April 2019 arXiv papers — page 44

Yun Soo Myung, De-Cheng Zou

We analyze the stability of scalarized charged black holes in the Einstein-Maxwell-Scalar (EMS) theory with quadratic coupling. These black holes are labelled by the number of $n=0,1,2,\cdots$, where $n=0$ is called the fundamental black hole and $n=1,2,\cdots$ denote the $n$-excited black holes. We show that the $n=0$ black hole is stable against full pertu

Michael Willis

We define a limiting $\mathfrak{sl}_N$ Khovanov-Rozansky homology for semi-infinite positive multi-colored braids, and we show that this limiting homology categorifies a highest-weight projector for a large class of such braids. This effectively completes the extension of Cautis' similar result for infinite twist braids, begun in our earlier papers with Isla

Sumanta Chakraborty, Dawood Kothawala, Alessandro Pesci

The Raychaudhuri equation for a geodesic congruence in the presence of a zero-point length has been investigated. This is directly related to the small-scale structure of spacetime and possibly captures some quantum gravity effects. The existence of such a minimum distance between spacetime events modifies the associated metric structure and hence the expans

Abram Handler, Brendan O'Connor

Search applications often display shortened sentences which must contain certain query terms and must fit within the space constraints of a user interface. This work introduces a new transition-based sentence compression technique developed for such settings. Our query-focused method constructs length and lexically constrained compressions in linear time, by

Udit Narayan Chowdhury

We consider the phenomenon of spontaneous pair production in presence of an external electric field for noncommutative Yang Mills theories. Using Maldacena's holographic conjecture the threshold electric field for pair production is computed from the quark-antiquark potential for noncommutative theories. As an effect of noncommutativity, the threshold electr

Aswin Shanmugam Subramanian, Xiaofei Wang, Shinji Watanabe, Toru Taniguchi

Sequence-to-sequence (S2S) modeling is becoming a popular paradigm for automatic speech recognition (ASR) because of its ability to jointly optimize all the conventional ASR components in an end-to-end (E2E) fashion. This report investigates the ability of E2E ASR from standard close-talk to far-field applications by encompassing entire multichannel speech e

Adam Clay, Tessa Reimer

Every left-invariant ordering of a group is either discrete, meaning there is a least element greater than the identity, or dense. Corresponding to this dichotomy, the spaces of left, Conradian, and bi-orderings of a group are naturally partitioned into two subsets. This note investigates the structure of this partition, specifically the set of dense orderin

Subhashis Hazarika, Haoyu Li, Ko-Chih Wang, Han-Wei Shen

Complex computational models are often designed to simulate real-world physical phenomena in many scientific disciplines. However, these simulation models tend to be computationally very expensive and involve a large number of simulation input parameters which need to be analyzed and properly calibrated before the models can be applied for real scientific st

Akshay Agrawal, Shane Barratt, Stephen Boyd, Enzo Busseti

We consider the problem of efficiently computing the derivative of the solution map of a convex cone program, when it exists. We do this by implicitly differentiating the residual map for its homogeneous self-dual embedding, and solving the linear systems of equations required using an iterative method. This allows us to efficiently compute the derivative op

Casper Daniel Dijkstra

I aim to clarify the physical content and significance of naturalness. Physicists' earliest understanding of naturalness, as an autonomy of scales (AoS) requirement provides the most cogent definition of naturalness and I will assert that i) this provides a uniform notion which undergirds a myriad prominent naturalness conditions, ii) this is a reasonabl

Mohammed H. Talafha, Ziad A. Talafha

In the past, the Arabs in Al-Hara Zone used many stars to deduce the seasons of the year and also to deduce the roads, at that time this was the most convenient way to figure their ways and to know the time of the year they have to travel or to planet, The most important used stars at that time were the Pleiades, Canopus, Arcturus, and other stars. This stud

N. G. Holmes, Ido Roll, D. A. Bonn

It is a well-studied notion that women are under-represented in the physical sciences, with a "leaky pipeline" metaphor describing how the number of women decreases at higher levels in academia[1,2]. It is unclear, however, where the major leaks exist and what factors are responsible for this[2]. Our focus here is on women in physics with an emphasis

Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit

Community detection in graphs, data clustering, and local pattern mining are three mature fields of data mining and machine learning. In recent years, attributed subgraph mining is emerging as a new powerful data mining task in the intersection of these areas. Given a graph and a set of attributes for each vertex, attributed subgraph mining aims to find cohe

