October 2020 arXiv papers — page 51

Maxwell X. Cai, Jeroen Bédorf, Vikram A. Saletore, Valeriu Codreanu

Galaxy mergers, the dynamical process during which two galaxies collide, are among the most spectacular phenomena in the Universe. During this process, the two colliding galaxies are tidally disrupted, producing significant visual features that evolve as a function of time. These visual features contain valuable clues for deducing the physical properties of

Dominik Hafemeyer, Florian Mannel

We study a PDE-constrained optimal control problem that involves functions of bounded variation as controls and includes the TV seminorm of the control in the objective. We apply a path-following inexact Newton method to the problems that arise from smoothing the TV seminorm and adding an $H^1$ regularization. We prove in an infinite-dimensional setting that

Syed Muhammad Kumail Raza, Juan Caballero

Identifying threats in a network traffic flow which is encrypted is uniquely challenging. On one hand it is extremely difficult to simply decrypt the traffic due to modern encryption algorithms. On the other hand, passing such an encrypted stream through pattern matching algorithms is useless because encryption ensures there aren't any. Moreover, evaluating

Soukaina Zayat, Salman Ghazal

Erd\"{o}s-Hajnal conjecture states that for every undirected graph $H$ there exists $ \epsilon(H) > 0 $ such that every undirected graph on $ n $ vertices that does not contain $H$ as an induced subgraph contains a clique or a stable set of size at least $ n^{\epsilon(H)} $. This conjecture has a directed equivalent version stating that for every tournament

Soukaina Zayat, Salman Ghazal

The celebrated Erd\"{o}s-Hajnal conjecture states that for every undirected graph $H$ there exists $ \epsilon(H) > 0 $ such that every undirected graph on $ n $ vertices that does not contain $H$ as an induced subgraph contains a clique or a stable set of size at least $ n^{\epsilon(H)} $. This conjecture has a directed equivalent version stating that for ev

Kexin Lv, Fan He, Xiaolin Huang, Jie Yang

Nowadays, more and more datasets are stored in a distributed way for the sake of memory storage or data privacy. The generalized eigenvalue problem (GEP) plays a vital role in a large family of high-dimensional statistical models. However, the existing distributed method for eigenvalue decomposition cannot be applied in GEP for the divergence of the empirica

Yilong Zhang

A pair of disjoint lines on a smooth cubic threefold determines an irreducible component of the Hilbert scheme. We prove that this component is smooth and isomorphic to the blow-up of the symmetric product of Fano varieties of lines on the diagonal. We also study its relation to the geometry of lines and singularities on the hyperplane sections and its relat

Soukaina Zayat, Salman Ghazal

A celebrated unresolved conjecture of Erd\"{o}s and Hajnal states that for every undirected graph $H$ there exists $ \epsilon(H) > 0 $ such that every undirected graph on $ n $ vertices that does not contain $H$ as an induced subgraph contains a clique or a stable set of size at least $ n^{\epsilon(H)} $. The conjecture has a directed equivalent version stat

Lida Kanari, Adélie Garin, Kathryn Hess

Methods of topological data analysis have been successfully applied in a wide range of fields to provide useful summaries of the structure of complex data sets in terms of topological descriptors, such as persistence diagrams. While there are many powerful techniques for computing topological descriptors, the inverse problem, i.e., recovering the input data

Miao-Hsuan Chien, Mostafa M. Shawrav, Kurt Hingerl, Philipp Taus

The determination of the chemical content is crucial for the quality control in high-precision device fabrication and advanced process development. For reliable chemical composition characterization, certain interaction volume of the target material is necessary for conventional techniques such as energy-dispersive X-ray spectroscopy (EDX) and electron energ

Gaetano Perone

Coronavirus disease (COVID-19) is a severe ongoing novel pandemic that has emerged in Wuhan, China, in December 2019. As of October 13, the outbreak has spread rapidly across the world, affecting over 38 million people, and causing over 1 million deaths. In this article, I analysed several time series forecasting methods to predict the spread of COVID-19 sec

L. S. Kimpton, B. J. Walker, C. L. Hall, B. Bintu

The eye grows during childhood to position the retina at the correct distance behind the lens to enable focused vision, a process called emmetropization. Animal studies have demonstrated that this growth process is dependent upon visual stimuli, while genetic and environmental factors that affect the likelihood of developing myopia have also been identified.

