November 2019 arXiv papers — page 24

Juan Cala, Patrik Lundström, Héctor Pinedo

In a previous article (see \cite{CNP}), we introduced and analyzed ring-theoretic properties of object unital $\mathcal{G}$-graded rings $R$, where $\mathcal{G}$ is a groupoid. In the present article, we analyze the category $\grmod$ of unitary $\G$-graded modules over such rings. Following ideas developed earlier by one of the authors in \cite{lundstrom2004

Chang-Yao Liao, Xian-Ting Liang

In this paper we derive the Lindblad and Redfield forms with and without secular approximation from the Born-Markov master equation for open quantum systems. The spectral correlation tensor of bath (the Fourier transform of the bath correlation function) and then the coefficients in the two forms of the master equation are reevaluated according to the scheme

Gang Wu1, Guodong Zhao, Yidong Song

State Machine Replication (SMR) is a fundamental approach to designing service with fault tolerance. However, its requirement for the deterministic execution of transactions often results in single-threaded replicas, which cannot fully exploit the multicore capabilities of today's processors. Therefore, parallel SMR has become a hot topic of recent research.

Xiaobo Wang, Shifeng Zhang, Shuo Wang, Tianyu Fu

Face recognition has witnessed significant progress due to the advances of deep convolutional neural networks (CNNs), the central task of which is how to improve the feature discrimination. To this end, several margin-based (\textit{e.g.}, angular, additive and additive angular margins) softmax loss functions have been proposed to increase the feature margin

Kewei Zhang

Relying on the recent work of Liu-Sz\'ekelyhidi we give a weak asymptotic estimate for the Bergman kernels of polarized K\"ahler manifolds with Ricci lower bound and Sobolev constant upper bound. We will also give a simple proof for the partial $C^0$ estimate along the (generalized) K\"ahler-Ricci flow on Fano manifolds.

Jiewen Xiao, Yuxin Wang, Xiang Feng, Dominik Legut

Here, we have identified the monolayer phase of Bi2O2Se as a promising two-dimensional semiconductor with ultra-high carrier mobility and giant electric polarization. Due to the strong reconstruction originated from the interlayer electrostatic force, we have applied structure prediction algorithms to explore the crystalline geometry of Bi2O2Se monolayer wit

Vladimir Kornijcuk, Dohun Kim, Guhyun Kim, Doo Seok Jeong

We propose a model for synaptic plasticity based on a calcium signaling cascade. The model simplifies the full signaling pathways from a calcium influx to the phosphorylation (potentiation) and dephosphorylation (depression) of glutamate receptors that are gated by fictive C1 and C2 catalysts, respectively. This model is based on tangible chemical reactions,

J. S. Rechy-García, M. A. Guerrero, S. Duarte Puertas, Y. -H. Chu

A significant fraction of planetary nebulae (PNe) exhibit collimated outflows, distinct narrow kinematical components with notable velocity shifts with respect to the main nebular shells typically associated with low-ionization compact knots and linear or precessing jet-like features. We present here a spatio-kinematical investigation of a sample of twelve P

Xiaoyi Zhang, Rodoniki Athanasiadou, Narges Razavian

Twitter data has been shown broadly applicable for public health surveillance. Previous public health studies based on Twitter data have largely relied on keyword-matching or topic models for clustering relevant tweets. However, both methods suffer from the short-length of texts and unpredictable noise that naturally occurs in user-generated contexts. In res

Yang Wang, Yang Cao, Zheng-Jun Zha, Jing Zhang

Contrast enhancement and noise removal are coupled problems for low-light image enhancement. The existing Retinex based methods do not take the coupling relation into consideration, resulting in under or over-smoothing of the enhanced images. To address this issue, this paper presents a novel progressive Retinex framework, in which illumination and noise of

Han Shi, Haozheng Fan, James T. Kwok

The (variational) graph auto-encoder and its variants have been popularly used for representation learning on graph-structured data. While the encoder is often a powerful graph convolutional network, the decoder reconstructs the graph structure by only considering two nodes at a time, thus ignoring possible interactions among edges. On the other hand, struct

Shun Xi, Jinlu Liu, Arjun Valiya Parambathu, Yuchong Zhang

In this work we present an efficient numerical algorithm for the solution of interfacial statistical associating fluid theory (iSAFT) in cylindrical geometry to facilitate the study of inhomogeneous fluids having curvatures. The new solution algorithm is shown to have a better time scaling than the elliptic function method by Malijevsky, and the transform me

