October 2020 arXiv papers — page 65

Biswesh Mohapatra, Gaurav Pandey, Danish Contractor, Sachindra Joshi

Popular dialog datasets such as MultiWOZ are created by providing crowd workers an instruction, expressed in natural language, that describes the task to be accomplished. Crowd workers play the role of a user and an agent to generate dialogs to accomplish tasks involving booking restaurant tables, calling a taxi etc. In this paper, we present a data creation

Ben Bar-Or, Jean-Baptiste Fouvry, Scott Tremaine

Fuzzy dark matter (FDM) is composed of ultra-light bosons having a de Broglie wavelength that is comparable to the size of the stellar component of galaxies at typical galactic velocities. FDM behaves like cold dark matter on large scales. However, on the scale of the de Broglie wavelength, an FDM halo exhibits density fluctuations that lead to relaxation, a

Ronan Laker, Timothy S. Horbury, Stuart D. Bale, Lorenzo Matteini

One of the main discoveries from the first two orbits of Parker Solar Probe (PSP) was the presence of magnetic switchbacks, whose deflections dominated the magnetic field measurements. Determining their shape and size could provide evidence of their origin, which is still unclear. Previous work with a single solar wind stream has indicated that these are lon

Sebastian Durst, Stefan Brüggenwirth

An intelligent radar resource management is an essential milestone in the development of a cognitive radar system. The quality of service based resource allocation model (Q-RAM) is a framework allowing for intelligent decision making but classical solutions seem insufficient for real-time application in a modern radar system. In this paper, we present a solu

Wei Zhang, Ning Liu, Yunfeng Zhang

Deep reinforcement learning (DRL) demonstrates great potential in mapless navigation domain. However, such a navigation model is normally restricted to a fixed configuration of the range sensor because its input format is fixed. In this paper, we propose a DRL model that can address range data obtained from different range sensors with different installation

Sadasiba Tripathy, Sandhyarani Das

In this investigation we analyze impact of diversification of agriculture on farmer's income, a study from primitive tribal groups from eastern ghats of India. We have taken crop diversification index to measure the extent and regression formalism to analyze the impact, of crop diversification. Descriptive statistics is employed to know the average income of

Paweł Holewa, Marek Burakowski, Anna Musiał, Nicole Srocka

Single-photon sources are key building blocks in most of the emerging secure telecommunication and quantum information processing schemes. Semiconductor quantum dots (QD) have been proven to be the most prospective candidates. However, their practical use in fiber-based quantum communication depends heavily on the possibility of operation in the telecom band

Igor Zagorodnov, Sergey Tomin, Ye Chen, Frank Brinker

We consider the collective beam dynamics at the injector section of the European XFEL. The results of the measurements for the longitudinal phase space (LPS) of the electron beam are compared with those obtained from numerical modeling. A new approach is proposed for the analysis of the self-field effects in the LPS measurements. It allows to determine accur

Daria Soboleva, Ondrej Skopek, Márius Šajgalík, Victor Cărbune

We present a novel multi-modal unspoken punctuation prediction system for the English language which combines acoustic and text features. We demonstrate for the first time, that by relying exclusively on synthetic data generated using a prosody-aware text-to-speech system, we can outperform a model trained with expensive human audio recordings on the unspoke

Yahao Shi, Xinyu Cao, Bin Zhou

Part mobility analysis is a significant aspect required to achieve a functional understanding of 3D objects. It would be natural to obtain part mobility from the continuous part motion of 3D objects. In this study, we introduce a self-supervised method for segmenting motion parts and predicting their motion attributes from a point cloud sequence representing

Javier Fernández, Luke Bornn

We present a fully convolutional neural network architecture that is capable of estimating full probability surfaces of potential passes in soccer, derived from high-frequency spatiotemporal data. The network receives layers of low-level inputs and learns a feature hierarchy that produces predictions at different sampling levels, capturing both coarse and fi

Vaisakh Shaj, Philipp Becker, Dieter Buchler, Harit Pandya

Estimating accurate forward and inverse dynamics models is a crucial component of model-based control for sophisticated robots such as robots driven by hydraulics, artificial muscles, or robots dealing with different contact situations. Analytic models to such processes are often unavailable or inaccurate due to complex hysteresis effects, unmodelled frictio