Unai Zabala, Igor Rodriguez, José María Martínez-Otzeta, Itziar Irigoien

Social robot capabilities, such as talking gestures, are best produced using data driven approaches to avoid being repetitive and to show trustworthiness. However, there is a lack of robust quantitative methods that allow to compare such methods beyond visual evaluation. In this paper a quantitative analysis is performed that compares two Generative Adversar

Lennard Böselt, Moritz Thürlemann, Sereina Riniker

Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations have been developed to simulate molecular systems, where an explicit description of changes in the electronic structure is necessary. However, QM/MM MD simulations are computationally expensive compared to fully classical simulations as all valence electrons are treated explici

Marek W. Rupniewski

Reconstruction of undersampled periodic signals of unknown period is an important signal processing operation. It is especially difficult operation when the sequences of samples are short and no information on the inter-sequence time distances is given. For such a case, there exist some algorithms that allow for approximation of the sampled signal. However,

Mohammad Mahmudur Rahman Khan, Md. Abu Bakr Siddique, Shadman Sakib, Anas Aziz

Temperature and rainfall have a significant impact on economic growth as well as the outbreak of seasonal diseases in a region. In spite of that inadequate studies have been carried out for analyzing the weather pattern of Bangladesh implementing the artificial neural network. Therefore, in this study, we are implementing a Long Short-term Memory (LSTM) mode

Tongqing Zhai, Yiming Li, Ziqi Zhang, Baoyuan Wu

Speaker verification has been widely and successfully adopted in many mission-critical areas for user identification. The training of speaker verification requires a large amount of data, therefore users usually need to adopt third-party data ($e.g.$, data from the Internet or third-party data company). This raises the question of whether adopting untrusted

Frederic Bouquet, Giovanni Organtini, Amel Kolli, Julien Bobroff

We created an introductory physics activity for undergrad students consisting in measuring by different methods the same physical quantity. It allows to confront students with questions of uncertainty, precision, and model versus theory. The aim was to measure the height of a building using only a smartphone and everyday low-cost equipment. We designed 61 me

Changzhen Ji, Xin Zhou, Conghui Zhu, Tiejun Zhao

The multi-role judicial debate composed of the plaintiff, defendant, and judge is an important part of the judicial trial. Different from other types of dialogue, questions are raised by the judge, The plaintiff, plaintiff's agent defendant, and defendant's agent would be to debating so that the trial can proceed in an orderly manner. Question generation is

Ehsan Hatefi, Adrien Kuntz

Gravitational critical collapse in the Einstein-axion-dilaton system is known to lead to continuous self-similar solutions characterized by the Choptuik critical exponent $\gamma$. We complete the existing literature on the subject by computing the linear perturbation equations in the case where the axion-dilaton system assumes a parabolic form. Next, we sol

Edward J Oughton, William Lehr, Konstantinos Katsaros, Ioannis Selinis

In recent years, significant attention has been directed toward the fifth generation of wireless broadband connectivity known as `5G`, currently being deployed by Mobile Network Operators. Surprisingly, there has been considerably less attention paid to `Wi-Fi 6`, the new IEEE 802.1ax standard in the family of Wireless Local Area Network technologies with fe

Junghoon Seo, Joon Suk Huh

Partial label learning (PLL) is a class of weakly supervised learning where each training instance consists of a data and a set of candidate labels containing a unique ground truth label. To tackle this problem, a majority of current state-of-the-art methods employs either label disambiguation or averaging strategies. So far, PLL methods without such techniq

R. Adhikari, K. Doesinger, P. Linder, B. Faina

The advances in the fields of scanning probe microscopy, scanning tunneling spectroscopy, point contact spectroscopy and point contact Andreev reflection spectroscopy to study the properties of conventional and quantum materials at cryogenic conditions have prompted the development of nanopositioners and nanoscanners with enhanced spatial resolution. Piezoel

Philipp Lücke, Philipp Schlicht

We use generalizations of concepts from descriptive set theory to study combinatorial objects of uncountable regular cardinality, focussing on higher Kurepa trees and the representation of the sets of cofinal branches through such trees as continuous images of function spaces. For different types of uncountable regular cardinals $\kappa$, our results provide

Alireza Taghizadeh, Kristian S. Thygesen, Thomas G. Pedersen

Nonlinear optical (NLO) phenomena such as harmonic generation, Kerr, and Pockels effects are of great technological importance for lasers, frequency converters, modulators, switches, etc. Recently, two-dimensional (2D) materials have drawn significant attention due to their strong and unique NLO properties. Here, we describe an efficient first-principles wor

