March 2020 arXiv papers — page 118

Patrick Chang, Etienne Pienaar, Tim Gebbie

We implement and test kernel averaging Non-Uniform Fast Fourier Transform (NUFFT) methods to enhance the performance of correlation and covariance estimation on asynchronously sampled event-data using the Malliavin-Mancino Fourier estimator. The methods are benchmarked for Dirichlet and Fejér Fourier basis kernels. We consider test cases formed from Geometri

Hongxin Wei, Lei Feng, Xiangyu Chen, Bo An

Deep Learning with noisy labels is a practically challenging problem in weakly supervised learning. The state-of-the-art approaches "Decoupling" and "Co-teaching+" claim that the "disagreement" strategy is crucial for alleviating the problem of learning with noisy labels. In this paper, we start from a different perspective and propos

Lucia Morotti

In this paper we completely classify irreducible tensor products of covering groups of symmetric and alternating groups in characteristic $\not=2$.

Mokhtari Yacine

In this paper, we deal with the boundary controllability and boundary stabilizability of the 1D wave equation in non-cylindrical domain of the form ($α(t)<x<β(t)$). By using the characteristics method, we prove under a natural assumption on the boundary functions that the 1D wave equation is controllable and stabilizable from one side of the boundary. Furthe

Tommi Heikkilä, Hanna Help, Alexander Meaney

This is the documentation for dynamic X-ray tomography measurements of a gel phantom diffused with potassium iodide contrast agent. The measured data and additional materials are available at http://www.fips.fi/dataset.php and Zenodo (DOI:10.5281/zenodo.7876521) for open use by the scientific community, as long as the data and this documentation at arXiv are

Joseph D. O&#39;Brien, Kevin Burke, Mark E. Burke, B. Ross Barmish

For sequential betting games, Kelly&#39;s theory, aimed at maximization of the logarithmic growth of one&#39;s account value, involves optimization of the so-called betting fraction $K$. In this Letter, we extend the classical formulation to allow for temporal correlation among bets. To demonstrate the potential of this new paradigm, for simplicity of exposi

Alex Amenta, Gennady Uraltsev

We prove $L^p$-boundedness of variational Carleson operators for functions valued in intermediate UMD spaces. This provides quantitative information on the rate of convergence of partial Fourier integrals of vector-valued functions. Our proof relies on bounds on wave packet embeddings into outer Lebesgue spaces on the time-frequency-scale space $\mathbb{R}^3

Andrzej Borowiec, Aleksander Kozak

A class of scalar-tensor theories (STT) including a non-metricity that unifies metric, Palatini and hybrid metric-Palatini gravitational actions with non-minimal interaction is proposed and investigated from the point of view of their consistency with generalized conformal transformations. It is shown that every such theory can be represented on-shell by a p

Pavel Záviška, Pavel Rajmic

The paper shows the potential of sparsity-based methods in restoring quantized signals. Following up on the study of Brauer et al. (IEEE ICASSP 2016), we significantly extend the range of the evaluation scenarios: we introduce the analysis (cosparse) model, we use more effective algorithms, we experiment with another time-frequency transform. The paper shows

Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, Isabelle Augenstein

Learning what to share between tasks has been a topic of great importance recently, as strategic sharing of knowledge has been shown to improve downstream task performance. This is particularly important for multilingual applications, as most languages in the world are under-resourced. Here, we consider the setting of training models on multiple different la

Dustin Wright, Isabelle Augenstein

As the first step of automatic fact checking, claim check-worthiness detection is a critical component of fact checking systems. There are multiple lines of research which study this problem: check-worthiness ranking from political speeches and debates, rumour detection on Twitter, and citation needed detection from Wikipedia. To date, there has been no stru

Peng Chen, Gui-Jun Ding, Jun-Nan Lu, José W. F. Valle

We propose a realistic theory of fermion masses and mixings using a five-dimensional warped scenario where all fermions propagate in the bulk and the Higgs field is localized on the IR brane. The assumed $T&#39;$ flavor symmetry is broken on the branes by flavon fields, providing a consistent scenario where fermion mass hierarchies arise from adequate choice

Vitali Halenka, Christopher J. Miller, Paige Vansickle

The 3D radial escape-velocity profile of galaxy clusters has been suggested to be a promising and competitive tool for constraining mass profiles and cosmological parameters in an accelerating universe. However, the observed line-of-sight escape profile is known to be suppressed compared to the underlying 3D radial (or tangential) escape profile. Past work h