Yixuan Sun, Pejman Sanaei, Lou Kondic, Linda J. Cummings

Pleated membrane filters, which offer larger surface area to volume ratios than unpleated membrane filters, are used in a wide variety of applications. However, the performance of the pleated filter, as characterized by a flux-throughput plot, indicates that the equivalent unpleated filter provides better performance under the same pressure drop. Earlier wor

Pingchuan Ma, Yao Zhou, Yu Lu, Wei Zhang

3D CNN shows its strong ability in learning spatiotemporal representation in recent video recognition tasks. However, inflating 2D convolution to 3D inevitably introduces additional computational costs, making it cumbersome in practical deployment. We consider whether there is a way to equip the conventional 2D convolution with temporal vision no requiring e

Priti Gupta, Haruka Suzuki, Hirotada Okawa, Kei-ichi Maeda

We study gravitational waves from a hierarchical three-body system up to first-order postNewtonian approximation. Under certain conditions, the existence of a nearby third body can cause periodic exchange between eccentricity of an inner binary and relative inclination, known as Kozai-Lidov oscillations. We analyze features of the waveform from the inner bin

Shilin Huang, Kenneth R. Brown

We study a class of gauge fixings of the Bacon-Shor code at the circuit level, which includes a subfamily of generalized surface codes. We show that for these codes, fault tolerance can be achieved by direct measurements of the stabilizers. By simulating our fault-tolerant scheme under biased noise, we show the possibility of optimizing the performance of th

Jiyuan Zhang, Mario Kieburg, Peter J. Forrester

The randomised Horn problem, in both its additive and multiplicative version, has recently drawn increasing interest. Especially, closed analytical results have been found for the rank-1 perturbation of sums of Hermitian matrices and products of unitary matrices. We will generalise these results to rank-1 perturbations for products of positive definite Hermi

Moritz Linkmann, Manuel Hohmann, Bruno Eckhardt

The occurrence of system-scale coherent structures, so-called condensates, is a well-known phenomenon in two-dimensional turbulence. Here, the transition to condensate formation is investigated as a function of the magnitude of the force and for different types of forcing. Random forces with constant mean energy input lead to a supercritical transition, whil

Hajir Roozbehani, Yury Polyanskiy

We study a problem of constructing codes that transform a channel with high bit error rate (BER) into one with low BER (at the expense of rate). Our focus is on obtaining codes with smooth ("graceful'') input-output BER curves (as opposed to threshold-like curves typical for long error-correcting codes). This paper restricts attention to binary erasure chann

Chia-Min Lin

The swampland criteria put significant constraints on inflation models. In this paper, I show that hilltop inflation on the brane may provide an initial condition for hilltop inflation and produce topological eternal inflation without violating the swampland distance and refined de Sitter criteria. This shows a way that string theory may not be incompatible

Ye Yuan, Wuyang Chen, Tianlong Chen, Yang Yang

Many real-world applications, such as city-scale traffic monitoring and control, requires large-scale re-identification. However, previous ReID methods often failed to address two limitations in existing ReID benchmarks, i.e., low spatiotemporal coverage and sample imbalance. Notwithstanding their demonstrated success in every single benchmark, they have dif

Yifan Sun, Nicolas Bohm Agostini, Shi Dong, David Kaeli

Moore's Law and Dennard Scaling have guided the semiconductor industry for the past few decades. Recently, both laws have faced validity challenges as transistor sizes approach the practical limits of physics. We are interested in testing the validity of these laws and reflect on the reasons responsible. In this work, we collect data of more than 4000 public

Changgong Zhang, Fangneng Zhan

The recent person re-identification research has achieved great success by learning from a large number of labeled person images. On the other hand, the learned models often experience significant performance drops when applied to images collected in a different environment. Unsupervised domain adaptation (UDA) has been investigated to mitigate this constrai

Jonathan Everts, Gavin G. G. King, Nicholas Lambert, Sacha Kocsis

Quantum magnonics is a new and active research field, leveraging the strong collective coupling between microwaves and magnetically ordered spin systems. To date work in quantum magnonics has focused on transition metals and almost entirely on ferromagnetic resonances in yttrium iron garnet (YIG). Antiferromagnetic systems have gained interest as they produc

Shantanu Chakraborty, Tim Baarslag, Michael Kaisers

This paper presents an automated peer-to-peer negotiation strategy for settling energy contracts among prosumers in a Residential Energy Cooperative considering heterogeneity prosumer preferences. The heterogeneity arises from prosumers' evaluation of energy contracts through multiple societal and environmental criteria and the prosumers' private preferences