Giovanni Italiano, Bruno Martelli, Matteo Migliorini

We construct some cusped finite-volume hyperbolic $n$-manifolds $M_n$ that fiber algebraically in all the dimensions $5\leq n \leq 8$. That is, there is a surjective homomorphism $\pi_1(M_n) \to \mathbb Z$ with finitely generated kernel. The kernel is also finitely presented in the dimensions $n=7, 8$, and this leads to the first examples of hyperbolic $n$-m

Felix Bartel, Daniel Potts, Michael Schmischke

In this paper we propose a tool for high-dimensional approximation based on trigonometric polynomials where we allow only low-dimensional interactions of variables. In a general high-dimensional setting, it is already possible to deal with special sampling sets such as sparse grids or rank-1 lattices. This requires black-box access to the function, i.e., the

B. Sánchez-Rey, A. Prados

We analyse the linear response properties of the uniformly heated granular gas. The intensity of the stochastic driving fixes the value of the granular temperature in the non-equilibrium steady state reached by the system. Here, we investigate two specific situations. First, we look into the ``direct'' relaxation of the system after a single (small) jump of

Solt Kovács, Housen Li, Lorenz Haubner, Axel Munk

Change point estimation is often formulated as a search for the maximum of a gain function describing improved fits when segmenting the data. Searching through all candidates requires $O(n)$ evaluations of the gain function for an interval with $n$ observations. If each evaluation is computationally demanding (e.g. in high-dimensional models), this can becom

Priya Subramanian, Daniel J. Ratliff, Alastair M. Rucklidge, Andrew J. Archer

The density distribution in solids is often represented as a sum of Gaussian peaks (or similar functions) centred on lattice sites or via a Fourier sum. Here, we argue that representing instead the $\mathit{logarithm}$ of the density distribution via a Fourier sum is better. We show that truncating such a representation after only a few terms can be highly a

Victor Selivanov, Svetlana Selivanova

We establish primitive recursive versions of some known facts about computable ordered fields of reals and computable reals, and then apply them to proving primitive recursiveness of some natural problems in linear algebra and analysis. In particular, we find a partial primitive recursive analogue of Ershov-Madison's theorem about real closures of computable

Sergey Gavrilov, Dmitry Gitman, Vadim Dmitriev, Anatolii Panferov

A number of physical processes occurring in a flat one-dimensional graphene structure under the action of strong time-dependent electric fields are considered. It is assumed that the Dirac model can be applied to the graphene as a subsystem of the general system under consideration, which includes an interaction with quantized electromagnetic field. The Dira

Voot Tangkaratt, Nontawat Charoenphakdee, Masashi Sugiyama

Robust learning from noisy demonstrations is a practical but highly challenging problem in imitation learning. In this paper, we first theoretically show that robust imitation learning can be achieved by optimizing a classification risk with a symmetric loss. Based on this theoretical finding, we then propose a new imitation learning method that optimizes th

Yacin Ameur, José Luis Romero

We consider planar Coulomb systems consisting of a large number $n$ of repelling point charges in the low temperature regime, where the inverse temperature $\beta$ grows at least logarithmically in $n$ as $n \longrightarrow \infty$, i.e., $\beta\gtrsim \log n$. Under suitable conditions on an external potential we prove results to the effect that the gas is

Matthew Ashman, Jonathan So, Will Tebbutt, Vincent Fortuin

Large, multi-dimensional spatio-temporal datasets are omnipresent in modern science and engineering. An effective framework for handling such data are Gaussian process deep generative models (GP-DGMs), which employ GP priors over the latent variables of DGMs. Existing approaches for performing inference in GP-DGMs do not support sparse GP approximations base

Matteo Verzobio

Let $P$ and $Q$ be two points on an elliptic curve defined over a number field $K$. For $\alpha\in \text{End}(E)$, define $B_\alpha$ to be the $\mathcal{O}_K$-integral ideal generated by the denominator of $x(\alpha(P)+Q)$. Let $\mathcal{O}$ be a subring of $\text{End}(E)$, that is a Dedekind domain. We will study the sequence $\{B_\alpha\}_{\alpha\in \mathc

T. Bando, S. Inoue, K. Shinohara, A. Isayama

In JT-60U, simultaneous excitation of n = 1 helical cores (HCs) and m/n = 2/1 Tearing Modes (TMs) was observed [T. Bando et al., Plasma Phys. Control. Fusion 61 115014 (2019)]. In this paper, we have investigated the excitation mechanism of n = 1 HCs with m/n = 2/1 TMs based on the experimental observations and a simple quasi-linear MHD model. In the previou