G. S. Oh, David J. Leblanc, Huei Peng

We present Vehicle Energy Dataset (VED), a novel large-scale dataset of fuel and energy data collected from 383 personal cars in Ann Arbor, Michigan, USA. This open dataset captures GPS trajectories of vehicles along with their time-series data of fuel, energy, speed, and auxiliary power usage. A diverse fleet consisting of 264 gasoline vehicles, 92 HEVs, an

Dong Cao, Dongdong Zhang, HaiBo Chen

Millions of people with severe speech disorders around the world may regain their communication capabilities through techniques of silent speech recognition (SSR). Using electroencephalography (EEG) as a biomarker for speech decoding has been popular for SSR. However, the lack of SSR text corpus has impeded the development of this technique. Here, we constru

Béranger Dumont, Simona Maggio, Ghiles Sidi Said, Quoc-Tien Au

Modern e-commerce catalogs contain millions of references, associated with textual and visual information that is of paramount importance for the products to be found via search or browsing. Of particular significance is the book category, where the author name(s) field poses a significant challenge. Indeed, books written by a given author (such as F. Scott

Yong Liu, Pavel Dmitriev, Yifei Huang, Andrew Brooks

This paper conducts an empirical investigation to evaluate transfer learning for classifying sales engagement emails arising from digital sales engagement platforms. Given the complexity of content and context of sales engagement, lack of standardized large corpora and benchmarks, limited labeled examples and heterogenous context of intent, this real-world u

Yan Liang, Xin Liu, Jianwen Zhang, Yangqiu Song

Unsupervised relation discovery aims to discover new relations from a given text corpus without annotated data. However, it does not consider existing human annotated knowledge bases even when they are relevant to the relations to be discovered. In this paper, we study the problem of how to use out-of-relation knowledge bases to supervise the discovery of un

Tao Li, Lei Lin

With billions of personal images being generated from social media and cameras of all sorts on a daily basis, security and privacy are unprecedentedly challenged. Although extensive attempts have been made, existing face image de-identification techniques are either insufficient in photo-reality or incapable of balancing privacy and usability qualitatively a

N. S. Manikandan, K. Ganesan

In a self-driving car, objection detection, object classification, lane detection and object tracking are considered to be the crucial modules. In recent times, using the real time video one wants to narrate the scene captured by the camera fitted in our vehicle. To effectively implement this task, deep learning techniques and automatic video annotation tool

Maria Gabriela Capeluto, Rebeca Falcione, Raquel Fernaandez Salvador, Aranxa Eceiza

We show that an azopolymer can be used to create a supramolecular architecture in a parallel process with patterned surface properties. By illuminating with an interference pattern, we created adhesion and charge patterns that reflect the molecular ordering. We studied the recording process in two limit situations. When birefringence dominates over mass tran

Fei Wang, Yunpeng Song, Jimuyang Zhang, Jinsong Han

Human doing actions will result in WiFi distortion, which is widely explored for action recognition, such as the elderly fallen detection, hand sign language recognition, and keystroke estimation. As our best survey, past work recognizes human action by categorizing one complete distortion series into one action, which we term as series-level action recognit

Shehu Maitama, Weidong Zhao

In this paper, we introduce a Laplace-type integral transform called the Shehu transform which is a generalization of the Laplace and the Sumudu integral transforms for solving differential equations in the time domain. The proposed integral transform is successfully derived from the classical Fourier integral transform and is applied to both ordinary and pa

Casper Daniel Dijkstra

Firstly, nonlocal field theories will be motivated, primarily in the gravity sector. We discuss how nonlocal theories of gravity can circumvent typical problems of finitely-many higher derivative theories and can, among other things, be either ghostfree and (potentially) renormalizable and yield a non-singular Newtonian potential. Afterwards we motivate fini

Nicolas Petit

We generalize the Wriggle polynomial, first introduced by L. Folwaczny and L. Kauffman, to the case of virtual tangles. This generalization naturally arises when considering the self-crossings of the tangle. We prove that the generalization (and, by corollary, the original polynomial) are Vassiliev invariants of order one for virtual knots, and study some si

Yurii A. Spirichev

It is shown that the necessary criterion for choosing the energy-momentum tensor of a physical system is the form of its linear invariant, which should be the lagrangian of this physical system. Examples of energy-momentum tensors that meet this criterion are given. For an electromagnetic field in vacuum, the linear invariant of the energy-momentum tensor mu

