October 2020 arXiv papers — page 12

Čestmir Burdík, Alexander A. Reshetnyak

A constrained BRST-BV Lagrangian formulation for totally symmetric massless HS fields in a $d$-dimensional Minkowski space is extended to a non-minimal constrained BRST-BV Lagrangian formulation by using a non-minimal BRST operator $Q_{c|\mathrm{tot}}$ with non-minimal Hamiltonian BFV oscillators $\overline{C}, \overline{\mathcal{P}}, \lambda, \pi$, as well

Ahmad B Qasim, Arnd Pettirsch

There is lots of scientific work about object detection in images. For many applications like for example autonomous driving the actual data on which classification has to be done are videos. This work compares different methods, especially those which use Recurrent Neural Networks to detect objects in videos. We differ between feature-based methods, which f

Bertrand Evrard, An Qu, Jean Dalibard, Fabrice Gerbier

Understanding the ground state of many-body fluids is a central question of statistical physics. Usually for weakly interacting Bose gases, most particles occupy the same state, corresponding to a Bose--Einstein condensate. However, another scenario may occur with the emergence of several, macroscopically populated single-particle states. The observation of

Prahladh Harsha, Sandeep Juneja, Daksh Mittal, Ramprasad Saptharishi

Mumbai, amongst the most densely populated cities in the world, has witnessed the fourth largest number of cases and the largest number of deaths among all the cities in India (as of 28th October 2020). Along with the rest of India, lockdowns (of varying degrees) have been in effect in Mumbai since March 25, 2020. Given the large economic toll on the country

Viktoria Stray, Anastasiia Tkalich, Nils Brede Moe

It is increasingly common to introduce agile coaches to help gain speed and advantage in agile companies. Following the success of Spotify, the role of the agile coach has branched out in terms of tasks and responsibilities, but little research has been conducted to examine how this role is practiced. This paper examines the role of the agile coach through 1

William Donnelly, Yikun Jiang, Manki Kim, Gabriel Wong

Progress in identifying the bulk microstate interpretation of the Ryu-Takayanagi formula requires understanding how to define entanglement entropy in the bulk closed string theory. Unfortunately, entanglement and Hilbert space factorization remains poorly understood in string theory. As a toy model for AdS/CFT, we study the entanglement entropy of closed str

Agnieszka Kowalska-Styczeń, Krzysztof Malarz

We examine how the randomness of behavior and the flow of information between agents affect the formation of opinions. Our main research involves the process of opinion evolution, opinion clusters formation and studying the probability of sustaining opinion. The results show that opinion formation (clustering of opinion) is influenced by both flow of informa

Dhruva Ganapathy, Lee McCuller, Jameson Graef Rollins, Evan D. Hall

Gravitational waves produced at kilohertz frequencies in the aftermath of a neutron star collision can shed light on the behavior of matter at extreme temperatures and densities that are inaccessible to laboratory experiments. Gravitational-wave interferometers are limited by quantum noise at these frequencies but can be tuned via their optical configuration

J. J. Relancio, S. Liberati

In the literature, there are several papers establishing a correspondence between a deformed kinematics and a nontrivial (momentum dependent) metric. In this work, we study in detail the relationship between the trajectories given by a deformed Hamiltonian and the geodesic motion obtained from a geometry in the cotangent bundle, finding that both trajectorie

John Cardy, Benjamin Doyon

We provide a simple geometric meaning for deformations of so-called $T{\overline T}$ type in relativistic and non-relativistic systems. Deformations by the cross products of energy and momentum currents in integrable quantum field theories are known to modify the thermodynamic Bethe ansatz equations by a "CDD factor". In turn, CDD factors may be interpreted

Joern Adamczewski-Musch, Nikolaus Kurz

The GOSIP (Gigabit Optical Serial Interface Protocol) provides communication via optical fibres between multiple kinds of front-end electronics and the KINPEX PCIe receiver board located in the readout host PC. In recent years a stack of device driver software has been developed to utilize this hardware for several scenarios of data acquisition. On top of th

Yi Zhang, Ruo-Yu Liu, S. Z. Chen, Xiang-Yu Wang

Recently, gamma-ray halos of a few degree extension have been detected around two middle-aged pulsars, namely, Geminga and PSR B0656+14, by the High Altitude Water Cherenkov observatory (HAWC). The gamma-ray radiation arise from relativistic electrons that escape the pulsar wind nebula and diffuse in the surrounding medium. The diffusion coefficient is found