Nicole Novielli, Fabio Calefato, Filippo Lanubile, Alexander Serebrenik

Sentiment analysis methods have become popular for investigating human communication, including discussions related to software projects. Since general-purpose sentiment analysis tools do not fit well with the information exchanged by software developers, new tools, specific for software engineering (SE), have been developed. We investigate to what extent SE

Oktay K. Pashaev

Starting from divisibility problem for Fibonacci numbers we introduce Fibonacci divisors, related hierarchy of Golden derivatives in powers of the Golden Ratio and develop corresponding quantum calculus. By this calculus, the infinite hierarchy of Golden quantum oscillators with integer spectrum determined by Fibonacci divisors, the hierarchy of Golden coher

Tobias Diez, Gerd Rudolph

Local normal form theorems for smooth equivariant maps between infinite-dimensional manifolds are established. These normal form results are new even in finite dimensions. The proof is inspired by the Lyapunov-Schmidt reduction for dynamical systems and by the Kuranishi method for moduli spaces. It uses a Slice Theorem for Fr\'echet manifolds as the main tec

Stephen Bauters, Andreas C. Scheinost, Katja Schmeide, Stephan Weiss

A general strategy for the determination of Tc oxidation state by new approach involving X-ray absorption near edge spectroscopy (XANES) at the Tc L3 edge is shown. A comprehensive series of 99Tc compounds, ranging from oxidation states I to VII, was measured and subsequently simulated within the framework of crystal-field multiplet theory. The observable tr

Yuan Miao

We present an exact solution to the asymptotic Bethe equation of weakly anisotropic Heisenberg spin chain, which is a set of non-linear algebraic equations. The solution describes the low-energy excitations above ferromagnetic ground state with fixed magnetisation, and it has a close relation to generalised Jacobi polynomial. It is equivalent to a generalise

Xin Wang, Bingrong Yu, Shun Zhou

In this paper, we investigate the double covering of modular $\Gamma^{}_5 \simeq A^{}_5$ group and derive all the modular forms of weight one for the first time. The modular forms of higher weights are also explicitly given by decomposing the direct products of weight-one forms. For the double covering group $\Gamma^\prime_5 \simeq A^\prime_5$, there exist t

Tony Lelièvre, Mouad Ramil, Julien Reygner

We consider classical solutions to the kinetic Fokker-Planck equation on a bounded domain $\mathcal O \subset~\mathbb{R}^d$ in position, and we obtain a probabilistic representation of the solutions using the Langevin diffusion process with absorbing boundary conditions on the boundary of the phase-space cylindrical domain $D = \mathcal O \times \mathbb{R}^d

Maciej Bendkowski

We investigate the asymptotic densities of theorems provable in Zermelo-Fraenkel set theory ZF and its extension ZFC including the axiom of choice. Assuming a canonical De Bruijn representation of formulae, we construct asymptotically large sets of sentences unprovable within ZF, yet provable in ZFC. Furthermore, we link the asymptotic density of ZFC theorem

Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet

Bayesian optimization (BO) is a prominent approach to optimizing expensive-to-evaluate black-box functions. The massive computational capability of edge devices such as mobile phones, coupled with privacy concerns, has led to a surging interest in federated learning (FL) which focuses on collaborative training of deep neural networks (DNNs) via first-order o

Prahlad Sharma

Let $f$ be a $SL(2,\mathbb{Z})$ holomorphic cusp form or the Eisenstien series $E(z,1/2)$ and $\pi$ be a $SL(3,\mathbb{Z})$ Hecke-Maass cusp form with its Langlands parameter $\mu$ in generic position i.e. away from Weyl chamber walls and away from self dual forms. We study an amplified second moment $\sum_{j} A(\pi_j)|L(1/2,\pi_j\times f)|^2$ and deduce the

Xinjian Luo, Yuncheng Wu, Xiaokui Xiao, Beng Chin Ooi

Federated learning (FL) is an emerging paradigm for facilitating multiple organizations' data collaboration without revealing their private data to each other. Recently, vertical FL, where the participating organizations hold the same set of samples but with disjoint features and only one organization owns the labels, has received increased attention. This p

Eleonora Giunchiglia, Thomas Lukasiewicz

Hierarchical multi-label classification (HMC) is a challenging classification task extending standard multi-label classification problems by imposing a hierarchy constraint on the classes. In this paper, we propose C-HMCNN(h), a novel approach for HMC problems, which, given a network h for the underlying multi-label classification problem, exploits the hiera

