September 2019 arXiv papers — page 34

Benoit Renault, Jacques Saraydaryan, Olivier Simonin

In this paper, we present an in-depth analysis of Navigation Among Movable Obstacles (NAMO) literature, notably highlighting that social acceptability remains an unadressed problem in this robotics navigation domain. The objectives of a Socially-Aware NAMO are defined and a first set of algorithmic propositions is built upon existing work. We developed a sim

J. Brüdern, K. Soundararajan

Motivated by a question of Venkataramana, we consider the greatest common divisor of $ϕ(f(n))$ where $f$ is a primitive polynomial with integer coefficients, and $n$ ranges over all natural numbers. Assuming Schinzel's hypothesis, we establish that this gcd may be bounded just in terms of the degree of the polynomial $f$. Unconditionally we establish suc

Ivan Babenko, Stephane Sabourau

We introduce the volume entropy semi-norm in real homology and show that it satisfies functorial properties similar to the ones of the simplicial volume. Answering a question of M. Gromov, we prove that the volume entropy semi-norm is equivalent to the simplicial volume semi-norm in every dimension. We also establish a roughly optimal upper bound on the syst

Michael Poli, Jinkyoo Park, Ilija Ilievski

Finance is a particularly challenging application area for deep learning models due to low noise-to-signal ratio, non-stationarity, and partial observability. Non-deliverable-forwards (NDF), a derivatives contract used in foreign exchange (FX) trading, presents additional difficulty in the form of long-term planning required for an effective selection of sta

Antonella Castellina

The Pierre Auger Observatory has collected data for more than 15 years, accumulating the world's largest exposure to ultrahigh energy cosmic rays (UHECRs). The energy spectrum of the UHECRs has been measured up to $10^{20.2}$ eV, and their mass composition has been studied exploiting both the fluorescence and surface detectors of the Observatory. The ana

Lisa Graziani, Stefano Melacci, Marco Gori

The growing ubiquity of Social Media data offers an attractive perspective for improving the quality of machine learning-based models in several fields, ranging from Computer Vision to Natural Language Processing. In this paper we focus on Facebook posts paired with reactions of multiple users, and we investigate their relationships with classes of emotions

Rémy Pawlak, Silas Hoffman, Jelena Klinovaja, Daniel Loss

Majorana fermions have recently garnered a great attention outside the field of particle physics, in condensed matter physics. In contrast to their particle physics counterparts, Majorana fermions are zero energy, chargeless, spinless, composite quasiparticles, residing at the boundaries of so-called topological superconductors. Furthermore, in opposition to

Antonios Charalambopoulos, Evanthia Douka, Stelios Mavratzas

A new formulation of boundary value problems in gradient elasticity is presented in this work. The main outcome is the construction of partial differential systems of second order, which are typically equivalent with the well known fourth order equation of gradient elasticity. Two alternative methodologies are developed and presented in the present work. The

Ying Ju, Fubang Zhao, Shijie Chen, Bowen Zheng

Conversational Question Answering is a challenging task since it requires understanding of conversational history. In this project, we propose a new system RoBERTa + AT +KD, which involves rationale tagging multi-task, adversarial training, knowledge distillation and a linguistic post-process strategy. Our single model achieves 90.4(F1) on the CoQA test set

Loïc M. Roch, Semion K. Saikin, Florian Häse, Pascal Friederich

Fast and inexpensive characterization of materials properties is a key element to discover novel functional materials. In this work, we suggest an approach employing three classes of Bayesian machine learning (ML) models to correlate electronic absorption spectra of nanoaggregates with the strength of intermolecular electronic couplings in organic conducting

Akshay Bansal, Diganta Mukherjee

We devise an optimal allocation strategy for the execution of a predefined number of stocks in a given time frame using the technique of discrete-time Stochastic Control Theory for a defined market model. This market structure allows an instant execution of the market orders and has been analyzed based on the assumption of discretized geometric movement of t

Roberto Di Cosmo

Software source code is an essential research output, and many research communities strongly encourage making the source code of the artefact available by archiving it in publicly-accessible long-term archives.Software Heritage is a non profit, long term universal archive specifically designed for software source code, and able to store not only a software a

F. Marin

Among all the astronomical sources investigated through the prism of polarimetry, active galactic nuclei (AGN) have proven to be the richest in terms of complex yet fundamental signatures that helped to understand their true nature. Indeed, AGN exhibit a wide range of wavelength-dependent polarimetric features that are intrinsically related to their multi-sc