Yuya Mino

The LHC is expected to increase its center-of-mass energy from 13 TeV to 14 TeV for Run 3 scheduled from 2022 to 2024. After Run 3, upgrades for the High-Luminosity-LHC (HL-LHC) programme are planned and the operation will start in 2027, increasing the instantaneous luminosity to 5.0 -- 7.5 times its nominal luminosity. Continuous upgrades of the ATLAS trigg

Miika Leinonen, Leena Salmela

The extraction of k-mers from sequencing reads is an important task in many bioinformatics applications, such as all DNA sequence analysis methods based on de Bruijn graphs. These methods tend to be more accurate when the used k-mers are unique in the analyzed DNA, and thus the use of longer k-mers is preferred. When the read lengths of short read sequencing

Thomas Van Riet

In the context of the Weak Gravity Conjecture the notion of quasi-extremality for black holes and branes was recently defined as the property of having either vanishing horizon size or surface gravity. It was derived that such objects obey a no-force condition. In this short note I present a simplified derivation that is essentially present in the formalism

Alessio Emanuele Biondo, Giulio Burgio, Alessandro Pluchino, Damiano Puglisi

In this paper we present a simplified model of a proportional taxation system where citizens decide whether to pay taxes or evade them. We initially derive a dynamic equation for the fraction of evaders and then present both its critical points and equilibrium stable states for a well-mixed population and for a fixed audit probability. Our theoretical predic

Anže Božič, Matej Kanduč

A large number of infectious diseases is transmitted by respiratory droplets. How long these droplets persist in the air, how far they can travel, and how long the pathogens they might carry survive are all decisive factors for the spread of droplet-borne diseases. The subject is extremely multifaceted and its aspects range across different disciplines, yet

Benjamin Hogan, William Lotko, Kevin Pham

Motivated by low-altitude cusp observations of small-scale (~ 1 km) field-aligned currents (SSFACs) interpreted as ionospheric Alfv\'en resonator modes, we investigated the effects of Alfv\'en wave energy deposition on thermospheric upwelling and the formation of air density enhancements in and near the cusp. Such density enhancements were commonly observed

Andre Alho, Takanori Sakai, Simon Oh, Cheng Cheng

Time-sensitive parcel deliveries, shipments requested for delivery in a day or less, are an increasingly important research subject. It is challenging to deal with these deliveries from a carrier perspective since it entails additional planning constraints, preventing an efficient consolidation of deliveries which is possible when demand is well known in adv

Alejandro Martín-Crespo, Sergio Saludes-Rodil, Enrique Baeyens

Load flexibility management is a promising approach to face the problem of balancing generation and demand in electrical grids. This problem is becoming increasingly difficult due to the variability of renewable energies. Thermostatically controlled loads can be aggregated and managed by a virtual battery, and they provide a cost-effective and efficient alte

Renju S. Mathew, Roshan O'Donnell, Danielle Pizzey, Ifan G. Hughes

We present a novel solution to automated beam alignment optimization. This device is based on a Raspberry Pi computer, stepper motors, commercial optomechanics and electronic devices, and the open source machine learning algorithm M-LOOP. We provide schematic drawings for the custom hardware necessary to operate the device and discuss diagnostic techniques t

Dario Cordero-Erausquin, Alexandros Eskenazis

Let $\mathscr{C}_n=\{-1,1\}^n$ be the discrete hypercube equipped with the uniform probability measure $\sigma_n$. Talagrand's influence inequality (1994) asserts that there exists $C\in(0,\infty)$ such that for every $n\in\mathbb{N}$, every function $f:\mathscr{C}_n\to\mathbb{C}$ satisfies $$\mathrm{Var}_{\sigma_n}(f) \leq C \sum_{i=1}^n \frac{\|\partial_if

Sergey Khoperskov, Igor Zinchenko, Branislav Avramov, Sergey Khrapov

Modern galaxy formation theory suggests that the misalignment between stellar and gaseous components usually results from an external gas accretion and/or interaction with other galaxies. The extreme case of the kinematic misalignment is demonstrated by so-called galaxies with counterrotation that possess two distinct components rotating in opposite directio

Marco Molari, Rémi Monasson, Simona Cocco

Affinity Maturation (AM) is the process through which the immune system is able to develop potent antibodies against new pathogens it encounters, and is at the base of the efficacy of vaccines. At its core AM is analogous to a Darwinian evolutionary process, where B-cells mutate and are selected on the base of their affinity for an Antigen (Ag), and Ag avail

David Criens

We prove a dual Yamada-Watanabe theorem for one-dimensional stochastic differential equations driven by quasi-left continuous semimartingales with independent increments. In particular, our result covers stochastic differential equations driven by (time-inhomogeneous) Levy processes. More precisely, we prove that weak uniqueness, i.e. uniqueness in law, impl