Yifan Xie, Xiang Yin, Shaoyuan Li

In this paper, we investigate the enforcement of opacity via supervisory control in the context of discrete-event systems. A system is said to be opaque if the intruder, which is modeled as a passive observer, can never infer confidently that the system is at a secret state. The design objective is to synthesize a supervisor such that the closed-loop system

R. Geertsema, K. Akiba, M. van Beuzekom, E. Buchanan

An extensive sensor testing campaign is presented, dedicated to measuring the charge collection properties of prototype candidates for the Vertex Locator (VELO) detector for the upgraded LHCb experiment. The charge collection is measured with sensors exposed to fluences of up to $8 \times 10^{15}~1~\mathrm{\,Me\kern -0.1em V}~ \mathrm{ \,n_{eq}}~{\mathrm{ \,

Quan Shuai, Tim de Jongh, Matthieu Besemer, Ad van der Avoird

The experimental characterization of scattering resonances in low energy collisions has proven to be a stringent test for quantum chemistry calculations. Previous measurements on the NO-H$_2$ system at energies down to $10$ cm$^{-1}$ challenged the most sophisticated calculations of potential energy surfaces available. In this report, we continue these inves

Alan F. Smeaton, Naveen Garaga Krishnamurthy, Amruth Hebbasuru Suryanarayana

In this paper we present the case for including keystroke dynamics in lifelogging. We describe how we have used a simple keystroke logging application called Loggerman, to create a dataset of longitudinal keystroke timing data spanning a period of more than 6 months for 4 participants. We perform a detailed analysis of this data by examining the timing infor

F. Cordoni, M. Missiaggia, A. Attili, S. M. Welford

The present work introduces a rigorous stochastic model, named Generalized Stochastic Microdosimetric Model (GSM2), to describe biological damage induced by ionizing radiation. Starting from microdosimetric spectra of energy deposition in tissue, we derive a master equation describing the time evolution of the probability density function of lethal and poten

Benjamin Berczi, Paul M. Saffin, Shuang-Yong Zhou

Gravitational collapse into a black hole has been extensively studied with classical sources. We develop a new formalism to simulate quantum fields forming a black hole. This formalism utilizes well-established techniques used for classical collapse by choosing a convenient coherent state, and simulates the matter fields quantum mechanically. Divergences are

Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan

Recently pre-trained language representation models such as BERT have shown great success when fine-tuned on downstream tasks including information retrieval (IR). However, pre-training objectives tailored for ad-hoc retrieval have not been well explored. In this paper, we propose Pre-training with Representative wOrds Prediction (PROP) for ad-hoc retrieval.

Pramod Kumar Mishra

. We consider three dimensional model of the Gaussian polymer chain in the presence of defects to understand the formation of a polymer aggregate where the aggregate is induced by the defects. The defects are acting as an attractive centres of the monomers and it induces aggregation of the monomers of the chain around the defects. It has been shown using the

Hartmut Koenitz, Mirjam Palosaari Eladhari, Sandy Louchart, Frank Nack

COST Action 18230 INDCOR (Interactive Narrative Design for Complexity Representations) is an interdisciplinary network of researchers and practitioners intended to further the use of interactive digital narratives (IDN1) to represent highly complex topics. IDN possess crucial advantages in this regard, but more knowledge is needed to realize these advantages

Thiago Bergamaschi, Monika Henzinger, Maximilian Probst Gutenberg, Virginia Vassilevska Williams

Maintaining and updating shortest paths information in a graph is a fundamental problem with many applications. As computations on dense graphs can be prohibitively expensive, and it is preferable to perform the computations on a sparse skeleton of the given graph that roughly preserves the shortest paths information. Spanners and emulators serve this purpos

Thibault Congy, Gennady El, Giacomo Roberti

The theory of soliton gas had been previously developed for unidirectional integrable dispersive hydrodynamics in which the soliton gas properties are determined by the overtaking elastic pairwise interactions between solitons. In this paper, we extend this theory to soliton gases in bidirectional integrable Eulerian systems where both head-on and overtaking

Sami Abdullah Abed, Irina Nikolaeva, Andrei Novikov

In this article we consider generalisation of Michelson contrast for positive operators of countably decomposable $W^*$-algebras and find a few several of its properties.