Avik Dutt, Momchil Minkov, Shanhui Fan

Conventional topological insulators support boundary states that have one dimension lower than the bulk system that hosts them, and these states are topologically protected due to quantized bulk dipole moments. Recently, higher-order topological insulators have been proposed as a way of realizing topological states that are two or more dimensions lower than

Xinyu Zhang

Cloud-based Enterprise Resources Planning (Cloud ERP) is hosting an ERP system through the cloud environment. Cloud ERP is responsible for organisational business processes such as purchasing, financial, and human resource by providing a real-time infrastructure for the enterprise. With the development of technology, cloud ERP is noticed by more and more ent

Runzhong Wang, Junchi Yan, Xiaokang Yang

Graph matching involves combinatorial optimization based on edge-to-edge affinity matrix, which can be generally formulated as Lawler's Quadratic Assignment Problem (QAP). This paper presents a QAP network directly learning with the affinity matrix (equivalently the association graph) whereby the matching problem is translated into a constrained vertex class

Shung-Ichi Ando, Young-Ho Song, Chang Ho Hyun

We study breakup of the deuteron induced by neutrinos in the neutral $\nu d\to \nu np$, $\bar{\nu} d\to \bar{\nu} np$ and the charged $\bar{\nu} d\to e^+ n n$, $\nu d\to e^- pp$ processes. Pionless effective field theory with dibaryon fields is used to calculate the total cross sections for neutrino energies $E_\nu$ from threshold to 20 MeV. Amplitudes are e

Hyunjun Eun, Sumin Lee, Jinyoung Moon, Jongyoul Park

Recent temporal action proposal generation approaches have suggested integrating segment- and snippet score-based methodologies to produce proposals with high recall and accurate boundaries. In this paper, different from such a hybrid strategy, we focus on the potential of the snippet score-based approach. Specifically, we propose a new snippet score-based m

Daniel K. Mark, Cheng-Ju Lin, Olexei I. Motrunich

We study a model of Rydberg atoms in a nearest-neighbor Rydberg blockaded regime, introduced by Lesanovsky in Phys. Rev. Lett. 108, 105301 (2012). This many-body model (which has one parameter $z$) has an exactly known gapped liquid ground state, and two exactly known low-lying excitations. We discover two new exact low-lying eigenstates. We also discuss beh

Caitlin Loeffler, Keylie M. Gibson, Lana Martin, Liz Chang

The human-associated microbiome is closely tied to human health and is of substantial clinical interest. Metagenomics-based tools are emerging for clinical diagnostics, tracking the spread of diseases, and surveillance of potential pathogens. In some cases, these tools are overcoming limitations of traditional clinical approaches. Metagenomics has limitation

Bruce Margon, Catherine Manea, Robert Williams, Howard E. Bond

We report the serendipitous discovery of an object, UVQS J060819.93-715737.4, with a spectrum dominated by extremely intense, narrow C II emission lines. The spectrum is similar to those of the very rare, late-type [WC11] low-mass Wolf-Rayet stars. Despite the recognition of these stars as a distinct class decades ago, there remains barely a handful of Galac

Zinovy Diskin, Harald König, Mark Lawford

Multiple (more than 2) model synchronization is ubiquitous and important for model driven engineering, but its theoretical underpinning gained much less attention than the binary case. Specifically, the latter was extensively studied by the bx community in the framework of algebraic models for update propagation called lenses. Now we make a step to restore t

Yu Xia, Zhiqiang Xu

We study the stable recovery of complex $k$-sparse signals from as few phaseless measurements as possible. The main result is to show that one can employ $\ell_1$ minimization to stably recover complex $k$-sparse signals from $m\geq O(k\log (n/k))$ complex Gaussian random quadratic measurements with high probability. To do that, we establish that Gaussian ra

Van-Hung Hoang, Anh-Thu Le

We present a theoretical investigation of high-harmonic generation (HHG) from impurity-doped materials using the time-dependent Schr\"odinger equation (TDSE) approach. We demonstrate the factorization of HHG yields as a product of an electron wave packet and the recombination cross section, in analogy to HHG from atoms and molecules in the gas phase. Further

S. Jannat, N. A. Chowdhury, A. Mannan, A. A. Mamun

The nonlinear propagation of ion-acoustic (IA) waves (IAWs) in a four component plasma medium (FCPM) containing inertial warm positive ions, and inertialess iso-thermal cold electrons as well as non-extensive ($q$-distributed) hot electrons and positrons is theoretically investigated. A nonlinear Schr\"{o}dinger equation (NLSE) is derived by using the reduct

Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang

Knowledge graphs (KGs) serve as useful resources for various natural language processing applications. Previous KG completion approaches require a large number of training instances (i.e., head-tail entity pairs) for every relation. The real case is that for most of the relations, very few entity pairs are available. Existing work of one-shot learning limits

Mohammad Rasoul Narimani

Electricity usage is a major portion of utility bills and the best place to start lowering them. An effective home energy management approach is introduced to decrease customers' electricity bills by determining the optimal appliance scheduling under hourly pricing based demand response (DR) strategies. The proposed approach specifically addresses consumer c

Daniil A. Kitchaev, Emily C. Schueller, Anton Van der Ven

The identification of general principles for stabilizing magnetic skyrmion phases in bulk materials over wide ranges of temperatures is a prerequisite to the development of skyrmion-based spintronic devices. Lacunar spinels with the formula GaM4X8 with M=V, Mo; X=S, Se are a convenient case study towards this goal as they are some of the first bulk systems s

Shu-Qing Zhong, Zi-Gao Dai, Xiang-Dong Li

Two accretion columns have been argued to form over the surface of a newborn millisecond magnetar for an extremely high accretion rate $\gtrsim1.8\times10^{-2}M_\odot\ {\rm s^{-1}}$ that may occur in the core-collapse of a massive star. In this paper, we investigate the characteristics of these accretion columns and their gravitational wave (GW) radiation. F

Koki Chonan, Nguyen Huynh Duy Khang, Masaaki Tanaka, Pham Nam Hai

We investigated the spin-dependent transport properties of a lateral spin-valve device with a 600 nm-long GaAs channel and ferromagnetic MnGa electrodes with perpendicular magnetization. Its current-voltage characteristics show nonlinear behavior below 50 K, indicating that tunnel transport through the MnGa/GaAs Schottky barrier is dominant at low temperatur

Khaldoon Ghanem, Alexander Y. Lozovoi, Ali Alavi

We identify and rectify a crucial source of bias in the initiator FCIQMC algorithm. Non-initiator determinants (i.e. determinants whose population is below the initiator threshold) are subject to a systematic {\em undersampling} bias, which in large systems leads to a bias in the energy when an insufficient number of walkers is used. We show that the accepta

Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu

Dynamic patterns are characterized by complex spatial and motion patterns. Understanding dynamic patterns requires a disentangled representational model that separates the factorial components. A commonly used model for dynamic patterns is the state space model, where the state evolves over time according to a transition model and the state generates the obs

T. Nathan Mundhenk, Barry Y. Chen, Gerald Friedland

We describe an explainable AI saliency map method for use with deep convolutional neural networks (CNN) that is much more efficient than popular fine-resolution gradient methods. It is also quantitatively similar or better in accuracy. Our technique works by measuring information at the end of each network scale which is then combined into a single saliency

David B. Kaplan, Srimoyee Sen

We construct a class of 2+1 dimensional relativistic quantum field theories which exhibit the Fractional Quantum Hall Effect in the infrared, both in the continuum and on the lattice. The UV completion consists of a perturbative $U(1)\times U(1)$ gauge theory with only integer-charged fields, while the low energy spectrum consists of nontrivial topological p

Nicholas Carrillo

Many body localization (MBL) is a phenomena that allows for the preservation of quantum information for long times. We study a variation of the disordered-Heisenberg model, which is known to exhibit an MBL phase [5][6], known as the quasi-Heisenberg model. Our model is a variation of the quasi-Heisenberg model with fields in both x and y directions. We found

Ehsan Tavanfar

We prove that if a local ring admits a (pd-)test module of finite complete intersection dimension, then it is a complete intersection ring. This answers, positively, a question proposed by Celikbas, Dao and Takahashi. To this aim, we first investigate another question raised by Celikbas and Sather- Wagstaff concerning ascent properties of (pd-)test complexes

Kamalika Ghatak, Kyung Nam Kang, Eui-Hyeok Yang, Dibakar Datta

Transition Metal Dichalcogenides (TMDs) are one of the most studied two-dimensional materials in the last 5-10 years due to their extremely interesting layer dependent properties. Despite the presence of vast research work on TMDs, the complex relationship between the electrochemical and physical properties make them the subject of further research. Our main

Sergey Zakharov, Wadim Kehl, Arjun Bhargava, Adrien Gaidon

We present an automatic annotation pipeline to recover 9D cuboids and 3D shapes from pre-trained off-the-shelf 2D detectors and sparse LIDAR data. Our autolabeling method solves an ill-posed inverse problem by considering learned shape priors and optimizing geometric and physical parameters. To address this challenging problem, we apply a novel differentiabl