Jiyi Zhang, Ee-Chien Chang, Hwee Kuan Lee

Many machine learning adversarial attacks find adversarial samples of a victim model ${\mathcal M}$ by following the gradient of some attack objective functions, either explicitly or implicitly. To confuse and detect such attacks, we take the proactive approach that modifies those functions with the goal of misleading the attacks to some local minimals, or t

Nathaniel Garton, Jarad Niemi, Alicia Carriquiry

Sparse, knot-based Gaussian processes have enjoyed considerable success as scalable approximations to full Gaussian processes. Certain sparse models can be derived through specific variational approximations to the true posterior, and knots can be selected to minimize the Kullback-Leibler divergence between the approximate and true posterior. While this has

Stjepan Meljanac, Tea Martinic-Bilac, Sasa Kresic-Juric

We introduce the generalized Heisenberg algebra $\mathcal{H}_n$ and construct realizations of the orthogonal and Lorentz algebras by power series in a semicompletion of $\mathcal{H}_n$. The obtained realizations are given in terms of the generating functions for the Bernoulli numbers. We also introduce an extension of the orthogonal and Lorentz algebras by q

Ary R. Ferreira

The chemistry (composition and bonding information) of metallic glasses (MGs) is at least as important as structural topology for understanding their properties and production/processing peculiarities. This article reports a machine learning (ML)-based approach that brings an unprecedented &#34;big picture&#34; view of chemical bond strengths in MGs of a pro

Erik Aurell, Jan Tuziemski

We consider a macroscopic quantum system such as a qubit, interacting with a bath of fermions as in the Fröhlich polaron model. The interaction Hamiltonian is thus linear in the macroscopic system variable, and bilinear in the fermions. Using the recently developed extension of Feynman-Vernon theory to non-harmonic baths we evaluate quadratic and the quartic

Marco Budinich

We explore the three separate isomorphisms that link together simple spinors, null vectors and the orthogonal group O(n) and exploit them to look back at these arguments from a unified viewpoint.

A. P. Serebrov, R. M. Samoilov

We present new results of measurements of reactor antineutrino flux and spectrum dependence on the distance in the range 6-12 meters from the center of the reactor core at SM-3 reactor (Dimitrovgrad, Russia). Additional measurements were carried out and set of data to perform statistical analysis was almost doubled since the previous report. Using all collec

Javier Larrosa, Emma Rollon

MaxSAT, the optimization version of the well-known SAT problem, has attracted a lot of research interest in the last decade. Motivated by the many important applications and inspired by the success of modern SAT solvers, researchers have developed many MaxSAT solvers. Since most research is algorithmic, its significance is mostly evaluated empirically. In th

Shiroman Prakash

The ternary Golay code -- one of the first and most beautiful classical error-correcting codes discovered -- naturally gives rise to an 11-qutrit quantum error correcting code. We apply this code to magic state distillation, a leading approach to fault-tolerant quantum computing. We find that the 11-qutrit Golay code can distill the &#34;most magic&#34; qutr

Li Huang, Ruofan Chen, Haiyan Lu

The ground state electronic structure and magnetic behaviors of curium dioxide (CmO$_{2}$) are controversial. In general, the formal valence of Cm ions in CmO$_{2}$ should be tetravalent. It implies a $5f^{6.0}$ electronic configuration and a non-magnetic ground state. However, it is in sharp contrast with the large magnetic moment measured by painstaking ex

Hui-Huang Chen

In the paper arXiv:2002.12065, the authors developed a new method to compute the exact overlap formulas between integrable boundary states and on-shell Bethe states in integrable spin chains. This method utilizes the coordinate Bethe ansatz representation of wave functions and singularity property of the off-shell overlaps. In this paper, we use this new met

David Rosser, Taylor Fryett, Albert Ryou, Abhi Saxena

Cavity-integrated transition metal dichalcogenide excitons have recently emerged as a promising platform to study strong light-matter interactions and related cavity quantum electrodynamics phenomena. While this exciton-cavity system is typically modeled as coupled harmonic oscillators, to account for the rich solid-state environment the effect of exciton-ph

Matthias Wiesenberger, Markus Held

We derive the balance equation for the Favre averaged angular momentum in toroidal not necessarily axisymmetric magnetic field equilibria. We find that the components of angular momentum are given by the covariant poloidal and toroidal components of ExB and parallel flow velocities and we separately identify all relevant stress tensors, torques and source te