Soonam Lee, Shuo Han, Paul Salama, Kenneth W. Dunn

Due to image blurring image deconvolution is often used for studying biological structures in fluorescence microscopy. Fluorescence microscopy image volumes inherently suffer from intensity inhomogeneity, blur, and are corrupted by various types of noise which exacerbate image quality at deeper tissue depth. Therefore, quantitative analysis of fluorescence m

Corrado Lattanzio, Pierangelo Marcati, Delyan Zhelyazov

In this paper we perform the analysis of spectral properties of the linearized system around constant states and dispersive shock for a 1-D compressible Euler system with dissipation--dispersion terms. The dispersive term is originated by the quantum effects described through the Bohm potential, as customary in Quantum Hydrodynamic models. The analysis perfo

Audrey Chung, Paul Fieguth, Alexander Wong

Evolutionary deep intelligence has recently shown great promise for producing small, powerful deep neural network models via the synthesis of increasingly efficient architectures over successive generations. Despite recent research showing the efficacy of multi-parent evolutionary synthesis, little has been done to directly assess architectural similarity be

Zoran Basrak

In the paper "The relativistic Doppler effect: when a zero-frequency shift or a red shift exists for sources approaching the observer, Ann. Phys. (Berlin) 523, No. 3, 239-246 (2011), DOI 10.1002/andp.201000099 by C. Wang the use of an erroneous equation ended up at a number of faulty conclusions which are corrected in the present Comment.

Hedi Regeiba, Jean Ludwig

Let $G=K\ltimes A$ be the semi-direct product group of a compact group $K$ acting on an abelian locally compact group $A$. We describe the $C^*$-algebra $C^*(G)$ of $G$ in terms of an algebra of operator fields defined over the spectrum of $G $, generalizing previous results obtained for some special classes of such groups.

Lina Yuan, Suzhi Bi, Xiaohui Lin, Hui Wang

In this paper, we consider a secondary wireless powered communication network (WPCN) underlaid to a primary point-to-point communication link. The WPCN consists of a multi-antenna hybrid access point (HAP) that transfers wireless energy to a cluster of low-power wireless devices (WDs) and receives sensing data from them. To tackle the inherent severe user un

Owen Pavel Fernández Piedra

This paper is devoted to the construction of the renormalized quantum stress energy tensor $\left<T_μ^ν\right>_{ren}$ for a massive scalar field with arbitrary coupling to the gravitational field of a pointlike global monopole, using the Schwinger-DeWitt approximation, up to second order in the inverse mass $μ$ of the field. The given stress energy tensor is

Wenbin Li, Aleš Leonardis, Jeannette Bohg, Mario Fritz

Understanding physical phenomena is a key competence that enables humans and animals to act and interact under uncertain perception in previously unseen environments containing novel objects and their configurations. In this work, we consider the problem of autonomous block stacking and explore solutions to learning manipulation under physics constraints wit

Mohannad Babli, Eva Onaindia

Automated planning technology has developed significantly. Designing a planning model that allows an automated agent to be capable of reacting intelligently to unexpected events in a real execution environment yet remains a challenge. This article describes a domain-independent approach to allow the agent to be context-aware of its execution environment and

Varun Jain, Gaurav Garg, Ramakrishna Perla, Ramya Hebbalaguppe

Hand gestures form an intuitive means of interaction in Mixed Reality (MR) applications. However, accurate gesture recognition can be achieved only through state-of-the-art deep learning models or with the use of expensive sensors. Despite the robustness of these deep learning models, they are generally computationally expensive and obtaining real-time perfo

Danko D. Georgiev, James F. Glazebrook

Protein clamps provide the cell with effective mechanisms for sensing of environmental changes and triggering adaptations that maintain homeostasis. The general physical mechanism behind protein clamping action, however, is poorly understood. Here, we explore the Davydov model for quantum transport of amide I energy, which is self-trapped in soliton states t

Wayne Lawton

If $f$ is a nonzero Bohr almost periodic function on $\mathbb R$ with a bounded spectrum we prove there exist $C_f > 0$ and integer $n > 0$ such that for every $u > 0$ the mean measure of the set $\{\, x \, : \, |f(x)| < u \, \}$ is less than $C_f\, u^{1/n}.$ For trigonometric polynomials with $\leq n + 1$ frequencies we show that $C_f$ can be chosen to depe