Navita Goyal, Balaji Vasan Srinivasan, Anandhavelu Natarajan, Abhilasha Sancheti

Style transfer has been widely explored in natural language generation with non-parallel corpus by directly or indirectly extracting a notion of style from source and target domain corpus. A common shortcoming of existing approaches is the prerequisite of joint annotations across all the stylistic dimensions under consideration. Availability of such dataset

Takuya Takarada, Bun'ei Sato, Masashi Omiya, Yasunori Hori

We report radial-velocity search for short-period planets in the Pleiades open cluster. We observed 30 Pleiades member stars at the Okayama Astrophysical Observatory (OAO) with High Dispersion Echelle Spectrograph (HIDES). To evaluate and mitigate the effects of stellar activity on radial-velocity measurements, we computed four activity indicators (FWHM, $V_

G. Cavoto, G. Chiarello, M. Hildebrandt, A. Hofer

An automatic target monitoring method based on photographs taken by a CMOS photo-camera has been developed for the MEG II detector. The technique could be adapted for other fixed-target experiments requiring good knowledge of their target position to avoid biases and systematic errors in measuring the trajectories of the outcoming particles. A CMOS-based, hi

Tao Lu, Yuanzhi Wang, Yanduo Zhang, Yu Wang

Recently, convolutional neural networks (CNNs) have been widely employed to promote the face hallucination due to the ability to predict high-frequency details from a large number of samples. However, most of them fail to take into account the overall facial profile and fine texture details simultaneously, resulting in reduced naturalness and fidelity of the

Jan Christian Blaise Cruz, Jose Kristian Resabal, James Lin, Dan John Velasco

Transformers represent the state-of-the-art in Natural Language Processing (NLP) in recent years, proving effective even in tasks done in low-resource languages. While pretrained transformers for these languages can be made, it is challenging to measure their true performance and capacity due to the lack of hard benchmark datasets, as well as the difficulty

Theodoros Papanikolaou, Vincent Vennin, David Langlois

Ultra-light primordial black holes, with masses $m_\mathrm{PBH}<10^9\mathrm{g}$, evaporate before big-bang nucleosynthesis and can therefore not be directly constrained. They can however be so abundant that they dominate the universe content for a transient period (before reheating the universe via Hawking evaporation). If this happens, they support large co

J. Kalt, M. Sternik, B. Krause, I. Sergueev

Self-organized silicide nanowires are considered as main building blocks of future nanoelectronics and have been intensively investigated. In nanostructures, the lattice vibrational waves (phonons) deviate drastically from those in bulk crystals, which gives rise to anomalies in thermodynamic, elastic, electronic, and magnetic properties. Hence, a thorough u

Alekos Cecchin

We examine mean field control problems on a finite state space, in continuous time and over a finite time horizon. We characterize the value function of the mean field control problem as the unique viscosity solution of a Hamilton-Jacobi-Bellman equation in the simplex. In absence of any convexity assumption, we exploit this characterization to prove converg

Mengyan Zhang, Cheng Soon Ong

We consider a variant of the best arm identification task in stochastic multi-armed bandits. Motivated by risk-averse decision-making problems, our goal is to identify a set of $m$ arms with the highest $\tau$-quantile values within a fixed budget. We prove asymmetric two-sided concentration inequalities for order statistics and quantiles of random variables

Yao Shi, Hui Bu, Xin Xu, Shaoji Zhang

In this paper, we present AISHELL-3, a large-scale and high-fidelity multi-speaker Mandarin speech corpus which could be used to train multi-speaker Text-to-Speech (TTS) systems. The corpus contains roughly 85 hours of emotion-neutral recordings spoken by 218 native Chinese mandarin speakers. Their auxiliary attributes such as gender, age group and native ac

P. Piekarz, D. Legut, E. Baldini, C. A. Belvin

Using density functional theory, we study the lattice dynamical properties of magnetite (Fe$_3$O$_4$) in the high-temperature cubic and low-temperature monoclinic phases. The calculated phonon dispersion curves and phonon density of states are compared with the available experimental data obtained by inelastic neutron, inelastic x-ray, and nuclear inelastic

Amit Kumar Trivedi, Jasvinder Pal Singh

The study identifies a clear evolution from traditional methods to more advanced machine learning approaches. Current algorithms face persistent challenges, including degraded image quality, damaged ridge structures, and background noise, which impact performance. To overcome these limitations, future research must focus on developing efficient algorithms wi