Kelly Gourdji, Antonia Rowlinson, Ralph A. M. J. Wijers, Adam Goldstein

What the progenitors of fast radio bursts (FRBs) are, and whether there are multiple types of progenitors are open questions. The advent of localized FRBs with host galaxy redshifts allows the various emission models to be directly tested for the first time. Given the recent localizations of two non-repeating FRBs (FRB 180924 and FRB 190523), we discuss a se

Rami Grossberg, Marcos Mazari-Armida

We introduce and study simple and supersimple independence relations in the context of AECs with a monster model. $Theorem$: Let $K$ be an AEC with a monster model. - If $K$ has a simple independence relation, then $K$ does not have the 2-tree property. - If $K$ has a simple independence relation with $(<\aleph_0)$-witness property, then $K$ does not have th

Alma Robinson, John H. Simonetti, Kasey Richardson, Megan Wawro

A large body of research shows that using interactive engagement pedagogy in the introductory physics classroom consistently results in significant student learning gains; however, with a few exceptions, those learning gains tend not to be accompanied by more expertlike attitudes and beliefs about physics and learning physics. In fact, in both traditionally

Simon Bortz, Steve Hofmann, José Luis Luna Garcia, Svitlana Mayboroda

This is the first part of a series of two papers where we study perturbations of divergence form second order elliptic operators $-\mathop{\operatorname{div}} A \nabla$ by first and zero order terms, whose coefficients lie in critical spaces, via the method of layer potentials. In particular, we show that the $L^2$ well-posedness of the Dirichlet, Neumann an

Peter M. Weber, Brian Stankus, Adam Kirrander

The advent of ultrafast pulsed X-ray free-electron lasers with very high brightness has enabled the determination of transient molecular structures of small and medium-sized organic molecules in excited states and undergoing chemical dynamics using X-ray scattering. This chapter provides an introduction into X-ray scattering theory and considers several impo

Maria Cristina Fortuna, Henk Hoekstra, Benjamin Joachimi, Harry Johnston

Intrinsic alignments (IAs) of galaxies are an important contaminant for cosmic shear studies, but the modelling is complicated by the dependence of the signal on the source galaxy sample. In this paper, we use the halo model formalism to capture this diversity and examine its implications for Stage-III and Stage-IV cosmic shear surveys. We account for the di

Riccardo Durastanti, Lorenzo Giacomelli, Giuseppe Tomassetti

We consider a cantilever beam which possesses a possibly non-uniform permanent magnetization, and whose shape is controlled by an applied magnetic field. We model the beam as a plane elastic curve and we suppose that the magnetic field acts upon the beam by means of a distributed couple that pulls the magnetization towards its direction. Given a list of targ

Daniel Perez, Jiahua Xu, Benjamin Livshits

Scalability has been a bottleneck for major blockchains such as Bitcoin and Ethereum. Despite the significantly improved scalability claimed by several high--profile blockchain projects, there has been little effort to understand how their transactional throughput is being used. In this paper, we examine recent network traffic of three major high-scalability

Hyeon Cho, Taehoon Kim, Hyung Jin Chang, Wonjun Hwang

We propose a self-supervised visual learning method by predicting the variable playback speeds of a video. Without semantic labels, we learn the spatio-temporal visual representation of the video by leveraging the variations in the visual appearance according to different playback speeds under the assumption of temporal coherence. To learn the spatio-tempora

W. E. V. Barker, A. N. Lasenby, M. P. Hobson, W. J. Handley

We propose a one-parameter extension to $Λ$CDM, expected to strongly affect cosmological tensions. An effective dark radiation component in the early universe redshifts away as hot dark matter, then quintessence, tracking the dominant equation-of-state parameter and leaving a falsifiable torsion field in the current epoch. This picture results from a new Poi

Chengying Gao, Qi Liu, Qi Xu, Limin Wang

We introduce the first method for automatic image generation from scene-level freehand sketches. Our model allows for controllable image generation by specifying the synthesis goal via freehand sketches. The key contribution is an attribute vector bridged Generative Adversarial Network called EdgeGAN, which supports high visual-quality object-level image con

Sven Otto, Jörg Breitung

It is well known that the conventional cumulative sum (CUSUM) test suffers from low power and large detection delay. In order to improve the power of the test, we propose two alternative statistics. The backward CUSUM detector considers the recursive residuals in reverse chronological order, whereas the stacked backward CUSUM detector sequentially cumulates