Endre Boros, Ondrej Cepek, Vladimir Gurvich, Kazuhisa Makino

Each voter $i \in I$ has $\alpha_i$ cards that (s)he distributes among the candidates $a \in A$ as a measure of approval. One (or several) candidate(s) who received the maximum number of cards is (are) elected. We provide polynomial algorithms to recognize voting forms and voting correspondences generated by such voting schemes in cases when either the numbe

Ludovico Lami, Ladislav Mišta,, Gerardo Adesso

We establish fundamental upper bounds on the amount of secret key that can be extracted from quantum Gaussian states by using only local Gaussian operations, local classical processing, and public communication. For one-way public communication, or when two-way public communication is allowed but Alice and Bob first perform destructive local Gaussian measure

Akash Bose, Subenoy Chakraborty

The paper deals with cosmology in modified f(T) gravity theory. With some phenomenological choices for the function f(T) it is possible to have cosmological solutions describing different phases of the evolution of the Universe for the homogeneous and isotropic FLRW model. By proper choice of the parameters involved in the function $f(T)$ and also in the cos

Hang Dong, Víctor Suárez-Paniagua, William Whiteley, Honghan Wu

Diagnostic or procedural coding of clinical notes aims to derive a coded summary of disease-related information about patients. Such coding is usually done manually in hospitals but could potentially be automated to improve the efficiency and accuracy of medical coding. Recent studies on deep learning for automated medical coding achieved promising performan

Yueqi Wang, Yoonho Lee, Pallab Basu, Juho Lee

Learning community structures in graphs has broad applications across scientific domains. While graph neural networks (GNNs) have been successful in encoding graph structures, existing GNN-based methods for community detection are limited by requiring knowledge of the number of communities in advance, in addition to lacking a proper probabilistic formulation

Esteban Andruchow, María Eugenia Di Iorio y Lucero

Let $H=H_+\oplus H_-$ be a fixed orthogonal decomposition of the complex Hilbert space $H$ in two infinite dimensional subspaces. We study the geometry of the set $P^p$ of selfadjoint projections in the Banach algebra $$ {\cal A}^p=\{A\in B(H): [A,E_+]\in B_p(H)\}, $$ where $E_+$ is the projection onto $H_+$ and $B_p(H)$ is the Schatten ideal of $p$-summable

Jae-Mo Lihm, Cheol-Hwan Park

The anharmonic lattice is a representative example of an interacting bosonic many-body system. The self-consistent harmonic approximation has proven versatile for the study of the equilibrium properties of anharmonic lattices. However, the study of dynamical properties therewithin resorts to an ansatz, whose validity has not yet been theoretically proven. He

Luca Salasnich, Fabio Sattin

The superfluidity of low-temperature bosons is well established in the collisional regime. In the collisionless regime, however, the presence of superfluidity is not yet fully clarified, in particular in lower spatial dimensions. Here we compare the Vlasov-Landau equation, which does not take into account the superfluid nature of the bosonic system, with the

Shokoufe Faraji

This paper introduces an alternative generalization of the static solution with quadrupole moment, the $\rm q$-metric, that describes a deformed compact object in the presence of the external fields characterized by multipole moments. In addition, we also examine the impact of the external fields up to quadrupole on the circular geodesics and the interplay o

Elden Elmanto, Rune Haugseng

Structures where we have both a contravariant (pullback) and a covariant (pushforward) functoriality that satisfy base change can be encoded by functors out of ($\infty$-)categories of spans (or correspondences). In this paper we study the more complicated setup where we have two pushforwards (an "additive" and a "multiplicative" one), satisfying a distribut

David R. Fuhrman, Bjarke Eltard Larsen

A discussion on Li et al. (2019) [Numerical computations of resonant sloshing using the modified isoAdvector method and the buoyancy-modified turbulence closure model. Appl. Ocean Res. 93, article no. 101829, DOI:10.1016.j.apor.2019.05.014] is provided. Some mis-characterizations regarding the work of Larsen and Fuhrman (2018) [On the over-production of turb

F. Salehi, M. Le, L. Railing, H. M. Milchberg

We demonstrate laser wakefield acceleration of quasi-monoenergetic electron bunches up to 15 MeV at 1 kHz repetition rate with 2.5 pC charge per bunch and a core with < 7 mrad beam divergence. Acceleration is driven by 5 fs, < 2.7 mJ laser pulses incident on a thin, near-critical density hydrogen gas jet. Low beam divergence is attributed to reduced sensitiv

Mohd Asad Siddiqui, Tabish Qureshi

According to Bohr's principle of complementarity, a quanton can behave either as a wave or a particle, depending on the choice of the experimental setup. Some recent two-path interference experiments have devised methods where one can have a quantum superposition of the two choices, thus indicating that a quanton may be in a superposition of wave and particl