A. Z. Bonanos, M. Yang, K. V. Sokolovsky, P. Gavras

The Hubble Space Telescope (HST) has obtained multi-epoch observations providing the opportunity for a comprehensive variability search aiming to uncover new variables. We have therefore undertaken the task of creating a catalog of variable sources based on version 3 of the Hubble Source Catalog (HSC), which relies on publicly available images obtained with

SeongUk Park, Nojun Kwak

Knowledge Distillation (KD) aims to transfer knowledge in a teacher-student framework, by providing the predictions of the teacher network to the student network in the training stage to help the student network generalize better. It can use either a teacher with high capacity or {an} ensemble of multiple teachers. However, the latter is not convenient when

Muhammad Uzair khan, Salman Sherin, Muhammad Zohaib Iqbal, Rubab Zahid

Context: A number of Systematic Mapping Studies (SMSs) that cover Software Engineering (SE) are reported in literature. Tertiary studies synthesize the secondary studies to provide a holistic view of an area. Objectives: We synthesize SMSs in SE to provide insights into existing SE areas and to investigate the trends and quality of SMSs. Methodology: We use

Javaria Imtiaz, Salman Sherin, Muhammad Uzair khan, Muhammad Zohaib Iqbal

Context: When an application evolves, some of the developed test cases break. Discarding broken test cases causes a significant waste of effort and leads to test suites that are less effective and have lower coverage. Test repair approaches evolve test suites along with applications by repairing the broken test cases. Objective: Numerous studies are publishe

Sören Christensen, Kristoffer Lindensjö

A moment constraint that limits the number of dividends in the optimal dividend problem is suggested. This leads to a new type of time-inconsistent stochastic impulse control problem. First, the optimal solution in the precommitment sense is derived. Second, the problem is formulated as an intrapersonal sequential dynamic game in line with Strotz' consis

Pietro D'Antuono

Starting from the classical definition of stress-life Wohler curve in the form of Basquin's law, an analytical procedure for the calibration of the four parameters Wohler curve (Weibull's law) for a plain specimen is proposed. The obtained parameters are then adjusted by means of an additional slope factor preserving the inflection point of the curve

Terry J. Bridgman, Willy Hereman

The method due to Nijhoff and Bobenko & Suris to derive Lax pairs for partial difference equations (PDeltaEs) is applied to edge constrained Boussinesq systems. These systems are defined on a quadrilateral. They are consistent around the cube but they contain equations defined on the edges of the quadrilateral. By properly incorporating the edge equations in

Daniel Hienert, Dagmar Kern

Log analysis in Web search showed that user sessions often contain several different topics. This means sessions need to be segmented into parts which handle the same topic in order to give appropriate user support based on the topic, and not on a mixture of topics. Different methods have been proposed to segment a user session to different topics based on t

Daniel Hienert, Dagmar Kern, Katarina Boland, Benjamin Zapilko

In the social sciences, researchers search for information on the Web, but this is most often distributed on different websites, search portals, digital libraries, data archives, and databases. In this work, we present an integrated search system for social science information that allows finding information around research data in a single digital library.

Chao Lu, Wei Xu, Shi Jin, Kezhi Wang

Quantized channel state information (CSI) plays a critical role in precoding design which helps reap the merits of multiple-input multiple-output (MIMO) technology. In order to reduce the overhead of CSI feedback, we propose a deep learning based CSI quantization method by developing a joint convolutional residual network (JCResNet) which benefits MIMO chann

Lucy H. Lin, Noah A. Smith

As distributed approaches to natural language semantics have developed and diversified, embedders for linguistic units larger than words have come to play an increasingly important role. To date, such embedders have been evaluated using benchmark tasks (e.g., GLUE) and linguistic probes. We propose a comparative approach, nearest neighbor overlap (N2O), that

Lei Zhao, Zouyi Jiang, Ruoshi Dong, Zhe Cao

High sampling speed can be achieved using multiple Analog-to-Digital Converters (ADCs) based on the Time-Interleaving A/D Conversion (TIADC) technique. Various types of methods were proposed to correct the mismatch errors among parallel ADC channels in TIADC systems, which would deteriorate the system performance. Traditional correction methods based on digi

Peipei Deng, Lei Zhao, Jiaming Lu, Pinzheng Xia

T0 detector, based on Multi-gap Resistive Plate Chambers (MRPC) technology, is one of the key components in the External Target Experiment. Through precision measurements of the MRPC signals, timing of the beam impact on target can be obtained and used as the start time for other detectors. A readout electronics system was designed for the T0 detector. Based