Ognjen Rudovic, Yuria Utsumi, Ricardo Guerrero, Kelly Peterson

We introduce a novel personalized Gaussian Process Experts (pGPE) model for predicting per-subject ADAS-Cog13 cognitive scores -- a significant predictor of Alzheimer&#39;s Disease (AD) in the cognitive domain -- over the future 6, 12, 18, and 24 months. We start by training a population-level model using multi-modal data from previously seen subjects using

Hakan Gokcesu, Suleyman S. Kozat

We study online convex optimization under stochastic sub-gradient observation faults, where we introduce adaptive algorithms with minimax optimal regret guarantees. We specifically study scenarios where our sub-gradient observations can be noisy or even completely missing in a stochastic manner. To this end, we propose algorithms based on sub-gradient descen

Jiawei Zhang

In this paper, we will provide an introduction to the derivative-free optimization algorithms which can be potentially applied to train deep learning models. Existing deep learning model training is mostly based on the back propagation algorithm, which updates the model variables layers by layers with the gradient descent algorithm or its variants. However,

Jiawei Zhang

In this paper, we will provide an introduction to the derivative-free optimization algorithms which can be potentially applied to train deep learning models. Existing deep learning model training is mostly based on the back propagation algorithm, which updates the model variables layers by layers with the gradient descent algorithm or its variants. However,

Kyle Kuan, Tosiron Adegbija

Much research has shown that applications have variable runtime cache requirements. In the context of the increasingly popular Spin-Transfer Torque RAM (STT-RAM) cache, the retention time, which defines how long the cache can retain a cache block in the absence of power, is one of the most important cache requirements that may vary for different applications

S. Vasiukov, F. Chiossi, C. Braggio, G. Carugno

The optical and scintillation properties of undoped, Si-doped, and Si, B co-doped GaAs samples were studied. The light yield specification and X-ray luminescence of GaAs over a wide IR region by using Si and InGaAs photodetectors are presented. The undoped GaAs demonstrated a narrow emission band at 838 nm (1.48 eV) and a low light output of about 2 ph/keV.

Jennifer Newman, Li Lin, Wenhao Chen, Stephanie Reinders

In this paper, we present a new reference dataset simulating digital evidence for image steganography. Steganography detection is a digital image forensic topic that is relatively unknown in practical forensics, although stego app use in the wild is on the rise. This paper introduces the first database consisting of mobile phone photographs and stego images

Caroline Grant Melles, David Joyner

Our main result is a generalized Dillon-type theorem, giving graph-theoretic conditions which guarantee that a $p$-ary function in an even number of variables is bent, for $p$ a prime number greater than 2. The key condition is that the component Cayley graphs associated to the values of the function are strongly regular, and either all of Latin square type,

M. Estienne, M. Fallot, A. Algora, J. Briz-Monago

A new summation method model of the reactor antineutrino energy spectrum is presented. It is updated with the most recent evaluated decay databases and with our Total Absorption Gamma-ray Spectroscopy measurements performed during the last decade. For the first time the spectral measurements from the Daya Bay experiment are compared with the detected antineu

Thiago Andrade, João Gama

Smartphones and portable devices have become ubiquitous and part of everyone&#39;s life. Due to the fact of its portability, these devices are perfect to record individuals&#39; traces and life-logging generating vast amounts of data at low costs. These data is emerging as a new source for studies in human mobility patterns raising the number of research pro

Mohammad Nur Hasan, Brian M. Kurkoski, Amin Sakzad, Emanuele Viterbo

In this paper, we develop an orthogonal precoding scheme for integer-forcing (IF) linear receivers using the steepest gradient algorithm. Although this scheme can be viewed as a special case of the unitary precoded integer-forcing (UPIF), it has two major advantages. First, the orthogonal precoding outperforms its unitary counterpart in terms of achievable r

Christopher Harshaw, Moran Feldman, Justin Ward, Amin Karbasi

It is generally believed that submodular functions -- and the more general class of $γ$-weakly submodular functions -- may only be optimized under the non-negativity assumption $f(S) \geq 0$. In this paper, we show that once the function is expressed as the difference $f = g - c$, where $g$ is monotone, non-negative, and $γ$-weakly submodular and $c$ is non-

