October 2020 arXiv papers — page 58

Simone Costa, Anita Pasotti

In this paper we define a new class of partially filled arrays, called $\lambda$-fold relative Heffter arrays, that are a generalisation of the Heffter arrays introduced by Archdeacon in 2015. After showing the connection of this new concept with several other ones, such as signed magic arrays, graph decompositions and relative difference families, we determ

David Loeffler, Christopher Skinner, Sarah Livia Zerbes

We construct an Euler system associated to regular algebraic, essentially conjugate self-dual cuspidal automorphic representations of GL(3) over imaginary quadratic fields, using the cohomology of Shimura varieties for GU(2, 1).

Alina Wettstein, Diddo Diddens, Andreas Heuer

We present the results from an extensive atomistic molecular dynamics simulation study of poly(ethylene oxide) (PEO) doped with various amounts of lithium-bis(trifluoromethane)sulfonimide (LiTFSI) salt under the influence of external electric field strengths up to $1\,$V/nm. The motivation stems from recent experimental reports on the nonlinear response of m

Hai Xu, Y. Sophia Dai, Jia-Sheng Huang, Zhaoyu Wang

In this paper we present a simple color-magnitude selection and obtain a large sample of 33,893 massive quiescent galaxies at intermediate redshifts (1<z<1.5). We choose the longest wavelength available in the Hyper-Supreme-Cam (HSC) deep survey, the Y band and i-Y color, to select the 4000A Balmer jump in passive galaxies to the highest redshift possible wi

Umair Khan, Javier Hernando

This report describes the submission from Technical University of Catalonia (UPC) to the VoxCeleb Speaker Recognition Challenge (VoxSRC-20) at Interspeech 2020. The final submission is a combination of three systems. System-1 is an autoencoder based approach which tries to reconstruct similar i-vectors, whereas System-2 and -3 are Convolutional Neural Networ

Mohamed Chabab, Samir Iraoui

In this paper, we have extended and deepened the study on fractional order phase transition (FPT) of a charged AdS black hole performed in [1]. We have carried out a detailed analysis of FPT for several AdS black hole prototypes: black hole surrounded by quintessence background, 5D Gauss-Bonnet, D dimensional RN-AdS BH, and lastly Kerr black holes. We have s

X. J. Li, Z. B. Zhang, X. L. Zhang, H. Y. Zhen

A comprehensive study is given to short gamma-ray bursts (sGRBs) in the third Swift/BAT GRB Catalog from December 2004 to July 2019. We examine in details the temporal properties of the three components in the prompt gamma-ray emission phase, including precursors, main peaks and extended emissions (EE). We investigate the similarity of the main peaks between

Erkka Haapasalo, Tristan Kraft, Juha-Pekka Pellonpää, Roope Uola

Recently, various non-classical properties of quantum states and channels have been characterized through an advantage they provide in specific quantum information tasks over their classical counterparts. Such advantage can be typically proven to be quantitative, in that larger amounts of quantum resources lead to better performance in the corresponding task

Pia Lochner, Jens Kerski, Annika Kurzmann, Andreas D. Wieck

We demonstrate by time-resolved resonance fluorescence measurements on a single self-assembled quantum dot an internal photo-effect that emits electrons from the dot by an intra-band excitation. We find a linear dependence of the optically generated emission rate on the excitation intensity and use a rate equation model to deduce the involved rates. The emis

Wenjing Zhu, Chengxiang Ding, Long Zhang, Wenan Guo

The special surface transition at (2+1)-dimensional quantum critical point is precluded in corresponding classical critical point. The mechanism of such behavior which is only found in dimerized Heisenberg models so far is still under debate. To illuminate the role of symmetry protected topological (SPT) phase in inducing such nonordinary behaviors, we study

Yafeng Chen, Wu Guo, Jingjing Shi, Jiajun Qi

In this work, we introduce metric learning (ML) to enhance the deep embedding learning for text-independent speaker verification (SV). Specifically, the deep speaker embedding network is trained with conventional cross entropy loss and auxiliary pair-based ML loss function. For the auxiliary ML task, training samples of a mini-batch are first arranged into p

J. Lozano, A. Agadjanov, J. Gegelia, U. -G. Meißner

We calculate the spin-averaged amplitude for doubly virtual forward Compton scattering off nucleons in the framework of manifestly Lorentz invariant baryon chiral perturbation theory at complete one-loop order $O(p^4)$. The calculations are carried out both in the infinite and in a finite volume. The obtained results allow for a detailed estimation the finit

