal dependencies among poses, cyclic rep

Li Deng, Zilong Liu, Yong Liang Guan, Xiaobei Liu

Algebraic codes such as BCH code are receiving renewed interest as their short block lengths and low/no error floors make them attractive for ultra-reliable low-latency communications (URLLC) in 5G wireless networks. This paper aims at enhancing the traditional adaptive belief propagation (ABP) decoding, which is a soft-in-soft-out (SISO) decoding for high-d

David Kohel

We develop a computational framework for the statistical characterization of Galois characters with finite image, with application to characterizing Galois groups and establishing equivalence of characters of finite images of $\mathrm{Gal}(\overline{\mathbb{Q}}/\mathbb{Q})$.

Alice Kerr

In this paper we investigate the geometric properties of quasi-trees, and prove some equivalent criteria. We give a general construction of a tree that approximates the ends of a geodesic space, and use this to prove that every quasi-tree is $(1,C)$-quasi-isometric to a simplicial tree. As a consequence, we show that Gromov's tree approximation lemma for hyp

Hong-lin Liao, Tao Tang, Tao Zhou

In this work, we propose a Crank-Nicolson-type scheme with variable steps for the time fractional Allen-Cahn equation. The proposed scheme is shown to be unconditionally stable (in a variational energy sense), and is maximum bound preserving. Interestingly, the discrete energy stability result obtained in this paper can recover the classical energy dissipati

Sifan Ye, Ting Wu, Michael Jarvis, Yuhao Zhu

Reconstructing 3D models from large, dense point clouds is critical to enable Virtual Reality (VR) as a platform for entertainment, education, and heritage preservation. Existing 3D reconstruction systems inevitably make trade-offs between three conflicting goals: the efficiency of reconstruction (e.g., time and memory requirements), the visual quality of th

Peter G. Casazza, Dorsa Ghoreishi

We will answer the most significant open problem in real phase retrieval by projections by showing it requires at least $2n-2$ projections to do phase retrieval in $\RR^n$.

Dai Feng, Richard Baumgartner

Tree based ensembles such as Breiman's random forest (RF) and Gradient Boosted Trees (GBT) can be interpreted as implicit kernel generators, where the ensuing proximity matrix represents the data-driven tree ensemble kernel. Kernel perspective on the RF has been used to develop a principled framework for theoretical investigation of its statistical propertie

Mohammad Hosein Fakheri, Ali Abdolali

Thanks to the pioneering studies conducted on the fields of transformation optics (TO) and metasurfaces, many unprecedented devices such as invisibility cloaks have been recently realized. However, each of these methods has some drawbacks limiting the applicability of the designed devices for real-life scenarios. For instance, TO studies lead to bulky coatin

Hongliang Zhang, Boya Di, Zhu Han, H. Vincent Poor

Reconfigurable intelligent surfaces (RISs) consisting of multiple reflective elements are a promising technique to enhance communication quality as they can create favorable propagation conditions. In this letter, we characterize the fundamental relations between the number of reflective elements and the system sum-rate in RIS-assisted multi-user communicati

Camila S. Agostino Peter M. E. Claessens, Fuat Balci, Yossi Zana

The role of specific cognitive processes in deviations from constant discounting in intertemporal choice is not well understood. We evaluated decreased impatience in intertemporal choice tasks independent of discounting rate and non-linearity in long-scale time representation; nonlinear time representation was expected to explain inconsistencies in discounti

Pintu Bhunia, Kais Feki, Kallol Paul

New inequalities for the $A$-numerical radius of the products and sums of operators acting on a semi-Hilbert space, i.e. a space generated by a positive semidefinite operator $A$, are established. In particular, it is proved for operators $T$ and $S,$ having $A$-adjoint, that $$ \omega_A(TS) \leq \frac{1}{2}\omega_A(ST)+\frac{1}{4}\Big(\|T\|_A\|S\|_A+\|TS\|_

Christina Lienstromberg, Tania Pernas-Castaño, Juan J. L. Velázquez

We study the dynamic behaviour of two viscous fluid films confined between two concentric cylinders rotating at a small relative velocity. It is assumed that the fluids are immiscible and that the volume of the outer fluid film is large compared to the volume of the inner one. Moreover, while the outer fluid is considered to have constant viscosity, the rheo

Asaf Miron, David Mukamel, Harald A. Posch

Emergent bath-mediated attraction and condensation arise when multiple particles are simultaneously driven through an equilibrated bath under geometric constraints. While such scenarios are observed in a variety of non-equilibrium phenomena, with an abundance of experimental and numerical evidence, little quantitative understanding of how these interactions

