June 2020 arXiv papers — page 33

Kabgyun Jeong, Kyu-Won Park, Jaewan Kim

We employ the relative entropy as a measure to quantify the difference of eigenmodes between Hermitian and non-Hermitian systems in elliptic optical microcavities. We have found that the average value of the relative entropy in the range of the collective Lamb shift is large, while that in the range of self-energy is small. Furthermore, the weak and strong i

Md. Motlubar Rahman, M. Monir Uddin, L. S. Andallah, Mahtab Uddin

This paper focuses on exploring efficient ways to find $\mathcal{H}_2$ optimal Structure-Preserving Model Order Reduction (SPMOR) of the second-order systems via interpolatory projection-based method Iterative Rational Krylov Algorithm (IRKA). To get the reduced models of the second-order systems, the classical IRKA deals with the equivalent first-order conv

Vaidyanathan P. R., Stefan Szeider

We present a new approach for learning the structure of a treewidth-bounded Bayesian Network (BN). The key to our approach is applying an exact method (based on MaxSAT) locally, to improve the score of a heuristically computed BN. This approach allows us to scale the power of exact methods -- so far only applicable to BNs with several dozens of random variab

Florian Eisele, Michael Livesey

We construct blocks of finite groups with arbitrarily large Morita Frobenius numbers, an invariant which determines the size of the minimal field of definition of the associated basic algebra. This answers a question of Benson and Kessar. This also improves upon a result of the second author where arbitrarily large $\mathcal{O}$-Morita Frobenius numbers are

Nicola Giuliani, Martin W. Hess, Antonio DeSimone, Gianluigi Rozza

In the study of micro-swimmers, both artificial and biological ones, many-query problems arise naturally. Even with the use of advanced high performance computing (HPC), it is not possible to solve this kind of problems in an acceptable amount of time. Various approximations of the Stokes equation have been considered in the past to ease such computational e

Ádám Bácsi, Catalin Pascu Moca, Gergely Zaránd, Balázs Dóra

We investigate the stability of a Luttinger liquid, upon suddenly coupling it to a dissipative environment. Within the Lindblad equation, the environment couples to local currents and heats the quantum liquid up to infinite temperatures. The single particle density matrix reveals the fractionalization of fermionic excitations in the spatial correlations by r

Eric Z. Chen, Terrence Chen, Shanhui Sun

We propose to formulate MRI image reconstruction as an optimization problem and model the optimization trajectory as a dynamic process using ordinary differential equations (ODEs). We model the dynamics in ODE with a neural network and solve the desired ODE with the off-the-shelf (fixed) solver to obtain reconstructed images. We extend this model and incorpo

Ahmed Aziz Ezzat, Sheng Liu, Dorit S. Hochbaum, Yu Ding

Statistical quality control in semiconductor manufacturing hinges on effective diagnostics of wafer bin maps, wherein a key challenge is to detect how defective chips tend to spatially cluster on a wafer--a problem known as spatial pattern recognition. Recently, there has been a growing interest in mixed-type spatial pattern recognition--when multiple defect

Hassam Ullah Sheikh, Ladislau Bölöni

The classic DQN algorithm is limited by the overestimation bias of the learned Q-function. Subsequent algorithms have proposed techniques to reduce this problem, without fully eliminating it. Recently, the Maxmin and Ensemble Q-learning algorithms have used different estimates provided by the ensembles of learners to reduce the overestimation bias. Unfortuna

Jean-Baptiste Bouvier, Melkior Ornik

Critical systems must be designed resilient to all kinds of malfunctions. We are especially interested by the loss of control authority over actuators. This malfunction considers actuators producing uncontrolled and possibly undesirable inputs. We investigate the design of resilient linear systems capable of reaching their target even after such a malfunctio

Selomit Ramirez-Uribe, Roger J. Hernandez-Pinto, German Rodrigo, German F. R. Sborlini

The perturbative approach to quantum field theories has made it possible to obtain incredibly accurate theoretical predictions in high-energy physics. Although various techniques have been developed to boost the efficiency of these calculations, some ingredients remain specially challenging. This is the case of multiloop scattering amplitudes that constitute

Esther Puyol-Antón, Chen Chen, James R. Clough, Bram Ruijsink

Advances in deep learning (DL) have resulted in impressive accuracy in some medical image classification tasks, but often deep models lack interpretability. The ability of these models to explain their decisions is important for fostering clinical trust and facilitating clinical translation. Furthermore, for many problems in medicine there is a wealth of exi

