September 2019 arXiv papers — page 29

Mohammad Akhlaghi

NoiseChisel is a program to detect very low signal-to-noise ratio (S/N) features with minimal assumptions on their morphology. It was introduced in 2015 and released within a collection of data analysis programs and libraries known as GNU Astronomy Utilities (Gnuastro). The 10th stable version of Gnuastro was released in August 2019 and NoiseChisel has signi

Alexander Mathis, Thomas Biasi, Steffen Schneider, Mert Yüksekgönül

Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe the generalization ability with three architecture classes (MobileNetV2s, ResNets, and EfficientNets) f

David Venuto, Leonard Boussioux, Junhao Wang, Rola Dali

Imitation learning seeks to learn an expert policy from sampled demonstrations. However, in the real world, it is often difficult to find a perfect expert and avoiding dangerous behaviors becomes relevant for safety reasons. We present the idea of \textit{learning to avoid}, an objective opposite to imitation learning in some sense, where an agent learns to

Kishan Chandan, Vidisha Kudalkar, Xiang Li, Shiqi Zhang

Effective human-robot collaboration (HRC) requires extensive communication among the human and robot teammates, because their actions can potentially produce conflicts, synergies, or both. We develop a novel augmented reality (AR) interface to bridge the communication gap between human and robot teammates. Building on our AR interface, we develop an AR-media

Jingyi Xu, Michael Danielczuk, Jeff Ichnowski, Jeffrey Mahler

Robot grasping of deformable hollow objects such as plastic bottles and cups is challenging as the grasp should resist disturbances while minimally deforming the object so as not to damage it or dislodge liquids. We propose minimal work as a novel grasp quality metric that combines wrench resistance and the object deformation. We introduce an efficient algor

Borja Balle, James Bell, Adria Gascon, Kobbi Nissim

A protocol by Ishai et al.\ (FOCS 2006) showing how to implement distributed $n$-party summation from secure shuffling has regained relevance in the context of the recently proposed \emph{shuffle model} of differential privacy, as it allows to attain the accuracy levels of the curator model at a moderate communication cost. To achieve statistical security $2

Diego Fernando Ramírez Jiménez

Se enuncia los principales teoremas empleados en la resoluci'on de tri'angulos oblicu'angulos. Con ellos, se ilustra c'omo resolver los cinco casos de resoluci'on que se presentan, incluyendo algunos caso at'ipicos (cuando se conoce el per'imetro y dos 'angulos internos, o un lado, el 'angulo comprendido entre los lados restantes, as'i como su suma). Luego,

Weilong Ren, Xiang Lian, Kambiz Ghazinour

Nowadays, efficient and effective processing over massive stream data has attracted much attention from the database community, which are useful in many real applications such as sensor data monitoring, network intrusion detection, and so on. In practice, due to the malfunction of sensing devices or imperfect data collection techniques, real-world stream dat

Bruno Scheihing Hitschfeld

In this thesis, we show how the structure of the landscape potential of the primordial Universe may be probed through the primordial density perturbations responsible for the origin of the cosmic microwave background anisotropies and the large-scale structure of our Universe. Isocurvature fields may have fluctuated across the barriers separating local minima

Karl Dilcher, Maciej Ulas

For each integer $n\geq 1$ we consider the unique polynomials $P, Q\in\mathbb{Q}[x]$ of smallest degree $n$ that are solutions of the equation $P(x)x^{n+1}+Q(x)(x+1)^{n+1}=1$. We derive numerous properties of these polynomials and their derivatives, including explicit expansions, differential equations, recurrence relations, generating functions, resultants,

Alp Aydinoglu, Victor M. Preciado, Michael Posa

While many robotic tasks, like manipulation and locomotion, are fundamentally based in making and breaking contact with the environment, state-of-the-art control policies struggle to deal with the hybrid nature of multi-contact motion. Such controllers often rely heavily upon heuristics or, due to the combinatoric structure in the dynamics, are unsuitable fo

René-Jean Essiambre, Roland Ryf, Sjoerd van der Heide, Juan I. Bonetti

We demonstrate the first transmission of a new twelve-dimensional modulation format over a three-core coupled-core multicore fiber. The format occupies a single time slot spread across all three linearly-coupled spatial modes and shows improved MI and GMI after transmission compared to PDM-QPSK.