Luis Ferroni

We provide a formula for the Ehrhart polynomial of the connected matroid of size $n$ and rank $k$ with the least number of bases, also known as a minimal matroid. We prove that their polytopes are Ehrhart positive and $h^*$-real-rooted (and hence unimodal). We prove that the operation of circuit-hyperplane relaxation relates minimal matroids and matroid poly

Kornilios Kourtis, Martino Dazzi, Nikolas Ioannou, Tobias Grosser

Computational memory (CM) is a promising approach for accelerating inference on neural networks (NN) by using enhanced memories that, in addition to storing data, allow computations on them. One of the main challenges of this approach is defining a hardware/software interface that allows a compiler to map NN models for efficient execution on the underlying C

Zhenguo Nie, Tong Lin, Haoliang Jiang, Levent Burak Kara

In topology optimization using deep learning, load and boundary conditions represented as vectors or sparse matrices often miss the opportunity to encode a rich view of the design problem, leading to less than ideal generalization results. We propose a new data-driven topology optimization model called TopologyGAN that takes advantage of various physical fie

Philipp Jell, Hannah Markwig, Felipe Rincón, Benjamin Schröter

We study the moduli space of $d$-dimensional linear subspaces contained in a fixed $(d+1)$-dimensional linear variety $X$, and its tropicalization. We prove that these moduli spaces are linear subspaces themselves, and thus their tropicalization is completely determined by their associated (valuated) matroids. We show that these matroids can be interpreted a

J. R. B. Peleteiro, C. E. Valcárcel

Mielke-Baekler gravity consists in the usual Einstein-Hilbert action with a cosmological term and rotational and translational Chern-Simons terms with arbitrary couplings. For a particular choice of these couplings, we can obtain Einstein-Hilbert action, its teleparallel equivalent, and the exotic Witten&#39;s gravity. In this work, we use the Chern-Simons f

Marija Todorić, Bruno Klajn, Dario Jukić, Hrvoje Buljan

We study a system of strongly interacting one-dimensional (1D) bosons on a ring pierced by a synthetic magnetic flux tube. By the Fermi-Bose mapping, this system is related to the system of spin-polarized non-interacting electrons confined on a ring and pierced by a solenoid (magnetic flux tube). On the ring there is an external localized delta-function pote

Steven Yuvan, Martin Bier

Over the last half century the liquid-gas phase transition and the magnetization phase transition have come to be well understood. After an order parameter, $r$, is defined, it can be derived how $r=0$ for $T>T_c$ and how $r \propto (T_c - T)^γ$ at lowest order for $T < T_c$. The value of $γ$ appears to not depend on physical details of the system, but very

Bhargavi Jonnadula, Jonathan P. Keating, Francesco Mezzadri

Representation theory and the theory of symmetric functions have played a central role in Random Matrix Theory in the computation of quantities such as joint moments of traces and joint moments of characteristic polynomials of matrices drawn from the Circular Unitary Ensemble and other Circular Ensembles related to the classical compact groups. The reason is

Olga Aryasova, Andrey Pilipenko, Sylvie Roelly

We study the asymptotic behaviour of a real-valued diffusion whose non-regular drift is given as a sum of a dissipative term and a bounded measurable one. We prove that two trajectories of that diffusion converge a.s. to one another at an exponential explicit rate as soon as the dissipative coefficient is large enough. A similar result in $L_p$ is obtained.

Dibakar Roychowdhury

We show that the (torsional) nonrelativistic string sigma models on $ R\times S^2 $ can be mapped into \emph{deformed} Rosochatius like integrable models in one dimension. We also explore the associated Hamiltonian constrained structure by introducing appropriate Dirac brackets. These results show some solid evidence of the underlying integrable structure in

Pierre Boldrini, Roya Mohayaee, Joseph Silk

Using fully GPU $N$-body simulations, we demonstrate for the first time that subhalos sink and transfer energy via dynamical friction into the centres of dwarf galaxies. This dynamical heating kicks any central massive black hole (MBH) out to tens of parsecs, especially at early epochs ($z$=1.5-3). This mechanism helps explain the observed off-center BHs in

Mirco Theile, Harald Bayerlein, Richard Nai, David Gesbert

Coverage path planning (CPP) is the task of designing a trajectory that enables a mobile agent to travel over every point of an area of interest. We propose a new method to control an unmanned aerial vehicle (UAV) carrying a camera on a CPP mission with random start positions and multiple options for landing positions in an environment containing no-fly zone