Babette de Wolff, Francesca Scarabel, Sjoerd Verduyn Lunel, Odo Diekmann

Pseudospectral approximation reduces DDE (delay differential equations) to ODE (ordinary differential equations). Next one can use ODE tools to perform a numerical bifurcation analysis. By way of an example we show that this yields an efficient and reliable method to qualitatively as well as quantitatively analyse certain DDE. To substantiate the method, we

Danfeng Hong, Naoto Yokoya, Gui-Song Xia, Jocelyn Chanussot

This paper addresses the problem of semi-supervised transfer learning with limited cross-modality data in remote sensing. A large amount of multi-modal earth observation images, such as multispectral imagery (MSI) or synthetic aperture radar (SAR) data, are openly available on a global scale, enabling parsing global urban scenes through remote sensing imager

Michael Rotman, Rafi Brada, Israel Beniaminy, Sangtae Ahn

Motion artefacts created by patient motion during an MRI scan occur frequently in practice, often rendering the scans clinically unusable and requiring a re-scan. While many methods have been employed to ameliorate the effects of patient motion, these often fall short in practice. In this paper we propose a novel method for removing motion artefacts using a

Kara A. Ponder, W. Michael Wood-Vasey, Anja Weyant, Nathan T. Barton

We analyze 143 Type Ia supernovae (SNeIa) observed in $H$ band (1.6-1.8 $μ$m) and find SNeIa are intrinsically brighter in $H$-band with increasing host galaxy stellar mass. We find SNeIa in galaxies more massive than $10^{10.43} M_{\odot}$ are $0.13 \pm 0.04$ mag brighter in $H$ than SNeIa in less massive galaxies. The same set of SNeIa observed at optical

Kaiyuan Yao, Nathan R. Finney, Jin Zhang, Samuel L. Moore

Broken symmetries induce strong nonlinear optical responses in materials and at interfaces. Twist angle can give complete control over the presence or lack of inversion symmetry at a crystal interface, and is thus an appealing knob for tuning nonlinear optical systems. In contrast to conventional nonlinear crystals with rigid lattices, the weak interlayer co

Farsane Tabataba-Vakili, Blandine Alloing, Benjamin Damilano, Hassen Souissi

Ultraviolet microdisk lasers are integrated monolithically into photonic circuits using a III-nitride on silicon platform with gallium nitride (GaN) as the main waveguiding layer. The photonic circuits consist of a microdisk and a pulley waveguide terminated by out-coupling gratings. We measure quality factors up to 3500 under continuous-wave excitation. Las

Lucas Zimmer, Marius Lindauer, Frank Hutter

While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, a recent trend in AutoML is to focus on neural architecture search. In this paper, we introduce Auto-PyTorch, which brings the best of these two worlds together by jointly and robustly optimizing the architecture of networks and the training hyperparameter

John Richards, David Piorkowski, Michael Hind, Stephanie Houde

As AI models and services are used in a growing number of highstakes areas, a consensus is forming around the need for a clearer record of how these models and services are developed to increase trust. Several proposals for higher quality and more consistent AI documentation have emerged to address ethical and legal concerns and general social impacts of suc

H. W. L. Naus, H. Polinder

Quantum computational experiments exploiting Noisy Intermediate-Scale Quantum (NISQ) devices to demonstrate violation of a Bell inequality are proposed. They consist of running specified quantum algorithms on few-qubit computers. If such a device assures entanglement and performs single-shot measurements, the detection loophole is avoided. Four concise quant

Eric J. Hanson, Job D. Rock

We prove that pointwise finite-dimensional S^1 persistence modules over an arbitrary field decompose uniquely, up to isomorphism, into the direct sum of a bar code and finitely-many Jordan cells. These persistence modules have also been called angle-valued or circular persistence modules. We allow either a cyclic order or partial order on S^1 and do not have

Zhiheng Li, Geemi P. Wellawatte, Maghesree Chakraborty, Heta A. Gandhi

The selection of coarse-grained (CG) mapping operators is a critical step for CG molecular dynamics (MD) simulation. It is still an open question about what is optimal for this choice and there is a need for theory. The current state-of-the art method is mapping operators manually selected by experts. In this work, we demonstrate an automated approach by vie

Juntao Wang, Ningzhong Shi, Xue Zhang, Gongjun Xu

Cognitive diagnosis models (CDMs) are useful statistical tools to provide rich information relevant for intervention and learning. As a popular approach to estimate and make inference of CDMs, the Markov chain Monte Carlo (MCMC) algorithm is widely used in practice. However, when the number of attributes, $K$, is large, the existing MCMC algorithm may become