Bangti Jin, Zehui Zhou, Jun Zou

Stochastic gradient descent (SGD) is a promising method for solving large-scale inverse problems, due to its excellent scalability with respect to data size. The current mathematical theory in the lens of regularization theory predicts that SGD with a polynomially decaying stepsize schedule may suffer from an undesirable saturation phenomenon, i.e., the conv

Jakob Bossek, Frank Neumann

In the area of evolutionary computation the calculation of diverse sets of high-quality solutions to a given optimization problem has gained momentum in recent years under the term evolutionary diversity optimization. Theoretical insights into the working principles of baseline evolutionary algorithms for diversity optimization are still rare. In this paper

Daniel Hausmann, Stefan Milius, Lutz Schröder

Logics and automata models for languages over infinite alphabets, such as Freeze LTL and register automata, serve the verification of processes or documents with data. They relate tightly to formalisms over nominal sets, such as nondetermininistic orbit-finite automata (NOFAs), where names play the role of data. Reasoning problems in such formalisms tend to

Yuting I. Li, Günther Turk, Paul B. Rohrbach, Patrick Pietzonka

Epidemiological forecasts are beset by uncertainties about the underlying epidemiological processes, and the surveillance process through which data are acquired. We present a Bayesian inference methodology that quantifies these uncertainties, for epidemics that are modelled by (possibly) non-stationary, continuous-time, Markov population processes. The effi

Harvey R. Brown

Noether's first theorem does not establish a one-way explanatory arrow from symmetries to conservation laws, but such an arrow is widely assumed in discussions of the theorem in the physics and philosophy literature. It is argued here that there are pragmatic reasons for privileging symmetries, even if they do not strictly justify explanatory priority. To th

Elena Voita, Rico Sennrich, Ivan Titov

In Neural Machine Translation (and, more generally, conditional language modeling), the generation of a target token is influenced by two types of context: the source and the prefix of the target sequence. While many attempts to understand the internal workings of NMT models have been made, none of them explicitly evaluates relative source and target contrib

Branden Chan, Stefan Schweter, Timo Möller

In this work we present the experiments which lead to the creation of our BERT and ELECTRA based German language models, GBERT and GELECTRA. By varying the input training data, model size, and the presence of Whole Word Masking (WWM) we were able to attain SoTA performance across a set of document classification and named entity recognition (NER) tasks for b

Serge A. Krasnokutski

The biological molecules delivered to Earth on the board of meteorites and comets were called one of the possible causes of the origin of life. Therefore, our understanding of the routes of formation of biomolecules in space should shed the light on the possibility of the existence of habitable extrasolar planets. The large abundance of organic molecules is

Noémie Jaquier, Leonel Rozo

Despite the recent success of Bayesian optimization (BO) in a variety of applications where sample efficiency is imperative, its performance may be seriously compromised in settings characterized by high-dimensional parameter spaces. A solution to preserve the sample efficiency of BO in such problems is to introduce domain knowledge into its formulation. In

Ezra Tampubolon, Haris Ceribasic, Holger Boche

In this work, we study the system of interacting non-cooperative two Q-learning agents, where one agent has the privilege of observing the other's actions. We show that this information asymmetry can lead to a stable outcome of population learning, which generally does not occur in an environment of general independent learners. The resulting post-learning p

Jamal Ou aali, Bouzid Manaut, Larbi Rahili, Souad Semlali

The aim of this study is to investigate the quadratic divergences using dimensional regularization within the context of the standard model extended by two real scalar singlets (TRSM). This extension provides three neutral scalar fields that mix, after developing its {\it vev}'s, leading to three CP-even Higgs bosons, namely: $h_1$, $h_2$ and $h_3$, which wo

Elisa I. Goettems, Thiago O. Maciel, Diogo O. Soares-Pinto, E. I. Duzzioni

The deterministic quantum computation with one qubit (DQC1) model is a restricted model of quantum computing able to calculate efficiently the normalized trace of a unitary matrix. In this work we analyse the quantum correlations named entanglement, Bell's nonlocality, quantum discord, and coherence generated by the DQC1 circuit considering only two qubits (

Théo Estienne, Maria Vakalopoulou, Enzo Battistella, Alexandre Carré

Image registration is one of the most challenging problems in medical image analysis. In the recent years, deep learning based approaches became quite popular, providing fast and performing registration strategies. In this short paper, we summarise our work presented on Learn2Reg challenge 2020. The main contributions of our work rely on (i) a symmetric form