Niclas Kruff, Christoph Lüders, Ovidiu Radulescu, Thomas Sturm

We present a symbolic algorithmic approach that allows to compute invariant manifolds and corresponding reduced systems for differential equations modeling biological networks which comprise chemical reaction networks for cellular biochemistry, and compartmental models for pharmacology, epidemiology and ecology. Multiple time scales of a given network are ob

S. Molatta, D. Opherden, J. Wosnitza, Z. T. Zhang

A number of recent experiments indicate that the iron-chalcogenide FeSe provides the long-sought possibility to study bulk superconductivity in the cross-over regime between the weakly coupled Bardeen--Cooper--Schrieffer (BCS) pairing and the strongly coupled Bose--Einstein condensation (BEC). We report on $^{77}$Se nuclear magnetic resonance experiments of

Michele Caraglio, Boris Marcone, Fulvio Baldovin, Enzo Orlandini

We develop a theoretical description of the topological disentanglement occurring when torus knots reach the ends of a semi-flexible polymer under tension. These include decays into simpler knots and total unknotting. The minimal number of crossings and the minimal knot contour length are the topological invariants playing a key role in the model. The crossi

Othman Benchekroun, Adel Rahimi, Qini Zhang, Tetiana Kodliuk

Explainable AI (XAI) is paramount in industry-grade AI; however existing methods fail to address this necessity, in part due to a lack of standardisation of explainability methods. The purpose of this paper is to offer a perspective on the current state of the area of explainability, and to provide novel definitions for Explainability and Interpretability to

Dominik Stallmann, Jan P. Göpfert, Julian Schmitz, Alexander Grünberger

Motivation: Innovative microfluidic systems carry the promise to greatly facilitate spatio-temporal analysis of single cells under well-defined environmental conditions, allowing novel insights into population heterogeneity and opening new opportunities for fundamental and applied biotechnology. Microfluidics experiments, however, are accompanied by vast amo

Philipp Arras, Martin Reinecke, Rüdiger Westermann, Torsten A. Enßlin

Radio interferometers do not measure the sky brightness distribution directly but rather a modified Fourier transform of it. Imaging algorithms, thus, need a computational representation of the linear measurement operator and its adjoint, irrespective of the specific chosen imaging algorithm. In this paper, we present a C++ implementation of the radio interf

M. Ahmadvand

We propose a low scale leptogenesis scenario in the framework of composite Higgs models supplemented with singlet heavy neutrinos. One of the neutrinos can also be considered as a dark matter candidate whose stability is guaranteed by a discrete $\mathbb{Z}_2 $ symmetry of the model. In the spectrum of the strongly coupled system, bound states heavier than t

Sang Yong Song, Yoon Sung Park, Yongchan Jeong, Min-Seok Kim

Magnetic atoms can break the Cooper pairs of superconductors, leading to the formation of Yu-Shiba-Rusinov (YSR) bound states inside superconducting gaps. Theory predicts that the YSR bound states can be controlled by tuning the electron density at the Fermi energy, but it has not been studied deeply. In this work, we studied the nature of YSR bound states i

Weiyuan Tang, Kun Ding, Guancong Ma

Non-Hermitian systems can produce branch singularities known as exceptional points (EPs). Different from singularities in Hermitian systems, the topological properties of an EP can involve either the winding of eigenvalues that produces a discriminant number (DN) or the eigenvector holonomy that generates a Berry phase. The multiplicity of topological invari

Peter Gangl, Stefan Köthe, Christiane Mellak, Alessio Cesarano

This paper deals with the design optimization of a synchronous reluctance machine to be used in an X-ray tube, where the goal is to maximize the torque, by means of gradient-based free-form shape optimization. The presented approach is based on the mathematical concept of shape derivatives and allows to obtain new motor designs without the need to introduce

Yasunari Nishikawa

We study a two-loop finiteness of an effective potential for a Higgs boson that is the fifth component of a gauge field in an $U(1)$ gauge theory coupled to quantum gravity on the five-dimensional space-time $M^4\times S^1$. There are two types of diagrams including quantum gravitational corrections. We find that only one type of diagram contributes to the e

Ivan Smith, Michael Wemyss

We discuss the symplectic topology of the Stein manifolds obtained by plumbing two 3-dimensional spheres along a circle. These spaces are related, at a derived level and working in a characteristic determined by the specific geometry, to local threefolds which contain two floppable $(-1,-1)$-curves meeting at a point. Using contraction algebras we classify s

Andrea Bracco, David Bresnahan, Pedro Palmeirim, Doris Arzoumanian

We present the identification of the previously unnoticed physical association between the Corona Australis molecular cloud (CrA), traced by interstellar dust emission, and two shell-like structures observed with line emission of atomic hydrogen (HI) at 21 cm. Although the existence of the two shells had already been reported in the literature, the physical