Amin Omidvar, Hossein Poormodheji, Aijun An, Gordon Edall

Today, most newsreaders read the online version of news articles rather than traditional paper-based newspapers. Also, news media publishers rely heavily on the income generated from subscriptions and website visits made by newsreaders. Thus, online user engagement is a very important issue for online newspapers. Much effort has been spent on writing interes

Alessio Meneghetti, Massimiliano Sala, Daniele Taufer

We lay the foundations for a blockchain scheme, whose consensus is reached via a proof of work algorithm based on the solution of consecutive discrete logarithm problems over the point group of elliptic curves. In the considered architecture, the curves are pseudorandomly determined by block creators, chosen to be cryptographically secure and changed every e

Mohammad Roohitavaf, Kun Ren, Gene Zhang, Sami Ben-romdhane

In this paper, we present the design of our LogPlayer that is a component responsible for fault-tolerant delivery of transactional mutations recorded on a WAL to the backend storage shards. LogPlayer relies on gRPC for asynchronous streaming. However, the design provided in this paper can be used with other asynchronous streaming platforms. We model check th

Pierre H. Richemond, Arinbjörn Kolbeinsson, Yike Guo

Deep reinforcement learning requires a heavy price in terms of sample efficiency and overparameterization in the neural networks used for function approximation. In this work, we use tensor factorization in order to learn more compact representation for reinforcement learning policies. We show empirically that in the low-data regime, it is possible to learn

Ehsan Aghaei, Gursel Serpen

This paper proposes a methodology for host-based anomaly detection using a semi-supervised algorithm namely one-class classifier combined with a PCA-based feature extraction technique called Eigentraces on system call trace data. The one-class classification is based on generating a set of artificial data using a reference distribution and combining the targ

Hardik B. Jain, Ian P. Roberts, Sriram Vishwanath

The wide bandwidths available at millimeter-wave (mmWave) frequencies have offered exciting potential to wireless communication systems and radar alike. Communication systems can offer higher rates and support more users with mmWave bands while radar systems can benefit from higher resolution captures. This leads to the possibility that portions of mmWave sp

Sebastián Pérez, Antonio Hales, Hauyu Baobab Liu, Zhaohuan Zhu

FU Orionis objects are low-mass pre-main sequence stars characterized by dramatic outbursts of several magnitudes in brightness. These outbursts are linked to episodic accretion events in which stars gain a significant portion of their mass. The physical processes behind these accretion events are not yet well understood. The archetypical FU Ori system, FU O

Joon Sang Kang, Man Li, Huan Wu, Huuduy Nguyen

Cubic boron arsenide (BAs) is an emerging semiconductor material with a record-high thermal conductivity of 1300 W/mK. However, many fundamental properties of BAs remain unexplored experimentally. Here, for the first time, we report the systematic experimental measurements of important physical properties of BAs, including the bandgap, optical refractive ind

Roman Bessonov, Sergey Denisov

Let $\mu$ be a measure from Szeg\H{o} class on the unit circle $\mathbb T$ and let $\{f_n\}$ be the family of Schur functions generated by $\mu$. In this paper, we prove a version of the classical Szeg\H{o}'s formula which controls the oscillation of $f_n$ on $\mathbb T$ for all $n \ge 0$. Then, we focus on an analog of Lusin's conjecture for polynomials $\{

Christantus O. Nnamani, Muhammad R. A. Khandaker, Mathini Sellathurai

This paper investigates unmanned aerial vehicle (UAV)-aided jamming technique for enabling physical layer keyless security in scenarios where the exact eavesdropper location is unknown. We assume that the unknown eavesdropper location is within an ellipse characterizing the coverage region of the transmitter. By sequentially optimizing the transmit power, th

Keyvan Ramezanpour, Paul Ampadu, William Diehl

While modern masking schemes provide provable security against passive side-channel analysis (SCA), such as power analysis, single faults can be employed to recover the secret key of ciphers even in masked implementations. In this paper, we propose random space masking (RS-Mask) as a countermeasure against both power analysis and statistical fault analysis (

Noriyuki Matsunaga, Daisuke Taniguchi, Mingjie Jian, Yuji Ikeda

Stellar absorption lines of heavy elements can give us various insights into the chemical evolution of the Galaxy and nearby galaxies. Recently developed spectrographs for the near-infrared wavelengths are becoming more and more powerful for producing a large number of high-quality spectra, but identification and characterization of the absorption lines in t