Eduardo Sebastián, Eduardo Montijano

This paper presents a novel control strategy to herd a group of non-cooperative evaders by means of a team of robotic herders. In herding problems, the motion of the evaders is typically determined by strong nonlinear reactive dynamics, escaping from the herders. Many applications demand the herding of numerous and/or heterogeneous entities, making the devel

Yang Jiao

We propose a method for joint multichannel speech dereverberation with two spatial-aware tasks: direction-of-arrival (DOA) estimation and speech separation. The proposed method addresses involved tasks as a sequence to sequence mapping problem, which is general enough for a variety of front-end speech enhancement tasks. The proposed method is inspired by the

Ben Li, Carsten Schütt, Elisabeth M. Werner

Affine invariant points and maps for sets were introduced by Gr\"unbaum to study the symmetry structure of convex sets. We extend these notions to a functional setting. The role of symmetry of the set is now taken by evenness of the function. We show that among the examples for affine invariant points are the classical center of gravity of a log-concave func

Tobias Alt, Joachim Weickert

We introduce an integrodifferential extension of the edge-enhancing anisotropic diffusion model for image denoising. By accumulating weighted structural information on multiple scales, our model is the first to create anisotropy through multiscale integration. It follows the philosophy of combining the advantages of model-based and data-driven approaches wit

Mauricio Bustamante, Oscar Randal-Williams

We study the infinite generation in the homotopy groups of the group of diffeomorphisms of $S^1 \times D^{2n-1}$, for $2n \geq 6$, in a range of degrees up to $n-2$. Our analysis relies on understanding the homotopy fibre of a linearisation map from the plus-construction of the classifying space of certain space of self-embeddings of stabilisations of this m

Arezou Rezazadeh, Sharu Theresa Jose, Giuseppe Durisi, Osvaldo Simeone

Meta-learning optimizes an inductive bias---typically in the form of the hyperparameters of a base-learning algorithm---by observing data from a finite number of related tasks. This paper presents an information-theoretic bound on the generalization performance of any given meta-learner, which builds on the conditional mutual information (CMI) framework of S

Eric Squires, Rohit Konda, Pietro Pierpaoli, Samuel Coogan

In this paper we discuss how to use a barrier function that is subject to kinematic constraints and limited sensing in order to guarantee that fixed wing unmanned aerial vehicles (UAVs) will maintain safe distances from each other at all times despite being subject to limited range sensing constraints. Prior work has shown that a barrier function can be used

Hung Do, Robert Malaney, Jonathan Green

Heterogeneous quantum networks consisting of mixed-technologies - Continuous Variable (CV) and Discrete Variable (DV) - will become ubiquitous as global quantum communication matures. Hybrid quantum-entanglement between CV and DV modes will be a critical resource in such networks. A leading candidate for such hybrid quantum entanglement is that between Schr\

Josep Domingo-Ferrer, Jordi Soria-Comas

In our data world, a host of not necessarily trusted controllers gather data on individual subjects. To preserve her privacy and, more generally, her informational self-determination, the individual has to be empowered by giving her agency on her own data. Maximum agency is afforded by local anonymization, that allows each individual to anonymize her own dat

Bugeon Jo, Hyeontae Kim, Hyung Do Kim, Chang Sub Shin

We study the cosmology of the dark sector consisting of (ultra) light scalars. Since the scalar mass is radiatively unstable, a special explanation is required to make the mass much smaller than the UV scale. There are two well-known mechanisms for the origin of scalar mass. The scalar can be identified as a pseudo-Goldstone boson, whose shift symmetry is ex

Taylor Brysiewicz, Claudia Fevola, Bernd Sturmfels

We examine quadratic surfaces in 3-space that are tangent to nine given figures. These figures can be points, lines, planes or quadrics. The numbers of tangent quadrics were determined by Hermann Schubert in 1879. We study the associated systems of polynomial equations, also in the space of complete quadrics, and we solve them using certified numerical metho

E. T. Akhmedov, P. A. Anempodistov, K. V. Bazarov, D. V. Diakonov

We study quantum fields on spacetimes having a bifurcate Killing horizon by allowing the possibility that left- and right- (in-going and out-going) modes have different temperatures. We consider in particular the Rindler for both massless and massive fields, the static de Sitter and Schwarzschild black hole backgrounds for massive fields. We find that in all

Erik Ekstedt, Gabriel Skantze

Syntactic and pragmatic completeness is known to be important for turn-taking prediction, but so far machine learning models of turn-taking have used such linguistic information in a limited way. In this paper, we introduce TurnGPT, a transformer-based language model for predicting turn-shifts in spoken dialog. The model has been trained and evaluated on a v