Benjamin Steinberg, Nóra Szakács

In this paper, we prove that the algebra of an étale groupoid with totally disconnected unit space has a simple algebra over a field if and only if the groupoid is minimal and effective and the only function of the algebra that vanishes on every open subset is the null function. Previous work on the subject required the groupoid to be also topologically prin

Alexandre Arsenault, Frédéric Sirois, Francesco Grilli

The H-formulation, used abundantly for the simulation of high temperature superconductors, has shown to be a very versatile and easily implementable way of modeling electromagnetic phenomena involving superconducting materials. However, the simulation of a full vector field in current-free domains unnecessarily adds degrees of freedom to the model, thereby i

Francis Williams, Matthew Trager, Joan Bruna, Denis Zorin

We present Neural Splines, a technique for 3D surface reconstruction that is based on random feature kernels arising from infinitely-wide shallow ReLU networks. Our method achieves state-of-the-art results, outperforming recent neural network-based techniques and widely used Poisson Surface Reconstruction (which, as we demonstrate, can also be viewed as a ty

Joris Bierkens, Sebastiano Grazzi, Kengo Kamatani, Gareth Roberts

This paper introduces the Boomerang Sampler as a novel class of continuous-time non-reversible Markov chain Monte Carlo algorithms. The methodology begins by representing the target density as a density, $e^{-U}$, with respect to a prescribed (usually) Gaussian measure and constructs a continuous trajectory consisting of a piecewise elliptical path. The meth

Mariarita Murabito, Juie Shetye, Marco Stangalini, Erwin Verwichte

Vortex structures in the Sun's chromosphere are believed to channel energy between different layers of the solar atmosphere. We investigate the nature and dynamics of two small-scale quiet-Sun rotating structures in the chromosphere. We analyse two chromospheric structures that show clear rotational patterns in spectropolarimetric observations taken with

Justin Dove, Jeffrey H. Shapiro

Growing interest in non-line-of-sight (NLoS) imaging, colloquially referred to as "seeing around corners", has led to the development of phasor-field ($\mathcal{P}$-field) imaging, wherein the field envelope of amplitude-modulated spatially-incoherent light is manipulated like an optical wave to directly probe a space that is otherwise shielded from

Lingyu Liu

In this paper we study a free boundary problem for a ratio-dependent predator-prey system in one space dimension, with the free boundary only caused by the prey. The long time behaviors of solution are discussed. Then we establish a spreading-vanishing dichotomy and the criteria for spreading and vanishing. Finally, when spreading occurs, an accurate limit o

Abdallah Daddi-Moussa-Ider

A deep understanding of the physical interactions between nanoparticles and target cell membranes is important in designing efficient nanocarrier systems for drug delivery applications. Here, we present a theoretical framework to describe the hydrodynamic flow field induced by a point-force singularity (Stokeslet) directed parallel to a finite-sized elastic

Ellen Powell

This review-style article presents an overview of recent progress in constructing and studying critical Gaussian multiplicative chaos. A proof that the critical measure in any dimension can be obtained as a limit of subcritical measures is given.

Yali Shao, Jeff Wagg, Ran Wang, Chris L. Carilli

We present Giant Metrewave Radio Telescope (GMRT) 323 MHz radio continuum observations toward 13 radio-loud quasars at $z>5$, sampling the low-frequency synchrotron emission from these objects. Among the 12 targets successfully observed, we detected 10 above $4σ$ significance, while 2 remain undetected. All of the detected sources appear as point sources. Co

Xiang Yu, Yuchong Zhang, Zhou Zhou

This paper studies competitions with rank-based reward among a large number of teams. Within each sizable team, we consider a mean-field contribution game in which each team member contributes to the jump intensity of a common Poisson project process; across all teams, a mean field competition game is formulated on the rank of the completion time, namely the

Heinrich Küttler, Nantas Nardelli, Alexander H. Miller, Roberta Raileanu

Progress in Reinforcement Learning (RL) algorithms goes hand-in-hand with the development of challenging environments that test the limits of current methods. While existing RL environments are either sufficiently complex or based on fast simulation, they are rarely both. Here, we present the NetHack Learning Environment (NLE), a scalable, procedurally gener

Pietro Colangelo, Fulvia De Fazio, Francesco Loparco

Inclusive semileptonic decays of beauty baryons are studied using the heavy quark expansion to ${\cal O}(1/m_b^3)$, at leading order in $α_s$. The case of a polarized decaying baryon is examined, with reference to $Λ_b$. An extension of the Standard Model effective Hamiltonian inducing $b \to U \ell {\bar ν}_ \ell$ transitions ($U=u,\,c$ and $\ell=e,\,μ,\,τ$