Boyu Zhou, Yichen Zhang, Xinyi Chen, Shaojie Shen

Autonomous exploration is a fundamental problem for various applications of unmanned aerial vehicles. Existing methods, however, were demonstrated to insufficient exploration rate, due to the lack of efficient global coverage, conservative motion plans and low decision frequencies. In this paper, we propose FUEL, a hierarchical framework that can support Fas

Daniel Murfet, Susan Wei, Mingming Gong, Hui Li

In singular models, the optimal set of parameters forms an analytic set with singularities and classical statistical inference cannot be applied to such models. This is significant for deep learning as neural networks are singular and thus "dividing" by the determinant of the Hessian or employing the Laplace approximation are not appropriate. Despite its pot

Yangjing Zhang, Kim-Chuan Toh, Defeng Sun

We consider the problem of learning a graph under the Laplacian constraint with a non-convex penalty: minimax concave penalty (MCP). For solving the MCP penalized graphical model, we design an inexact proximal difference-of-convex algorithm (DCA) and prove its convergence to critical points. We note that each subproblem of the proximal DCA enjoys the nice pr

Costanza Ronchi, Federico Soria, Lorenzo Ferraro, Silvana Botti

Donor-modified TiO 2 nanoparticles are interesting hybrid systems shifting the absorption edge of this semiconductor from the ultra-violet to the visible or infrared light spectrum, which is a benefit for several applications ranging from photochemistry, photocatalysis, photovoltaics, or photodynamic therapy. Here, we investigate the absorption properties of

S. Zurita-Zurita, Francisco J. Escribano, J. Sáez-Landete, J. A. Rodríguez-Manfredi

In the present article we analyze data from two temperature sensors of the Mars Science Laboratory, which has been active in Mars since August 2012. Temperature measurements received from the rover are noisy and must be processed and validated before being delivered to the scientific community. Currently, a simple Moving Average (MA) filter is used to perfor

Anthony G. O'Farrell, Gavin Armstrong

Let $k$ be a natural number. We consider $k$-times continuously-differentiable real-valued functions $f:E\to\mathbb{R}$, where $E$ is some interval on the line having positive length. For $0<\alpha<1$ let $I_\alpha(f)$ denote the set of values $y\in\mathbb{R}$ whose preimage $f^{-1}(y)$ has Hausdorff dimension $\dim f^{-1}(y) \ge \alpha$. We consider how lar

D. Valentinis, J. Zaanen, D. van der Marel

A highlight of Fermi-liquid phenomenology, as explored in neutral $^3$He, is the observation that in the collisionless regime shear stress propagates as if one is dealing with the transverse phonon of a solid. The existence of this $"$transverse zero sound$"$ requires that the quasiparticle mass enhancement exceeds a critical value. Could such a propagating

Fredrik Hellström, Giuseppe Durisi

We present a framework to derive bounds on the test loss of randomized learning algorithms for the case of bounded loss functions. Drawing from Steinke & Zakynthinou (2020), this framework leads to bounds that depend on the conditional information density between the the output hypothesis and the choice of the training set, given a larger set of data samples

Z. L. Wen, J. L. Han

We first present a catalogue of photometric redshifts for 14.68 million galaxies derived from the 7-band photometric data of Hyper Suprime-Cam Subaru Strategic Program and the Wide-field Infrared Survey Explorer using the nearest-neighbour algorithm. The redshift uncertainty is about 0.024 for galaxies of z<0.7, and steadily increases with redshift to about

Felix I. Stamm, Leonie Neuhäuser, Florian Lemmerich, Michael T. Schaub

Network analysis provides powerful tools to learn about a variety of social systems. However, most analyses implicitly assume that the considered relational data is error-free, reliable and accurately reflects the system to be analysed. Especially if the network consists of multiple groups, this assumption conflicts with a range of systematic biases, measure

Jee-weon Jung, Hee-Soo Heo, Ha-Jin Yu, Joon Son Chung

This work presents a novel back-end framework for speaker verification using graph attention networks. Segment-wise speaker embeddings extracted from multiple crops within an utterance are interpreted as node representations of a graph. The proposed framework inputs segment-wise speaker embeddings from an enrollment and a test utterance and directly outputs

Xun Liang, Qingfeng Guan, Keith C. Clarke, Shishi Liu

Cellular Automata (CA) are widely used to model the dynamics within complex land use and land cover (LULC) systems. Past CA model research has focused on improving the technical modeling procedures, and only a few studies have sought to improve our understanding of the nonlinear relationships that underlie LULC change. Many CA models lack the ability to simu