Sherif Saad, Farhan Mahmood, William Briguglio, Haytham Elmiligi

New computing paradigms, modern feature-rich programming languages and off-the-shelf software libraries enabled the development of new sophisticated malware families. Evidence of this phenomena is the recent growth of fileless malware attacks. Fileless malware or memory resident malware is an example of an Advanced Volatile Threat (AVT). In a fileless malwar

Long Jiang, Na Wang, Wen-Cong Chen, Xiang-Dong Li

According to the recycling model, neutron stars in low-mass X-ray binaries were spun up to millisecond pulsars (MSPs), which indicates that all MSPs in the Galactic plane ought to be harbored in binaries. However, about $20\%$ Galactic field MSPs are found to be solitary. To interpret this problem, we assume that the accreting neutron star in binaries may co

Naoki Kitazawa

A fold map is a smooth map at each singular point of which it is represented as the product map of a Morse function and the identity map on an open ball. A special generic map is a fold map such that the Morse function can be taken as a natural height function on an unit disk. The class of special generic maps includes a Morse function with exactly two singu

Eric L. Nielsen, Robert J. De Rosa, Jason J. Wang, Johannes Sahlmann

We present new observations of the planet beta Pictoris b from 2018 with GPI, the first GPI observations following conjunction. Based on these new measurements, we perform a joint orbit fit to the available relative astrometry from ground-based imaging, the Hipparcos Intermediate Astrometric Data (IAD), and the Gaia DR2 position, and demonstrate how to incor

F. Ramírez-Ramírez, E. Flores-Olmedo, G. Báez, E. Sadurní

Solid state physics deals with systems composed of atoms with strongly bound electrons. The tunneling probability of each electron is determined by interactions that typically extend to neighboring sites, as their corresponding wave amplitudes decay rapidly away from an isolated atomic core. This kind of description is essential to material science, and it r

Mateus P. Mota, Daniel C. Araujo, Francisco Hugo Costa Neto, Andre L. F. de Almeida

We design a self-exploratory reinforcement learning (RL) framework, based on the Q-learning algorithm, that enables the base station (BS) to choose a suitable modulation and coding scheme (MCS) that maximizes the spectral efficiency while maintaining a low block error rate (BLER). In this framework, the BS chooses the MCS based on the channel quality indicat

Anastasiya Ivanova, Dmitry Pasechnyuk, Dmitry Grishchenko, Egor Shulgin

In this paper, we present a generic framework that allows accelerating almost arbitrary non-accelerated deterministic and randomized algorithms for smooth convex optimization problems. The main approach of our envelope is the same as in Catalyst (Lin et al., 2015): an accelerated proximal outer gradient method, which is used as an envelope for a non-accelera

Mario Coutino, Elvin Isufi, Takanori Maehara, Geert Leus

In this work, we explore the state-space formulation of network processes to recover the underlying structure of the network (local connections). To do so, we employ subspace techniques borrowed from system identification literature and extend them to the network topology inference problem. This approach provides a unified view of the traditional network con

Ezra Getzler, Sean Weinz Pohorence

In the Batalin-Vilkovisky formalism, gauge conditions are expressed as Lagrangian submanifolds in the space of fields and antifields. We discuss a way of patching together gauge conditions over different parts of the space of fields, and apply this method to extend the light-cone gauge for the superparticle to a conic neighbourhood of the forward light-cone

Christina Osborne

The classifying diagram was defined by Rezk and is a generalization of the nerve of a category; in contrast to the nerve, the classifying diagram of two categories is equivalent if and only if the categories are equivalent. In this paper we prove that the classifying diagram of any category is characterized in terms of classifying spaces of stabilizers of gr

Rahul Soni, Nitin Kaushal, Satoshi Okamoto, Elbio Dagotto

We study ribbons of the dice two-dimensional lattice (that we call ``dice ladders'') known to have nontrivial topological properties, such as Chern numbers 2 [Wang and Y. Ran, Phys. Rev. B {\bf 84}, 241103 (2011)]. Our main results are two folded: (1) Analyzing the tight-binding model in the presence of Rashba spin-orbit coupling and an external magnetic fie

Antoine Tordeux, Andreas Schadschneider, Sylvain Lassarre

Stop-and-go waves are commonly observed in traffic and pedestrian flows. In most traffic models they occur through a phase transition after fine tuning of parameters when the model has unstable homogeneous solutions. Inertia effects are believed to play an important role in this mechanism. Here, we present a novel explanation for stop-and-go waves based on s