Jia Qian, Hiba Nassar, Lars Kai Hansen

\ac{fl} proposed a distributed \ac{ml} framework where every distributed worker owns a complete copy of global model and their own data. The training is occurred locally, which assures no direct transmission of training data. However, the recent work \citep{zhu2019deep} demonstrated that input data from a neural network may be reconstructed only using knowle

Cheng Tan, Ming-Xun Deng, Feixiang Xiang, Guolin Zheng

Monolayer WTe2 is predicted to be a quantum spin Hall insulator (QSHI) and electron transport along its edges has been experimentally observed. However, the 'smoking gun' of QSHI, spin momentum locking of the edge electrons, has not been experimentally demonstrated. We propose a model to establish the relationship between the anisotropic magnetoresistance (A

Andrew Brown, Jaesung Huh, Arsha Nagrani, Joon Son Chung

The goal of this work is to investigate the performance of popular speaker recognition models on speech segments from movies, where often actors intentionally disguise their voice to play a character. We make the following three contributions: (i) We collect a novel, challenging speaker recognition dataset called VoxMovies, with speech for 856 identities fro

Roberto Mossa

Inspired by the work of Z. Lu and G. Tian [8], A. Loi, F. Salis and F. Zuddas address in [5] the problem of studying those K\"ahler manifolds satisfying the $\Delta$-property, i.e. such that on a neighborhood of each of its points the $k$-th power of the K\"ahler Laplacian is a polynomial function of the complex Euclidean Laplacian, for all positive integer

Wojciech Kulczycki, Edward Malec

We numerically investigate the validity of recent modifications of the Penrose inequality that include angular momentum. Formulations expressed in terms of asymptotic mass and asymptotic angular momentum are contradicted. We analyzed numerical solutions describing polytropic stationary toroids around spinning black holes.

Alessandro Candido, Giuseppe Clemente, Massimo D'Elia, Federico Rottoli

We discuss the discretization of Yang-Mills theories on Dynamical Triangulations in the compact formulation, with gauge fields living on the links of the dual graph associated with the triangulation, and the numerical investigation of the minimally coupled system by Monte Carlo simulations. We provide, in particular, an explicit construction and implementati

Yan Guo, Ian Tice

In this paper we study the dynamics of an incompressible viscous fluid evolving in an open-top container in two dimensions. The fluid mechanics are dictated by the Navier-Stokes equations. The upper boundary of the fluid is free and evolves within the container. The fluid is acted upon by a uniform gravitational field, and capillary forces are accounted for

D. Aristizabal Sierra, V. De Romeri, L. J. Flores, D. K. Papoulias

Reactor neutrino experiments provide a rich environment for the study of axionlike particles (ALPs). Using the intense photon flux produced in the nuclear reactor core, these experiments have the potential to probe ALPs with masses below 10 MeV. We explore the feasibility of these searches by considering ALPs produced through Primakoff and Compton-like proce

P. D. Klaassen, V. C. Geers, S. M. Beard, A. D. O'Brien

The Mid-Infrared Instrument (MIRI) on the James Webb Space Telescope (JWST), has imaging, four coronagraphs and both low and medium resolution spectroscopic modes . Being able to simulate MIRI observations will help commissioning of the instrument, as well as get users familiar with representative data. We designed the MIRI instrument simulator (MIRISim) to

Dietmar Pfeifer, Doreen Strassburger, Joerg Philipps

In this paper we review Bernstein and grid-type copulas for arbitrary dimensions and general grid resolutions in connection with discrete random vectors possessing uniform margins. We further suggest a pragmatic way to fit the dependence structure of multivariate data to Bernstein copulas via grid-type copulas and empirical contingency tables. Finally, we di

Parsa Ghorbani

In the presence of a real singlet scalar field with $\mathbb{Z}_2$ symmetry in addition to the Higgs field in the Standard Model, we analytically investigate all possible one-step and two-step electroweak phase transitions (EWPT) in the high-temperature expansion limit. In particular, we examine the possibility of a first-order phase transition in an interme

Lukas Brantner, Joe Waldron

We construct a Galois correspondence for finite purely inseparable field extensions $F/K$, generalising a classical result of Jacobson for extensions of exponent one (where $x^p \in K$ for all $x\in F$).