Yoshinori Kurimoto

Particle tracking simulations with space charge effects are very important for high-intensity proton rings. Since they include not only Hamilton mechanics of a single particle but constructing charge densities and solving Poisson equations to obtain the electromagnetic field due to the space charge, they are extremely time-consuming. We have newly developed

Arpit Merchant, Michael Mathioudakis

The task of node classification is to infer unknown node labels, given the labels for some of the nodes along with the network structure and other node attributes. Typically, approaches for this task assume homophily, whereby neighboring nodes have similar attributes and a node's label can be predicted from the labels of its neighbors or other proximate (i.e

Zifei Zhang, Kai Qiao, Jian Chen, Ningning Liang

Though deep neural networks perform challenging tasks excellently, they are susceptible to adversarial examples, which mislead classifiers by applying human-imperceptible perturbations on clean inputs. Under the query-free black-box scenario, adversarial examples are hard to transfer to unknown models, and several methods have been proposed with the low tran

Qinyuan Wu, Yong Deng, Neal Xiong

Negation operation is important in intelligent information processing. Different with existing arithmetic negation, an exponential negation is presented in this paper. The new negation can be seen as a kind of geometry negation. Some basic properties of the proposed negation is investigated, we find that the fix point is the uniform probability distribution.

Masao Iwamatsu

As the simplest model of transition between the superhydrophobic Cassie-Baxter (CB) and Wenzel (W) states of a macroscopic droplet sitting on a microscopically rough or corrugated substrate, a substrate whose surface is covered by identical truncated or inverted truncated conical pores is considered. The free energy landscapes of the intrusion and extrusion

Manuel Kaufmann, Emre Aksan, Jie Song, Fabrizio Pece

In this paper we propose a convolutional autoencoder to address the problem of motion infilling for 3D human motion data. Given a start and end sequence, motion infilling aims to complete the missing gap in between, such that the filled in poses plausibly forecast the start sequence and naturally transition into the end sequence. To this end, we propose a si

James Liley, Samuel R Emerson, Bilal A Mateen, Catalina A Vallejos

Machine learning is increasingly being used to generate prediction models for use in a number of real-world settings, from credit risk assessment to clinical decision support. Recent discussions have highlighted potential problems in the updating of a predictive score for a binary outcome when an existing predictive score forms part of the standard workflow,

Anna Valette, Guillaume Valette

Let $\Omega$ be a subanalytic bounded open subset of $\mathbb{R}^n$, with possibly singular boundary. We show that given $p\in [1,\infty)$, there is a constant $C$ such that for any $u\in W^{1,p}(\Omega)$ we have $||u-u_{\Omega}||_{L^p} \le C||\nabla u||_{L^p},$ where we have set $u_{\Omega}:=\frac{1}{|\Omega|}\int_{\Omega} u.$

Zihao Wu

We study the open string pair production between two D3 branes, which will give rise to similar effect as Schwinger pair production for observers on one of the D3 branes. The D3 branes are placed parallel at a distance, and they are carrying world-volume electromagnetic fluxes that takes general form. We derive the pair production rate by computing the inter

Makoto Fujiwara, Taishi Kurahashi

We refine the arithmetical hierarchy of various classical principles by finely investigating the derivability relations between these principles over Heyting arithmetic. We mainly investigate some restricted versions of the law of excluded middle, de Morgan's law, the double negation elimination, the collection principle and the constant domain axiom.

Tatiana Likhomanenko, Qiantong Xu, Jacob Kahn, Gabriel Synnaeve

Recent results in end-to-end automatic speech recognition have demonstrated the efficacy of pseudo-labeling for semi-supervised models trained both with Connectionist Temporal Classification (CTC) and Sequence-to-Sequence (seq2seq) losses. Iterative Pseudo-Labeling (IPL), which continuously trains a single model using pseudo-labels iteratively re-generated a

Jorik Jooken, Pieter Leyman, Tony Wauters, Patrick De Causmaecker

In this article we propose a heuristic algorithm to explore search space trees associated with instances of combinatorial optimization problems. The algorithm is based on Monte Carlo tree search, a popular algorithm in game playing that is used to explore game trees and represents the state-of-the-art algorithm for a number of games. Several enhancements to

Ziheng Zhang, Jiaoyan Chen, Xi Chen, Hualuo Liu

Embedding-based entity alignment has been widely investigated in recent years, but most proposed methods still rely on an ideal supervised learning setting with a large number of unbiased seed mappings for training and validation, which significantly limits their usage. In this study, we evaluate those state-of-the-art methods in an industrial context, where

Clément Sarrazin

In this article, we introduce a method to approximate solutions of some variational mean field game problems with congestion, by finite sets of player trajectories. These trajectories are obtained by solving a minimization problem similar to the initial variational problem. In this discretized problem, congestion is penalized by a Moreau envelop with the 2-W

Takashi Ichikawa

We construct the universal Mumford curve of given genus as a family of Mumford curves over the deformation space of degenerate curves in the category of arithmetic formal geometry. Furthermore, we give explicit formulas of abelian differentials and their periods of the universal Mumford curve.