Anatoli Fedynitch, Juan-Pablo Yáñez

The IceCube Neutrino Detector observes tens of thousands of atmospheric neutrinos every year with its low energy extension DeepCore, covering the neutrino energy range from GeV to TeV. These neutrinos can be used to study particle interactions in conditions that are inaccessible to current accelerator-based experiments. Here, we present constraints concernin

Xingshun Gao, Lei Zhao, Jinxin Liu, Zouyi Jiang

A fully digital beam position and phase measurement (BPPM) system was designed for the linear accelerator (LINAC) in Accelerator Driven Sub-critical System (ADS) in China. Phase information is obtained from the summed signals from four pick-ups of the Beam Position Monitor (BPM). Considering that the delay variations of different analog circuit channels woul

Jianqing Fan, Jianhua Guo, Shurong Zheng

Determining the number of common factors is an important and practical topic in high dimensional factor models. The existing literatures are mainly based on the eigenvalues of the covariance matrix. Due to the incomparability of the eigenvalues of the covariance matrix caused by heterogeneous scales of observed variables, it is very difficult to give an accu

Abigail See, Aneesh Pappu, Rohun Saxena, Akhila Yerukola

Large neural language models trained on massive amounts of text have emerged as a formidable strategy for Natural Language Understanding tasks. However, the strength of these models as Natural Language Generators is less clear. Though anecdotal evidence suggests that these models generate better quality text, there has been no detailed study characterizing t

Arbaaz Khan, Vijay Kumar, Alejandro Ribeiro

In this paper, we present a learning method to solve the unlabelled motion problem with motion constraints and space constraints in 2D space for a large number of robots. To solve the problem of arbitrary dynamics and constraints we propose formulating the problem as a multi-agent problem. In contrast to previous works that propose using learning solutions f

Jorge L. Barrera, Markus J. Geiss, Kurt Maute

Two approaches that use a density field for seeding holes in level set topology optimization are proposed. In these approaches, the level set field describes the material-void interface while the density field describes the material distribution within the material phase. Both fields are optimized simultaneously by coupling them through either a single abstr

Nitish Bahadur, Randy Paffenroth

Dimension Estimation (DE) and Dimension Reduction (DR) are two closely related topics, but with quite different goals. In DE, one attempts to estimate the intrinsic dimensionality or number of latent variables in a set of measurements of a random vector. However, in DR, one attempts to project a random vector, either linearly or non-linearly, to a lower dime

Allen Nie, Arturo L. Pineda, Matt W. Wright Hannah Wand, Bryan Wulf

As genetic sequencing costs decrease, the lack of clinical interpretation of variants has become the bottleneck in using genetics data. A major rate limiting step in clinical interpretation is the manual curation of evidence in the genetic literature by highly trained biocurators. What makes curation particularly time-consuming is that the curator needs to i

Pei Lv, Haiyu Yu, Junxiao Xue, Junjin Cheng

Localizing objects with weak supervision in an image is a key problem of the research in computer vision community. Many existing Weakly-Supervised Object Localization (WSOL) approaches tackle this problem by estimating the most discriminative regions with feature maps (activation maps) obtained by Deep Convolutional Neural Network, that is, only the objects

Jiang Zhang, Xiao-Dong Yu, Gui-Lu Long, Qi-Kun Xue

We show that topological equivalence classes of circles in a two-dimensional square lattice can be used to design dynamical decoupling procedures to protect qubits attached on the edges of the lattice. Based on the circles of the topologically trivial class in the original and the dual lattices, we devise a procedure which removes all kinds of local Hamilton

Chandan Pradhan, Ang Li, Changyang She, Yonghui Li

We consider computation offloading for Internet-of-things (IoT) applications in multiple-input-multiple-output (MIMO) cloud-radio-access-network (C-RAN). Due to the limited battery life and computational capability in the IoT devices (IoTDs), the computational tasks of the IoTDs are offloaded to a MIMO C-RAN, where a MIMO radio resource head (RRH) is connect

Philipp V. Rouast, Marc T. P. Adam

Automatic detection of individual intake gestures during eating occasions has the potential to improve dietary monitoring and support dietary recommendations. Existing studies typically make use of on-body solutions such as inertial and audio sensors, while video is used as ground truth. Intake gesture detection directly based on video has rarely been attemp