Ahmed S. Shamsaldin, Tarik A. Rashid, Rawan A. Al-Rashid Agha, Nawzad K. Al-Salihi

Swarm Intelligence is a metaheuristic optimization approach that has become very predominant over the last few decades. These algorithms are inspired by animals&#39; physical behaviors and their evolutionary perceptions. The simplicity of these algorithms allows researchers to simulate different natural phenomena to solve various real-world problems. This pa

Marco De Nadai, Angelo Cardoso, Antonio Lima, Bruno Lepri

Cognition has been found to constrain several aspects of human behaviour, such as the number of friends and the number of favourite places a person keeps stable over time. This limitation has been empirically defined in the physical and social spaces. But do people exhibit similar constraints in the digital space? We address this question through the analysi

Subarna Tripathi, Sharath Nittur Sridhar, Sairam Sundaresan, Hanlin Tang

Structured representations such as scene graphs serve as an efficient and compact representation that can be used for downstream rendering or retrieval tasks. However, existing efforts to generate realistic images from scene graphs perform poorly on scene composition for cluttered or complex scenes. We propose two contributions to improve the scene compositi

Eren Balevi, Jeffrey G. Andrews

We propose a novel deep learning-based channel estimation technique for high-dimensional communication signals that does not require any training. Our method is broadly applicable to channel estimation for multicarrier signals with any number of antennas, and has low enough complexity to be used in a mobile station. The proposed deep channel estimator can ou

Phillip S. Harrington, Andrew Raich

The $L^2$ theory of the $\bar\partial$ operator on domains in $\mathbb{C}^n$ is predicated on establishing a good basic estimate. Typically, one proves not a single basic estimate but a family of basic estimates that we call a family of strong closed range estimates. Using this family of estimates on $(0,q)$-forms as our starting point, we establish necessar

Seonghun Cho, Johan Lim, Deepak Nag Ayyala, Junyong Park

For the mean vector test in high dimension, Ayyala et al.(2017,153:136-155) proposed new test statistics when the observational vectors are M dependent. Under certain conditions, the test statistics for one-same and two-sample cases were shown to be asymptotically normal. While the test statistics and the asymptotic results are valid, some parts of the proof

Ahmed Bchatnia, Naima Mehenaoui

In this paper, we prove the exponential decay of local energy for the Klein-Gordon equation with localized critical nonlinearity. The proof relies on generalized Strichartz estimates, and semi-group of Lax-Phillips.

Jorge A. Pérez-Hernández, Luis Benet

Using a purely Newtonian model for the Solar System, we investigate the dynamics of comet 1P/Halley considering in particular the Lyapunov and power spectra of its orbit, using the nominal initial conditions of JPL&#39;s Horizons system. We carry out precise numerical integrations of the $(N+1)$-restricted problem and the first variational equations, conside

Ivan Lisenkov, Roman Khymyn, Johan Akerman, Nian X. Sun

A theory of magnetization dynamics in ferrimagnetic materials with antiparallel aligned spin sub-lattices under action of spin-transfer torques (STT) is developed. We consider magnetization dynamics in GdFeCo layers in two cases of magnetic anisotropy: easy plane and easy axis. We demonstrate that, (i) for the easy plane anisotropy the precession of the Néel

Huy Dinh, Harbir Antil, Yanlai Chen, Elena Cherkaev

We propose a novel numerical algorithm utilizing model reduction for computing solutions to stationary partial differential equations involving the spectral fractional Laplacian. Our approach utilizes a known characterization of the solution in terms of an integral of solutions to classical elliptic problems. We reformulate this integral into an expression w

Pouya Bashivan, Martin Schrimpf, Robert Ajemian, Irina Rish

Despite remarkable successes achieved by modern neural networks in a wide range of applications, these networks perform best in domain-specific stationary environments where they are trained only once on large-scale controlled data repositories. When exposed to non-stationary learning environments, current neural networks tend to forget what they had previou

A. Archer, W. Benbow, R. Bird, R. Brose

We conduct a search for periodic emission in the very high-energy gamma-ray band (VHE; E > 100 GeV) from a total of 13 pulsars in an archival VERITAS data set with a total exposure of over 450 hours. The set of pulsars includes many of the brightest young gamma-ray pulsars visible in the Northern Hemisphere. The data analysis resulted in non-detections of pu

Mauro Bonafini, Giandomenico Orlandi, Edouard Oudet

In this paper we consider the Euclidean Steiner tree problem and, more generally, (single sink) Gilbert--Steiner problems as prototypical examples of variational problems involving 1-dimensional connected sets in $\mathbb{R}^n$. Following the the analysis for the planar case presented in [4], we provide a variational approximation through Ginzburg--Landau ty

Jeremy Rickard

We show that the group of bounded sequences of elements of $\mathbb{Z}[\sqrt 2]$ is an example of an abelian group with several well known, and not so well known, pathological properties. It appears to be simpler than all previously known examples for some of these properties, and at least simpler to describe for others.