Toshifumi Noumi, Kaishu Saito, Jiro Soda, Daisuke Yoshida

We consider an $O(d,d;\mathbb{Z})$ invariant massive deformation of double field theory at the level of free theory. We study Kaluza-Klein reduction on $R^{1,n-1} \times T^{d}$ and derive the diagonalized second order action for each helicity mode. Imposing the absence of ghosts and tachyons, we obtain a class of consistency conditions which include the well

U. Buchenau

The strain field surrounding the center of low frequency vibrational modes is analyzed for numerically created binary glasses with a 1/r^10 repulsive interatomic potential. Outside the unstable inner core of five to twenty atoms, one finds a mixture of a motion similar to the string motion in the core with the strain field of three oscillating elastic dipole

Chandra Prakash

The microscopic origin of black hole entropy remains one of the central puzzles in quantum gravity. In this work, we investigate the statistical entropy of scalar fields propagating in stationary axisymmetric spacetimes using the thin-film modification of the 't Hooft brick wall method. We derive a generalized expression for the free energy of both superradi

Felix Taubner, Florian Tschopp, Tonci Novkovic, Roland Siegwart

Current research on visual place recognition mostly focuses on aggregating local visual features of an image into a single vector representation. Therefore, high-level information such as the geometric arrangement of the features is typically lost. In this paper, we introduce a novel learning-based approach to place recognition, using RGB-D cameras and line

Clément Rebuffel, Laure Soulier, Geoffrey Scoutheeten, Patrick Gallinari

In language generation models conditioned by structured data, the classical training via maximum likelihood almost always leads models to pick up on dataset divergence (i.e., hallucinations or omissions), and to incorporate them erroneously in their own generations at inference. In this work, we build ontop of previous Reinforcement Learning based approaches

Kohsuke Sumiyoshi, Sho Fujibayashi, Yuichiro Sekiguchi, Masaru Shibata

We study properties of neutrino transfer in a remnant of neutron star merger, consisting of a massive neutron star and a surrounding torus. We perform numerical simulations of the neutrino transfer by solving the Boltzmann equation with momentum-space angles and energies of neutrinos for snapshots of the merger remnant having elongated shapes. The evaluation

Roberto Bondesan, Max Welling

We develop a new quantum neural network layer designed to run efficiently on a quantum computer but that can be simulated on a classical computer when restricted in the way it entangles input states. We first ask how a classical neural network architecture, both fully connected or convolutional, can be executed on a quantum computer using quantum phase estim

Andreja Bencan, Emad Oveisi, Sina Hashemizadeh, Vignaswaran K. Veerapandiyan

The nature of the "forbidden" local- and long-range polar order in nominally nonpolar paraelectric phases of ferroelectric materials has been an open question since the discovery of ferroelectricity in oxide perovskites (ABO3). A currently considered model suggests locally correlated displacements of B-site atoms along a subset of <111> cubic directions. Suc

Dominique Devriese, Eric Mark Martin, Marco Patrignani

Recursive types extend the simply-typed lambda calculus (STLC) with the additional expressive power to enable diverging computation and to encode recursive data-types (e.g., lists). Two formulations of recursive types exist: iso-recursive and equi-recursive. The relative advantages of iso- and equi-recursion are well-studied when it comes to their impact on

M. Kakenov, V. I. Kukulin, V. N. Pomerantsev, O. Bayakhmetov

Properties of six-quark dibaryons in nuclear medium are considered by example of $A=6$ nuclei within the three-cluster $α+2N$ model. Dibaryon production in nuclei leads to the appearance of a three-body force between the dibaryon and nuclear core. This non-conventional scalar force is shown to provide an additional attractive contribution to the three-body b

Cillian Harney, Leonardo Banchi, Stefano Pirandola

Quantum Channel Discrimination (QCD) presents a fundamental task in quantum information theory, with critical applications in quantum reading, illumination, data-readout and more. The extension to multiple quantum channel discrimination has seen a recent focus to characterise potential quantum advantage associated with quantum enhanced discriminatory protoco

Pavel Tonkaev, Yuri Kivshar

Future technologies underpinning high-performance optical communications, ultrafast computations and compact biosensing will rely on densely packed reconfigurable optical circuitry based on nanophotonics. For many years, plasmonics was considered as the only available platform for nanoscale optics, but the recently emerged novel field of Mie resonant metapho

Dayanand Mishra, Namit Mahajan

We give detailed results of $\mathcal{O}(\alpha)$ QED corrections (both real emission and virtual corrections) to $B\to K\ell^+\ell^-$ modes. Requiring the real emission to be gauge invariant, the structure of the contact term(s) is fixed. The calculation is done with a fictitious photon mass as the IR regulator and results are shown to be independent of it,