Pramod Kumar Mishra

We model a macromolecule as an infinitely long Gaussian semi-flexible polymer chain and the conformations of the chain were realized in the nano cube using a cubic lattice. A modified version of the recursion relations is used to calculate the grand canonical partition function of the chain to investigate distinct thermo-dynamical properties of the nano poly

Jin Hu, Zhongliang Sun, Xuekai Xu, Mengqi Guo

Probabilistic shaping (PS) is investigated as a potential technique to approach the Shannon limit. However, it has been proved that conventional carrier phase recovery (CPR) algorithm designed for uniform distribution may have extra penalty in PS systems. In this paper, we find that the performance of QPSK partition algorithm is degenerated when PS is implem

Pramod Kumar Mishra

A lattice model of the directed self-avoiding walk is used to estimate the possibility on the formation of an infinitely long linear semi-flexible copolymer chain. The copolymer chain is assumed to composed of four different types of the monomers. A method of the recursion relations is used to solve the proposed model analytically to show that the probabilit

Sungho Suh, Jihun Kim, Paul Lukowicz, Yong Oh Lee

Document image enhancement and binarization methods are often used to improve the accuracy and efficiency of document image analysis tasks such as text recognition. Traditional non-machine-learning methods are constructed on low-level features in an unsupervised manner but have difficulty with binarization on documents with severely degraded backgrounds. Con

Jürgen Jost, Raffaella Mulas

Chemical hypergraphs and their associated normalized Laplace operators are generalized and studied in the case where each vertex--hyperedge incidence has a real coefficient. We systematically study the effect of symmetries of a hypergraph on the spectrum of the Laplacian.

Michael Backenköhler, Luca Bortolussi, Gerrit Großmann, Verena Wolf

Many probabilistic inference problems such as stochastic filtering or the computation of rare event probabilities require model analysis under initial and terminal constraints. We propose a solution to this bridging problem for the widely used class of population-structured Markov jump processes. The method is based on a state-space lumping scheme that aggre

Jean Kieffer

We design efficient algorithms to evaluate modular equations of Siegel and Hilbert type for abelian surfaces over number fields or finite fields using complex approximations. Their output is provably correct when the associated graded ring of modular forms over Z is explicitly known; this includes the Siegel case, and the Hilbert case for the quadratic field

Michel Dubois-Violette, Blas Torrecillas

This paper is devoted to the study of the quadratic algebras with relations generated by superpotentials which are exterior 3-forms. Such an algebra is regular if and only if it is Koszul and is then a 3-Calabi-Yau domain. After some general results we investigate the case of the algebras generated in low dimensions $n$ with $n\leq 7$. We show that whenever

Guangda Ji, Zhanxing Zhu

Knowledge distillation is a strategy of training a student network with guide of the soft output from a teacher network. It has been a successful method of model compression and knowledge transfer. However, currently knowledge distillation lacks a convincing theoretical understanding. On the other hand, recent finding on neural tangent kernel enables us to a

Shing Yan Li, Yu-Cheng Qiu, S. -H. Henry Tye

Guided by the naturalness criterion for an exponentially small cosmological constant, we present a string theory motivated 4-dimensional $\mathcal{N}=1$ non-linear supergravity model (or its linear version with a nilpotent superfield) with spontaneous supersymmetry breaking. The model encompasses the minimal supersymmetric standard model, the racetrack K\"ah

Emre Akoz, Amin Mivehchi, Keith W. Moored

Inviscid computations are presented of a self-propelled virtual body connected to a combined heaving and pitching foil that uses continuous and intermittent motions. It is determined that intermittent swimming can improve efficiency when the dimensionless heave ratio is $h^* < 0.7$ while it degrades efficiency for $h^* \geq 0.7$. This is a consequence of the

Ta-Yuan Liu, I-Hsiang Wang

In this work, fundamental limits and optimal mechanisms of privacy-preserving data release that aims to minimize the privacy leakage under utility constraints of a set of multiple tasks are investigated. While the private feature to be protected is typically determined and known by the sanitizer, the target task is usually unknown. To address the lack of inf

Yanzhi Chen, Dinghuai Zhang, Michael Gutmann, Aaron Courville

We consider the fundamental problem of how to automatically construct summary statistics for implicit generative models where the evaluation of the likelihood function is intractable, but sampling data from the model is possible. The idea is to frame the task of constructing sufficient statistics as learning mutual information maximizing representations of t