David Viennot

We consider the competition between decoherence processes and an iterated quantum purification protocol. We show that this competition can be modelled by a nonlinear map onto the quaternion space. This nonlinear map has complicated behaviours, inducing a fractal border between the area of the quantum states dominated by the effects of the purification and th

Mehdi Ashrafi, Ali Mahdifar, Ehsan Amooghorban

In this paper, we introduce an algebraic approach to construct Fokas-Lagerstrom coherent states. To do so, we define deformed creation and annihilation operators associated to this system and investigate their algebra. We show that these operators satisfy the $f$-deformed Weyl-Heisenberg algebra. Then, we propose a theoretical scheme to generate the aforemen

Julian Bernhard, Klemens Esterle, Patrick Hart, Tobias Kessler

Predicting and planning interactive behaviors in complex traffic situations presents a challenging task. Especially in scenarios involving multiple traffic participants that interact densely, autonomous vehicles still struggle to interpret situations and to eventually achieve their own mission goal. As driving tests are costly and challenging scenarios are h

J. -M. Caillol

We present a reversible and symplectic algorithm called ROLL, for integrating the equations of motion in molecular dynamics simulations of simple fluids on a hypersphere $\mathcal{S}^d$ of arbitrary dimension $d$. It is derived in the framework of geometric algebra and shown to be mathematically equivalent to algorithm RATTLE. An application to molecular dyn

Evangelia Kyrimi, Somayyeh Mossadegh, Nigel Tai, William Marsh

Various AI models are increasingly being considered as part of clinical decision-support tools. However, the trustworthiness of such models is rarely considered. Clinicians are more likely to use a model if they can understand and trust its predictions. Key to this is if its underlying reasoning can be explained. A Bayesian network (BN) model has the advanta

Sarah Eberle, Bastian Harrach

In this paper, we deal with the inverse problem of the shape reconstruction of inclusions in elastic bodies. The main idea of this reconstruction is based on the monotonicity property of the Neumann-to-Dirichlet operator presented in a former article of the authors. Thus, we introduce the so-called standard as well as linearized monotonicity tests in order t

Cong Tri Pham, Mai Chi Luong, Dung Van Hoang, Antoine Doucet

Melanoma, one of most dangerous types of skin cancer, re-sults in a very high mortality rate. Early detection and resection are two key points for a successful cure. Recent research has used artificial intelligence to classify melanoma and nevus and to compare the assessment of these algorithms to that of dermatologists. However, an imbalance of sensitivity

Timo Richarz, Jakob Scholbach

Relying on recent advances in the theory of motives we develope a general formalism for derived categories of motives with Q-coefficients on perfect (ind-)schemes. As an application we give a motivic refinement of Zhu&#39;s geometric Satake equivalence for Witt vector affine Grassmannians in this set-up.

António Machiavelo, Nikolaos Tsopanidis

In this paper, using quaternion arithmetic in the ring of Lipschitz integers, we present a proof of Zh\`i-W\v{e}i S\={u}n's "1-3-5 conjecture" for integral solutions, and for all natural numbers greater than a specific constant. This, together with computations done by the authors and a colleague, which checked the validity of the conjecture up to that const

Yair Hayut, Menachem Magidor

We provide a model theoretical and tree property like characterization of $λ$-$Π^1_1$-subcompactness and supercompactness. We explore the behaviour of those combinatorial principles at accessible cardinals.

Harrie Hendriks, Martien C. A. van Zuijlen

Let $v_1,v_2,...,v_n$ be real numbers whose squares add up to $1$. Consider the $2^n$ signed sums of the form $S=\sum_{i=1}^n \pm v_i.$ Holzman and Kleitman (1992) proved that at least $\frac38=0.375$ of these sums satisfy $|S|\leq 1.$ By using bounds for appropriate moments of $S,$ Boppana and Holzman (2017) were able to improve the bound to $\frac{13}{32}=

Wei Leng, Lili Ju

By utilizing the perfectly matched layer (PML) and source transfer techniques, the diagonal sweeping domain decomposition method (DDM) was recently developed for solving the high-frequency Helmholtz equation in $\mathbb{R}^n$, which uses $2^n$ sweeps along respective diagonal directions with checkerboard domain decomposition. Although this diagonal sweeping

Clara Loeh, Marco Moraschini

We show that the Connes-Consani semi-norm on singular homology with real coefficients, defined via s-modules, coincides with the ordinary $\ell^1$-semi-norm on singular homology in all dimensions.