Lin Yan, D. Perley, S. Schulze, R. Lunnan

Helium is expected to be present in the ejecta of some hydrogen-poor superluminous supernovae (SLSN-I). However, so far only one event, PTF10hgi has been identified with He features in its photospheric spectra (Quimby et al. 2018). We present the discovery of a new He-rich SLSN-I, ZTF19aawfbtg (SN2019hge) at $z=0.0866$. This event has more than 10 optical sp

Sreeya Ghosh, Sudhakar Sahoo, Sk. Sarif Hassan, Jayanta Kumar Das

Cellular Automaton (CA) and an Integral Value Transformation (IVT) are two well established mathematical models which evolve in discrete time steps. Theoretically, studies on CA suggest that CA is capable of producing a great variety of evolution patterns. However computation of non-linear CA or higher dimensional CA maybe complex, whereas IVTs can be manipu

Saubhik Sarkar, Tomasz Sowiński

We study the effect of inter-component interactions on the dynamical properties of quantum walkers. We consider the simplest situation of two indistinguishable non-interacting walkers on a tilted optical lattice interacting with a walker from a different component. The mediated effect of the third particle is then analyzed in the backdrop of various controll

Joon Sern Lee, Gui Peng David Yam, Jin Hao Chan

Homoglyph attacks are a common technique used by hackers to conduct phishing. Domain names or links that are visually similar to actual ones are created via punycode to obfuscate the attack, making the victim more susceptible to phishing. For example, victims may mistake "|inkedin.com" for "linkedin.com" and in the process, divulge personal d

Nicolas Kovensky, Andreas Schmitt

We point out a new configuration in the Witten-Sakai-Sugimoto model, allowing baryons in the pointlike approximation to coexist with fundamental quarks. The resulting phase is a holographic realization of quarkyonic matter, which is predicted to occur in QCD at a large number of colors, and possibly plays a role in real-world QCD as well. We find that hologr

Abdolkarim Saeedi, Maryam Saeedi, Arash Maghsoudi

The corona virus is already spread around the world in many countries, and it has taken many lives. Furthermore, the world health organization (WHO) has announced that COVID-19 has reached the global epidemic stage. Early and reliable diagnosis using chest CT-scan can assist medical specialists in vital circumstances. In this work, we introduce a computer ai

Xingjun Ma, Linxi Jiang, Hanxun Huang, Zejia Weng

Evaluating the robustness of a defense model is a challenging task in adversarial robustness research. Obfuscated gradients have previously been found to exist in many defense methods and cause a false signal of robustness. In this paper, we identify a more subtle situation called Imbalanced Gradients that can also cause overestimated adversarial robustness.

David Méndez

We raise the problem of realisability of rings as $\{X,X\}$ the ring of stable homotopy classes of self-maps of a space $X$. By focusing on $A_n^2$-polyhedra, we show that the direct sum of three endomorphism rings of abelian groups, one of which must be free, is realisable as $\{X,X\}$ modulo the acyclic maps. We also show that $\mathbb{F}_p^3$ is not reali

Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma

Stochastic gradient descent (SGD) and its variants are mainstream methods to train deep neural networks. Since neural networks are non-convex, more and more works study the dynamic behavior of SGD and the impact to its generalization, especially the escaping efficiency from local minima. However, these works take the over-simplified assumption that the covar

Alan C. Santos, Celso J. Villas-Boas, Romain Bachelard

We propose a variational principle to compute a quantum adiabatic brachistochrone (QAB) for open systems. Using the notion of "adiabatic speed" based on the energy gaps, we derive a Lagrangian associated to the functional measuring the time spent to achieve adiabatic behavior, which in turn allows us to perform the optimization. The QAB is illustrate

Rafael da Camara, Marcelo Marinho, Suzana Sampaio, Saulo Cadete

The dissipation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions, affecting over 100 countries in a couple of weeks. The evolution of the disease and its economic impact is highly uncertain, which brings challenges for newly created software companies. Software startups are companies that create innova

Lanqing Guo, Zhiyuan Zha, Saiprasad Ravishankar, Bihan Wen

Constructing effective image priors is critical to solving ill-posed inverse problems in image processing and imaging. Recent works proposed to exploit image non-local similarity for inverse problems by grouping similar patches and demonstrated state-of-the-art results in many applications. However, compared to classic methods based on filtering or sparsity,