Huixiang Huang, Renjie Wu, Jingbiao Huang, Jucai Lin

Generative adversarial network (GAN) still exists some problems in dealing with speech enhancement (SE) task. Some GAN-based systems adopt the same structure from Pixel-to-Pixel directly without special optimization. The importance of the generator network has not been fully explored. Other related researches change the generator network but operate in the t

Hong Liu, Oleg Pikhurko, Maryam Sharifzadeh, Katherine Staden

We present a sufficient condition for the stability property of extremal graph problems that can be solved via Zykov's symmetrisation. Our criterion is stated in terms of an analytic limit version of the problem. We show that, for example, it applies to the inducibility problem for an arbitrary complete bipartite graph $B$, which asks for the maximum number

Duarte Azevedo, Rodrigo Capucha, Emanuel Gouveia, António Onofre

In this paper we propose a new reconstruction method to explore the low mass region in the associated production of top-quark pairs ($t\bar{t}$) with a generic scalar boson ($\phi$) at the LHC. The new method of mass reconstruction shows an improved resolution of at least a factor of two in the low mass region when compared to previous methods, without the l

Yanshen Li, Kai Leong Chong, Hanieh Bazyar, Rob G. H. Lammertink

Micro and nanodroplets have many important applications such as in drug delivery, liquid-liquid extraction, nanomaterial synthesis and cosmetics. A commonly used method to generate a large number of micro or nanodroplets in one simple step is solvent exchange (also called nanoprecipitation), in which a good solvent of the droplet phase is displaced by a poor

Xuan Qin, Meizhu Liu, Yifan Hu, Christina Moo

In this paper, we propose a method that efficiently utilizes appearance features and text vectors to accurately classify political posters from other similar political images. The majority of this work focuses on political posters that are designed to serve as a promotion of a certain political event, and the automated identification of which can lead to the

Mudit Rai, Daniel Boyanovsky

We study transition rates and cross sections from first principles in a spatially flat radiation dominated cosmology. We consider a model of scalar particles to study scattering and heavy particle production from pair annihilation, drawing more general conclusions. The S-matrix formulation is ill suited to study these ubiquitous processes in a rapidly expand

John Ioannis Stavroulakis, Elena Braverman

There is a close connection between stability and oscillation of delay differential equations. For the first-order equation $$ x^{\prime}(t)+c(t)x(\tau(t))=0,~~t\geq 0, $$ where $c$ is locally integrable of any sign, $\tau(t)\leq t$ is Lebesgue measurable, $\lim_{t\rightarrow\infty}\tau(t)=\infty$, we obtain sharp results, relating the speed of oscillation a

Aniruddh Herle, Janamejaya Channegowda, Kali Naraharisetti

Electric Vehicles (EVs) are rapidly increasing in popularity as they are environment friendly. Lithium Ion batteries are at the heart of EV technology and contribute to most of the weight and cost of an EV. State of Charge (SOC) is a very important metric which helps to predict the range of an EV. There is a need to accurately estimate available battery capa

E. Zubko, E. Chornaya, M. Zheltobryukhov, A. Matkin

We measured the degree of linear polarization P of comet C/2018 V1 (Machholz-Fujikawa-Iwamoto) with the broadband Johnson V filter in mid-November of 2018. Within a radius of \r{ho}=17,000 km of the inner coma, we detected an extremely low linear polarization at phase angles from 83 to 91.2 degree and constrained the polarization maximum to Pmax = (6.8 +/- 1

Nan Chu

An open source symbolic tool for vector fields analysis 'SymFields' is developed in Python. The SymFields module is constructed upon Python symbolic module sympy, which could only conduct scaler field analysis. With SymFields module, you can conduct vector analysis for general curvilinear coordinates regardless whether it is orthogonal or not. In SymFields,

Mauro Cuevas, Mojtaba Karimi, Carlos J Zapata-Ropdriguez

The ability to control the laser modes within a subwavelength resonator is of key relevance in modern optoelectronics. This work deals with the theoretical research on optical properties of a PT--symmetric nano--scaled dimer formed by two dielectric wires, one is with loss and the other with gain, wrapped with graphene sheets. We show the existence of two no

Anne-Sophie Bonnet-Ben Dhia, Simon N. Chandler-Wilde, Sonia Fliss, Christophe Hazard

The Half-Space Matching (HSM) method has recently been developed as a new method for the solution of 2D scattering problems with complex backgrounds, providing an alternative to Perfectly Matched Layers (PML) or other artificial boundary conditions. Based on half-plane representations for the solution, the scattering problem is rewritten as a system of integ

Neil Thomas, Margaret Paczkowski

A commissioning survey of the Lookout Observatory has observed fourteen faint (V ~ 13 to 17) variables in the region of the exoplanet Kepler-8b. Three of these are variable star candidates discovered by the Asteroid Terrestrial-Impact Last Alert System (ATLAS) and confirmed here. The ATLAS survey identified 315,000 probable variables within its wide-field su