Ludvig Sinander

I prove an envelope theorem with a converse: the envelope formula is equivalent to a first-order condition. Like Milgrom and Segal's (2002) envelope theorem, my result requires no structure on the choice set. I use the converse envelope theorem to extend to general outcomes and preferences the canonical result in mechanism design that any increasing allocati

Shikhar Vashishth, Shyam Upadhyay, Gaurav Singh Tomar, Manaal Faruqui

The attention layer in a neural network model provides insights into the model's reasoning behind its prediction, which are usually criticized for being opaque. Recently, seemingly contradictory viewpoints have emerged about the interpretability of attention weights (Jain & Wallace, 2019; Vig & Belinkov, 2019). Amid such confusion arises the need to understa

Iddo Ben-Ari, Behrang Forghani

A discrete-time Markov chain can be transformed into a new Markov chain by looking at its states along iterations of an almost surely finite stopping time. By the optional stopping theorem, any bounded harmonic function with respect to the transition function of the original chain is harmonic with respect to the transition function of the transformed chain.

Zhe Zhang, Shabbir Ahmed, Guanghui Lan

Recently, there has been a growing interest in distributionally robust optimization (DRO) as a principled approach to data-driven decision making. In this paper, we consider a distributionally robust two-stage stochastic optimization problem with discrete scenario support. While much research effort has been devoted to tractable reformulations for DRO proble

Liam Dobson

In the present paper we construct braid group actions on quantum symmetric pair coideal subalgebras of type AIII/AIV. This completes the proof of a conjecture by Kolb and Pellegrini in the case where the underlying Lie algebra is $\mathfrak{sl}_n$. The braid group actions are defined on the generators of the coideal subalgebras and the defining relations and

Bradley W. Brock, Noam D. Elkies, Bruce W. Jordan

We generalize the classical theory of periodic continued fractions (PCFs) over ${\mathbf Z}$ to rings ${\mathcal O}$ of $S$-integers in a number field. Let ${\mathcal B}=\{\beta, {\beta^*}\}$ be the multi-set of roots of a quadratic polynomial in ${\mathcal O}[x]$. We show that PCFs $P=[b_1,\ldots,b_N,\bar{a_1\ldots ,a_k}]$ of type $(N,k)$ potentially conver

Kevin Doherty, David Baxter, Edward Schneeweiss, John Leonard

Modern robotic systems sense the environment geometrically, through sensors like cameras, lidar, and sonar, as well as semantically, often through visual models learned from data, such as object detectors. We aim to develop robots that can use all of these sources of information for reliable navigation, but each is corrupted by noise. Rather than assume that

Julianna D. Ianni, Rajath E. Soans, Sivaramakrishnan Sankarapandian, Ramachandra Vikas Chamarthi

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin \& eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatop

Kathy Li, Iñigo Urteaga, Chris H. Wiggins, Anna Druet

The menstrual cycle is a key indicator of overall health for women of reproductive age. Previously, menstruation was primarily studied through survey results; however, as menstrual tracking mobile apps become more widely adopted, they provide an increasingly large, content-rich source of menstrual health experiences and behaviors over time. By exploring a da

Yanying Wu

Gene Ontology (GO) is the most important resource for gene function annotation. It provides a way to unify biological knowledge across different species via a dynamic and controlled vocabulary. GO is now widely represented in the Semantic Web standard Web Ontology Language (OWL). OWL renders a rich logic constructs to GO but also has its limitations. On the

Jackson D. Miller, Felicia H. Ullstad, H. Joe Trodahl, Ben. J. Ruck

We report an investigation of the ferromagnetic semiconductor rare earth nitrides (RENs) for their potential for cryogenic-temperature electronics and spintronics application. We have indentified ohmic contacts suitable for the device structures that demand electron transport through interface layers, and grown REN/insulator/REN heterostructures that display

Hugh Morton, Alexander Pokorny, Peter Samuelson

We give a presentation of the Kauffman (BMW) skein algebra of the torus, which is the "type BCD" analogue of the Homflypt skein algebra of torus which was computed by the first and third authors. In the appendix we show this presentation is compatible with the Frohman-Gelca description of the Kauffman bracket (Temperley-Lieb) skein algebra of the torus [FG00

Shusen Wang

Random feature mapping (RFM) is a popular method for speeding up kernel methods at the cost of losing a little accuracy. We study kernel ridge regression with random feature mapping (RFM-KRR) and establish novel out-of-sample error upper and lower bounds. While out-of-sample bounds for RFM-KRR have been established by prior work, this paper's theories are hi