Priyamvada Natarajan, Angelo Ricarte, Vivienne Baldassare, Jillian Bellovary

The origin and properties of black hole seeds that grow to produce the detected population of supermassive black holes are unconstrained at present. Despite the existence of several potentially feasible channels for the production of initial seeds in the high redshift universe, since even actively growing seeds are not directly observable at these epochs, di

Arkady Molev-Shteiman, Xiao-Feng Qi, Laurence Mailaender

Based on a new equivalent model of quantizer with noisy input recently presented in [23], we propose a new low complexity receiver that takes into account the nonlinear distortion (NLD) generated by Analog to Digital converter (ADC) with insufficient resolution. The strength of new model is that it presents the NLD as a function of only the desired part of i

Jennifer B. Bergner, Karin I. Oberg, Edwin A. Bergin, Ryan A. Loomis

Molecular lines observed towards protoplanetary disks carry information about physical and chemical processes associated with planet formation. We present ALMA Band 6 observations of C2H, HCN, and C18O in a sample of 14 disks spanning a range of ages, stellar luminosities, and stellar masses. Using C2H and HCN hyperfine structure fitting and HCN/H13CN isotop

Henric Krawczynski, Giorgio Matt, Adam R. Ingram, Roberto Taverna

This white paper highlights compact object and fundamental physics science opportunities afforded by high-throughput broadband (0.1-60 keV) X-ray polarization observations. X-ray polarimetry gives new observables with geometric information about stellar remnants which are many orders of magnitude too small for direct imaging. The X-ray polarimetric data also

Arkady Molev-Shteiman, Xiao-Feng Qi, Laurence Mailaender

Based on an equivalent model for quantizers with noisy inputs recently presented in [35], we propose a method of digital dithering at the transmitter that may significantly reduce the resolution requirements of MIMO downlink Digital to Analog Convertors (DAC). We use this equivalent model to analyze the effect of the dither Probability Density Function (PFD)

Tom Zimmerman, Sachin Junnarkar

The technique of current splitting is presented as part of an integrated circuit development for an X-ray imager. This method enables integration of charge signals of unprecedented magnitude in small pixels, achieving a dynamic range of ${10^5}$. Results from two front end prototypes are given and a final optimized design is proposed.

Varun Chandra Jammula, Anshul Rai, Yezhou Yang

Given a mapped environment, we formulate the problem of visually tracking and following an evader using a probabilistic framework. In this work, we consider a non-holonomic robot with a limited visibility depth sensor in an indoor environment with obstacles. The mobile robot that follows the target is considered a pursuer and the agent being followed is cons

Sheida Ahmadi, Marina Schmidt, Raymond J. Spiteri, Richard K. Bowles

Fluids confined to quasi-one-dimensional channels exhibit a dynamic crossover from single file diffusion to normal diffusion as the channel becomes wide enough for particles to hop past each other. In the crossover regime, where hopping events are rare, the diffusion coefficient in the long time limit can be related to a hopping time that measures the averag

Kamber R. Schwarz, Richard Teague, Edwin A. Bergin

Line ratios for different transitions of the same molecule have long been used as a probe of gas temperature. Here we use ALMA observations of the N2H+ J~=~1-0 and J~=~4-3 lines in the protoplanetary disk around TW Hya to derive the temperature at which these lines emit. We find an averaged temperature of 39~K with a one sigma uncertainty of 2~K for the radi

Mahdi Naghiloo

Quantum technology has been rapidly growing due to its potential revolutionary applications. In particular, superconducting qubits provide a strong light-matter interaction as required for quantum computation and in principle can be scaled up to a high level of complexity. However, obtaining the full benefit of quantum mechanics in superconducting circuits r