Yong Chen, Lu Wang, Jiajia Hu, Mingbin Ye

Fall event detection, as one of the greatest risks to the elderly, has been a hot research issue in the solitary scene in recent years. Nevertheless, there are few researches on the fall event detection in complex background. Different from most conventional background subtraction methods which depend on background modeling, Mask R-CNN method based on deep l

Gwendoline De Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michèle Sebag

Recent advances in deep learning from probability distributions successfully achieve classification or regression from distribution samples, thus invariant under permutation of the samples. The first contribution of the paper is to extend these neural architectures to achieve invariance under permutation of the features, too. The proposed architecture, calle

Artūrs Bērziņš, Jan Helmig, Fabian Key, Stefanie Elgeti

In recent years, numerical methods in industrial applications have evolved from a pure predictive tool towards a means for optimization and control. Since standard numerical analysis methods have become prohibitively costly in such multi-query settings, a variety of reduced order modeling (ROM) approaches have been advanced towards complex applications. In t

Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens

By using the framework of Determinantal Point Processes (DPPs), some theoretical results concerning the interplay between diversity and regularization can be obtained. In this paper we show that sampling subsets with kDPPs results in implicit regularization in the context of ridgeless Kernel Regression. Furthermore, we leverage the common setup of state-of-t

Nick Whiteley, Lorenzo Rimella

We introduce a new method for inference in stochastic epidemic models which uses recursive multinomial approximations to integrate over unobserved variables and thus circumvent likelihood intractability. The method is applicable to a class of discrete-time, finite-population compartmental models with partial, randomly under-reported or missing count observat

Jaewoo Park, Yeseul Jeon, Minsuk Shin, Minjeong Jeon

Longitudinal item response data are common in social science, educational science, and psychology, among other disciplines. Studying the time-varying relationships between items is crucial for educational assessment or designing marketing strategies from survey questions. Although dynamic network models have been widely developed, we cannot apply them direct

Duo Xu, Matthias Heil, Thomas Seeböck, Marc Avila

Interactions between fluids and elastic solids are ubiquitous in application ranging from aeronautical and civil engineering to physiological flows. Here we study the pulsatile flow through a two-dimensional Starling resistor as a simple model for unsteady flow in elastic vessels. We numerically solve the equations governing the flow and the large-displaceme

Jonathan Wermelinger

We show that the moduli space of positive Ricci curvature metrics on all the total spaces of $S^7$-bundles over $S^8$ which are rational homology spheres has infinitely many path components. Furthermore, we carry out the diffeomorphism classification of quotients of Milnor spheres by a certain involution and show that the moduli space of metrics of non-negat

Petr Opletal, Jaroslav Valenta, Petr Proschek, Vladimír Sechovský

UCoGa and URhGa, two isostructural compounds show opposite signs of the initial response of Curie temperature to applied hydrostatic premenssure. To determine the physical origin of this contradiction the magnetization data measured with respect to temperature, magnetic field and hydrostatic pressure were analyzed in the framework of the Takahashi's spin

Eugenio Angriman, Maria Predari, Alexander van der Grinten, Henning Meyerhenke

The ubiquity of massive graph data sets in numerous applications requires fast algorithms for extracting knowledge from these data. We are motivated here by three electrical measures for the analysis of large small-world graphs $G = (V, E)$ -- i.e., graphs with diameter in $O(\log |V|)$, which are abundant in complex network analysis. From a computational po

Joshua J. Guanzon, Austin P. Lund, Timothy C. Ralph

We describe a multi-mode passive linear optical network which emulates the two-photon number statistics of a beam splitter, irrespective on where the two photons enter the network. This is done by firstly defining general properties that the generator of the network matrix must fulfil. We then show that the network's effective transmission coefficient ca

Lior Zarfaty, Eli Barkai, David A. Kessler

We consider the extreme value statistics of $N$ independent and identically distributed random variables, which is a classic problem in probability theory. When $N\to\infty$, fluctuations around the maximum of the variables are described by the Fisher-Tippett-Gnedenko theorem, which states that the distribution of maxima converges to one out of three limitin

Brett C. Addison, Jonathan Horner, Robert A. Wittenmyer, Alexis Heitzmann

We report measurements of the sky-projected spin-orbit angle for AU\,Mic\,b, a Neptune-size planet orbiting a very young ($\sim20$\,Myr) nearby pre-main sequence M dwarf star which also hosts a bright, edge-on, debris disk. The planet was recently discovered from preliminary analysis of radial velocity observations and confirmed to be transiting its host sta

Huaiyang Huang, Haoyang Ye, Yuxiang Sun, Ming Liu

Incorporating prior structure information into the visual state estimation could generally improve the localization performance. In this letter, we aim to address the paradox between accuracy and efficiency in coupling visual factors with structure constraints. To this end, we present a cross-modality method that tracks a camera in a prior map modelled by th

Antoine Douai

We study the interplay between Sabbah's mixed Hodge structure for regular functions and Ehrhart theory for polytopes. To this end, we analyze the properties of the Poincaré polynomial of the Hodge filtration of this mixed Hodge structure.