Julie L Newcomb, Rastislav Bodik

Programs that respond to asynchronous events are challenging to write; they are difficult to reason about and tricky to test and debug. Because these programs can have a huge space of possible input timings and interleaving, the programmer may easily miss corner cases. We propose applying synthesis to aid programmers in creating programs more easily and with

Kai Shinbrough, Yanting Teng, Bin Fang, Virginia O. Lorenz

We develop a Hamiltonian formalism to study energy and position/momentum correlations between a single Stokes photon and a single material excitation that are created as a pair in the spontaneous Raman scattering process. Our approach allows for intuitive separation of the effects of spectral linewidth, chromatic dispersion, and collection angle on these cor

Emily Hannigan, Bing Song, Gagan Khandate, Maximilian Haas-Heger

In this paper, we propose a method for generating undulatory gaits for snake robots. Instead of starting from a pre-defined movement pattern such as a serpenoid curve, we use a Model Predictive Control approach to automatically generate effective locomotion gaits via trajectory optimization. An important advantage of this approach is that the resulting gaits

Carlo Cenedese, Giuseppe Belgioioso, Yu Kawano, Sergio Grammatico

In this paper, we study proximal type dynamics in the context of noncooperative multi-agent network games. These dynamics arise in different applications, since they describe distributed decision making in multi-agent networks, e.g., in opinion dynamics, distributed model fitting and network information fusion, where the goal of each agent is to seek an equi

Eren Balevi, Jeffrey G. Andrews

This paper proposes a novel deep learning-based error correction coding scheme for AWGN channels under the constraint of one-bit quantization in the receivers. Specifically, it is first shown that the optimum error correction code that minimizes the probability of bit error can be obtained by perfectly training a special autoencoder, in which "perfectly" ref

Brandon Laughlin, Christopher Collins, Karthik Sankaranarayanan, Khalil El-Khatib

This paper presents a framework which enables a user to more easily make corrections to adversarial texts. While attack algorithms have been demonstrated to automatically build adversaries, changes made by the algorithms can often have poor semantics or syntax. Our framework is designed to facilitate human intervention by aiding users in making corrections.

Mengjiao Zhang, Shusen Wang

Collaborative learning allows participants to jointly train a model without data sharing. To update the model parameters, the central server broadcasts model parameters to the clients, and the clients send updating directions such as gradients to the server. While data do not leave a client device, the communicated gradients and parameters will leak a client

Yanpei Shi, Qiang Huang, Thomas Hain

While the use of deep neural networks has significantly boosted speaker recognition performance, it is still challenging to separate speakers in poor acoustic environments. To improve robustness of speaker recognition system performance in noise, a novel two-stage attention mechanism which can be used in existing architectures such as Time Delay Neural Netwo

Yu Tang, Yining Wen, Li Jin

In this article, we study the classical shortest queue problem under the influence of malicious attacks, which is relevant to a variety of engineering system including transportation, manufacturing, and communications. We consider a homogeneous Poisson arrival process of jobs and two parallel exponential servers with symmetric service rates. A system operato

D. A. Bryman, R. Shrock

A detailed discussion is given of the analysis of recent data to obtain improved upper bounds on the couplings $|U_{e4}|^2$ and $|U_{\mu 4}|^2$ for a mainly sterile neutrino mass eigenstate $\nu_4$. Using the excellent agreement among ${\cal F}t$ values for superallowed nuclear beta decay, an improved upper limit is derived for emission of a $\nu_4$. The agr

Tanwi Mallick, Prasanna Balaprakash, Eric Rask, Jane Macfarlane

Traffic forecasting approaches are critical to developing adaptive strategies for mobility. Traffic patterns have complex spatial and temporal dependencies that make accurate forecasting on large highway networks a challenging task. Recently, diffusion convolutional recurrent neural networks (DCRNNs) have achieved state-of-the-art results in traffic forecast

Shao-Jiang Wang

Recently, a novel phenomenon is observed for vacuum decay to proceed via classically allowed dynamical evolution from initial configurations of false vacuum fluctuations. With the help of some occasionally developed large fluctuations in time derivative of a homogeneous scalar field that is initially sitting at the false vacuum, the flyover vacuum decay is p

Jeremy D. Schnittman

In the science fiction film $Interstellar$, a band of intrepid astronauts sets out to explore a system of planets orbiting a supermassive black hole, searching for a world that may be conducive to hosting human life. While the film legitimately boasts a relatively high level of scientific accuracy, it is still restricted by Hollywood sensitivities and limita