Alessandro Doldi, Marco Frittelli

We investigate to which extent the relevant features of (static) Systemic Risk Measures can be extended to a conditional setting. After providing a general dual representation result, we analyze in greater detail Conditional Shortfall Systemic Risk Measures. In the particular case of exponential preferences, we provide explicit formulas that also allow us to

Hanmo Li, Mengyang Gu

The COVID-19 outbreak is asynchronous in US counties. Mitigating the COVID-19 transmission requires not only the state and federal level order of protective measures such as social distancing and testing, but also public awareness of time-dependent risk and reactions at county and community levels. We propose a robust approach to estimate the heterogeneous p

Deviprasath Palani, Daniel Hoenig, Leon Karpa

We report on a method for measuring ac Stark shifts observed in stored light experiments while simultaneously determining the energetic splitting between the electronic ground states involved in the two-photon transition. To this end we make use of the frequency matching effect in light storage spectroscopy. We find a linear dependence on the intensity of th

Resha Dwika Hefni Al-Fahsi, Kevin Aldian Winanta, Fauzan Pradana, Igi Ardiyanto

NightOwl is a robotic platform designed exclusively for a wheeled service robot. The robot navigates autonomously in omnidirectional fashion movement and equipped with LIDAR to sense the surrounding area. The platform itself was built using the Robot Operating System (ROS) and written in two different programming languages (C++ and Python). NightOwl is compo

Azlan Iqbal

Human preference or taste within any domain is usually a difficult thing to identify or predict with high probability. In the domain of chess problem composition, the same is true. Traditional machine learning approaches tend to focus on the ability of computers to process massive amounts of data and continuously adjust 'weights' within an artificial neural

Chuansheng Dai, Zhipeng Dong, Jiaqiang Lin, Yimin Zhang

We demonstrate an all-fiber spatiotemporal mode-locked laser based on graded-index multimode fiber. Due to the high damage threshold of graded-index multimode fiber devices, the output single-pulse energy reach up to 11.67 nJ. The beam quality at mode-locked state is significantly improved compared with continuous wave state as a result of the self-cleaning

Cagri Metin, Mehmet Akif Ezan

Here we show the hairpin vortices point the upstream direction of flow instead of downstream, and this characteristic is found intrinsic behavior for turbulent buoyancy-driven boundary layer. We uncover the coherent vortices straddle high-speed streak instead of low-speed streak; moreover, the quadrant of the tangential Reynolds shear stresses dominates the

Dmitrii N. Maksimov, Valeriy S. Gerasimov, Silvia Romano, Sergey P. Polyutov

We consider refractive index sensing with optical bounds states in the continuum (BICs) in dielectric gratings. Applying a perturbative approach we derived the differential sensitivity and the figure of merit of a sensor operating in the spectral vicinity of a BIC. Optimisation design approach for engineering an effective sensor is proposed. An analytic form

Jiaan Qi, Hui Khoon Ng

Randomized benchmarking has emerged as a popular and easy-to-implement experimental technique for gauging the quality of gate operations in quantum computing devices. A typical randomized benchmarking procedure identifies the exponential decay in the fidelity as the benchmarking sequence of gates increases in length, and the decay rate is used to estimate th

Soumen Sarkar, Peter Zvengrowski

D. Davis introduced projective product spaces in 2010 as a generalization of real projective spaces and discussed some of their topological properties. On the other hand, Dold manifolds were introduced by A. Dold in 1956 to study the generators of the non-oriented cobordism ring. Recently, in 2019, A. Nath and P. Sankaran made a modest generalization of Dold

Lan Wu, Ki Myung Brian Lee, Liyang Liu, Teresa Vidal-Calleja

In this letter, we introduce the Log-Gaussian Process Implicit Surface (Log-GPIS), a novel continuous and probabilistic mapping representation suitable for surface reconstruction and local navigation. Our key contribution is the realisation that the regularised Eikonal equation can be simply solved by applying the logarithmic transformation to a GPIS formula