Huy Quoc To, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen, Anh Gia-Tuan Nguyen

As biological gender is one of the aspects of presenting individual human, much work has been done on gender classification based on people names. The proposals for English and Chinese languages are tremendous; still, there have been few works done for Vietnamese so far. We propose a new dataset for gender prediction based on Vietnamese names. This dataset c

Nicolai Shatsky, Alexander Belinski, Alexander Dodin, Serguey Zheltoukhov

The new SAI MSU observatory 2.5-meter telescope and capabilities of its current instrumentation are described. The facility operates actively since 2014 in parallel to the engineering works. It has delivered a number of prominent results in the field of optical and near-infrared photometry and spectroscopy as well as newly developed observational techniques

Pavan Nukala, Majid Ahmadi, Yingfen Wei, Sytze de Graaf

Unconventional ferroelectricity, robust at reduced nanoscale sizes, exhibited by hafnia-based thin-films presents tremendous opportunities in nanoelectronics. However, the exact nature of polarization switching remains controversial. Here, we investigate epitaxial Hf0.5Zr0.5O2 (HZO) capacitors, interfaced with oxygen conducting metals (La0.67Sr0.33MnO3, LSMO

Archana Dixit, Vinod Kumar Bhardwaj, Anirudh Pradhan

In this manuscript, we have researched the cosmic expansion phenomenon in flat FRW Universe through the interaction of the recently proposed R$\grave{e}$nyi holographic dark energy (RHDE). For this reason, we assumed Hubble (H) and Granda--Oliveros (GO) horizons as IR cut-off in the framework of $f(R, T)$ gravity. With this choice for IR cut-off, we can obta

Takuya Kiyokawa, Jun Takamatsu, Tsukasa Ogasawara

Aiming to generate easy-to-handle assembly sequences for robotic assembly, this study tackles assembly sequence generation by considering two tradeoff objectives: (1) insertion conditions and (2) degrees of constraints among assembled parts. We propose a multiobjective genetic algorithm to balance these two objectives for generating assembly sequences. Furth

July X. Li, Joseph M. Renes, Pascal O. Vontobel

In previous work, we have shown that pseudocodewords can be used to characterize the behavior of decoders not only for classical codes but also for quantum stabilizer codes. With the insights obtained from this pseudocodewords-based analysis, we have also introduced a two-stage decoder based on pseudocodewords for quantum cycle codes that leads to improved d

Yuki Noguchi, Takayuki Yamada

In this paper, we propose a level set-based topology optimization method for the unit-cell design of acoustic metasurfaces by using a two-scale homogenization method. Based on previous works, we first propose a homogenization method for acoustic metasurfaces that can be combined with topology optimization. In this method, a nonlocal transmission condition de

Takuya Kiyokawa, Tatsuya Sakuma, Jun Takamatsu, Tsukasa Ogasawara

To design a general-purpose assembly robot system that can handle objects of various shapes, we propose a soft jig that fits to the shapes of assembly parts. The functionality of the soft jig is based on a jamming gripper developed in the field of soft robotics. The soft jig has a bag covered with a malleable silicone membrane, which has high friction, elong

René Schuster, Christian Unger, Didier Stricker

Contrary to the ongoing trend in automotive applications towards usage of more diverse and more sensors, this work tries to solve the complex scene flow problem under a monocular camera setup, i.e. using a single sensor. Towards this end, we exploit the latest achievements in single image depth estimation, optical flow, and sparse-to-dense interpolation and

Ran Long, Christian Rauch, Tianwei Zhang, Vladimir Ivan

This work presents a novel RGB-D SLAM approach to simultaneously segment, track and reconstruct the static background and large dynamic rigid objects that can occlude major portions of the camera view. Previous approaches treat dynamic parts of a scene as outliers and are thus limited to a small amount of changes in the scene, or rely on prior information fo

Tommaso Perani, Marco Liscidini

We theoretically study light propagation in guided Bloch surface waves (BSWs) supported by photonic crystal ridges. We demonstrate that low propagation losses can be achieved just by a proper design of the multilayer to obtain photonic band gaps for both light polarizations. We present a design strategy based on a Fourier analysis that allows one to obtain i

Victor J. Exposito Jimenez, Christian Schwarzl, Szilard Josvai

Since an automotive driving vehicle is controlled by Advanced Driver-Assistance Systems (ADAS) / Automated Driving (AD) functions, the selected sensors for the perception process become a key component of the system. Therefore, the necessity of ensuring precise data is crucial. But the correctness of the data is not the only part that has to be ensured, the