Ulrich Krupp, Christian Haase, Wenwen Song, Wolfgang Bleck

Nowadays, most structural integrity concepts rely on simplified isotropic ma-terial data that are used within continuum mechanics modeling approaches. In contrast, modern casting and forming processes yield complex microstruc-tures coming along with pronounced gradients in the material's properties in various length scales. By means of additive manufacturing

Gonzalo Cousillas, Jorge Groisman, Juliana Xavier

We study the dynamics of Topologically Anosov homeomorphisms of non compact surfaces. In the case of surfaces of genus zero and finite type, we classify them. We prove that if $f:S \to S$, is a Topologically Anosov homeomorphism where $S$ is a non-compact surface of genus zero and finite type, then $S= \R ^ 2$ and $f$ is conjugate to a homothety or reverse h

Xiang Chen, Igor Krivenko, Matthew B. Stone, Alexander I. Kolesnikov

The physics of weak itinerant ferromagnets is challenging due to their small magnetic moments and the ambiguous role of local interactions governing their electronic properties, many of which violate Fermi liquid theory. While magnetic fluctuations play an important role in the materials' unusual electronic states, the nature of these fluctuations and the pa

Dimitris Boskos, Jorge Cortés, Sonia Martínez

Distributional ambiguity sets provide quantifiable ways to characterize the uncertainty about the true probability distribution of random variables of interest. This makes them a key element in data-driven robust optimization by exploiting high-confidence guarantees to hedge against uncertainty. This paper explores the construction of Wasserstein ambiguity s

Wei Zhu, Qiang Qiu, Robert Calderbank, Guillermo Sapiro

Encoding the scale information explicitly into the representation learned by a convolutional neural network (CNN) is beneficial for many computer vision tasks especially when dealing with multiscale inputs. We study, in this paper, a scaling-translation-equivariant (ST-equivariant) CNN with joint convolutions across the space and the scaling group, which is

William Clark, Anthony Bloch

The evolution of a Lagrangian mechanical system is variational. Likewise, when dealing with a hybrid Lagrangian system (a system with discontinuous impacts), the impacts can also be described by variations. These variational impacts are given by the so-called Weierstrass-Erdmann corner conditions. Therefore, hybrid Lagrangian systems can be completely unders

Rustam Pirmagomedov, Yevgeni Koucheryavy

Internet of Things (IoT) technology has delivered new enablers for improving human abilities. These enablers promise an enhanced quality of life and professional efficiency; however, the synthesis of IoT and human augmentation technologies has also extended IoT-related challenges far beyond the current scope. These potential challenges associated with IoT-em

Vedran Sekara, Elisa Omodei, Laura Healy, Jan Beise

Today, 95% of the global population has 2G mobile phone coverage and the number of individuals who own a mobile phone is at an all time high. Mobile phones generate rich data on billions of people across different societal contexts and have in the last decade helped redefine how we do research and build tools to understand society. As such, mobile phone data

Thomas N. Haider

Statistical topic models are increasingly and popularly used by Digital Humanities scholars to perform distant reading tasks on literary data. It allows us to estimate what people talk about. Especially Latent Dirichlet Allocation (LDA) has shown its usefulness, as it is unsupervised, robust, easy to use, scalable, and it offers interpretable results. In a p

Thomas Gurriet, Maegan Tucker, Alexis Duburcq, Guilhem Boeris

This paper presents and experimentally demonstrates a novel framework for variable assistance on lower body exoskeletons, based upon safety-critical control methods. Existing work has shown that providing some freedom of movement around a nominal gait, instead of rigidly following it, accelerates the spinal learning process of people with a walking impedimen

Sheung Chi Chan, James Cheney, Pramod Bhatotia, Thomas Pasquier

System level provenance is of widespread interest for applications such as security enforcement and information protection. However, testing the correctness or completeness of provenance capture tools is challenging and currently done manually. In some cases there is not even a clear consensus about what behavior is correct. We present an automated tool, Pro

Christopher Amato, Andrea Baisero

To coordinate with other systems, agents must be able to determine what the systems are currently doing and predict what they will be doing in the future---plan and goal recognition. There are many methods for plan and goal recognition, but they assume a passive observer that continually monitors the target system. Real-world domains, where information gathe

Maarten V. de Hoop, Teemu Saksala, Gunther Uhlmann, Jian Zhai

We consider the mixed ray transform of tensor fields on a three-dimensional compact simple Riemannian manifold with boundary. We prove the injectivity of the transform, up to natural obstructions, and establish stability estimates for the normal operator on generic three dimensional simple manifold in the case of 1+1 and 2+2 tensors fields. We show how the a