Johannes Vrana, Ripudaman Singh

Cyber technologies are offering new horizons for quality control in manufacturing and safety assurance in-service of physical assets. The line between non-destructive evaluation (NDE) and Industry 4.0 is getting blurred since both are sensory data-driven domains. This multidisciplinary approach has led to the emergence of a new capability: NDE 4.0. The NDT c

Ashif Mustafa, Manideepa Saha

In this paper, we propose and analyze iterative method based on projection techniques to solve a non-singular linear system Ax = b. In particular, for a given positive integer m, m-dimensional successive projection method (mD-SPM) for symmetric definite matrix A, is generalized for non-singular matrix A. Moreover, it is proved that mD-SPM gives better result

Vipin Chandra Dubey, Umesh Kumar Sharma

In this work, we use the statefinder parameter diagnostic to the Holographic principal inspired dark energy models, taking into consideration, the Tsallis Holographic dark energy (THDE) model, the standard Holographic dark energy (HDE) model, and the R$\acute{e}$nyi holographic dark energy (RHDE) model. The evolutionary behaviour of first statefinder $r(z)$,

Jang-Hyun Kim, Jongmin Lee, Hee-Seok Oh

This paper presents a new approach for dimension reduction of data observed in a sphere. Several dimension reduction techniques have recently developed for the analysis of non-Euclidean data. As a pioneer work, Hauberg (2016) attempted to implement principal curves on Riemannian manifolds. However, this approach uses approximations to deal with data on Riema

Antoine Amarilli, Pierre Bourhis, Stefan Mengel, Matthias Niewerth

We consider the information extraction framework known as document spanners, and study the problem of efficiently computing the results of the extraction from an input document, where the extraction task is described as a sequential variable-set automaton (VA). We pose this problem in the setting of enumeration algorithms, where we can first run a preprocess

Yuto Hosaka, Shigeyuki Komura, Alexander S. Mikhailov

Mechanochemically active enzymes change their shapes within every turnover cycle. Therefore, they induce circulating flows in the solvent around them and behave as oscillating hydrodynamic force dipoles. Because of non-equilibrium fluctuating flows collectively generated by the enzymes, mixing in the solution and diffusion of passive particles within it are

Liuquan Wang, Yifan Yang

We develop an approach to establish $1/π$-series from bimodular forms. Utilizing this approach, we obtain new families of $2$-variable $1/π$-series associated to Zagier&#39;s sporadic Apery-like sequences.

Claudio Zito, Fabio Tesser, Mauro Nicolao, Piero Cosi

In this study, we present an innovative technique for speaker adaptation in order to improve the accuracy of segmentation with application to unit-selection Text-To-Speech (TTS) systems. Unlike conventional techniques for speaker adaptation, which attempt to improve the accuracy of the segmentation using acoustic models that are more robust in the face of th

Yushi Qiu, Reiji Suda

What makes untrained deep neural networks (DNNs) different from the trained performant ones? By zooming into the weights in well-trained DNNs, we found it is the location of weights that hold most of the information encoded by the training. Motivated by this observation, we hypothesize that weights in stochastic gradient-based method trained DNNs can be sepa

Lei Kang, Pau Riba, Yaxing Wang, Marçal Rusiñol

Although current image generation methods have reached impressive quality levels, they are still unable to produce plausible yet diverse images of handwritten words. On the contrary, when writing by hand, a great variability is observed across different writers, and even when analyzing words scribbled by the same individual, involuntary variations are conspi

Matthieu Garcin

The absolute-moment method is widespread for estimating the Hurst exponent of a fractional Brownian motion $X$. But this method is biased when applied to a stationary version of $X$, in particular an inverse Lamperti transform of $X$, with a linear time contraction of parameter $θ$. We present an adaptation of the absolute-moment method to this framework and

Dingran Rui, Luzhao Sun, N. Kang, Jiayu Li

We report on low-temperature transport study of a single layer graphene (SLG)-twisted bilayer graphene (tBLG) junction device. The SLG-tBLG junction in the device is grown by chemical vapor deposition and the device is fabricated in a Hall-bar configuration on Si/SiO$_2$ substrate. The longitudinal resistances across the SLG-tBLG junction (cross-junction res