Naoki Kitazawa

Special generic maps are higher dimensional versions of Morse functions with exactly two singular points, characterizing spheres topologically except 4-dimensional cases and 4-dimensional standard spheres. The class of such maps also contains canonical projections of unit spheres. This class is interesting from the viewpoint of algebraic topology and differe

Aman Madaan, Yiming Yang

This paper presents the first study on using large-scale pre-trained language models for automated generation of an event-level temporal graph for a document. Despite the huge success of neural pre-training methods in NLP tasks, its potential for temporal reasoning over event graphs has not been sufficiently explored. Part of the reason is the difficulty in

Walid Al Misba, Tahmid Kaisar, Dhritiman Bhattacharya, Jayasimha Atulasimha

We propose energy efficient strain control of domain wall (DW) in a perpendicularly magnetized nanoscale racetrack on a piezoelectric substrate that can implement multi state synapse to be utilized in neuromorphic computing platforms. In conjunction with SOT from to a current flowing in the heavy metal layer, strain is generated by applying a voltage across

Tae-Min Choi, Ji-Su Kang, Jong-Hwan Kim

Time-series data with missing values are commonly encountered in many fields, such as healthcare, meteorology, and robotics. The imputation aims to fill the missing values with valid values. Most imputation methods trained the models implicitly because missing values have no ground truth. In this paper, we propose Random Drop Imputation with Self-training (R

João Luís Rosa, Douglas A. Ferreira, Dionisio Bazeia, Francisco S. N. Lobo

In this work, we study 5-dimensional braneworld scenarios in the scalar-tensor representation of the generalized hybrid metric-Palatini gravitational theory. We start by considering a model for a brane supported purely by the gravitational scalar fields of the theory and then consider other distinct cases where the models are also supported by an additional

Vikram Ravindranath, M. S. Santhanam

If a localized quantum state in a tight-binding model with structural aperiodicity is subject to noisy evolution, then it is generally expected to result in diffusion and delocalization. In this work, it is shown that the localized phase of the kicked Aubry-Andr\'e-Harper (AAH) model is robust to the effects of noisy evolution, for long times, provided that

S. Sivaprasad Kumar, Kush Arora

This paper deals with some radius results and inclusion relations that are established for functions in a newly defined subclass of starlike functions associated with a petal shaped domain.

Elena Di Lavore, Alessandro Gianola, Mario Román, Nicoletta Sabadini

We show that Span(Graph)*, an algebra for open transition systems introduced by Katis, Sabadini and Walters, satisfies a universal property. By itself, this is a justification of the canonicity of this model of concurrency. However, the universal property is itself of interest, being a formal demonstration of the relationship between feedback and state. Inde

Luigi Filippo Chiara, Marco Edoardo Rosti, Francesco Picano, Luca Brandt

We analyze a suspension of deformable particles in a pressure-driven flow. The suspension is composed of neutrally buoyant initially spherical particles and a Newtonian carrier fluid, and the flow is solved by means of direct numerical simulations, using a fully Eulerian method based on a one-continuum formulation. The solid phase is modeled with an incompre

Rui Wang, Baigeng Wang, Tigran A. Sedrakyan

Two-dimensional quantum antiferromagnets host rich physics, including long-range ordering, high-$T_c$ superconductivity, quantum spin liquid behavior, topological ordering, a variety of other exotic phases, and quantum criticalities. Frustrating perturbations in antiferromagnets may give rise to strong quantum fluctuations, challenging the theoretical unders

R. Alonso, Y. Morimoto, W. Sun, T. Yang

This paper gives the first affirmative answer to the question of the global existence of Boltzmann equations without angular cutoff in the $L^\infty$-setting. In particular, we show that when the initial data is close to equilibrium and the perturbation is small in $L^2 \cap L^\infty$ with a polynomial decay tail, the Boltzmann equation has a global solution

Alessandro Pesci

In this paper, we consider a specific model, implementing the existence of a fundamental limit distance $L_0$ between (space or time separated) points in spacetime, which in the recent past has exhibited the intriguing feature of having a minimum-length Ricci scalar $R_{(q)}$ that does not approach the ordinary Ricci scalar $R$ in the limit of vanishing $L_0

Zhen Zhang, Liang Zheng, Gang Chen, Hong-Ge Xu

A dynamically constrained phase-space coalescence model plus PACIAE model was used to predict the exotic resonant state $Z_c^{\pm}(3900)$ yield, transverse momentum distribution, and the rapidity distribution with $|y| < 6$ and $p_T < 10$ GeV/c in $pp$ collisions at $\sqrt{s} = 1.96, 7$ and 13 TeV, respectively. The yield of the $Z_c^{\pm}(3900)$ is estimate