KwanTo Lai, Daniel Finkelstein-Shapiro, Arnaud Devos, Pierre-Adrien Mante

In recent years, the manipulation of Fano resonances in the time domain has unlocked deep insights into a broad spectrum of systems' coherent dynamics. Here, inelastic scattering of light with coherent acoustic phonons is harnessed to achieve complex Fano resonances. The sudden change of phonon momentum during reflection leads to a transition from anti-Stoke

A. Micera, A. N. Zhukov, R. A. López, M. E. Innocenti

We present results of two-dimensional fully kinetic Particle-In-Cell simulation in order to shed light on the role of whistler waves in the scattering of strahl electrons and in the heat flux regulation in the solar wind. We model the electron velocity distribution function as initially composed of core and strahl populations as typically encountered in the

Patrick Delorme

We establish the analog for real spherical varieties of the Scattering Theorem of Sakellaridis and Venkatesh (\cite{SV}, Theorem 7.3.1) for p-adic spherical varieties. We use properties of the Harish-Chandra homomorphism of Knop for invariant differential operators of the variety, special coverings of the variety and spectral projections.

Sang-Eon Lee, Myeong-jun Oh, Sanghyun Ji, Jinsu Kim

With the emergence of Dirac fermion physics in the field of condensed matter, magnetic quantum oscillations (MQOs) have been used to discern the topology of orbits in Dirac materials. However, many previous researchers have relied on the single-orbit Lifshiftz-Kosevich formula, which overlooks the significant effect of degenerate orbits on MQOs. Since the si

Ziyan Song

The p-adic Simpson correspondence due to Faltings is a p-adic analogue of non-abelian Hodge theory. The following is the main result of this article: The correspondence for line bundles can be enhanced to a rigid analytic morphism of moduli spaces under certain smallness conditions. In the complex setting, Simpson shows that there is a complex analytic morph

Michael Hecht, Krzysztof Gonciarz, Jannik Michelfeit, Vladimir Sivkin

We extend Newton and Lagrange interpolation to arbitrary dimensions. The core contribution that enables this is a generalized notion of non-tensorial unisolvent nodes, i.e., nodes on which the multivariate polynomial interpolant of a function is unique. By validation, we reach the optimal exponential Trefethen rates for a class of analytic functions, we term

Zeinab Rezaei

Interaction between dark matter and dark energy as one of not completely solved problems in cosmology has been studied extensively. This interaction affects the cosmic structures. In this regard, the shape of cosmic voids can be influenced by the dark matter and dark energy interaction. Here, employing the dynamical dark energy model constrained by the obser

Xichao Zhang, Jing Xia, Motohiko Ezawa, Oleg A. Tretiakov

We show a topological spin texture called "bimeronium" in magnets with in-plane magnetization. It is a topological counterpart of skyrmionium in perpendicularly magnetized magnets and can be seen as a combination of two bimerons with opposite topological charges. We report the static structure and spin-orbit-torque-induced dynamics of an isolated bimeronium

Chan Young Park, Xinru Yan, Anjalie Field, Yulia Tsvetkov

Specific lexical choices in narrative text reflect both the writer's attitudes towards people in the narrative and influence the audience's reactions. Prior work has examined descriptions of people in English using contextual affective analysis, a natural language processing (NLP) technique that seeks to analyze how people are portrayed along dimensions of p

Amit Shrestha, Katsuhiko Higuchi, Shunsuke Yoshida, Masahiko Higuchi

Graphene is a highly promising material in the field of spin electronics. Recent experiments on electron spin resonance have observed a reduction in the g-factor of graphene. In our previous paper [J. Phys. Soc. Jpn. 88, 094707 (2019)], we demonstrated that one of sources for this reduction is the diamagnetic property of graphene. However, the diamagnetic pr

Mohammad Golshani, Saharon Shelah

Answering a question of Harrington, we show that there exists a proper forcing notion, which adds a minimal real $\eta \in \prod_{i<\omega} n^*_i$, which is eventually different from any old real in $\prod_{i<\omega} n^*_i$, where the sequence $\langle n^*_i \mid i<\omega \rangle$ grows slowly.