A. Matulis, A. Acus

A classical system, which is analogous to the quantum one with a backflow of probability, is proposed. The system consists of a chain of masses interconnected by springs, as well attached by other springs to fixed supports. Thanks to the last springs the cutoff frequency and dispersion appears in the spectrum of waves propagating along the chain. It is shown

E. Stern-Taulats, P. Lloveras, M. Barrio, J. -Ll. Tamarit

Electrically driven thermal changes in PbSc0.5Ta0.5O3 bulk ceramics are investigated using temperature and electric-field dependent differential scanning calorimetry and infrared thermometry. On first application and removal of electric field, we find asymmetries in the magnitude of isothermal entropy change $\Delta$ S and adiabatic temperature change $\Delt

Guy D. Moore

Shear viscosity is a dynamical property of fluid systems close to equilibrium, describing resistance to sheared flow. After reviewing the physics of viscosity and the reason it is usually difficult to compute, I discuss its importance within the theory of QCD and the obstacles to carrying out such a computation. A diagrammatic analysis requires extensive res

Julieta Martinez, Jashan Shewakramani, Ting Wei Liu, Ioan Andrei Bârsan

Compressing large neural networks is an important step for their deployment in resource-constrained computational platforms. In this context, vector quantization is an appealing framework that expresses multiple parameters using a single code, and has recently achieved state-of-the-art network compression on a range of core vision and natural language proces

Demetrio Logoteta, Jiang Cao, Marco Pala, Philippe Dollfus

The availability of transistors capable of operating at low supply voltage is essential to improve the key performance metric of computing circuits, i.e., the number of operations per unit energy. In this paper, we propose a new device concept for energy-efficient, steep-slope transistors based on heterojunctions of 2D materials. We show that by injecting el

Hamilton Araujo, Martin Bordemann, Benedikt Hurle

In this paper we shall show the equivalence of algebraic and analytic localisation for algebras of smooth deformation quantization for several situations. The proofs are based on old work by Whitney, Malgrange and Tougeron on the commutative algebra of smooth function rings from the 60's and 70's.

Daniil M. Lukin, Melissa A. Guidry, Jelena Vučković

Optically-addressable solid-state spin defects are promising candidates for storing and manipulating quantum information using their long coherence ground state manifold; individual defects can be entangled using photon-photon interactions, offering a path toward large scale quantum photonic networks. Quantum computing protocols place strict limits on the ac

Erik Duse

In this paper we show how a second order scalar uniformly elliptic equation on divergence form with measurable coefficients and Dirichlet boundary conditions can be transformed into a first order elliptic system with half-Dirichlet boundary condition. This first order system involves Hodge-Dirac operators and can be seen as a natural generalization of the Be

Charles E. Thornton, R. Michael Buehrer, Anthony F. Martone

Pulse-agile radar systems have demonstrated favorable performance in dynamic electromagnetic scenarios. However, the use of non-identical waveforms within a radar's coherent processing interval may lead to harmful distortion effects when pulse-Doppler processing is used. This paper presents an online learning framework to optimize detection performance while

Yingwei Li, Zhuotun Zhu, Yuyin Zhou, Yingda Xia

Although deep neural networks have been a dominant method for many 2D vision tasks, it is still challenging to apply them to 3D tasks, such as medical image segmentation, due to the limited amount of annotated 3D data and limited computational resources. In this chapter, by rethinking the strategy to apply 3D Convolutional Neural Networks to segment medical

L. Boyd, E. Rofors, J. R. M. Annand, K. G. Fissum

The characteristics of the Solid-state Neutron Detector, under development for neutron-scattering measurements at the European Spallation Source, have been simulated with a Geant4-based computer code. The code models the interations of thermal neutrons and ionising radiation in the 6Li-doped scintillating glass of the detector, the production of scintillatio

Quanjun Lang, Fei Lu

We introduce a nonparametric algorithm to learn interaction kernels of mean-field equations for 1st-order systems of interacting particles. The data consist of discrete space-time observations of the solution. By least squares with regularization, the algorithm learns the kernel on data-adaptive hypothesis spaces efficiently. A key ingredient is a probabilis

Niv DeMalach, Jaime Kigel, Marcelo Sternberg

Ecological theory predicts that the soil seed bank stabilises the composition of annual plant communities in the face of environmental variability. However, long-term data on the community dynamics in the seed bank and the standing vegetation are needed to test this prediction. We tested the hypothesis that the composition of the seed bank undergoes lower te

João Caldeira, Fernando Brito e Abreu, Jorge Cardoso, José Reis

Context : Software comprehension and maintenance activities, such as refactoring, are said to be negatively impacted by software complexity. The methods used to measure software product and processes complexity have been thoroughly debated in the literature. However, the discernment about the possible links between these two dimensions, particularly on the b