Jongmin Seo, Casey Fleeter, Andrew M. Kahn, Alison L. Marsden

Numerical models are increasingly used for non-invasive diagnosis and treatment planning in coronary artery disease, where service-based technologies have proven successful in identifying hemodynamically significant and hence potentially dangerous vascular anomalies. Despite recent progress towards clinical adoption, many results in the field are still based

Jessica Velasco, Leandro Alberto, Henrick Dave Ambatali, Marlon Canilang

This study presents a system that combines a conventional refrigerator, microcontrollers and a smart phone to create an inventory monitoring that can monitor the stocks inside the refrigerator wirelessly by accessing an Android application. The developed refrigerator uses a sensor network system that is installed in a respective compartment inside the refrig

Filiberto Ares, Amilcar R. de Queiroz, Marcia R. Tenser

We consider electromagnetism in a cylindrical manifold coupled to a nonrelativistic charged point-particle. Through the relation between this theory and the Landau model on a torus, we study the entanglement between the particle and the electromagnetic field. In particular, we compute the entanglement entropy in the ground state, which is degenerate, obtaini

Hao Ding, Siyuan Qiao, Alan Yuille, Wei Shen

The key to a successful cascade architecture for precise instance segmentation is to fully leverage the relationship between bounding box detection and mask segmentation across multiple stages. Although modern instance segmentation cascades achieve leading performance, they mainly make use of a unidirectional relationship, i.e., mask segmentation can benefit

Kyle M. Whitcomb, Chandralekha Singh

Analysis of institutional data for physics majors showing predictive relationships between required mathematics and physics courses in various years is important for contemplating how the courses build on each other and whether there is need to make changes to the curriculum for the majors to strengthen these relationships. We use 15 years of institutional d

Milutin Blagojević, Branislav Cvetković

Black hole thermodynamics of the Kerr-AdS spacetime in three-dimensional general relativity is analyzed using a Hamiltonian approach. The values of the conserved charges and entropy, obtained by a proper treatment of the AdS asymptotic conditions, are shown to satisfy the first law of black hole dynamics.

John Holler, Risto Vuorio, Zhiwei Qin, Xiaocheng Tang

Order dispatching and driver repositioning (also known as fleet management) in the face of spatially and temporally varying supply and demand are central to a ride-sharing platform marketplace. Hand-crafting heuristic solutions that account for the dynamics in these resource allocation problems is difficult, and may be better handled by an end-to-end machine

Palani R. Jothi, Jan P. Scheifers, Yuemei Zhang, Mohammed Alghamdi

Layered van der Waals (vdW) crystals with intrinsic magnetic properties such as high Curie temperature (TC) and large perpendicular magnetic anisotropy (PMA) are key to the development and application of spintronic devices. The ferromagnetic vdW metal Fe3-xGeTe2 (FGT) has gained prominence recently due to its high TC (220 K) and strong PMA. Here, we introduc

Zhiyuan Geng, Wei Wang

We study radial symmetric point defects with degree $\frac {k}{2}$ in 2D disk or $\mathbb{R}^2$ in $Q$-tensor framework with singular bulk energy, which is defined by Bingham closure. First, we obtain the existence of solutions for the profiles of radial symmetric point defects with degree $\frac k2$ in 2D disk or $\mathbb{R}^2$. Then we prove that the solut

Daniel Wiebking

We extend Babai's quasipolynomial-time graph isomorphism test (STOC 2016) and develop a quasipolynomial-time algorithm for the multiple-coset isomorphism problem. The algorithm for the multiple-coset isomorphism problem allows to exploit graph decompositions of the given input graphs within Babai's group-theoretic framework. We use it to develop a graph isom

Benedikt Eggert, Alexander Schmeink, Johanna Lill, Maciej O. Liedke Andreas Wagner

Changes of the magnetic and crystal structure on the microscopic scale in 40 nm FeRh thin films have been applied to investigate the phenomena of a disorder induced ferromagnetism at room temperature initiated through light ion-irradiation with fluences up to 0.125 Ne$^+$/nm$^{-2}$. Magnetometry shows an increase of magnetic ordering at low temperatures and

Orencio Duran Vinent, Bruno Andreotti, Philippe Claudin, Christian Winter

Subaqueous and aeolian bedforms are ubiquitous on Earth and other planetary environments. However, it is still unclear which hydrodynamical mechanisms lead to the observed variety of morphologies of self-organized natural patterns such as ripples, dunes or compound bedforms. Here we present simulations with a coupled hydrodynamic and sediment transport model