Chenyang Zhong, Robert Tibshirani

In this paper, we explore a method for treating survival analysis as a classification problem. The method uses a "stacking" idea that collects the features and outcomes of the survival data in a large data frame, and then treats it as a classification problem. In this framework, various statistical learning algorithms (including logistic regression, random f

Edoardo Ballico, Emanuele Ventura

Let $X$ be a complex projective variety defined over $\mathbb R$. Recently, Bernardi and the first author introduced the notion of admissible rank with respect to $X$. This rank takes into account only decompositions that are stable under complex conjugation. Such a decomposition carries a label, i.e., a pair of integers recording the cardinality of its tota

Joshua Lackman

The van Est map is a map from Lie groupoid cohomology (with respect to a sheaf taking values in a representation) to Lie algebroid cohomology. We generalize the van Est map to allow for more general sheaves, namely to sheaves of sections taking values in a (smooth or holomorphic) $G$-module, where $G$-modules are structures which differentiate to representat

O. de Melo, C. de Melo, G. Santana, J. Santoyo

Porous silicon layers were embedded with ZnTe using the isothermal close space sublimation technique. The presence of ZnTe was demonstrated using cross-sectional energy dispersive spectroscopy maps. ZnTe embedded samples present intense room temperature photoluminescence along the whole visible range. We ascribe this PL to ZnTe nanocrystals of different size

Giuseppe Tomassetti

We discuss the role of the extra force $$ \mathbf f_{\rm e}=-\frac 1 2(\nabla\cdot\mathbf v)\mathbf v $$ in the system of partial differential equations \begin{equation*} \left\{ \begin{aligned} &\frac{\partial\mathbf v}{\partial \rm t}+(\mathbf v\cdot\nabla)\mathbf v+\nabla \mathrm p-\frac 1 {\rm Re}\Delta\mathbf v=\mathbf f+\mathbf f_{\rm e},\\ &\frac 1 {\

Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa

Deep learning approaches based on convolutional neural networks (CNNs) have been successful in solving a number of problems in medical imaging, including image segmentation. In recent years, it has been shown that CNNs are vulnerable to attacks in which the input image is perturbed by relatively small amounts of noise so that the CNN is no longer able to per

Aaron Yi Ding, Gianluca Limon De Jesus, Marijn Janssen

The security of the Internet of Things (IoT) has attracted much attention due to the growing number of IoT-oriented security incidents. IoT hardware and software security vulnerabilities are exploited affecting many companies and persons. Since the causes of vulnerabilities go beyond pure technical measures, there is a pressing demand nowadays to demystify I

Adán Cabello

The totalitarian principle establishes that `anything not forbidden is compulsory'. The problem of quantum correlations is explaining what selects the set of quantum correlations for a Bell and Kochen-Specker (KS) contextuality scenario. Here, we show that two assumptions and a version of the totalitarian principle lead to the quantum correlations. The assum

Fan Sang, Daehee Jang, Ming-Wei Shih, Taesoo Kim

Global corporations (e.g., Google and Microsoft) have recently introduced a new model of cloud services, fuzzing-as-a-service (FaaS). Despite effectively alleviating the cost of fuzzing, the model comes with privacy concerns. For example, the end user has to trust both cloud and service providers who have access to the application to be fuzzed. Such concerns

Mustafa Gökhan Benli, Burak Kaya

In this paper, we determine the descriptive complexity of subsets of the Polish space of marked groups defined by various group theoretic properties. In particular, using Grigorchuk groups, we establish that the sets of solvable groups, groups of exponential growth and groups with decidable word problem are $\mathbf{\Sigma}^0_2$-complete and that the sets of

Gleb Lukicov

The $g-2$ experiment successfully completed its second data taking period (Run-2) between March and July 2019, with the analysis of Run-1 and Run-2 data currently proceeding. The final goal of the experiment is to determine the muon magnetic anomaly, $a_{\mu}=\frac{g-2}{2}$, to a precision of 140 ppb. Essential to reducing the systematic uncertainty on $a_{\

Konstantinos Karvounis

We define a family of the braid group representations via the action of the $R$-matrix (of the quasitriangular extension) of the restricted quantum $\mathfrak{sl}(2)$ on a tensor power of a simple projective module. This family is an extension of the Lawrence representation specialized at roots of unity. Although the center of the braid group has finite orde