Puhai Yang, Heyan Huang, Xianling Mao

Scalability for handling unknown slot values is a important problem in dialogue state tracking (DST). As far as we know, previous scalable DST approaches generally rely on either the candidate generation from slot tagging output or the span extraction in dialogue context. However, the candidate generation based DST often suffers from error propagation due to

Steffen Borgwardt, Cornelius Brand, Andreas Emil Feldmann, Martin Koutecký

Linear programs (LPs) can be solved by polynomially many moves along the circuit direction improving the objective the most, so-called deepest-descent steps (dd-steps). Computing these steps is NP-hard (De Loera et al., arXiv, 2019), a consequence of the hardness of deciding the existence of an optimal circuit-neighbor (OCNP) on LPs with non-unique optima. W

Yingjie Li, Ye Xu, Yan Sun, Ji Yang

To date, few studies have focused on protostellar outflow feedback at scales larger than several parsecs. To address this paucity of research, we investigate the effects of feedback from CO outflow candidates on their parent clouds over $\sim$ 110 deg$^2$ toward the W3/4/5 complex and its surroundings. Our search identified 265 $^{13}$CO clouds with radii be

Neill Lambert, Tarun Raheja, Simon Cross, Paul Menczel

The "hierarchical equations of motion" (HEOM) method is a powerful exact numerical approach to solve the dynamics and find the steady-state of a quantum system coupled to a non-Markovian and non-perturbative environment. Originally developed in the context of physical chemistry, it has also been extended and applied to problems in solid-state physics, optics

Jianlei Chi, Yu Qu, Ting Liu, Qinghua Zheng

Software vulnerabilities are now reported at an unprecedented speed due to the recent development of automated vulnerability hunting tools. However, fixing vulnerabilities still mainly depends on programmers' manual efforts. Developers need to deeply understand the vulnerability and try to affect the system's functions as little as possible. In this paper, w

Yavar Kian, Katya Krupchyk, Gunther Uhlmann

We show that the knowledge of the Dirichlet-to-Neumann maps given on an arbitrary open non-empty portion of the boundary of a smooth domain in $\mathbb{R}^n$, $n\ge 2$, for classes of semilinear and quasilinear conductivity equations, determines the nonlinear conductivities uniquely. The main ingredient in the proof is a certain $L^1$-density result involvin

Alexander Premet, Lewis Topley

Let $G$ be connected reductive algebraic group defined over an algebraically closed field of characteristic $p > 0$ and suppose that $p$ is a good prime for the root system of $G$, the derived subgroup of $G$ is simply connected and the Lie algebra $\mathfrak{g} = \operatorname{Lie}(G)$ admits a non-degenerate Ad$(G)$-invariant symmetric bilinear form. Given

Vamoua Yachongka, Hideki Yagi, Yasutada Oohama

In the present paper, we investigate the fundamental trade-off of identification, secrecy, storage, and privacy-leakage rates in biometric identification systems for hidden or remote Gaussian sources. We introduce a technique for deriving the capacity region of these rates by converting the system to one where the data flow is in one-way direction. Also, we

Yani Feng, Kejun Tang, Lianxing He, Pingqiang Zhou

This work proposes a novel tensor train random projection (TTRP) method for dimension reduction, where pairwise distances can be approximately preserved. Our TTRP is systematically constructed through a tensor train (TT) representation with TT-ranks equal to one. Based on the tensor train format, this new random projection method can speed up the dimension r

Vladimir Rovenski

A pseudo-Riemannian manifold endowed with $k>2$ orthogonal complementary distributions (called a Riemannian almost multi-product structure) appears in such topics as multiply warped products, the webs composed of several foliations, Dupin hypersurfaces and in stu\-dies of the curvature and Einstein equations. In this article, we consider the following two pr

Soonwook Kim, Donggyu B. Sohn, Christopher W. Peterson, Gaurav Bahl

We demonstrate a synthetic Hall effect for light, using an acousto-optically modulated nanophotonic resonator chain. To produce this effect, we simultaneously generate the required synthetic electric field using temporal modulation, and the required synthetic magnetic field using spatial modulation of the resonator chain. We show how the combination of these

Lutz Schimansky-Geier, Benjamin Lindner, Sebastian Milster, Alexander B. Neiman

We propose a model for demixing of two species by assuming a density-dependent effective diffusion coefficient of the particles. Both sorts of microswimmers diffuse as active overdamped Brownian particles with a noise intensity that is determined by the surrounding density of the respective other species within a sensing radius $r_s$. A higher concentration

Yiping Guo, Howard D. Bondell

Probabilistic principal component analysis (PPCA) is a probabilistic reformulation of principal component analysis (PCA), under the framework of a Gaussian latent variable model. To improve the robustness of PPCA, it has been proposed to change the underlying Gaussian distributions to multivariate $t$-distributions. Based on the representation of $t$-distrib