Melvin Hochster, Jack Jeffries

We study when $R \to S$ has the property that prime ideals of $R$ extend to prime ideals or the unit ideal of $S$, and the situation where this property continues to hold after adjoining the same indeterminates to both rings. We prove that if $R$ is reduced, every maximal ideal of $R$ contains only finitely many minimal primes of $R$, and prime ideals of $R[

Rui-Xing Zhang, Jay D. Sau, S. Das Sarma

We propose a general theoretical framework for both constructing and diagnosing inversion-protected higher-order topological superconductors using Kitaev building blocks, a higher-dimensional generalization of Kitaev's one-dimensional Majorana model. For a given crystalline symmetry, the Kitaev building blocks serve as a complete basis to construct all possi

Bertalan Bodor, Erkko Lehtonen, Thomas Quinn-Gregson, Nikolaas Verhulst

When does the complex product of a given number of subsets of a group generate the same subgroup as their union? We answer this question in a more general form by introducing HS-stability and characterising the HS-stable involution subsemigroup generated by a subset of a given involution semigroup. We study HS-stability for the special cases of regular ${}^{

Benjamin Bedert, George Cooper, Thomas Oliver, Pengcheng Zhang

We prove various converse theorems for automorphic forms on \Gamma_0(N), each assuming fewer twisted functional equations than the last. We show that no twisting at all is needed for holomorphic modular forms in the case that N is 18, 20, or 24 - these integers are the smallest multiples of 4 or 9 not covered by earlier work of Conrey-Farmer. This developmen

Qitao Shi, Ya-Lin Zhang, Longfei Li, Xinxing Yang

Machine learning techniques have been widely applied in Internet companies for various tasks, acting as an essential driving force, and feature engineering has been generally recognized as a crucial tache when constructing machine learning systems. Recently, a growing effort has been made to the development of automatic feature engineering methods, so that t

Victor P. Goncalves, Yuri Lima, Roman Pasechnik, Michal Šumbera

A phenomenological study of the isolated photon production in high energy $pp$ and $pA$ collisions at RHIC and LHC energies is performed. Using the color dipole approach we investigate the production cross section differential in the transverse momentum of the photon considering three different phenomenological models for the universal dipole cross section.

Adrian Hauswirth, Florian Dörfler, Andrew Teel

This paper concerns a new class of discontinuous dynamical systems for constrained optimization. These dynamics are particularly suited to solve nonlinear, non-convex problems in closed-loop with a physical system. Such approaches using feedback controllers that emulate optimization algorithms have recently been proposed for the autonomous optimization of po

Sen Li, Kameshwar Poolla, Pravin Varaiya

This paper describes the impact on transportation network companies (TNCs) of the imposition of a congestion charge and a driver minimum wage. The impact is assessed using a market equilibrium model to calculate the changes in the number of passenger trips and trip fare, number of drivers employed, the TNC platform profit, the number of TNC vehicles, and cit

D. Glavan, S. P. Miao, T. Prokopec, R. P. Woodard

We use a simplified formalism to re-compute the single graviton loop contribution to the self-mass of a massless, conformally coupled scalar on de Sitter background which was originally made by Boran, Kahya and Park [1-3]. Our result resolves the problem with the flat space correspondence limit that was pointed out by Fröb [4]. We discuss how this computatio

Nirmit Sakre, Asao Habe, Alex R. Pettitt, Takashi Okamoto

We study effect of magnetic field on massive dense core formation in colliding unequal molecular clouds by performing magnetohydrodynamic simulations with sub-parsec resolution (0.015 pc) that can resolve the molecular cores. Initial clouds with the typical gas density of the molecular clouds are immersed in various uniform magnetic fields. The turbulent mag

Gianluca Frison, Moritz Diehl

This paper introduces HPIPM, a high-performance framework for quadratic programming (QP), designed to provide building blocks to efficiently and reliably solve model predictive control problems. HPIPM currently supports three QP types, and provides interior point method (IPM) solvers as well (partial) condensing routines. In particular, the IPM for optimal c

Byungsoo Ko, Geonmo Gu

Learning the distance metric between pairs of samples has been studied for image retrieval and clustering. With the remarkable success of pair-based metric learning losses, recent works have proposed the use of generated synthetic points on metric learning losses for augmentation and generalization. However, these methods require additional generative networ