Joshua P. Keller, Adam A. Szpiro

Unmeasured, spatially-structured factors can confound associations between spatial environmental exposures and health outcomes. Adding flexible splines to a regression model is a simple approach for spatial confounding adjustment, but the spline degrees of freedom do not provide an easily interpretable spatial scale. We describe a method for quantifying the

Rojin Aslani, Mehdi Rasti, Ata Khalili

In this paper, we develop an energy efficient resource allocation scheme for orthogonal frequency division multiple access (OFDMA) networks with in-band full-duplex (IBFD) communication between the base station and user equipments (UEs) considering a realistic self-interference (SI) model. Our primary aim is to maximize the system energy efficiency (EE) thro

Lars Lindemann, Dimos V. Dimarogonas

The use of spatio-temporal logics in control is motivated by the need to impose complex spatial and temporal behavior on dynamical systems, and to control these systems accordingly. Synthesizing correct-by-design control laws is a challenging task resulting in computationally demanding methods. We consider efficient automata-based planning for continuous-tim

Stacy McGaugh

We discuss a model for the Milky Way obtained by fitting the observed terminal velocities with the radial acceleration relation. The resulting stellar surface density profile departs from a smooth exponential disk, having bumps and wiggles that correspond to massive spiral arms. These features are used to estimate the term for the logarithmic density gradien

Junhao Li, Yuan Yao, Adam A. Holmes, Matthew Otten

We describe a method for computing near-exact energies for correlated systems with large Hilbert spaces. The method efficiently identifies the most important basis states (Slater determinants) and performs a variational calculation in the subspace spanned by these determinants. A semistochastic approach is then used to add a perturbative correction to the va

Zeyu Zhou, Zuxin Jin, Tian Qiu, Andrew M. Rappe

We investigate a simple and robust scheme for choosing the phases of adiabatic electronic states smoothly (as a function of geometry) so as to maximize the performance of ab initio non-adiabatic dynamics methods. Our approach is based upon consideration of the overlap matrix ($\mathbf{U}$) between basis functions at successive points in time and selecting th

Emilio Almansi, Verónica Becher

We study a construction published by Donald Knuth in 1965 yielding a completely uniformly distributed sequence of real numbers. Knuth's work is based on de Bruijn sequences of increasing orders and alphabet sizes, which grow exponentially in each of the successive segments composing the generated sequence. In this work we present a similar albeit simpler con

Serim Ryou, Seong-Gyun Jeong, Pietro Perona

We propose a novel loss function that dynamically rescales the cross entropy based on prediction difficulty regarding a sample. Deep neural network architectures in image classification tasks struggle to disambiguate visually similar objects. Likewise, in human pose estimation symmetric body parts often confuse the network with assigning indiscriminative sco

Guilherme Ferraz de Arruda, Giovanni Petri, Yamir Moreno

Our understanding of the dynamics of complex networked systems has increased significantly in the last two decades. However, most of our knowledge is built upon assuming pairwise relations among the system's components. This is often an oversimplification, for instance, in social interactions that occur frequently within groups. To overcome this limitation,

Maciej Kucharski

We study $L^p$ bounds for two kinds of Riesz transforms on $\mathbb{R}^d$ related to the harmonic oscillator. We pursue an explicit estimate of their $L^p$ norms that is independent of the dimension $d$ and linear in $\max(p, p/(p-1))$.

Václav Blažej, Jiří Fiala, Giuseppe Liotta

We study planar straight-line drawings of graphs that minimize the ratio between the length of the longest and the shortest edge. We answer a question of Lazard et al. [Theor. Comput. Sci. 770 (2019), 88--94] and, for any given constant $r$, we provide a $2$-tree which does not admit a planar straight-line drawing with a ratio bounded by $r$. When the ratio

Jens Niklas Eberhardt

We construct an ungraded version of Beilinson-Ginzburg-Soergel's Koszul duality for Langlands dual flag varieties, inspired by Beilinson's construction of rational motivic cohomology in terms of $K$-theory. For this, we introduce and study categories $\operatorname{DK}_{\mathcal{S}}(X)$ of $\mathcal{S}$-constructible $K$-motivic sheaves on varieties $X$ with

Nouamane Laanait, Joshua Romero, Junqi Yin, M. Todd Young

We introduce novel communication strategies in synchronous distributed Deep Learning consisting of decentralized gradient reduction orchestration and computational graph-aware grouping of gradient tensors. These new techniques produce an optimal overlap between computation and communication and result in near-linear scaling (0.93) of distributed training up