Toshio Horiuchi, Peter Kumlin

In a bounded smooth domain of Rn, we shall establish Kato's inequalities involving measures for p-Laplace operator up to the boundary under suitable assumptions. Keywords: Kato's inequality, $p$-Laplace operator

Vinicius Pavanelli Vianna, Luiz Otavio Murta Junior

Mutual information (MI) is the standard method used in image registration and the most studied one but can diverge and produce wrong results when used in an automated manner. In this study we compared the results of the ITK Mattes MI function, used in 3D Slicer and ITK derived software solutions, and our own MICUDA Shannon and Tsallis MI functions under the

Barnaby Norris, Joss Bland-Hawthorn

Astronomers have come to recognize the benefits of photonics, often in combination with optical systems, in solving longstanding experimental problems in Earth-based astronomy. Here, we explore some of the recent advances made possible by integrated photonics. We also look to the future with a view to entirely new kinds of astronomy, particularly in an era o

Zoran Vondraček

In this paper, we look at a probabilistic approach to a non-local quadratic form that has lately attracted some interest. This form is related to a recently introduced non-local normal derivative. The goal is to construct two Markov process: one corresponding to that form and the other which is related to a probabilistic interpretation of the Neuman problem.

Daniel Sanchez, Weiwei Wan, Kensuke Harada

In this paper, we present a planner for manipulating tethered tools using dual-armed robots. The planner generates robot motion sequences to maneuver a tool and its cable while avoiding robot-cable entanglements. Firstly, the planner generates an Object Manipulation Motion Sequence (OMMS) to handle the tool and place it in desired poses. Secondly, the planne

Hongxuan Ma, Wei Zou, Zheng Zhu, Siyang Sun

In the field of navigation and visual servo, it is common to calculate relative pose by feature points on markers, so keeping markers in camera's view is an important problem. In this paper, we propose a novel approach to calculate field-of-view (FOV) constraint of markers for camera. Our method can make the camera maintain the visibility of all feature

Young-Pil Choi, Jaeseung Lee, Seok-Bae Yun

In this paper, we are concerned with the local-in-time well-posedness of a fluid-kinetic model in which the BGK model with density dependent collision frequency is coupled with the inhomogeneous Navier-Stokes equation through drag forces. To the best knowledge of authors, this is the first result on the existence of local-in-time smooth solution for particle

C. Y. Tan, Y. B. Koh, K. H. Ng, K. H. Ng

Structural Change Analysis of Active Cryptocurrency Market

Cheng Chi, Shifeng Zhang, Junliang Xing, Zhen Lei

Head and human detection have been rapidly improved with the development of deep convolutional neural networks. However, these two tasks are often studied separately without considering their inherent correlation, leading to that 1) head detection is often trapped in more false positives, and 2) the performance of human detector frequently drops dramatically

Yun Zhao, Yuqing Chen, Yuqiong Kang, Li Wang

Lithium-ion batteries have attracted enormous interests recently as promising power sources. However, the safety issue associated with the employment of highly flammable liquid electrolyte impedes the further development of next-generation lithium-ion batteries. Recently, researchers reported the use of electrospun core-shell fiber as the battery separator c

Fan Zhang

Beginning with Hartle and Hawking's no-boundary proposal, it has long been known that the pathology of a big bang singularity can be suppressed if a transition into Riemannian (Euclidean) metric signature (the usual singularity theorems become invalid in this region) occurs when we track back along cosmic time. A vital component of this type of models, t

Manuel Fernandez, David P. Woodruff, Taisuke Yasuda

Consider a variant of the Mastermind game in which queries are $\ell_p$ distances, rather than the usual Hamming distance. That is, a codemaker chooses a hidden vector $\mathbf{y}\in\{-k,-k+1,\dots,k-1,k\}^n$ and answers to queries of the form $\Vert\mathbf{y}-\mathbf{x}\Vert_p$ where $\mathbf{x}\in\{-k,-k+1,\dots,k-1,k\}^n$. The goal is to minimize the numb

M. S. Sherwin, C. Cates, B. Serapiglia, Y. Dora

At present, nearly quantum-limited heterodyne receivers for Terahertz (THz) frequencies require cooling to temperatures below 4K. We are working to build semiconductor-based "tunable antenna-coupled intersubband terahertz" (TACIT) heterodyne mixers for 1-5 THz. We predict that they can achieve single-sideband noise temperatures of a few hundred K wit

Jürgen Herzog, Guangjun Zhu

In this paper it is shown that a sortable ideal $I$ is Freiman if and only if its sorted graph is chordal. This characterization is used to give a complete classification of Freiman principal Borel ideals and of Freiman Veronese type ideals with constant bound.