Vasileios Karavias, Ben Day, Pietro Liò

Neural networks used for multi-interaction trajectory reconstruction lack the ability to estimate the uncertainty in their outputs, which would be useful to better analyse and understand the systems they model. In this paper we extend the Factorised Neural Relational Inference model to output both a mean and a standard deviation for each component of the pha

Yuki M. Asano, Mandela Patrick, Christian Rupprecht, Andrea Vedaldi

A large part of the current success of deep learning lies in the effectiveness of data -- more precisely: labelled data. Yet, labelling a dataset with human annotation continues to carry high costs, especially for videos. While in the image domain, recent methods have allowed to generate meaningful (pseudo-) labels for unlabelled datasets without supervision

Lijun Bo, Huafu Liao, Xiang Yu

This paper studies the finite horizon portfolio management by optimally tracking a ratcheting capital benchmark process. It is assumed that the fund manager can dynamically inject capital into the portfolio account such that the total capital dominates a non-decreasing benchmark floor process at each intermediate time. The tracking problem is formulated to m

Virginia Bordignon, Vincenzo Matta, Ali H. Sayed

This work addresses the problem of sharing partial information within social learning strategies. In traditional social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate information from private observations to form their beliefs over a set of hypotheses; second, a

Sevdzhan Hakkaev, Milena Stanislavova, Atanas Stefanov

We study the periodic cubic derivative non-linear Schrödinger equation (dNLS) and the (focussing) quintic non-linear Schrödinger equation (NLS). These are both $L^2$ critical dispersive models, which exhibit threshold type behavior, when posed on the line ${\mathbb R}$. We describe the (three parameter) family of non-vanishing bell-shaped solutions for the p

Cunzhuo Zhao, Yuanwei Liu, Yunlong Cai, Minjian Zhao

In this work, we explore the potential benefits of deploying unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) with sub-6GHz band and small cells terrestrial base stations (TBSs) with millimeter wave (mmWave) band in a hybrid heterogeneous networks (HetNets). A flexible non-orthogonal multiple access (NOMA) based user association policy is propo

Daniel Gromada

We study glued tensor and free products of compact matrix quantum groups with cyclic groups -- so-called tensor and free complexifications. We characterize them by studying their representation categories and algebraic relations. In addition, we generalize the concepts of global colourization and alternating colourings from easy quantum groups to arbitrary c

E. Capozzi, E. Alsina Ballester, L. Belluzzi, M. Bianda

Several strong resonance lines, such as H I Ly-$α$, Mg II k, Ca II K, Ca I 4227 Å\, which are characterized by deep and broad absorption profiles in the solar intensity spectrum, show conspicuous linear scattering polarization signals when observed in quiet regions close to the solar limb. Such signals show a characteristic triplet-peak structure, with a sha

Zijian Wang, Mylene Pischella, Luc Vandendorpe

This paper considers uplink multiple access (MA) transmissions, where the MA technique is adaptively selected between Non Orthogonal Multiple Access (NOMA) and Orthogonal Multiple Access (OMA). Two types of users, namely Internet of Things (IoT) and enhanced mobile broadband (eMBB) coexist with different metrics to be optimized, energy efficiency (EE) for Io

Kentaro Nakamura

In this article, we construct zeta morphisms for the universal deformations of odd absolutely irreducible two dimensional mod p Galois representations satisfying some mild assumptions, and prove that our zeta morphisms interpolate Kato's zeta morphisms for Galois representations associated to Hecke eigen cusp newforms. The existence of such morphisms was

Andreas Pusch, Milos Dubajic, Michael P. Nielsen, Gavin J. Conibeer

Hot carrier solar cells promise theoretical power conversion efficiencies far beyond the single junction limit. However, practical implementations of hot carrier solar cells have lagged far behind those theoretical predictions. Reciprocity relations for electro-luminescence from conventional single junction solar cells have been extremely successful in drivi