Steven Abel, Thibaut Coudarchet, Hervé Partouche

We consider an open-string realisation of $\mathcal{N}=2\to \mathcal{N}=0$ spontaneous breaking of supersymmetry in four-dimensional Minkowski spacetime. It is based on type IIB orientifold theory compactified on $T^2\times T^4/\mathbb{Z}_2$, with Scherk--Schwarz supersymmetry breaking implemented along $T^2$. We show that in the regions of moduli space wher

Pedro Lara-Benítez, Manuel Carranza-García, Francisco Martínez-Álvarez, José C. Riquelme

Processing data streams arriving at high speed requires the development of models that can provide fast and accurate predictions. Although deep neural networks are the state-of-the-art for many machine learning tasks, their performance in real-time data streaming scenarios is a research area that has not yet been fully addressed. Nevertheless, there have bee

Zheng Wang, Cheng Long, Gao Cong, Yiding Liu

Similar trajectory search is a fundamental problem and has been well studied over the past two decades. However, the similar subtrajectory search (SimSub) problem, aiming to return a portion of a trajectory (i.e., a subtrajectory) which is the most similar to a query trajectory, has been mostly disregarded despite that it could capture trajectory similarity

Jian Liang, Yunbo Wang, Dapeng Hu, Ran He

This work addresses the unsupervised domain adaptation problem, especially in the case of class labels in the target domain being only a subset of those in the source domain. Such a partial transfer setting is realistic but challenging and existing methods always suffer from two key problems, negative transfer and uncertainty propagation. In this paper, we b

Karl Schlag, Andriy Zapechelnyuk

We introduce a solution concept for extensive-form games of incomplete information in which players need not assign likelihoods to what they do not know about the game. This is embedded in a model in which players can hold multiple priors. Players make choices by looking for compromises that yield a good performance under each of their updated priors. Our so

Alessio Zappone, Marco Di Renzo, Farshad Shams, Xuewen Qian

Reconfigurable intelligent surfaces have emerged as a promising technology for future wireless networks. Given that a large number of reflecting elements is typically used, and that the surface has no signal processing capabilities, a major challenge is to cope with the overhead that is required to estimate the channel state information and to report the opt

Giulio Cerbai

Pattern avoiding machines were recently introduced by Claesson, Ferrari and the current author to gain a better understanding of the classical $2$-stacksort problem. In this paper we generalize these devices by allowing permutations with repeated elements, also known as Cayley permutations. The main result is a description of those patterns such that the cor

Ann-Kathrin Elm, Jan Kurkofka

Carmesin has extended Robertson and Seymour&#39;s tree-of-tangles theorem to the infinite tangles of locally finite infinite graphs. We extend it further to the infinite tangles of all infinite graphs. Our result has a number of applications for the topology of infinite graphs, such as their end spaces and their compactifications.

Marcel Algueró, Sébastien Descotes-Genon, Joaquim Matias, Martín Novoa-Brunet

We apply the formalism of amplitude symmetries to the angular distribution of the decays $B \to D^* \ell ν$ for $\ell=e,μ,τ$. We show that the angular observables used to describe the distribution of this class of decays are not independent in absence of New Physics contributing to tensor operators. We derive sets of relations among the angular coefficients

Ignacio Piquero-Zulaica, Aran Garcia-Lekue, Luciano Colazzo, Claudio K. Krug

Designing molecular organic semiconductors with distinct frontier orbitals is key for the development of devices with desirable properties. Generating defined organic nanostructures with atomic precision can be accomplished by on-surface synthesis. We use this dry chemistry to introduce topological variations in a conjugated poly-para-phenylene chain in the

Kazi Nazmul Haque, Rajib Rana, John H. L. Hansen, Björn Schuller

Recent improvements in Generative Adversarial Neural Networks (GANs) have shown their ability to generate higher quality samples as well as to learn good representations for transfer learning. Most of the representation learning methods based on GANs learn representations ignoring their post-use scenario, which can lead to increased generalisation ability. H

C. Wessler, B. Roessli, K. W. Krämer, B. Delley

Quantum spin liquids are materials that feature quantum entangled spin correlations and avoid magnetic long-range order at T = 0 K. Particularly interesting are two-dimensional honeycomb spin lattices where a plethora of exotic quantum spin liquids have been predicted. Here, we experimentally study an effective S=1/2 Heisenberg honeycomb lattice with competi

K. Cieliebak, E. Volkov

We introduce eight versions of cyclic homology of a mixed complex and study their properties. In particular, we determine their behaviour with respect to Chen iterated integrals.