Eric S. Endres, Steve Ndengue, Olga Lakhmanskaya, Seunghyun Lee

We have studied the fundamental rotational relaxation and excitation collision of OH- J=0 <-> 1 with helium at different collision energies. Using state-selected photodetachment in a cryogenic ion trap, the collisional excitation of the first excited rotational state of OH- has been investigated and absolute inelastic collision rate coefficients have been ex

Beáta Bényi, Matthieu Josuat-Vergès

In this note we present a combinatorial proof of an identity involving poly-Bernoulli numbers and Genocchi numbers. We introduce the combinatorial objects, $m-$barred Callan sequences and show that the identity holds in a more general manner.

Sebastian Buschjäger, Philipp-Jan Honysz, Lukas Pfahler, Katharina Morik

Data summarization has become a valuable tool in understanding even terabytes of data. Due to their compelling theoretical properties, submodular functions have been in the focus of summarization algorithms. These algorithms offer worst-case approximations guarantees to the expense of higher computation and memory requirements. However, many practical applic

S Anupama, Prasan Shedligeri, Abhishek Pal, Kaushik Mitra

Learning-based methods have enabled the recovery of a video sequence from a single motion-blurred image or a single coded exposure image. Recovering video from a single motion-blurred image is a very ill-posed problem and the recovered video usually has many artifacts. In addition to this, the direction of motion is lost and it results in motion ambiguity. H

Matthew T. Reeves, Kwan Goddard-Lee, Guillaume Gauthier, Oliver R. Stockdale

We experimentally study emergence of microcanonical equilibrium states in the turbulent relaxation dynamics of a two-dimensional chiral vortex gas. Same-sign vortices are injected into a quasi-two-dimensional disk-shaped atomic Bose-Einstein condensate using a range of mechanical stirring protocols. The resulting long-time vortex distributions are found to b

Renjie Zheng, Mingbo Ma, Baigong Zheng, Kaibo Liu

Simultaneous speech-to-speech translation is widely useful but extremely challenging, since it needs to generate target-language speech concurrently with the source-language speech, with only a few seconds delay. In addition, it needs to continuously translate a stream of sentences, but all recent solutions merely focus on the single-sentence scenario. As a

Fuwei Li, Lifeng Lai, Shuguang Cui

In this paper, we investigate the adversarial robustness of feature selection based on the $\ell_1$ regularized linear regression model, namely LASSO. In the considered model, there is a malicious adversary who can observe the whole dataset, and then will carefully modify the response values or the feature matrix in order to manipulate the selected features.

Simppa Äkäslompolo, Jan Paul Koschinsky, Joona Kontula, Christoph Bidermann

In this work, a Serpent 2 neutronics model of the Wendelstein 7-X (W7-X) stellarator is prepared, and an response function for the Scintillating-Fibre neutron detector (SciFi) is calculated using the model. The neutronics model includes the simplified geometry for the key components of the stellarator itself as well as the torus hall. The objective of the mo

Yasuhide Miura, Yuhao Zhang, Emily Bao Tsai, Curtis P. Langlotz

Neural image-to-text radiology report generation systems offer the potential to improve radiology reporting by reducing the repetitive process of report drafting and identifying possible medical errors. However, existing report generation systems, despite achieving high performances on natural language generation metrics such as CIDEr or BLEU, still suffer f

Chi-Liang Liu, Tsung-Yuan Hsu, Yung-Sung Chuang, Chung-Yi Li

Token embeddings in multilingual BERT (m-BERT) contain both language and semantic information. We find that the representation of a language can be obtained by simply averaging the embeddings of the tokens of the language. Given this language representation, we control the output languages of multilingual BERT by manipulating the token embeddings, thus achie

Anton Petrunin

We discuss Besicovitch inequality, width, and systole of manifolds.

Jiannan Tian, Cody Rivera, Sheng Di, Jieyang Chen

Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that data compression is becoming a critical technique to mitigate the storage burden and data movement cost. Huffman coding is arguably the most efficient Entropy coding algorithm in inf

Sameer Dharur, Purva Tendulkar, Dhruv Batra, Devi Parikh

Recent research in Visual Question Answering (VQA) has revealed state-of-the-art models to be inconsistent in their understanding of the world -- they answer seemingly difficult questions requiring reasoning correctly but get simpler associated sub-questions wrong. These sub-questions pertain to lower level visual concepts in the image that models ideally sh