Xitong Yang, Xiaodong Yang, Ming-Yu Liu, Fanyi Xiao

In this paper, we propose Spatio-TEmporal Progressive (STEP) action detector---a progressive learning framework for spatio-temporal action detection in videos. Starting from a handful of coarse-scale proposal cuboids, our approach progressively refines the proposals towards actions over a few steps. In this way, high-quality proposals (i.e., adhere to action

Morris Ang

Discrete and continuum Liouville first passage percolation (DLFPP, LFPP) are two approximations of the conjectural $γ$-Liouville quantum gravity (LQG) metric, obtained by exponentiating the discrete Gaussian free field (GFF) and the circle average regularization of the continuum GFF respectively. We show that these two models can be coupled so that with high

Anupam Gupta, Guru Guruganesh, Binghui Peng, David Wajc

We study the minimum-cost metric perfect matching problem under online i.i.d arrivals. We are given a fixed metric with a server at each of the points, and then requests arrive online, each drawn independently from a known probability distribution over the points. Each request has to be matched to a free server, with cost equal to the distance. The goal is t

Rathish Das, Shih-Yu Tsai, Sharmila Duppala, Jayson Lynch

A determinacy race occurs if two or more logically parallel instructions access the same memory location and at least one of them tries to modify its content. Races often lead to nondeterministic and incorrect program behavior. A data race is a special case of a determinacy race which can be eliminated by associating a mutual-exclusion lock or allowing atomi

Srilakshmi Pattabiraman, Ryan Gabrys, Olgica Milenkovic

Motivated by polymer-based data-storage platforms that use chains of binary synthetic polymers as the recording media and read the content via tandem mass spectrometers, we propose a new family of codes that allows for unique string reconstruction and correction of one mass error. Our approach is based on introducing redundancy that scales logarithmically wi

Daisuke Kadoh, Takeru Kamei, Hiroto So

We study a cyclic Leibniz rule, which provides a systematic approach to lattice supersymmetry, using a numerical method with a transfer matrix. The computation is carried out in N=2 supersymmetric quantum mechanics with the phi^6-interaction for weak and strong couplings. The computed energy spectra and supersymmetric Ward-Takahashi identities are compared w

Dingxin Zhang

Mimicking Ogus&#39;s construction, we define a site, for varieties over a field of char. p > 0, using Monsky--Washnitzer algebras/weak formal schemes. We prove a comparison theorem between the MW cohomology and a certain analytic cohomology.

P. Markos, K. A. Muttalib

Studies of possible localization of phonons in nanomaterials have gained importance in recent years in the context of thermoelectricity where phonon-localization can reduce thermal conductivity, thereby improving the efficiency of thermoelectric devices. However, despite significant efforts, phonon-localization has not yet been observed experimentally in rea

Sandro Claudio Lera, Didier Sornette

Hierarchical structures are ubiquitous in human and animal societies, but a fundamental understanding of their raison d&#39;être has been lacking. Here, we present a general theory in which hierarchies are obtained as the optimal design that strikes a balance between the benefits of group productivity and the costs of communication for coordination. By maxim

Ioannis Thanopulos, Vasilios Karanikolas, Nikos Iliopoulos, Emmanuel Paspalakis

We introduce a photonic nanostructure made of two dimensional materials that can lead to non-Markovian dynamics in the spontaneous emission of a nearby quantum emitter. Specifically, we investigate the spontaneous emission dynamics of a two-level quantum emitter with picosecond free-space decay time, modelling J-aggregates, close to a MoS$_2$ nanodisk. Rever

Hagit Shatkay, Stanley B. Zdonik

Many new database application domains such as experimental sciences and medicine are characterized by large sequences as their main form of data. Using approximate representation can significantly reduce the required storage and search space. A good choice of representation, can support a broad new class of approximate queries, needed in these domains. These

Logan J. Prust, Philip Chang

We outline the methodology of simulating common envelope evolution (CEE) with the moving-mesh code MANGA. We extend MANGA to include multiple time-steps. This provides substantial speedups for problems with large dynamic range. We describe the implementation of realistic equations of state relevant in stellar structure and the generation of suitable initial

Ian Wong, Aakash Mishra, Michael E. Brown

We present multiband photometric observations of nine Centaurs. Five of the targets are known active Centaurs (167P/CINEOS, 174P/Echeclus, P/2008 CL94, P/2011 S1, and C/2012 Q1), and the other four are inactive Centaurs belonging to the redder of the two known color subpopulations (83982 Crantor, 121725 Aphidas, 250112 2002 KY14, and 281371 2008 FC76). We me