Pablo Pedregal

Non-locality is being intensively studied in various PDE-contexts and in variational problems. The numerical approximation also looks challenging, as well as the application of these models to Continuum Mechanics and Image Analysis, among other areas. Even though there is a growing body of deep and fundamental knowledge about non-locality, for variational pr

E. Picazzio, I. V. Luk'yanyk, O. V. Ivanova, E. Zubko

We report photometric observations of comet 29P/Schwassmann-Wachmann 1 made on August 12, 2016 with the broadband B, V, R and I filters and the SOAR 4.1-meter telescope (Chile). We find the comet active at that time. Enhanced images obtained in all filters reveal three radial features in the 29P/ Schwassmann-Wachmann 1 coma, regardless of the image-processin

Maddalena Dilucca, Giulio Cimini, Sergio Forcelloni, Andrea Giansanti

We study the correlation between the codon usage bias of genetic sequences and the network features of protein-protein interaction (PPI) in bacterial species. We use PCA techniques in the space of codon bias indices to show that genes with similar patterns of codon usage have a significantly higher probability that their encoded proteins are functionally con

Baiyu Peng, Yao Mu, Yang Guan, Shengbo Eben Li

Safety is essential for reinforcement learning (RL) applied in real-world situations. Chance constraints are suitable to represent the safety requirements in stochastic systems. Previous chance-constrained RL methods usually have a low convergence rate, or only learn a conservative policy. In this paper, we propose a model-based chance constrained actor-crit

Ahmet Kerem Aksoy, Mahdyar Ravanbakhsh, Begüm Demir

The development of accurate methods for multi-label classification (MLC) of remote sensing (RS) images is one of the most important research topics in RS. The MLC methods based on convolutional neural networks (CNNs) have shown strong performance gains in RS. However, they usually require a high number of reliable training images annotated with multiple land

Pushyami Kaveti, Hanumant Singh

There is a general expectation that robots should operate in urban environments often consisting of potentially dynamic entities including people, furniture and automobiles. Dynamic objects pose challenges to visual SLAM algorithms by introducing errors into the front-end. This paper presents a Light Field SLAM front-end which is robust to dynamic environmen

Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola

A wide range of machine learning applications such as privacy-preserving learning, algorithmic fairness, and domain adaptation/generalization among others, involve learning invariant representations of the data that aim to achieve two competing goals: (a) maximize information or accuracy with respect to a target response, and (b) maximize invariance or indep

Anita Behme, Apostolos Sideris

We derive the Markov-modulated generalized Ornstein-Uhlenbeck process by embedding a Markov-modulated random recurrence equation in continuous time. The obtained process turns out to be the unique solution of a certain stochastic differential equation driven by a bivariate Markov-additive process. We present this stochastic differential equation as well as i

Stefanos Tsimenidis

Fuzzy Cognitive Maps (FCMs) is a complex systems modeling technique which, due to its unique advantages, has lately risen in popularity. They are based on graphs that represent the causal relationships among the parameters of the system to be modeled, and they stand out for their interpretability and flexibility. With the late popularity of FCMs, a plethora

Shaojun Wu, Shan Jin, Dingding Wen, Donghong Han

Quantum reinforcement learning (QRL) is a promising paradigm for near-term quantum devices. While existing QRL methods have shown success in discrete action spaces, extending these techniques to continuous domains is challenging due to the curse of dimensionality introduced by discretization. To overcome this limitation, we introduce a quantum Deep Determini

Vasiliki Kondyli, Mehul Bhatt, Evgenia Spyridonos

A people-centred approach for designing large-scale built-up spaces necessitates systematic anticipation of user's embodied visuo-locomotive experience from the viewpoint of human-environment interaction factors pertaining to aspects such as navigation, wayfinding, usability. In this context, we develop a behaviour-based visuo-locomotive complexity model tha

Matteo Seclì, Tomoki Ozawa, Massimo Capone, Iacopo Carusotto

We develop a semiclassical theory of laser oscillation into a chiral edge state of a topological photonic system endowed with a frequency-dependent gain. As an archetypal model of this physics, we consider a Harper-Hofstadter lattice embedding population-inverted two-level atoms as gain material. We show that a suitable design of the spatial distribution of

Waqqas-ur-Rehman Butt, Martin Servin

This paper presents static object detection and segmentation method in videos from cluttered scenes. Robust static object detection is still challenging task due to presence of moving objects in many surveillance applications. The level of difficulty is extremely influenced by on how you label the object to be identified as static that do not establish the o