Lukas Weber, Stefan Wessel

Dangling edge spins of two-dimensional quantum critical antiferromagnets display strongly enhanced spin correlations with scaling dimensions that fall outside of the classical theory of surface critical phenomena. We provide large-scale quantum Monte Carlo results for both spin and bond correlation functions for the case of the columnar dimer model in partic

Ludovic Arnould, Claire Boyer, Erwan Scornet, Sorbonne Lpsm

Random forests on the one hand, and neural networks on the other hand, have met great success in the machine learning community for their predictive performance. Combinations of both have been proposed in the literature, notably leading to the so-called deep forests (DF) (Zhou \& Feng,2019). In this paper, our aim is not to benchmark DF performances but to i

Feng Li, Runmin Cong, Huihui Bai, Yifan He

Recently, convolutional neural network (CNN) has demonstrated significant success for image restoration (IR) tasks (e.g., image super-resolution, image deblurring, rain streak removal, and dehazing). However, existing CNN based models are commonly implemented as a single-path stream to enrich feature representations from low-quality (LQ) input space for fina

Massimo Venaruzzo, Andrea Abba, Carlo Tintori, Yuri Venturini

The FERS-5200 is the new CAEN Front-End Readout System for large detector arrays. It consists in a compact, distributed and easy-deployable solution integrating front-end based on ASICs, A/D conversion, data processing, synchronization and readout. Using the appropriate Front-End the solution perfectly fits a wide range of detectors such as SiPMs, multianode

Isaac Gerg, Vishal Monga

Synthetic aperture sonar (SAS) requires precise positional and environmental information to produce well-focused output during the image reconstruction step. However, errors in these measurements are commonly present resulting in defocused imagery. To overcome these issues, an \emph{autofocus} algorithm is employed as a post-processing step after image recon

Gustavo H. Silvestre, Lidiane O. Pinto, Juliana S. Bernardes, Roberto H. Miwa

Cellulose disassembly is an important issue in designing nanostructures using cellulose-based materials. In this work, we present a joint of experimental and theoretical study addressing the disassembly of cellulose nanofibrils. Through 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) mediated oxidation processes, combined with atomic force microscopy results, w

Claude-Michel Brauner, Robert Roussarie, Peipei Shang, Linwan Zhang

In this paper we consider a system of two reaction-diffusion equations that models diffusional-thermal combustion with stepwise ignition-temperature kinetics and fractional reaction order 0 < $\alpha$ < 1. We turn the free interface problem into a scalar free boundary problem coupled with an integral equation. The main intermediary step is to reduce the scal

Mohamad Gharib, Paolo Lollini, Andrea Ceccarelli, Andrea Bondavalli

One of the main challenges in integrating Cyber-Physical System-of-Systems (CPSoS) to function as a single unified system is the autonomy of its Cyber-Physical Systems (CPSs), which may lead to a lack of coordination among CPSs and results in various kinds of conflicts. We advocate that to efficiently integrate CPSs within the CPSoS, we may need to adjust th

Lennart Husvogt, Stefan B. Ploner, Siyu Chen, Daniel Stromer

Optical coherence tomography angiography (OCTA) is a novel and clinically promising imaging modality to image retinal and sub-retinal vasculature. Based on repeated optical coherence tomography (OCT) scans, intensity changes are observed over time and used to compute OCTA image data. OCTA data are prone to noise and artifacts caused by variations in flow spe

Benedikt Eiteneuer, Oliver Niggemann

Anomaly detection is the task of detecting data which differs from the normal behaviour of a system in a given context. In order to approach this problem, data-driven models can be learned to predict current or future observations. Oftentimes, anomalous behaviour depends on the internal dynamics of the system and looks normal in a static context. To address

Sonja Jäckle, Elias Röger, Volker Dicken, Benjamin Geisler

In February 2020 the first human infection with SARS-CoV-2 was reported in Germany. Since then the local public health offices have been responsible to monitor and react to the dynamics of the pandemic. One of their major tasks is to contain the spread of the virus after potential spreading events, for example when one or multiple participants have a positiv

Jeff Connor, Paolo Leonetti

Let $\mathcal{I},\mathcal{J}$ be two ideals on $\mathbf{N}$ which contain the family $\mathrm{Fin}$ of finite sets. We provide necessary and sufficient conditions on the entries of an infinite real matrix $A=(a_{n,k})$ which maps $\mathcal{I}$-convergent bounded sequences into $\mathcal{J}$-convergent bounded sequences and preserves the corresponding ideal l

Noah J. Goodall

Road vehicle travel at a reasonable speed involves some risk, even when using computer-controlled driving with failure-free hardware and perfect sensing. A fully-automated vehicle must continuously decide how to allocate this risk without a human driver's oversight. These are ethical decisions, particularly in instances where an automated vehicle cannot avoi

Long Hu, Guillaume Olive

The goal of this article is to present the minimal time needed for the null controllability and finite-time stabilization of one-dimensional first-order $2 \times 2$ linear hyperbolic systems. The main technical point is to show that we cannot obtain a better time. The proof combines the backstepping method with the Titchmarsh convolution theorem.