Boris Tsirelson

Contrary to popular misconception, the question in the title is far from simple. It involves sets of numbers on the first level, sets of sets of numbers on the second level, and so on, endlessly. The infinite hierarchy of the levels involved distinguishes the concept of "definable number" from such notions as "natural number", "rational number", "algebraic n

Daniel Fuentes-Keuthan

We put a model structure on a full subcategory of based multicategories in which the weak equivalences are created by the K-theory functor of Elmendorf-Mandell, providing a model categorical lift of Thomason's theorem on the modeling of connective spectra by symmetric monoidal categories. We note that this lifts to a semi-modelstructure on based multicategor

Jacob Holm, Valerie King, Mikkel Thorup, Or Zamir

Each vertex of an arbitrary simple graph on $n$ vertices chooses $k$ random incident edges. What is the expected number of edges in the original graph that connect different connected components of the sampled subgraph? We prove that the answer is $O(n/k)$, when $k\ge c\log n$, for some large enough $c$. We conjecture that the same holds for smaller values o

Jerimiah Wright

The purpose of this experiment was to use the known analytical techniques to study the creation, simulation, and measurements of molecular Hamiltonians. The techniques used consisted of the Linear Combination of Atomic Orbitals (LCAO), the Linear Combination of Unitaries (LCU), and the Phase Estimation Algorithm (PEA). The molecules studied were $H_2$ with a

Timo C. Wunderlich, Akos F. Kungl, Eric Müller, Johannes Schemmel

Future developments in artificial intelligence will profit from the existence of novel, non-traditional substrates for brain-inspired computing. Neuromorphic computers aim to provide such a substrate that reproduces the brain's capabilities in terms of adaptive, low-power information processing. We present results from a prototype chip of the BrainScaleS-2 m

Alan M. Lewis, Timothy C. Berkelbach

Linear and non-linear spectroscopies are powerful tools used to investigate the energetics and dynamics of electronic excited states of both molecules and crystals. While highly accurate \emph{ab initio} calculations of molecular spectra can be performed relatively routinely, extending these calculations to periodic systems is challenging. Here, we present c

Uche Onyekpe, Stratis Kanarachos, Michael E. Fitzpatrick

Over the past decade, several researchers have presented various optimisation algorithms for use in truss design. The no free lunch theorem implies that no optimisation algorithm fits all problems; therefore, the interest is not only in the accuracy and convergence rate of the algorithm but also the tuning effort and population size required for achieving th

Weiyu Liu, Angel Daruna, Sonia Chernova

Semantic grasping is the problem of selecting stable grasps that are functionally suitable for specific object manipulation tasks. In order for robots to effectively perform object manipulation, a broad sense of contexts, including object and task constraints, needs to be accounted for. We introduce the Context-Aware Grasping Engine, which combines a novel s

Yuezhou Zhang, Zhicheng Yang, Ke Lan, Xiaoli Liu

Understanding the sleep quality and architecture is essential to human being's health, which is usually represented using multiple sleep stages. A standard sleep stage determination requires Electroencephalography (EEG) signals during the expensive and labor-intensive Polysomnography (PSG) test. To overcome this inconvenience, cardiorespiratory signals are p

Benjamin E. Stahl, WeiKang Zheng, Thomas de Jaeger, Alexei V. Filippenko

We present BVRI and unfiltered light curves of 93 Type Ia supernovae (SNe Ia) from the Lick Observatory Supernova Search (LOSS) follow-up program conducted between 2005 and 2018. Our sample consists of 78 spectroscopically normal SNe Ia, with the remainder divided between distinct subclasses (three SN 1991bg-like, three SN 1991T-like, four SNe Iax, two pecul

T. de Jaeger, W. Zheng, B. E. Stahl, A. V. Filippenko

In this work, BV RI light curves of 55 Type II supernovae (SNe II) from the Lick Observatory Supernova Search program obtained with the Katzman Automatic Imaging Telescope and the 1 m Nickel telescope from 2006 to 2018 are presented. Additionally, more than 150 spectra gathered with the 3 m Shane telescope are published. We conduct an analyse of the peak abs

Reyhane Alidousti, Mostafa Shakhsi-Niaee

Peptide nucleic acids (PNAs) are artificial nucleic acids with a peptide backbone instead of sugar phosphate backbone of DNA or RNA. Their resistance to degradation, selectivity and greater binding affinity in comparison to usual nucleic acids led to consideration of their great potential for different applications. For example, they can be used in molecular

Moncef Ghazel, Sadok Kallel

We verify that for a finite simplicial complex $X$ and for piecewise linear loops on $X$, the "thin" loop space is a topological group of the same homotopy type as the space of continuous loops. This turns out not to be the case for the higher loops.