Ruy Luiz Milidiú, Rafael Henrique Santos Rocha

The goal of Ordinal Regression is to find a rule that ranks items from a given set. Several learning algorithms to solve this prediction problem build an ensemble of binary classifiers. Ranking by Projecting uses interdependent binary perceptrons. These perceptrons share the same direction vector, but use different bias values. Similar approaches use indepen

Thomas D. Rueter, Thomas G. Rizzo, JoAnne L. Hewett

The nature of dark matter (DM) and how it might interact with the particles of the Standard Model (SM) is one of greatest mysteries currently facing particle physics, and addressing these issues should provide some understanding of how the observed relic abundance was produced. One widely considered production mechanism, a weakly interacting massive particle

Cassidy Laidlaw, Soheil Feizi

We explore adversarial robustness in the setting in which it is acceptable for a classifier to abstain---that is, output no class---on adversarial examples. Adversarial examples are small perturbations of normal inputs to a classifier that cause the classifier to give incorrect output; they present security and safety challenges for machine learning systems.

Karen Meagher, Peter Sin

We prove that every 2-transitive group has a property called the EKR-module property. This property gives a characterization of the maximum intersecting sets of permutations in the group. Specifically, the characteristic vector of any maximum intersecting set in a 2-transitive group is the linear combination of the characteristic vectors of the stabilizers o

Tobias Schlosser, Michael Friedrich, Danny Kowerko

Inspired by the human visual perception system, hexagonal image processing in the context of machine learning deals with the development of image processing systems that combine the advantages of evolutionary motivated structures based on biological models. While conventional state-of-the-art image processing systems of recording and output devices almost ex

Tobias Schlosser, Frederik Beuth, Michael Friedrich, Danny Kowerko

Automated visual inspection in the semiconductor industry aims to detect and classify manufacturing defects utilizing modern image processing techniques. While an earliest possible detection of defect patterns allows quality control and automation of manufacturing chains, manufacturers benefit from an increased yield and reduced manufacturing costs. Since cl

Le Qiao, Maxime Ignacio, Gary W. Slater

Analyte translocation involves three phases: (i) diffusion in the loading solution; (ii) capture by the pore; (iii) threading. The capture process remains poorly characterized because it cannot easily be visualized or inferred from indirect measurements. The capture performance of a device is often described by a \textit{capture radius} generally defined as

A Khodja, A Kadja, F Benamira, L Guechi

The problem of a Klein-Gordon particle moving in equal vector and scalar Rosen-Morse-type potentials is solved in the framework of Feynman's path integral approach. Explicit path integration leads to a closed form for the radial Green's function associated with different shapes of the potentials. For $q\leq -1$, and $\frac{1}{2\alpha }\ln \left\vert q\right\

Francisco Martínez López

In this thesis, we have studied the information loss paradox in detail. As a first step, we have derived the main results of quantum field theory in a curved background. We have discussed the case of the free scalar Klein-Gordon field and concluded with a derivation of the so-called Unruh effect in Minkowski spacetime. After giving a brief survey of necessar

Federico Olmedo, Alejandro Díaz-Caro

In this abstract we study the resource consumption of quantum programs. Specifically, we focus on the expected runtime of programs and, inspired by recent methods for probabilistic programs, we develop a calculus \`a la weakest precondition to formally and systematically derive the (exact) expected runtime of quantum programs. Notably, the calculus admits a

Jonathan Jedwab

The merit factor of a $\{-1, 1\}$ binary sequence measures the collective smallness of its non-trivial aperiodic autocorrelations. Binary sequences with large merit factor are important in digital communications because they allow the efficient separation of signals from noise. It is a longstanding open question whether the maximum merit factor is asymptotic

Joshua Grice

The class of all subdirectly irreducible groups belonging to a variety generated by a finite nilpotent group can be axiomatised by a finite set of elementary sentences.

Till Martini, Markus Schulze

We calculate the $\mathcal{O}(\alpha)$ weak corrections to top quark pair production at the LHC and include anomalous electroweak interactions from dimension-six operators. The loop calculation and renormalization are consistently done within the Standard Model Effective Field Theory. Sensitivity to the involved operators is exposed through the virtual corre

Claudia Cicone, Roberto Maiolino, Susanne Aalto, Sebastien Muller

We present interferometric observations of the CN(1-0) line emission in Mrk231 and combine them with previous observations of CO and other H$_2$ gas tracers to study the physical properties of the massive molecular outflow. We find a strong boost of the CN/CO(1-0) line luminosity ratio in the outflow, which is unprecedented compared to any other known Galact