Man-Chun Lee, Aaron Naber, Robin Neumayer

Consider a sequence of Riemannian manifolds $(M^n_i,g_i)$ with scalar curvatures and entropies bounded below by small constants $R_i,\mu_i \geq-\epsilon_i$. The goal of this paper is to understand notions of convergence and the structure of limits for such spaces. Even in the seemingly rigid case $\epsilon_i\to 0$, we construct examples showing that such a s

H. Spreeuw, S. Yatawatta, B. van Werkhoven, F. Diblen

As astronomical instruments become more sensitive, the requirements for the calibration software become more stringent; without accurate calibration solutions, thermal noise levels in images will not be reached and the scientific output of the instrument is degraded. Calibration requires bright sources with known properties, in particular with respect to the

Alexey Kuzmin, Lyudmila Turowska

Given a skew-symmetric real $n\times n$ matrix $\Theta$ we consider the universal enveloping $C^*$-algebra $\mathsf{CAR}_\Theta$ of the $*$-algebra generated by $a_1, \ldots, a_n$ subject to the relations \[ a_i^* a_i + a_i a_i^* = 1, \ \] \[ a_i^* a_j = e^{2 \pi i \Theta_{i,j}} a_j a_i^*, \] \[ a_i a_j = e^{-2 \pi i \Theta_{i,j}} a_j a_i. \] We prove that $

Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada

Detecting influential features in non-linear and/or high-dimensional data is a challenging and increasingly important task in machine learning. Variable selection methods have thus been gaining much attention as well as post-selection inference. Indeed, the selected features can be significantly flawed when the selection procedure is not accounted for. We pr

Arash Behboodi, Holger Rauhut, Ekkehard Schnoor

Various iterative reconstruction algorithms for inverse problems can be unfolded as neural networks. Empirically, this approach has often led to improved results, but theoretical guarantees are still scarce. While some progress on generalization properties of neural networks have been made, great challenges remain. In this chapter, we discuss and combine the

Zhiguo Ding, Michael E. Zieve

We determine all degree-4 rational functions f(X) in F_q(X) which permute P^1(F_q), and answer two questions of Ferraguti and Micheli about the number of such functions and the number of equivalence classes of such functions up to composing with degree-one rational functions. We also determine all degree-8 rational functions f(X) in F_q(X) which permute P^1(

Masazumi Honda, Naotaka Kubo

It has been conjectured that duality cascade occurs in the $\mathcal{N}=3$ supersymmetric Yang-Mills Chern-Simons theory with the gauge group $U(N )_k \times U(N+M )_{-k}$ coupled to two bi-fundamental hypermultiplets. The brane picture suggests that this duality cascade can be generalized to a class of 3d $\mathcal{N}=3$ supersymmetric quiver gauge theories

Ofir E. Alon

A solvable model of a periodically-driven trapped mixture of Bose-Einstein condensates, consisting of $N_1$ interacting bosons of mass $m_1$ driven by a force of amplitude $f_{L,1}$ and $N_2$ interacting bosons of mass $m_2$ driven by a force of amplitude $f_{L,2}$, is presented. The model generalizes the harmonic-interaction model for mixtures to the time-d

Liangrui Pan, Pronthep Pipitsunthonsan, Chalongrat Daengngam, Mitchai Chongcheawchamnan

With noisy environment caused by fluoresence and additive white noise as well as complicated spectrum fingerprints, the identification of complex mixture materials remains a major challenge in Raman spectroscopy application. In this paper, we propose a new scheme based on a constant wavelet transform (CWT) and a deep network for classifying complex mixture.