Filipe Matusalem, Lars Matthes, Jürgen Furthmüller, Marcelo Marques

The third-rank tensor of the static spin Hall conductivity is investigated for two-dimensional (2D) topological insulators by electronic structure calculations. Its seeming quantization is numerically demonstrated for highly symmetric systems independent of the gap size. 2D crystals with hexagonal and square Bravais lattice show similar effects, while true r

F. M. Hahne, P. Klimas, J. S. Streibel

The signum-Gordon model in 1+1 dimensions possesses the exact shockwave solution with discontinuity of the field at the light cone and infinite gradient energy. The energy of a regular part of the wave inside the light cone is finite and it grows linearly with time. The initial data for such waves contain a field configuration which is null in the space and

A. A. Poblaguev, A. Zelenski, E. Aschenauer, G. Atoian

The Polarized Atomic Hydrogen Gas Jet Target polarimeter is employed by the Relativistic Heavy Ion Collider (RHIC) to measure the absolute polarization of each colliding proton beam. Polarimeter detectors and data acquisition were upgraded in 2015 to increase solid angle, energy range and energy resolution. These upgrades and advanced systematic error analys

Georgy V. Pushkarev, Vladimir G. Mazurenko, Vladimir V. Mazurenko, Danil W. Boukhvalov

First principles calculations of magnetic and electronic properties of VSe2 describing the transition between two structural phases(H,T) were performed. Results of the calculations evidence rather low energy barrier ( 0.60 eV for monolayer) for transition betweenthe phases. The energy required for the deviation of Se atom or whole layer of selenium atoms on

Mourad Choulli

We summarize in these notes the course given at the Summer School of AIP 2019 held in Grenoble from July 1st to July 5th. This course was mainly devoted to the determination of the unbounded potential in a Schr\"odinger equation from the associated Dirichlet-to-Neumann map (abbreviated to DN map in this text). We establish a stability inequality for potentia

Wanchun Shen

We introduce a probability distribution on $\mathcal{P}([0,1]^d)$, the space of all Borel probability measures on $[0,1]^d$. Under this distribution, almost all measures are shown to have infinite upper quasi-Assouad dimension and zero lower quasi-Assouad dimension (hence the upper and lower Assouad dimensions are almost surely infinite or zero). We also ind

Manas K Patra

Metrics and pseudometrics are defined on the group of unitary operators in a Hilbert space. Several explicit formulas are derived. A special feature of the work is investigation of pseudometrics in unitary groups. The rich classes of pseudometrics have many interesting applications. Three such applications, distinguishibility of unitary operators, quantum co

Faisal Etminan, Mohammad Mehdi Firoozabadi

We derive a simple Woods-Saxon type form for the potentials between $Y=\Xi, \Omega$ and $\alpha$ by using a single-folding potential method, based on a separable $Y$-nucleon potential. Accordingly, the potentials $\Xi+\alpha$ and $\Omega+\alpha$ are obtained using the ESC08c Nijmegens $\Xi N$ potential (in $^{3}S_{1}$ channel) and HAL QCD Collaboration $\Ome

Tseleung So, Stephen Theriault

Let $M$ be a smooth, orientable, closed, connected $4$-manifold and suppose that $H_1(M;\mathbb{Z})$ is finitely generated and has no $2$-torsion. We give a homotopy decomposition of the suspension of $M$ in terms of spheres, Moore spaces and $\Sigma\mathbb{C}P^{2}$. This is used to calculate any reduced generalized cohomology theory of $M$ as a group and to

Pooya Abolghasemi, Ladislau Bölöni

Recent research demonstrated that it is feasible to end-to-end train multi-task deep visuomotor policies for robotic manipulation using variations of learning from demonstration (LfD) and reinforcement learning (RL). In this paper, we extend the capabilities of end-to-end LfD architectures to object manipulation in clutter. We start by introducing a data aug

Kevin Chen, Michael Gutperle

In this note we construct a solution of six-dimensional $F(4)$ gauged supergravity using $AdS_2\times S^3$ warped over an interval as an ansatz. The solution is completely regular, preserves eight of the sixteen supersymmetries of the $AdS_6$ vacuum and is a holographic realization of a line defect in a dual five-dimensional theory. We calculate the expectat