Nadav Barak, Sivan Sabato

We consider a novel challenge: approximating a distribution without the ability to randomly sample from that distribution. We study how such an approximation can be obtained using *weight queries*. Given some data set of examples, a weight query presents one of the examples to an oracle, which returns the probability, according to the target distribution, of

Dan Frumin, Robbert Krebbers, Lars Birkedal

We present a new version of ReLoC: a relational separation logic for proving refinements of programs with higher-order state, fine-grained concurrency, polymorphism and recursive types. The core of ReLoC is its refinement judgment $e \precsim e' : τ$, which states that a program $e$ refines a program $e'$ at type $τ$. ReLoC provides type-directed str

Daniel B. Wilson, Francis G. Woodhouse, Matthew J. Simpson, Ruth E. Baker

Transport in crowded, complex environments occurs across many spatial scales. Geometric restrictions can hinder the motion of individuals and, combined with crowding between individuals, can have drastic effects on global transport phenomena. However, in general, the interplay between crowding and geometry in complex real-life environments is poorly understo

Bayan Al Muhander, Jason Wiese, Omer Rana, Charith Perera

The balance between protecting users' privacy while providing cost-effective devices that are functional and usable is a key challenge in the burgeoning Internet of Things (IoT) industry. While in traditional desktop and mobile contexts the primary user interface is a screen, in IoT screens are rare or very small, which invalidate most of the traditional

Anurag Singh

For $r\geq 1$, the $r$-matching complex of a graph $G$, denoted $M_r(G)$, is a simplicial complex whose faces are the subsets $H \subseteq E(G)$ of the edge set of $G$ such that the degree of any vertex in the induced subgraph $G[H]$ is at most $r$. In this article, we give a closed form formula for the homotopy type of the $(n-2)$-matching complex of comple

Thorsten Beckmann, Georg Oberdieck

We study the equivariant category associated to a finite group action on the derived category of coherent sheaves of a smooth projective variety. We discuss decompositions of the equivariant category and faithful actions, prove the existence of a Serre functor, give a criterion for the equivariant category to be Calabi--Yau, and describe an obstruction for a

Muhammad Mohtasim Sajjad, Dhammika Jayalath, Yu-Chu Tian, Carlos J. Bernardos

The 3GPP has provided its first standard specifications for network slicing in the recent Release 15. The fundamental principles are specified which constitute the standard network slicing framework. These specifications, however, lack the session continuation mechanisms among slices, which is a fundamental requirement to achieve inter-slice mobility. In thi

Georgios Aliferis, Vasilios Zarikas

A successful baryogenesis mechanism is proposed in the cosmological framework of Brans-Dicke modified gravity. Primordial black holes with small mass are produced at the end of the Brans-Dicke field domination era. The Hawking radiation reheats a spherical region around every black hole to a high temperature and the electroweak symmetry is restored there. A

Nick E. Mavromatos, Alex Soto

We extend the study of a previous publication \cite{amsot} on Schwinger-Dyson dynamical mass generation for fermions and pseudoscalar fields (axion-like particles (ALP)), in field theories containing Yukawa type interactions between the fermions and ALPs, by incorporating anomaly terms and/or (constant) axial background fields. The latter are linked to some

Francisco Cruz, Richard Dazeley, Peter Vamplew, Ithan Moreira

Robotic systems are more present in our society everyday. In human-robot environments, it is crucial that end-users may correctly understand their robotic team-partners, in order to collaboratively complete a task. To increase action understanding, users demand more explainability about the decisions by the robot in particular situations. Recently, explainab

S. Hengst, J. P. Marshall, J. Horner, S. C. Marsden

Asteroids and comets (planetesimals) are created in gas- and dust-rich protoplanetary discs. The presence of these planetesimals around main-sequence stars is usually inferred from the detection of excess continuum emission at infrared wavelengths from dust grains produced by destructive processes within these discs. Modelling of the disc structure and dust

Daisuke Ishii, Saito Fujii

One of the effective model checking methods is to utilize the efficient decision procedure of SAT (or SMT) solvers. In a SAT-based model checking, a system and its property are encoded into a set of logic formulas and the safety is checked based on the satisfiability of the formulas. As the encoding methods are improved and crafted (e.g., k-induction and IC3

Yaxiong Yuan, Lei Lei, Thang Xuan Vu, Symeon Chatzinotas

In unmanned aerial vehicle (UAV) applications, the UAV's limited energy supply and storage have triggered the development of intelligent energy-conserving scheduling solutions. In this paper, we investigate energy minimization for UAV-aided communication networks by jointly optimizing data-transmission scheduling and UAV hovering time. The formulated pro

S. Carolan, A. A. Vidotto, P. Plavchan, C. Villarreal D'Angelo

Here, we study the dichotomy of the escaping atmosphere of the newly discovered close-in exoplanet AU Mic b. On one hand, the high EUV stellar flux is expected to cause a strong atmospheric escape in AU Mic b. On the other hand, the wind of this young star is believed to be very strong, which could reduce or even inhibit the planet's atmospheric escape.