Li-Pang Chen

High-dimensional sparse modeling with censored survival data is of great practical importance, and several methods have been proposed for variable selection based on different models. However, the impact of biased sample caused by left-truncation and covariates measurement error to variable selection is not fully explored. In this paper, we mainly focus on t

Yazhou Tu, Sara Rampazzi, Bin Hao, Angel Rodriguez

Temperature sensing and control systems are widely used in the closed-loop control of critical processes such as maintaining the thermal stability of patients, or in alarm systems for detecting temperature-related hazards. However, the security of these systems has yet to be completely explored, leaving potential attack surfaces that can be exploited to take

S. Vaitiekėnas, P. Krogstrup, C. M. Marcus

Multiply connected superconductors smaller than the coherence length show destructive superconductivity, characterized by reentrant quantum phase transitions driven by magnetic flux. We investigate the dependence of destructive superconductivity on flux, transverse magnetic field, temperature, and current in InAs nanowires with a surrounding epitaxial Al she

Zhi Zhang, Jiachen Yang, Hongyuan Zha

Traffic congestion in metropolitan areas is a world-wide problem that can be ameliorated by traffic lights that respond dynamically to real-time conditions. Recent studies applying deep reinforcement learning (RL) to optimize single traffic lights have shown significant improvement over conventional control. However, optimization of global traffic condition

Fábio Souza, Rodrigo Nogueira, Roberto Lotufo

Recent advances in language representation using neural networks have made it viable to transfer the learned internal states of a trained model to downstream natural language processing tasks, such as named entity recognition (NER) and question answering. It has been shown that the leverage of pre-trained language models improves the overall performance on m

Stephen A. Vavasis, Katerina D. Papoulia, M. Reza Hirmand

Cohesive fracture is among the few techniques able to model complex fracture nucleation and propagation with a sharp (nonsmeared) representation of the crack. Implicit time-stepping schemes are often favored in mechanics due to their ability to take larger time steps in quasistatic and moderate dynamic problems. Furthermore, initially rigid cohesive models a

Tom Pilvelait, Sam Dillavou, Shmuel M. Rubinstein

The real area of contact of a frictional interface changes rapidly when the normal load is altered, and evolves slowly when normal load is held constant, aging over time. Traditionally, the total area of contact is considered a proxy for the frictional strength of the interface. Here we show that the state of a frictional interface is not entirely defined by

Saeed Afrasiabi-Gorgani, Gerhard Wunder

The OFDM waveform exhibits high fluctuation in the signal envelope which causes distortion in the nonlinear power amplifier of the transmitter. Peak-to-Average Power Ratio (PAPR) and Cubic Metric (CM) are the common metrics to quantify the phenomenon. A promising approach for PAPR or CM reduction is Sign Selection which is based on altering the signs of the

Stefan Klus, Feliks Nüske, Sebastian Peitz, Jan-Hendrik Niemann

We derive a data-driven method for the approximation of the Koopman generator called gEDMD, which can be regarded as a straightforward extension of EDMD (extended dynamic mode decomposition). This approach is applicable to deterministic and stochastic dynamical systems. It can be used for computing eigenvalues, eigenfunctions, and modes of the generator and

Pengfei Zhang

In this paper, we study the evaporation dynamics of the Sachdev-Ye-Kitaev (SYK) model, with an initial temperature $T_\chi$, by coupling it to a thermal bath with lower temperature $T_\psi<T_\chi$ modeled by a larger SYK model. The coupling between the small system and the bath is turned on at time $t=0$. Then the system begins to envolve and finally becomes

Klaus W. Hodapp, Bo Reipurth, Bertil Pettersson, John Tonry

We report photometry and spectroscopy of the outburst of the young stellar object ESO-Halpha 99. The outburst was first noticed in Gaia alert Gaia18dvc and later by ATLAS. We have established the outburst light curve with archival ATLAS ``Orange'' filter photometry, Gaia data, new V-band photometry, and J, H, and K_s photometry from IRIS and UKIRT. The brigh