Frederik Nathan, Rongchun Ge, Snir Gazit, Mark S. Rudner

Recent work [M. H. Kolodrubetz et al, PRL 120, 150601] has demonstrated that periodically driven one-dimensional fermionic systems can support quantized energy pumping resulting from an adiabatic modulation of a second parameter. In this work, we explore this topological Floquet-Thouless energy pump in the quasiperiodic driving regime where the parametric dr

Keijo Mönkkönen

If a non-reversible Finsler norm is the sum of a reversible Finsler norm and a closed 1-form, then one can uniquely recover the 1-form up to potential fields from the boundary distance data. We also show a boundary rigidity result for Randers metrics where the reversible Finsler norm is induced by a Riemannian metric which is boundary rigid. Our theorems gen

Yizhou Peng, Jicheng Zhang, Haobo Zhang, Haihua Xu

Human can recognize speech, as well as the peculiar accent of the speech simultaneously. However, present state-of-the-art ASR system can rarely do that. In this paper, we propose a multilingual approach to recognizing English speech, and related accent that speaker conveys using DNN-HMM framework. Specifically, we assume different accents of English as diff

Yu-An Chung, Yonatan Belinkov, James Glass

Self-supervised speech representation learning has recently been a prosperous research topic. Many algorithms have been proposed for learning useful representations from large-scale unlabeled data, and their applications to a wide range of speech tasks have also been investigated. However, there has been little research focusing on understanding the properti

Michael Gnewuch, Hendrik Pasing, Christian Weiß

We prove a generalized Faulhaber inequality to bound the sums of the $j$-th powers of the first $n$ (possibly shifted) natural numbers. With the help of this inequality we are able to improve the known bounds for bracketing numbers of $d$-dimensional axis-parallel boxes anchored in $0$ (or, put differently, of lower left orthants intersected with the $d$-dim

Minho Ryu, Kichun Lee

A pre-trained language model, BERT, has brought significant performance improvements across a range of natural language processing tasks. Since the model is trained on a large corpus of diverse topics, it shows robust performance for domain shift problems in which data distributions at training (source data) and testing (target data) differ while sharing sim

Yujie Nie, Renjie Zhou

Phase sensitivity determines the lowest optical path length (OPL) value that can be detected from the noise floor in a quantitative phase microscopy (QPM) system. The temporal phase sensitivity is known to be limited by both photon shot-noise and a variety of noise sources from electronic devices and environment. To beat temporal phase sensitivity limit, we

Golnaz Moallem, Don D. Pathirage, Joel Reznick, James Gallagher

This paper introduces an automated vision system for animal detection in trail-camera images taken from a field under the administration of the Texas Parks and Wildlife Department. As traditional wildlife counting techniques are intrusive and labor intensive to conduct, trail-camera imaging is a comparatively non-intrusive method for capturing wildlife activ

Dibyajyoti Chakravarti, Koustav Hazra, Riya Kayal, Sudip Sasmal

The Unitary Group Adapted State-Specific Multi-Reference Perturbation Theory (UGA-SSMRPT2) developed by Mukherjee et al [J. Comput. Chem. 2015, 36, 670] has successfully realized the goal of studying bond dissociation in a numerically stable, spin-preserving and size-consistent manner. In this paper, we explore and analyse the UGA-SSMRPT2 theory in the descr

Nicolas Verzelen, Magalie Fromont, Matthieu Lerasle, Patricia Reynaud-Bouret

Given a times series ${\bf Y}$ in $\mathbb{R}^n$, with a piece-wise contant mean and independent components, the twin problems of change-point detection and change-point localization respectively amount to detecting the existence of times where the mean varies and estimating the positions of those change-points. In this work, we tightly characterize optimal

Jifeng Shao, Yuntian Liu, Meng Zeng, Jingyuan Li

The magnetic structures of MnBi2Te4(Bi2Te3)n can be manipulated by tuning the interlayer coupling via the number of Bi2Te3 spacer layers n, while the intralayer ferromagnetic (FM) exchange coupling is considered too robust to control. By applying hydrostatic pressure up to 3.5 GPa, we discover opposite responses of magnetic properties for n = 1 and 2. MnBi4T

Yasuaki Kobayashi, Kazuhiro Kurita, Kunihiro Wasa

Kimelfeld and Sagiv [Kimelfeld and Sagiv, PODS 2006], [Kimelfeld and Sagiv, Inf. Syst. 2008] pointed out the problem of enumerating $K$-fragments is of great importance in a keyword search on data graphs. In a graph-theoretic term, the problem corresponds to enumerating minimal Steiner trees in (directed) graphs. In this paper, we propose a linear-delay and