Enrique G. Marin, Damiano Marian, Giuseppe Iannaccone, Gianluca Fiori

We propose a device concept, based on monolayer stanene, able to provide highly polarized spin currents (up to a $98\%$) with voltage-controlled spin polarization operating at room temperature and with small operating voltage ($0.3$ V). The concept exploits the presence of spin-polarized edge states in a stanene nanoribbon. The spin polarization of the total

Carolina Vittoria Beccari, Giulio Casciola, Marie-Laurence Mazure

We provide a numerical method to determine the critical lengths of linear differential operators with constant real coefficients. The need for such a procedure arises when the orders increase. The interest of this article is clearly on the practical side since knowing the critical lengths permits an optimal use of the associated kernels. The efficiency of th

Dieye Moustapha

In this work, we found a non trivial topology to achieve the controllability for linear and nonlinear system in finite or infinite time horizon. We give several examples illustrating this topologizing method for the controllability results. We obtain by the way the controllability for the one dimensional Schrödinger. We also apply this method to achieve the

Hooman Davoudiasl, Peter B. Denton

The initial data from the Event Horizon Telescope (EHT) on M87$^*$, the supermassive black hole at the center of the M87 galaxy, provide direct observational information on its mass, spin, and accretion disk properties. A combination of the EHT data and other constraints provide evidence that M87$^*$ has a mass $\sim 6.5 \times 10^9\,M_\odot$ and dimensionle

Abdullah AlShelahi, Jingxing Wang, Mingdi You, Eunshin Byon

This paper presents a new prediction model for time series data by integrating a time-varying Geometric Brownian Motion model with a pricing mechanism used in financial engineering. Typical time series models such as Auto-Regressive Integrated Moving Average assumes a linear correlation structure in time series data. When a stochastic process is highly volat

Peter Carr, Andrey Itkin

In this paper we apply Markovian approximation of the fractional Brownian motion (BM), known as the Dobric-Ojeda (DO) process, to the fractional stochastic volatility model where the instantaneous variance is modelled by a lognormal process with drift and fractional diffusion. Since the DO process is a semi-martingale, it can be represented as an \Ito diffus

Per Kristian Lehre, Phan Trung Hai Nguyen

We perform a rigorous runtime analysis for the Univariate Marginal Distribution Algorithm on the LeadingOnes function, a well-known benchmark function in the theory community of evolutionary computation with a high correlation between decision variables. For a problem instance of size $n$, the currently best known upper bound on the expected runtime is $\mat

Sashank J. Reddi, Satyen Kale, Sanjiv Kumar

Several recently proposed stochastic optimization methods that have been successfully used in training deep networks such as RMSProp, Adam, Adadelta, Nadam are based on using gradient updates scaled by square roots of exponential moving averages of squared past gradients. In many applications, e.g. learning with large output spaces, it has been empirically o

A. Stegmeir, A. Ross, T. Body, M. Francisquez

Turbulent dynamics in the scrape-off layer (SOL) of magnetic fusion devices is intermittent with large fluctuations in density and pressure. Therefore, a model is required that allows perturbations of similar or even larger magnitude to the time-averaged background value. The fluid-turbulence code GRILLIX is extended to such a global model, which consistentl

Youbao Tang, Yuxing Tang, Jing Xiao, Ronald M. Summers

This paper proposes a novel framework for lung segmentation in chest X-rays. It consists of two key contributions, a criss-cross attention based segmentation network and radiorealistic chest X-ray image synthesis (i.e. a synthesized radiograph that appears anatomically realistic) for data augmentation. The criss-cross attention modules capture rich global co

Maria Rosaria Formica, Eugeny Ostrovsky, Leonid Sirota

We prove that the Grand Lebesgue Space, builded on a unimodular locally compact topological group, forms a Banach algebra relative to the convolution.

Hans Franzen, Markus Reineke

We give a short introduction to Cohomological Hall algebras of quivers and describe the semistable Cohomological Hall algebra of central slope of the Kronecker quiver in terms of generators and relations.

Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng

We present a novel language representation model enhanced by knowledge called ERNIE (Enhanced Representation through kNowledge IntEgration). Inspired by the masking strategy of BERT, ERNIE is designed to learn language representation enhanced by knowledge masking strategies, which includes entity-level masking and phrase-level masking. Entity-level strategy