Daniel Seita, Aditya Ganapathi, Ryan Hoque, Minho Hwang

Sequential pulling policies to flatten and smooth fabrics have applications from surgery to manufacturing to home tasks such as bed making and folding clothes. Due to the complexity of fabric states and dynamics, we apply deep imitation learning to learn policies that, given color (RGB), depth (D), or combined color-depth (RGBD) images of a rectangular fabri

Shih-Ting Huang, Yannick Düren, Kristoffer H. Hellton, Johannes Lederer

Personalized medicine has become an important part of medicine, for instance predicting individual drug responses based on genomic information. However, many current statistical methods are not tailored to this task, because they overlook the individual heterogeneity of patients. In this paper, we look at personalized medicine from a linear regression standp

Sarira Sahu, Carlos E. Lopez Fortin, Shigehiro Nagataki

The high energy peaked blazars are known to undergo episodes of flaring in GeV-TeV gamma-rays involving different time scales and the flaring mechanism is not well understood despite long term simultaneous multiwavelength observations. These gamma-rays en route to Earth undergo attenuation by the extra galactic background light. Using the photohadronic model

Xiaoqing Wang, Sebastian Rosenzweig, Nick Scholand, H. Christian M. Holme

Purpose: To develop a single-shot multi-slice T1 mapping method by combing simultaneous multi-slice (SMS) excitations, single-shot inversion-recovery (IR) radial fast low-angle shot (FLASH) and a nonlinear model-based reconstruction method. Methods: SMS excitations are combined with a single-shot IR radial FLASH sequence for data acquisition. A previously de

Michael J. Lopez

Most historical National Football League (NFL) analysis, both mainstream and academic, has relied on public, play-level data to generate team and player comparisons. Given the number of oft omitted variables that impact on-field results, such as play call, game situation, and opponent strength, findings tend to be more anecdotal than actionable. With the rel

Sandro M. Reia, Paulo F. Gomes, José F. Fontanari

Axelrod's model for the dissemination of culture combines two key ingredients of social dynamics: social influence, through which people become more similar when they interact, and homophily, which is the tendency of individuals to interact preferentially with similar others. In Axelrod's model, the agents are fixed to the nodes of a network and are allowed

Rithwik Tom, Timothy Rose, Imanuel Bier, Harriet O'Brien

Genarris is an open-source Python package for generating random molecular crystal structures with physical constraints for seeding crystal structure prediction algorithms and training machine learning models. Here we present a new version of the code, containing several major improvements. An MPI-based parallelization scheme has been implemented, which facil

Alexander Michel, Marc Sher

A popular framework for exploring Lorentz violation is the Standard Model Extension. This extension contains a large number of parameters that can be bounded in various experiments. Most studies, however, focus on the fermion or photon sector. Here, we consider Lorentz violation in the weak vector boson sector. The strongest bounds come from measurements of

Yu Shi, Ji-Chong Yang

It has been well established that quantum mechanics (QM) violates Bell inequalities (BI), which are consequences of local realism (LR). Remarkably QM also violates Leggett inequalities (LI), which are consequences of a class of nonlocal realism called crypto-nonlocal realism (CNR). Both LR and CNR assume that measurement outcomes are determined by preexistin

Giacomo Del Nin, Kennedy Obinna Idu

We prove criteria for $\mathcal{H}^k$-rectifiability of subsets of $\mathbb{R}^n$ with $C^{1,\alpha}$ maps, $0<\alpha\leq 1$, in terms of suitable approximate tangent paraboloids. We also provide a version for the case when there is not an a priori tangent plane, measuring on dyadic scales how close the set is to lying in a $k$-plane. We then discuss the rel

Itay Shomroni, Liu Qiu, Tobias J. Kippenberg

We propose a scheme to prepare a macroscopic mechanical oscillator in a catlike state, close to a coherent state superposition. The mechanical oscillator, coupled by radiation-pressure interaction to a field in an optical cavity, is first prepared close to a squeezed vacuum state using a reservoir engineering technique. The system is then probed using a shor

Michael J. Catanzaro, Justin Curry, Brittany Terese Fasy, Jānis Lazovskis

We consider different notions of equivalence for Morse functions on the sphere in the context of persistent homology, and introduce new invariants to study these equivalence classes. These new invariants are as simple, but more discerning than existing topological invariants, such as persistence barcodes and Reeb graphs. We give a method to relate any two Mo

Gokhan Unel, Sezen Sekmen, Anna Monica Toon

We present CutLang, an analysis description language and runtime interpreter for high energy collider physics data analyses. An analysis description language is a declerative domain specific language that can express all elements of a data analysis in an easy and unambiguous way. A full-fledged human readable analysis description language, incorporating logi