Matthew Baumgart, Raman Sundrum

In-In perturbation theory is a vital tool for cosmology and nonequilibrium physics. Here, we reconcile an apparent conflict between two of its important aspects with particular relevance to De Sitter/inflationary contexts: (i) the need to slightly deform unitary time evolution with an i*epsilon prescription that projects the free (&#34;Bunch-Davies&#34;) vac

Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi

Embedding learning of categorical features (e.g. user/item IDs) is at the core of various recommendation models including matrix factorization and neural collaborative filtering. The standard approach creates an embedding table where each row represents a dedicated embedding vector for every unique feature value. However, this method fails to efficiently han

Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He

Representation learning on user-item graph for recommendation has evolved from using single ID or interaction history to exploiting higher-order neighbors. This leads to the success of graph convolution networks (GCNs) for recommendation such as PinSage and LightGCN. Despite effectiveness, we argue that they suffer from two limitations: (1) high-degree nodes

Keiya Ishiguro, Tatsuo Kobayashi, Hajime Otsuka

We explore the geometrical origin of CP and the spontaneous CP violation in Calabi-Yau compactifications. We find that the CP symmetry is identified with an outer automorphism of the symplectic modular group in the large complex structure regime of Calabi-Yau threefolds, thereby enlarging the symplectic modular group to their semidirect product group. The sp

Luzhe Huang, Yilin Luo, Yair Rivenson, Aydogan Ozcan

Volumetric imaging of samples using fluorescence microscopy plays an important role in various fields including physical, medical and life sciences. Here we report a deep learning-based volumetric image inference framework that uses 2D images that are sparsely captured by a standard wide-field fluorescence microscope at arbitrary axial positions within the s

Ryuichiro Akaho, Akira Harada, Hiroki Nagakura, Kohsuke Sumiyoshi

We develop a neutrino transfer code for core-collapse simulations, that directly solves the multidimensional Boltzmann equations in full general relativity. We employ the discrete ordinate method, which discretizes the six dimensional phase space. The code is an extension of our special relativistic code coupled to a Newtonian hydrodynamics code, which is cu

Kyu-Hyun Chae, Mariangela Bernardi, Helena Dominguez Sanchez, Ravi K. Sheth

Dark matter phenomena in rotationally supported galaxies exhibit a characteristic acceleration scale of $g_\dagger \approx 1.2\times 10^{-10}$ m s$^{-2}$. Whether this acceleration is a manifestation of a universal scale, or merely an emergent property with an intrinsic scatter, has been debated in the literature. Here we investigate whether a universal acce

Shubhra Kanti Karmaker Santu, Md. Mahadi Hassan, Micah J. Smith, Lei Xu

As big data becomes ubiquitous across domains, and more and more stakeholders aspire to make the most of their data, demand for machine learning tools has spurred researchers to explore the possibilities of automated machine learning (AutoML). AutoML tools aim to make machine learning accessible for non-machine learning experts (domain experts), to improve t

Monika Sinha, Manoj Ghosh

The magnetic field associated with neutron stars is generally believed to be threaded inside the star. In the presence of a magnetic field, the plasma present in the interior of the star goes through several processes that lead to magnetic field evolution. It is thought that magnetar activities are mainly due to field decay. The most important process of fie

Yoshitaka Hatta, Bo-Wen Xiao, Feng Yuan, Jian Zhou

We investigate the effect of soft gluon radiations on the azimuthal angle correlation between the total and relative momenta of two jets in inclusive and exclusive dijet processes. We show that the final state effect induces a sizable $\cos(2\phi)$ anisotropy due to gluon emissions near the jet cones. The phenomenological consequences of this observation are

Jerome Wolfman, Beatrice Negulescu, Antoine Ruyter, Ndioba Niang

In this chapter we will describe a new development of combinatorial pulsed laser deposition (CPLD) which targets the exploration of interface libraries. The idea is to modulate continuously the composition of interfaces on a few atomic layers in order to alter their functional properties. This unique combinatorial synthesis of interfaces is possible due to v

Sean McBane, Youngsoo Choi

Lattice-type structures can provide a combination of stiffness with light weight that is desirable in a variety of applications. Design optimization of these structures must rely on approximations of the governing physics to render solution of a mathematical model feasible. In this paper, we propose a topology optimization (TO) formulation that approximates

Carla Farsi, Emily Proctor, Christopher Seaton

Eilers et al. have recently completed the geometric classification of unital graph $C^\ast$-algebras up to Morita equivalence using a set of moves on the corresponding digraphs. We explore the question of whether these moves preserve the nonzero elements of the spectrum of a finite digraph, which in this paper is allowed to have loops and parallel edges. We