Niko Moritz, Takaaki Hori, Jonathan Le Roux

Semi-supervised learning has demonstrated promising results in automatic speech recognition (ASR) by self-training using a seed ASR model with pseudo-labels generated for unlabeled data. The effectiveness of this approach largely relies on the pseudo-label accuracy, for which typically only the 1-best ASR hypothesis is used. However, alternative ASR hypothes

Harneet Kaur, Nisha, Amit Goyal, Thokala Soloman Raju

We present exact bright, dark and rogue soliton solutions of generalized higherorder nonlinear Schrodinger equation, describing the ultrashort beam propagation in tapered waveguide amplifier, via a similarity transformation connected with the constant-coefficient Sasa-Satsuma and Hirota equations. Our exact analysis takes recourse to identify the allowed tap

Simon Geisler, Daniel Zügner, Stephan Günnemann

Perturbations targeting the graph structure have proven to be extremely effective in reducing the performance of Graph Neural Networks (GNNs), and traditional defenses such as adversarial training do not seem to be able to improve robustness. This work is motivated by the observation that adversarially injected edges effectively can be viewed as additional s

Patrick Liscio

We analyze the poset of moves in chip-firing, as defined by Klivans and Liscio. Answering a question of Propp, we show that the move poset forms the join-irreducibles of the poset of configurations. The proof involves a graph augmentation and an analysis of configurations in which only one firing move is available. We then use this framework to analyze the p

Guoxing Wang, Yuxuan Wang, Xiaofeng Xu, Yongqi Xu

We present a precise and efficient computation of the two-loop amplitudes entering the Higgs boson pair production process via gluon fusion. Our approach is based on the small-Higgs-mass expansion while keeping the full dependence on the top quark mass and other kinematic invariants. We compare our results to the up-to-date predictions based on a combination

Heiko Augustin, Niklaus Berger, Alessandro Bravar, Konrad Briggl

The Mu3e experiment aims to find or exclude the lepton flavour violating decay $\mu^+\to e^+e^-e^+$ with a sensitivity of one in 10$^{16}$ muon decays. The first phase of the experiment is currently under construction at the Paul Scherrer Institute (PSI, Switzerland), where beams with up to 10$^8$ muons per second are available. The detector will consist of

Chenyu Liu, Wangbin Ding, Lei Li, Zhen Zhang

Delineating the brain tumor from magnetic resonance (MR) images is critical for the treatment of gliomas. However, automatic delineation is challenging due to the complex appearance and ambiguous outlines of tumors. Considering that multi-modal MR images can reflect different tumor biological properties, we develop a novel multi-modal tumor segmentation netw

Richard Sharp, Anastasios Stylianou

In this article, we consider a counting problem for orbits of hyperbolic rational maps on the Riemann sphere, where constraints are placed on the multipliers of orbits. Using arguments from work of Dolgopyat, we consider varying and potentially shrinking intervals, and obtain a result which resembles a local central limit theorem for the logarithm of the abs

Yong Zheng, Andrew Emerick, Mary E. Putman, Jessica K. Werk

Using 10 sightlines observed with the Hubble Space Telescope/Cosmic Origins Spectrograph, we study the circumgalactic medium (CGM) and outflows of IC1613, which is a low-mass ($M_*\sim10^8~M_\odot$), dwarf irregular galaxy on the outskirts of the Local Group. Among the sightlines, 4 are pointed towards UV-bright stars in IC1613, and the other 6 sightlines ar

Michael Freedman, Vyacheslav Krushkal, Christopher J. Leininger, Alan W. Reid

We introduce and study the notion of filling links in 3-manifolds: a link L is filling in M if for any 1-spine G of M which is disjoint from L, $\pi_1(G)$ injects into $\pi_1(M\smallsetminus L)$. A weaker "k-filling" version concerns injectivity modulo k-th term of the lower central series. For each k>1 we construct a k-filling link in the 3-torus. The proof

Silvia Biondi, Andrey Alexandrov, Behcet Alpat, Giovanni Ambrosi

The FragmentatiOn Of Target (FOOT) experiment aims to provide precise nuclear cross-section measurements for two different fields: hadrontherapy and radio-protection in space. The main reason is the important role the nuclear fragmentation process plays in both fields, where the health risks caused by radiation are very similar and mainly attributable to the

Xin Ma, Xiaoqiang Zhou, Huaibo Huang, Zhenhua Chai

Most deep learning based image inpainting approaches adopt autoencoder or its variants to fill missing regions in images. Encoders are usually utilized to learn powerful representational spaces, which are important for dealing with sophisticated learning tasks. Specifically, in image inpainting tasks, masks with any shapes can appear anywhere in images (i.e.