Jorge Lauret, Marina Nicolini

A complete classification of left-invariant closed G2-structures on Lie groups which are extremally Ricci pinched, up to equivalence and scaling, is obtained. There are five of them, they are defined on five different completely solvable Lie groups and the G2-structure is exact in all cases except one, given by the only example in which the Lie group is unim

Mesay Samuel Gondere, Lars Schmidt-Thieme, Abiot Sinamo Boltena, Hadi Samer Jomaa

Amharic is the official language of the Federal Democratic Republic of Ethiopia. There are lots of historic Amharic and Ethiopic handwritten documents addressing various relevant issues including governance, science, religious, social rules, cultures and art works which are very reach indigenous knowledge. The Amharic language has its own alphabet derived fr

Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu

Hierarchical reinforcement learning has demonstrated significant success at solving difficult reinforcement learning (RL) tasks. Previous works have motivated the use of hierarchy by appealing to a number of intuitive benefits, including learning over temporally extended transitions, exploring over temporally extended periods, and training and exploring in a

A. F. Tzortzakakis, N. Flytzanis

In this thesis we study short Josephson junctions which include a region with Rashba spin-orbit coupling effect. Our junctions consists of two superconductors (S) and a 2-dimensional electron gas (2DEG) layer between them: S/2DEG/S junction. We also include two thin insulating interfaces between the superconductors and the 2DEG, which are capable of both nor

Marco Polini, Andre K Geim

Recent advances in materials science have made it possible to achieve conditions under which electrons in metals start behaving as highly viscous fluids, "thicker than honey", and exhibit fascinating hydrodynamic effects. In this short review we provide a popular introduction to the emerging field of electron hydrodynamics.

Shiwali Mohan, Hesham Rakha, Matthew Klenk

Our research aims at developing intelligent systems to reduce the transportation-related energy expenditure of a large city by influencing individual behavior. We introduce COPTER - an intelligent travel assistant that evaluates multi-modal travel alternatives to find a plan that is acceptable to a person given their context and preferences. We propose a for

Graham E. Rowlands, Minh-Hai Nguyen, Sriharsha V. Aradhya, Shengjie Shi

We characterize the nanosecond pulse switching performance of the three-terminal magnetic tunnel junctions (MTJs), driven by the spin Hall effect (SHE) in the channel, at a cryogenic temperature of 3 K. The SHE-MTJ devices exhibit reasonable magnetic switching and reliable current switching by as short pulses as 1 ns of $<10^{12}$ A/m$^{2}$ magnitude, exceed

Agnieszka Bartłomiejczyk, Marek Bodnar

We analyse a model of Hes1 gene transcription and protein synthesis with a negative feedback loop. The effect of multiple binding sites in the Hes1 promoter as well as the dimer formation process are taken into account. We consider three, possibly different, time scales connected with: (i) the process of binding to/dissolving from a binding site, (ii) format

Wei Cai, Xiaoguang Li, Lizuo Liu

In this paper, we propose a phase shift deep neural network (PhaseDNN), which provides a uniform wideband convergence in approximating high frequency functions and solutions of wave equations. The PhaseDNN makes use of the fact that common DNNs often achieve convergence in the low frequency range first, and a series of moderately-sized DNNs are constructed a

Michel Rottleuthner, Thomas C. Schmidt, Matthias Wählisch

Energy-constrained sensor nodes can adaptively optimize their energy consumption if a continuous measurement exists. This is of particular importance in scenarios of high dynamics such as energy harvesting or adaptive task scheduling. However, self-measuring of power consumption at reasonable cost and complexity is unavailable as a generic system service. In

Marina A. Ferreira, Jani Lukkarinen, Alessia Nota, Juan J. L. Velázquez

We study coagulation equations under non-equilibrium conditions which are induced by the addition of a source term for small cluster sizes. We consider both discrete and continuous coagulation equations, and allow for a large class of coagulation rate kernels, with the main restriction being boundedness from above and below by certain weight functions. The w

M. Ajello, M. Arimoto, M. Axelsson, L. Baldini

We report on the observations of gamma-ray burst (GRB) 190114C by the Fermi Gamma-ray Space Telescope and the Neil Gehrels Swift Observatory. The early-time observations reveal multiple emission components that evolve independently, with a delayed power-law component that exhibits significant spectral attenuation above 40 MeV in the first few seconds of the