László Csató

This paper investigates the fairness of the 2018 FIFA World Cup qualifying competition via Monte Carlo simulations. The qualifying probabilities are calculated for 102 nations, all teams except for African and European countries. A method is proposed to quantify the degree of unfairness. Although the qualifications within four FIFA confederations are constru

Joel Friedman, Doron Puder

The main goal of this note is to illustrate the advantage of analyzing the non-backtracking spectrum of a regular graph rather than the ordinary spectrum. We show that by switching to non-backtracking spectrum, the method of proof used in [Puder 2015, arXiv::1212.5216] yields a bound of $2\sqrt{d-1}+\frac{2}{\sqrt{d-1}}$ instead of the original $2\sqrt{d-1}+

Fabien Pazuki, Martin Widmer

We prove a new Bertini-type Theorem with explicit control of the genus, degree, height, and the field of definition of the constructed curve. As a consequence we provide a general strategy to reduce certain height and rank estimates on abelian varieties over a number field $K$ to the case of jacobian varieties defined over a suitable extension of $K$.

Bin Zhu

A positive semidefinite Toeplitz matrix, which often arises as the finite covariance matrix of a stationary random process, can be decomposed as the sum of a nonnegative multiple of the identity corresponding to a white noise, and a singular term corresponding to a purely deterministic process. Moreover, the singular nonnegative Toeplitz matrix admits a uniq

Xingwen Zheng, Ningzhe Hou, Pascal Johannes Daniel Dinjens, Ruifeng Wang

Novel robotic grippers have captured increasing interests recently because of their abilities to adapt to varieties of circumstances and their powerful functionalities. Differing from traditional gripper with mechanical components-made fingers, novel robotic grippers are typically made of novel structures and materials, using a novel manufacturing process. I

Alexander A. Mushtukov, Valery F. Suleimanov, Sergey S. Tsygankov, Simon Portegies Zwart

It has been recently discovered that the transition of X-ray pulsars to the low luminosity state ($L\lesssim10^{35}\,{\rm erg\,s^{-1}}$) is accompanied by a dramatic spectral change. Namely, the typical power-law-like spectrum with high energy cutoff transforms into a two-component structure with a possible cyclotron absorption feature on top of it. It was p

Mark Kelbert, Harold A. Moreno-Franco

This paper studies {a} mixed singular/switching stochastic control problem for a multidimensional diffusion with multiples regimes on a bounded domain. Using probabilistic, partial differential equation (PDE) and penalization techniques, we show that the value function associated with this problem agrees with the solution to a Hamilton-Jacobi-Bellman (HJB) e

Celestine Mendler-Dünner, Aurelien Lucchi

We study preconditioned gradient-based optimization methods where the preconditioning matrix has block-diagonal form. Such a structural constraint comes with the advantage that the update computation is block-separable and can be parallelized across multiple independent tasks. Our main contribution is to demonstrate that the convergence of these methods can

Toru Nakashika, Kohei Yatabe

In audio applications, one of the most important representations of audio signals is the amplitude spectrogram. It is utilized in many machine-learning-based information processing methods including the ones using the restricted Boltzmann machines (RBM). However, the ordinary Gaussian-Bernoulli RBM (the most popular RBM among its variations) cannot directly

Yuji Shirai, Kazunari Hashimoto, Ryuta Tezuka, Chikako Uchiyama

We study a limit cycle of a quantum Otto engine whose each cycle consists of two finite-time quantum isochoric (heating or cooling) processes and two quantum adiabatic work-extracting processes. Considering a two-level system as a working substance that weakly interacts with two reservoirs comprising an infinite number of bosons, we investigate the non-Marko

Ryan Donnelly, Matthew Lorig

We consider the problem of maximizing portfolio value when an agent has a subjective view on asset value which differs from the traded market price. The agent's trades will have a price impact which affect the price at which the asset is traded. In addition to the agent's trades affecting the market price, the agent may change his view on the asset&#