Philip Winchester, Vassilios Dallas, Peter D. Howell

We analyse the nonlinear dynamics of the large scale flow in Rayleigh-B\'enard convection in a two-dimensional, rectangular geometry of aspect ratio $\Gamma$. We impose periodic and free-slip boundary conditions in the streamwise and spanwise directions, respectively. As Rayleigh number Ra increases, a large scale zonal flow dominates the dynamics of a moder

Zhiguo Ding, Michael E. Zieve

We describe the absolute values on a field which simultaneously extend absolute values on two subfields. We also give a common generalization of many versions of Abhyankar's lemma on ramification indices, which is both widely applicable and easy to state. We then apply these results to count points on the fibered product of two curve morphisms C --> X and D

Amir Weiss, Gregory W. Wornell

One of the main drawbacks of the well-known Direct Position Determination (DPD) method is the requirement that raw signal data be transferred to a common processor. It would therefore be of high practical value if DPD$-$or a modified version thereof$-$could be successfully applied to a coarsely quantized version of the raw data, thus alleviating the requirem

Siddarth Asokan, Chandra Sekhar Seelamantula

Generative adversarial networks (GANs) were originally envisioned as unsupervised generative models that learn to follow a target distribution. Variants such as conditional GANs, auxiliary-classifier GANs (ACGANs) project GANs on to supervised and semi-supervised learning frameworks by providing labelled data and using multi-class discriminators. In this pap

Kishor Jothimurugan, Osbert Bastani, Rajeev Alur

We propose a novel hierarchical reinforcement learning framework for control with continuous state and action spaces. In our framework, the user specifies subgoal regions which are subsets of states; then, we (i) learn options that serve as transitions between these subgoal regions, and (ii) construct a high-level plan in the resulting abstract decision proc

T. Morishita

The Hubble Space Telescope (HST) has been providing tremendous survey efficiency via its pure-parallel mode, by observing another field in parallel with the primary instrument in operation for the primary observation. In this study, we present a new archival project, SuperBoRG, which aims at compiling data taken in extragalactic parallel programs of HST with

Kaie Kubjas, Luca Sodomaco, Elias Tsigaridas

Low-rank approximation with zeros aims to find a matrix of fixed rank and with a fixed zero pattern that minimizes the Euclidean distance to a given data matrix. We study the critical points of this optimization problem using algebraic tools. In particular, we describe special linear, affine, and determinantal relations satisfied by the critical points. We a

Amber A. Medina, Jennifer G. Winters, Jonathan M. Irwin, David Charbonneau

We present a study of flare rates, rotation periods, and spectroscopic activity indicators of 125 single stars within 15 parsecs and with masses between 0.1$-$0.3 $M_\odot$ observed during the first year of the TESS mission, with the goal of elucidating the relationship between these various magnetically connected phenomena. We gathered multi-epoch high reso

Enno Keßler, Artan Sheshmani, Shing-Tung Yau

In this article we define stable supercurves and super stable maps of genus zero via labeled trees. We prove that the moduli space of stable supercurves and super stable maps of fixed tree type are quotient superorbifolds. To this end, we prove a slice theorem for the action of super Lie groups on Riemannian supermanifolds and discuss superorbifolds. Further

Bo Fu, Zi-Ang Hu, Chang-An Li, Jian Li

Chiral Majorana hinge modes are characteristic of a second-order topological superconductor in three dimensions. Here we systematically study pairing symmetry in the point group D_{2h}, and find that the leading pairing channels can be of s-, d-, and s+id-wave pairing in Dirac materials. Except for the odd-parity s-wave pairing superconductivity, the s+id-wa

Asaf Karagila

This text is meant for analysis students who want to learn more about the effects of the axiom of choice on functional analysis, and the things that may go wrong in its absence. As this is a text aimed for analysis students, we will not focus on the set theoretic proofs or dwell on any particular set theoretic assumptions that are needed in order to prove ce

Marek Tylutki, Gabriel Wlazłowski

Reconnecting vortices in a superfluid allow for the energy transfer between different length scales and its subsequent dissipation. The present picture assumes that the dynamics of a reconnection is driven mostly by the phase of the order parameter, and this statement can be justified in the case of Bose-Einstein Condensates (BECs), where vortices have a sim

Hailong Li, Hua Jiang, Chui-Zhen Chen, X. C. Xie

Recently, the search for an axion insulator state in the ferromagnet-3D topological insulator (TI) heterostructure and $\mathrm{MnBi_2Te_4}$ has attracted intensive interest. However, its detection remains difficult in experiments. We systematically investigate the disorder-induced phase transition of the axion insulator state in a 3D TI with antiparallel ma

Konstantin Eder, Hanno Sahlmann

In this paper, we study a class of symmetry reduced models of $\mathcal{N}=1$ supergravity using self-dual variables. It is based on a particular Ansatz for the gravitino field as proposed by D'Eath et al. We show that the essential part of the constraint algebra in the classical theory closes. In particular, the (graded) Poisson bracket between the left and