Patrick Lutz, James Walsh

This paper is an investigation of the relationship between G\"odel's second incompleteness theorem and the well-foundedness of jump hierarchies. It follows from a classic theorem of Spector's that the relation $\{(A,B) \in \mathbb{R}^2 : \mathcal{O}^A \leq_H B\}$ is well-founded. We provide an alternative proof of this fact that uses G\"odel's second incompl

Raya Dastidar, Kuntal Misra, Stefano Valenti, Jamison Burke

We present the photometry and spectroscopy of SN 2015an, a Type II Supernova (SN) in IC 2367. The recombination phase of the SN lasts up to $\sim$120 d, with a decline rate of 1.24 mag/100d, higher than the typical SNe IIP. The SN exhibits bluer colours than most SNe II, indicating higher ejecta temperatures. The absolute $V$-band magnitude of SN 2015an at 5

Daniel F. Tracey, Eva G. Noya, Jonathan P. K. Doye

We introduce a scheme to design patchy particles so that a given target crystal is the global free-energy minimum at sufficiently low temperature. A key feature is a torsional component to the potential that only allows binding when particles have the correct relative orientations. In all examples studied, the target crystal structures readily assembled on a

Andrzej Chlebicki, Pawel Jakubczyk

We study the $O(2)$ model with $\mathbb{Z}_4$-symmetric perturbations within the framework of nonperturbative renormalization group (RG) for spatial dimensionality $d=2$ and $d=3$. In a unified framework we resolve the relatively complex crossover behavior emergent due to the presence of multiple RG fixed points. In $d=3$ the system is controlled by the $XY$

Jordan Ott, Erik Linstead, Nicholas LaHaye, Pierre Baldi

Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sharing is necessary. If so, to which degree of precision? If not, what are the alternatives? The goal of this s

Pierre Touboul, Gilles Métris, Manuel Rodrigues, Yves André

The Weak Equivalence Principle (WEP), stating that two bodies of different compositions and/or mass fall at the same rate in a gravitational field (universality of free fall), is at the very foundation of General Relativity. The MICROSCOPE mission aims to test its validity to a precision of $10^{-15}$, two orders of magnitude better than current on-ground te

Eric Jankowski, Charles R. Johnson, Derek Lim

The still-unsolved problem of determining the set of eigenvalues realized by $n$-by-$n$ doubly stochastic matrices, those matrices with row sums and column sums equal to $1$, has attracted much attention in the last century. This problem is somewhat algebraic in nature, due to a result of Birkhoff demonstrating that the set of doubly stochastic matrices is t

Juan Manuel Armaleo, Diana López Nacir, Federico R. Urban

Binary pulsars can be excellent probes of ultra-light dark matter. We consider the scenario where the latter is represented by a spin-2 field. The coherent oscillations of the dark matter field perturb the dynamics of binary systems, leading to secular effects for masses that resonate with the binary systems. For the range $10^{-23}$eV $\lesssim m \lesssim 1

T. A. Assefa, Y. Cao, J. Diao, K. Kisslinger

Translational/rotational symmetry breaking and recovery in condensed matter systems are closely related to exotic physical properties such as superconductivity (SC), magnetism, spin density waves (SDW) and charge density waves (CDW). The interplay between different order parameters is intricate and often subject to intense debate, as in the case of CDW order

Jinyuan Jia, Ahmed Salem, Michael Backes, Yang Zhang

In a membership inference attack, an attacker aims to infer whether a data sample is in a target classifier's training dataset or not. Specifically, given a black-box access to the target classifier, the attacker trains a binary classifier, which takes a data sample's confidence score vector predicted by the target classifier as an input and predicts the dat

P. O. Sukhachov, M. V. Rakov, O. M. Teslyk, E. V. Gorbar

The transport properties and electron states in cylinder nanowires of Dirac and Weyl semimetals are studied paying special attention to the structure and properties of the surface Fermi arcs. The latter make the electric charge and current density distributions in nanowires strongly nonuniform as the majority of the charge density is accumulated at the surfa

Augustine Musukwa, Massimiliano Sala, Marco Zaninelli

In this paper some cryptographic properties of Boolean functions, including weight, balancedness and nonlinearity, are studied, particularly focusing on splitting functions and cubic Boolean functions. Moreover, we present some quantities derived from the behaviour of second-order derivatives which allow us to determine whether a quadratic or cubic function